Lead Data Scientist at Merck Life Science KGaA, Darmstadt, Germany
Machine Learning and Probabilistic Modeling

I work at the boundary between physical simulations and machine learning. I have 5+ years experience in machine learning and data science, and my background is in theoretical physics. Born in Sardinia, but I've been living in the Rhein-Neckar region for the past 10 years. Cat person.

Alessandro is a highly experienced data scientist with a Bachelor’s degree in computer science and a Master’s in data science. He has collaborated with various companies and organizations and currently holds the role of senior data scientist at logistics giant Kuehne+Nagel. Alessandro is particularly passionate about statistics and digital experimentation and has a strong track record of applying these skills to solve complex problems. He shares his knowledge regularly, speaking at events like the Data Innovation Summit and ODSC.

Alexander C. S. Hendorf has over 20 years of experience in digitalization, data, and artificial intelligence. As an independent consultant, he focuses on the practical implementation, adoption, and communication of data- and AI-driven strategies and decision-making processes.

While still in law school, he worked as a DJ—before dropping out to join a transatlantic music start-up. The venture evolved into a decent independent label group and, eventually, a small stock corporation, where Alexander became a partner and, at 28, took over as COO. He led the company’s digital transformation and designed systems that could scale with growth. This entrepreneurial journey laid the foundation for his deep understanding of business strategy, technology, and innovation.

After closing the chapter on digital music, Alexander turned his focus to data science and AI—initially driven by curiosity, with weekends on Coursera and evenings on GPUs. That passion evolved into a career advising organizations on AI integration, data strategy, and building impact-driven teams.

Some say he just picks the flashiest jobs—record label owner, data scientist—but really, he follows his passion: for what’s new, what matters, and what connects people and technology.

Today, he supports clients—especially in regulated or legacy-heavy industries—in aligning emerging technologies with real-world business goals. His work emphasizes cultural impact, sustainable change, and interdisciplinary thinking.

Alexander is a recognized expert in data intelligence and a frequent speaker and chair at international conferences, including PyCon DE & PyData, Data2Day, and EuroPython. He’s a Python Software Foundation Fellow, EuroPython Fellow, and board member of the Python Software Verband (Germany).

Since 2024, he has been driving Pioneers Hub, a non-profit supporting vibrant, inclusive tech communities—and helping innovators keep pace in a rapidly changing world.

Economist and Data Scientist. I spend most of my week working on online auctions at Trivago. In the evenings and weekend, I work on open source packages for regression modeling and inference in R and Python.

Mathematician who got into coding and enjoys it way too much. One of the three core developers of BayBE, the Bayesian Optimization Package developed at Merck KGaA, Darmstadt. Also working on antibody and retrosynthesis projects.

Interested in everything the intersection between mathematics and computer science has to offer, as well as in best practices for coding. Always curious to learn!

Alexander Stigsen is the Chief Product Officer at Exasol, where he leads product strategy and innovation for one of the world’s fastest analytics databases. With a deep-rooted background in engineering and a career spanning more than two decades, Alexander has been at the forefront of database technology and product development.
He is best known as the founder and former CEO of Realm, a groundbreaking mobile database platform that quickly became one of the most widely adopted solutions for mobile app developers worldwide. Under his leadership, Realm was used in applications on over a billion devices and was ultimately acquired by MongoDB, further cementing his influence in the data infrastructure space.
Alexander brings a unique perspective that bridges the worlds of engineering, product leadership, and entrepreneurship. At conferences, he shares insights on building scalable data systems, innovating in developer tools, and navigating the startup-to-acquisition journey—all with a focus on delivering products that developers love.

Alexander Uhlig is the CEO of Code17, the company behind getML. With a background in Physics, he leads the development of getML and has worked hands-on with data teams to build prediction models across various domains, including healthcare, trading, and e-commerce.

My background is particle physics, where I was completely spoiled by access to large amounts of data and the freedom to try out every hot ML algorithm on it. The experiments I participated in were so-called large scale experiments (e.g Large Hadron Collider) and had from 500+ up to 2.5k other people working on them. So in addition to physics, I was exposed to the best software development practices that helped us to avoid a complete mess and destroy the Universe.

Afterwards I was working as Data Scientist in various fields and recently became "Solution Architect ML/AI and BI" at big enterprise company.

During my free time, I like learning new tools and techniques and implementing them in end-to-end AI/ML and IoT projects. My experience has also been very helpful in guiding data analysts, data scientists, and machine learning engineers as a mentor and contributing to the growth of the next generation of data scientist elite.

Technical Lead Data & AI working on GenAI topics for E.ON Digital Technology GmbH. Happy to present our work publicly.

Andy Kitchen is a AI/neuroscience researcher, startup founder, and all-around hacker. He co-founded Cortical Labs where the team taught live brain cells to play pong. He's still trying to figure out how to catch the ghost in the machine.

I received my PhD in Machine Learning (ML) and Natural Language Processing (NLP) from the University of Bonn and Fraunhofer IAIS where I was member of the Text Mining group. Now I work on AI and data driven products, mostly focused on applications in the medical and healthcare domain.
My main passion is in NLP, especially for the German language, and Information Retrieval (IR). Sometimes I build Recommender Systems.

I'm Anna-Lena, a machine learning engineer living in Bonn, Germany. I'm very passionate about learning and love to share my knowledge with other people. Besides machine learning I love teaching Python and have been a regular guest on PyCon events and podcasts.

Anna Varzina is a Data Science Engineer at Lighthouse, where she has been developing data-driven solutions for the hospitality industry since 2021. She specialises in working with large datasets and performing complex data transformations using Python and SQL to extract meaningful insights.
This is Anna's first time speaking at PyCon/PyData, and she is excited to share her experiences in overcoming the challenges of building reliable and scalable data workflows.

Anthony Harrison has been developing and delivering mission-critical applications for over 40 years working on various complex programs where he held various roles in software, systems and cyber engineering, as well as providing technical leadership for a number of programmes.

He is the Founder and Director of APH10, and co-founder of SBOM Europe, and is a leading source of expertise in Software Bill of Materials (SBOM). He has been developing open source software actively for a number of years; most recently, the applications have been related to supporting the software supply chain through utilities to generate and analyse software bills of materials (SBOMs).

He has been a mentor for the Google Summer of Code for the past four years via the Python Software Foundation and is a mentor for his local CoderDojo in Manchester teaching students Python.

Arne Grobrügge, M. Sc. Wirtschaftsinformatiker mit Schwerpunkt Maschinelles Lernen und Informationssicherheit, arbeitet als Data Scientist bei der scieneers GmbH. Im Rahmen von diversen Kundenprojekten entwickelt und überwacht er den Einsatz von Sprachmodellen und Mulit-Agenten Systemen in Unternehmen, um innovative und wertschöpfende Lösungen zu schaffen.

AI engineer at Typetone, where I'm taming LLMs to automate end-to-end marketing.

We help unburden SMEs and solopreneurs from doing their content marketing, and this task is surprisingly hard for LLMs to solve yet!

In past lives personalized marketing at ING as a data scientist and ran a non-profit in Kyrgyzstan.

Barak Amar is a principal engineer at lakeFS with over 25 years of experience spanning startups and enterprise environments. He specializes in distributed systems and backend architecture, designing scalable solutions. He is passionate about programming languages and contributes to open-source projects.

As part of the founding team at lakeFS, he has helped build the product while recently also gaining experience in product management.

When not on the keyboard, he is an avid runner who maintains a regular training schedule.

Ben has been identifying as a Rustacean since 2018. With a background in UI/UX, he's excited to use Rust to make products that are faster, more resilient, and delightful for his users. He's currently a Staff Engineer at Aleph Alpha, where he uses Rust to make AI applications easier to build and operate.

I completed my PhD in deep learning based time series forecasting in 2023 with the Karlsruhe Institute of Technology. In sktime, I am focusing on forecasting methods (mainly deep learning based ones) and implementing pipelines.

Bernhard is a Senior Data Scientist at Merck with a PhD in deep learning and over 5 years of experience in applying data science and data engineering within different industries. For more information you can connect with him on LinkedIn. 🙂

Bo Dong is a Principal Technical Product Manager on the CUDA team. He is responsible for distributed computing including Legate and other technologies/products at NVIDIA.

Bogdan Girman is an expert in Machine Learning and DevOps, with extensive experience in implementing scalable, reproducible ML systems. He is passionate about bridging the gap between development and operations in AI.

Caio holds a PhD in Computer Science and has been working with data and AI both in academia and industry since 2014. Currently working as a DS/MLE Consultant at Xebia Data, he is particularly keen on neural networks in its many forms and applications. His enthusiasm even led him to make a neural network fit inside a business card. With experience designing and taking applications into production, Caio has been recently focusing on how (Generative)AI can augment human productivity.

Six years ago, I discovered that my passion was in the field of data and artificial intelligence. I decided to move from Venezuela to Chile in search of new challenges and currently found one of them in Estonia, where I have had the opportunity to work on teams in Latin America, Europe and Africa.

I have been able to work on projects related to artificial intelligence, machine learning and deep learning, especially in the field of marketing, which has allowed me to help traditional companies adopt a data-driven approach. However, my latest challenge has been working at the fastest mobility company in Europe, where I have been able to apply all my knowledge and skills in a highly dynamic and constantly evolving environment.

I have had to develop different programs in Python, using SQL and No-SQL to build cloud structures that can handle large volumes of information. I have learned to work with DataBricks and DBT, and I am familiar with Google Cloud and AWS. I have also explored tools such as Airflow, CloudRun, App Engine, BigQuery, S3, DynamoDB, MongoDB, among others.

My focus has always been on the areas of statistics and mathematics, seeking to solve recurrent problems in business through techniques of computer vision, natural language processing, regression or classification algorithms, and neural networks. I have generated dashboards in Looker, Looker Studio, Tableau and Power BI, also custom reports, alerts and complex artificial intelligence models, leading teams of four to ten people, being the bridge between marketers and technical teams.

I still have a long way to go to become the "Marketing Scientist" I want to be, but I am grateful for all the opportunities and challenges I have faced so far. I am certainly eager to continue learning and growing in my career, looking for new challenges that will take me to spaces that I have not yet explored.

Hi! I am Carsten. I have been working in the data and analytics environment for seven years. As a data scientist, I am excited by the challenge of translating the business into optimizable algorithms and creating real impact. As a self-taught programmer, I am just as absorbed in the technical challenges, preferably in the cloud.

After having a career as a Data Scientist and Developer Advocate, Cheuk dedicated her work to the open-source community. Currently, she is working as AI developer advocate for JetBrains. She has co-founded Humble Data, a beginner Python workshop that has been happening around the world. She has served the EuroPython Society board for two years and is now a fellow and director of the Python Software Foundation.

Dr. Chong Shen Ng is a Research Engineer at Flower Labs with over a decade of experience in both research and industry, specializing in federated learning, data science, and parallel computing. As a key developer, he focuses on scaling Flower to deploy privacy-enhanced distributed AI solutions for real-world applications. Chong Shen is passionate about contributing to the open-source community, developing trustworthy AI systems through federated learning, and advancing edge AI technologies. A dedicated advocate for open-source software, he has co-chaired PyData Global events and volunteered at SciPy and PyData London conferences.

A data scientist that goes beyond conventional methods to build robust and trustworthy AI models and solutions.
- Experience in industry leading companies and a fairly short research background in Explainable AI in NLP.
- Background in mathematics.
- Always keeping up to date with the latest AI research and findings.
- Competing in Machine Learning competitions.

I’m a Senior Machine Learning Engineer at E.ON Energidistribution AB in Malmö, Sweden. With a background in theoretical particle physics, I transitioned into the field of machine learning and software development, leveraging open-source technologies like Python to drive innovation and collaboration.

At E.ON, I’ve been involved in several image analysis projects. Notably, I co-authored the "STORM" project, which aims to improve the documentation process and ensure compliance with standards through AI-driven automated checks.

On a mission to structure unstructured text with NLP

Ex-cofounder with 8 years experience in NLP

I come from a mixed Hungarian-Dutch background and live in Nuremberg at the moment

In my free time I enjoy improv theatre and swimming

Christian has 12+ years of experience in the scientific application of python in academic and industry settings. He is one of the founders of prokube.ai where he builds an MLOps platform build around Kubeflow, MLFlow, Kubernetes, and a host of other open source tools. He also holds a PhD in physics, where he gained experiences in maintaining a distributed compute clusters. Christian is a maintainer of several OSS projects.

Christian hat einige Jahre als Physiker auf dem Gebiet der experimentellen Quantenoptik geforscht und sich seit 2024 auf Data Science und Künstliche Intelligenz spezialisiert.

For more than ten years, Clemens Hübner has been working at the interface between software and security. After roles as a software developer and in penetration testing, he joined inovex in 2018 as a software security engineer. Today, he supports development projects at the conception and implementation level and is a trainer both in-house and for clients. He advises on secure development processes and DevSecOps. As speaker, he is invited to national and international conferences.

Cosima Meyer is a data scientist with a strong focus on making machine learning models explainable and accessible. Passionate about trustworthy AI, she is committed to building systems that are not only technically robust but also transparent and ethical. As a Google's Women Techmakers Ambassador and an active member of PyLadies, Cosima is dedicated to fostering inclusive and collaborative communities, working to bridge the two groups and create spaces for knowledge-sharing and growth.

During her PhD studies at the University of Mannheim, Cosima discovered her enthusiasm for sharing knowledge through technical blog posts and developing open-source software. Her work reflects a blend of technical expertise and a passion for community building, inspiring others to explore, learn, and contribute to the fields of AI and data science.

Danica began her career as a software engineer in data visualization and warehousing with a business intelligence team where she served as a point-person for standards and best practices in data visualization across her company. In 2018, Danica moved to San Francisco and pivoted to backend engineering with a derivatives data team which was responsible for building and maintaining the infrastructure that processes millions of financial market data per second in near real-time. Her first project on this team involved Kafka Streams and Kafka Connect. From there, she immersed herself in the world of data streaming and found herself quite at home in the Apache Kafka and Apache Flink communities. She now leads the open source advocacy efforts at Snowflake, supporting Apache Iceberg and Apache Polaris (incubating). Outside of work, Danica is passionate about sustainability, increasing diversity in the technical community, and keeping her many houseplants alive. She can be found on X (Bluesky and Mastodon), talking about tech, plants, and baking @TheDanicaFine.

I am currently a software engineer at QuantCo. Previously, I worked as a researcher in program analysis and software testing at the Technical University of Munich.

Daniel is the CTO at Userlike, a leading SaaS company providing innovative customer communication solutions. He has a degree in Computer Science from the University of Karlsruhe and has been writing software professionally for over 20 years. He enjoys sharing his experiences and helping fellow developers level up their software development skills, and presented before at various Django and Python conferences throughout Europe. When not in front of a keyboard, he can be found training for his next marathon or building intricate Lego contraptions with his son.

Hi, I'm Daniel, a PhD student in digital neuropathology at Julius-Maximilians-University Würzburg and a research associate at the University Hospital Augsburg as well as Neu-Ulm University of Applied Sciences. My work focuses on applying computer vision techniques to automate analysis processes in the pathological departments and provide physicians with the tools to conduct machine learning on their own.

Daniel Stolpmann received the B.Sc. and M.Sc. degrees in computer science and engineering from Hamburg University of Technology (TUHH), Germany, in 2017 and 2019. During his master studies, he started working at the Institute of Communication Networks (ComNets) as a student assistant and became a research fellow after his graduation. At ComNets, he conducted research on machine learning for communication networks, network coding and network emulation. In 2024, he joined Tegtmeier Inkubator as a senior software developer and started working on AI-enabled smart home systems.

Darya Petrashka is a Data Scientist at SLB with 5 years of experience, focusing on supply chain projects in data analysis, NLP, and generative AI. She is passionate about using data for problem-solving, with a strong interest in classical machine learning, NLP, and AWS services. An AWS Community Builder and Authorized Instructor, Darya actively shares her expertise through public speaking at various industry events, including AWS Community Days, AWS Cloud Day, and PyCon. A dedicated learner, Darya continually hones her skills by participating in workshops, courses, and tech schools.

Hello, I’m Dr. Daryna Dementieva. Driven by both personal experiences and a deep passion, I am a dedicated advocate and researcher focused on leveraging AI and NLP for Positive Social Impact. Currently (as a technical person) I am exploring collaborations with NGOs and social scientists to bridge the gap between cutting-edge AI technology and societal needs. My goal is to share insights on responsible AI and Data Science, inspiring and enabling projects in these fields to transition from concept to impactful reality.

I am a creative Software Engineer and a skilled Consultant with experiences in Software Project Management, for both Product Development and Customer Projects. Furthermore I have a strong Database background by being specialized on NoSQL Database Systems. My experience with Redis spans performance engineering, post-sales consultancy, technical education, and client library and ecosystem integration engineering.

Hey there! I'm Dennis Weyland, and I've been part of the Blue Yonder team for the last five years. I kicked off my career as a Data Scientist but soon found my groove in Data Engineering. Python has been my go-to language for the past seven years, and I love diving into project setups to make everything run smoothly. Before diving into my professional career, I studied Physics at KIT, where I completed my master's thesis and discovered my passion for Python software development and machine learning.

Outside of work I'm passionate about running, diving, and climbing.

Dirk Jung has more than 20 years of experience in the IT industry. In his position as Senior Solution Engineer at Snowflake Computing, he supports companies in building modern data and analysis platforms in the cloud. In his professional career, he has held various positions at SAS Institute, Blue Yonder and Datameer, among others. He specializes in business intelligence, predictive analytics and data warehousing.

Dominik Falkner completed his bachelor's degree in Software Engineering in 2018 and his master's degree in Data Science and Engineering with a specialization in Data Analysis in Production and Marketing at Hagenberg University of Applied Sciences in 2020.

During his studies, he already worked on various software systems, including some for collecting and storing data. Since 2019, he has been employed by the RISC Software GmbH as a Data Scientist, working in customer and research projects. His interests and focus lie in the following disciplines:

Employing machine learning techniques.
The fusion of expert knowledge and machine learning methods
Predictive and prescriptive analytics
Design and architecture of software systems

In the course of his work as a Data Scientist, he mainly deals with time series analyses and classification settings from various industries. In 2022 he will start his PhD studies at the Institute for Formal Models and Verification at Johannes Kepler University in Linz.

I'm an MLOps Engineer from Berlin working at the start-up 1KOMMA5°, and I'm part of the women's tech podcast Unmute IT. I aim to empower underrepresented groups to have a say in shaping the algorithms that impact our world today. Also, I’m always on the lookout for the best coffee shop in town ☕️

Hello! My name is Evelyne Groen and I am a Senior Machine Learning engineer at Malt. A long time ago I studied physics in Amsterdam, after which I moved to Berlin to discover the world of data science. Currently I'm working at Malt as a machine learning engineer exploring the boundaries between devops and data.

Lead AI/ML scientist at ZEISS Meditec with 10+ years of experience in algorithm design for multimodal unstructured data (image, time series, geospatial data). Expert in developing innovative algorithms with statistical methods, shallow and deep
machine learning, and pre-trained Large Language Models (LLMs); specifically for satellite data and niche medical sensors. Recipient of innovation awards from the German Aerospace Center (DLR) and IEEE for novel algorithms and data products for satellite missions. Previous work experience at German Aerospace Center (DLR) and DataRobot Inc.

After my PhD in Astronomy @ Max Planck Institute for Astronomy in Heidelberg, I have switched from academia to industry. Working as a Data Scientist @ DSC GmbH I am developing in python for various projects including those involving language models. I am attending PyData meetings in Heidelberg and even presented a lightning talk on my "Croshapes" hobby project.

Kristian is a freelance Python trainer who wrote his first lines of Python in the year 11111001111. After a career writing software for life science research, he has been teaching Python, Data Analysis and Machine Learning throughout Europe since 2011. More recently, he has built data pipelines for the real estate and medical sector.

Kristian has translated 5 Python books and written 2 more himself, in addition to numerous teaching guides. Kristian has collected 364 stars on Advent of Code. His knowledge about async is, unfortunately, miserable. His favorite Python module is 're'. Kristian believes everybody can learn programming.

You can find Kristians teaching materials on https://www.academis.eu

Lisa is an accomplished educator, researcher, and freelancer specializing in data science, natural language processing (NLP), and artificial intelligence. With a PhD in Intelligent Systems from UCL and a master's from Imperial College London, Lisa has extensive experience in academia and industry, having taught at UCL, and contributed to impactful projects like those with Cancer Research UK.

A digital nomad at heart, Lisa teaches corporate clients and supervises university students worldwide, focusing on Python, machine learning, and NLP. Known for their engaging teaching style and passion for problem-solving, they are currently developing innovative courses and creating a YouTube channel featuring masterclasses on data analysis and machine learning.

Driven by a love for teaching, research, and helping others succeed, Lisa is exploring opportunities to return to academia, with aspirations to lecture in Eastern Europe and Central Asia. Multilingual and versatile, they are shaping the future of data science education while continuing to inspire learners globally.

Dr Maren Westermann works as a machine learning engineer at DB Systel GmbH and holds a PhD in environmental science. She is a self taught Pythonista, a member of the documentation and contributor experience team, respectively at the open source machine learning library scikit-learn, and a team member of the open source library Narwhals. She is also a co-organiser of PyLadies Berlin where she mainly hosts open source hack nights.

Dr Maria Börner is a legal tech expert in the use of AI and heads the AI Competence Centre at Westernacher Solutions. In her role, she is responsible for the development of AI tools in the government, legal and church sectors. She has been working in AI for more than 8 years and bridges the gap between AI development and customers. She volunteers to support the Women in AI network by organising partnerships and visibility.

I'm Marisa, I live in Lübeck, Germany, I'm a mathematician and Team Lead at inovex. With a passion for data, demystification, and people, I’m on a mission to bridge the gap between complex mathematical concepts and real-world understanding. Whether it’s through interpretability, explainability, or fostering equal opportunity and fairness, I believe that math can – and should – be accessible to everyone.

Dr. Yves J. Hilpisch is the founder and CEO of The Python Quants (https://tpq.io), a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading, computational finance, and asset management.

Yves has a Diploma in Business Administration, a Ph.D. in Mathematical Finance, and is Adjunct Professor for Computational Finance.

Yves is the author of seven books (https://home.tpq.io/books):

• Reinforcement Learning for Finance (2024, O’Reilly)
• Financial Theory with Python (2021, O’Reilly)
• Artificial Intelligence in Finance (2020, O’Reilly)
• Python for Algorithmic Trading (2020, O’Reilly)
• Python for Finance (2018, 2nd ed., O’Reilly)
• Listed Volatility and Variance Derivatives (2017, Wiley Finance)
• Derivatives Analytics with Python (2015, Wiley Finance)

Yves is the director of Certificate in Python for Finance (CPF) Program, a comprehensive, systematic online training program preparing students, academics, and professionals alike for the challenges faced by financial institutions in data science, computation, trading, and artificial intelligence. He also lectures on computational finance, machine learning, and algorithmic trading at the CQF Program (http://cqf.com).

Yves is the originator of the financial analytics library DX Analytics (http://dx-analytics.com) and organizes Meetup group events, conferences, and Bootcamps about Python, artificial intelligence, and algorithmic trading in London (http://pqf.tpq.io) and New York (http://aifat.tpq.io). He has given keynote speeches at technology conferences in the United States, Europe, and Asia.

Dr. Einat Orr has 20+ years of experience building R&D organizations and leading the technology vision at multiple companies, the latest being Similarweb, that IPO in NYSE last May. Currently she serves as Co-founder and CEO of Treeverse, the company behind lakeFS, an open source platform that delivers a git-like experience to object-storage based data lakes. She received her PhD. in Mathematics from Tel Aviv University, in the field of optimization in graph theory.

Data Engineer at Schwarz IT in Berlin, Germany. Where she helps power AI use cases across Europe's largest retailer: the Schwarz Group. Loves showcasing the importance of good data engineering practices, building reliable systems and bringing order to the chaos.

I am Liza - Applied Scientist at AWS Generative AI Innovation Center and am based in Berlin. I am passionate about AI/ML, finance and software security topics. In my spare time, I enjoy spending time with my family, sports, learning new technologies, and table quizzes.

Emanuele is an engineer, researcher, and entrepreneur with a passion for artificial intelligence.

He earned his PhD by exploring time series forecasting in the energy sector and spent time as a guest researcher at EPFL in Lausanne. Today, he is co-founder and Head of AI at xtream, a boutique company that applies cutting-edge technology to solve complex business challenges.

Emanuele is also a contract professor in AI at the Catholic University of Milan. He has published eight papers in international journals and contributed to over 30 international conferences worldwide. His engagements include AMLD Lausanne, ODSC London, WeAreDevelopers Berlin, PyData Berlin, PyData Paris, PyCon Florence, the Swiss Python Summit in Zurich, and Codemotion Milan.

Emanuele has been a guest lecturer at Italian, Swiss, and Polish universities.

techie, software engineer & researcher building ai/ml tools with keen interest in edtech. co-founder and builder of Quipu.

also working as a part-time engineer at MICE Portal, where he supports transformation of the company processes with agentic ai-backed approaches.

Emily is a software engineer with an interest in developer tooling and platform engineering. When she's not working with computers, she can usually be found making misshapen pottery or exploring Berlin's parks with her dog.

I lead the Engineering function at Tasman Analytics, a boutique data consultancy. We act as an interim/fractional data team and have built many, many data stacks for our clients. We are passionate about helping clients leverage the power of their data.

Personally, I have a background of mechanical engineering and have worked across a range of sectors including sustainability, energy, property, construction and architecture. I am an engineer at heart and perennially look to hone the craft of engineering.

Writing Python makes me incredibly happy.

Seasoned Software & Data Engineering Professional with extensive experience in high-frequency trading systems, data warehousing, and cloud solutions. Expert in optimizing mission-critical systems and implementing engineering best practices. Specialized in Python, SQL and cloud technologies.

Currently working as a Freelance Developer focusing on software and data engineering.

Skilled in developing distributed systems, data pipelines, and performance optimization, consistently delivering solutions that maximize business value.

Fabian combines his passion for data, machine learning, and computer games with his professional activities. In addition to his role as Head of Business Intelligence at Lotum, a mobile game publisher, he also lectures at TH Köln, where he leads a project group focused on game data science. Additionally, Fabian co-organizes the Cologne AI and Machine Learning Meetup (CAIML), hosting bi-monthly events that bring together the local AI and ML community.

Senior Data Scientist and Engineer at Airbus, leading the development of flight plan optimisation and continuous air traffic prediction services based on time series forecasting with ML and physics models.

Florian Teutsch possesses extensive knowledge in the field of generative AI and works as a Machine Learning Engineer at inovex. After successfully completing his studies in Information Systems at the University of Cologne in 2020, he worked for two years as a Data Scientist on an innovative AI-based image search. Since joining inovex, he has been able to continuously expand his practical experience in the field of generative AI.

Florian is Head of Data Science & Mathematical Modeling at inovex GmbH, an IT project center driven by innovation and quality, focusing its services on ‘Digital Transformation’. He holds a PhD in mathematics, has more than 10 years of experience in predictive & prescriptive analytics use-cases and likes everything math 🤯

Physicist, ML Engineer, Agile adept. I’d rather have a taste of everything than specialize. Eager to learn, unlearn, try out, share, help.

I'm a software developer. My goal with my opensource work is to help other people to develop better software faster.

Frank is a Hector-Endowed Fellow and PI at the ELLIS Institute Tübingen and has been a full professor for Machine Learning at the University of Freiburg (Germany) since 2016. Previously, he has been an Emmy Noether Research Group Lead at the University of Freiburg since 2013. Before that, he did a PhD (2004-2009) and postdoc (2009-2013) at the University of British Columbia (UBC) in Canada. He received the 2010 CAIAC doctoral dissertation award for the best thesis in AI in Canada, as well as several best paper awards and prizes in international ML competitions. He is a Fellow of ELLIS and EurAI, Director of the ELLIS unit Freiburg, and the recipient of 3 ERC grants. Frank is best known for his research on automated machine learning (AutoML), including neural architecture search, efficient hyperparameter optimization, and meta-learning. He co-authored the first book on AutoML and the prominent AutoML tools Auto-WEKA, Auto-sklearn and Auto-PyTorch, won the first two AutoML challenges with his team, is co-teaching the first MOOC on AutoML, co-organized 15 AutoML-related workshops at ICML, NeurIPS and ICLR, and founded the AutoML conference as general chair in 2022. In recent years, his focus has been on the intersection of foundation models and AutoML, prominently including the first foundation model for tabular data, TabPFN.

Frank is deeply passionate about technological advancements and a co-founder of neunzehn innovations, a company specializing in AI solutions. His professional background combines entrepreneurial experience—having established an innovation and strategy consultancy focused on strategy and deep tech—with several years at a major software corporation. Throughout his tenure in the software industry, he contributed to multiple product and service launches, working across various teams to bring new offerings to market.
Outside the office, he enjoys discovering new horizons in the camper van.

Franz Kiraly is Director at the German Center for Open Source AI, the by software footprint largest German non-profit for open source AI software.

He is also the original founder and a core developer of sktime.

Hi my name is Franz and I’m an open source and python enthuisiast:

• father of 3 girls
• major in psychology
• chess hobbiyst
• competitive ultimate frisbee player
• likes cooking and baking sourdough bread

Guadalupe is a Theoretical Cosmologist working in understanding how the Universe began, how it evolved and what its ultimate fate could be. In particular, she is interested in studying alternative cosmological models with state-of-the-art astrophysical data using advanced statistical techniques and data science algorithms. Furthermore, she is interested in forecasting the performance of new experiments or new observables, for instance, Gravitational Waves.

She holds a Bachelor's in Physics from the University of Cantabria, and Master's and PhD degrees in Cosmology from Leiden University. Currently, she is a Research Fellow in Space Science at the European Space Agency. Moreover, she is an active member of the Euclid Consortium: the scientific group behind the data explotaition of the ESA Euclid mission. In particular, she is the maintainer of the code "Cosmology Likelihood for Observables in Euclid" or simply, CLOE. This software is part of the official data anlysics pipeline that will be eventually used to extract cosmological constraints of the Euclid data. Within the consortium, she is also co-leading the responsible group in charge of testing models beyond-Standard Cosmological Models to discernish the nature of Dark Matter or Dark Energy, or to test alternative inflationary models.

I'm Hannah, a data and machine learning engineer living in Karlsruhe, Germany. With a strong interest in Artificial Intelligence, I am excited to start my journey in this dynamic field. I am passionate about teaching and take great pleasure in breaking down complex concepts and making them accessible to others, fostering a collaborative learning environment.

Hendrik is a C++ developer and works on software for analysis of pipeline inspection data. This includes topics like machine learning,
numerical mathematics and distributed computing. Before this he completed his PhD in physics at the University of Osnabrück with a thesis about quantum mechanics and
numerical simulations where he got to know and and love programming and complex, mathematical tasks.
His favorite programming languages, in which he also has the most experience, are C++, Python and Rust. He describes himself as a "learning enthusiast"
who always gets absorbed in trying out new things. Therefore, he values being up to date with programming languages
and using the latest features of them in a meaningful way.

Henrik is an ML researcher at Helmut Schmidt University, specializing in the application of ML in cyber-physical systems. In his current project, he is developing an anomaly detection and diagnostic AI system for use with data from the International Space Station. Before returning to academia, Henrik spent five years as a data scientist in various consulting roles, where he had the opportunity to delve into a range of exciting datasets. During this time, Henrik became a Python and Kubeflow enthusiast.

Dr. Illia Babounikau is an accomplished data scientist with extensive expertise in machine learning and forecasting. He holds a Ph.D. in Physics from Hamburg University and initially pursued an academic career, focusing on large-scale data analysis and machine learning applications. His contributions have been instrumental in international scientific collaborations, including the CMS experiment at CERN’s Large Hadron Collider and the COMET project at J-PARC.

For the past five years, Dr. Babounikau has been a Data Scientist at Blue Yonder, specializing in developing and fine-tuning advanced forecasting models for retail planning and inventory management. He leads the design and implementation of tailored machine-learning solutions, addressing complex challenges within supply chains across diverse industries.

Dr. Babounikau is passionate about bridging the gap between data science and business strategy, ensuring machine learning models are aligned with business objectives to drive data-informed decision-making.

Ines Montani is a developer specializing in tools for AI and NLP technology. She’s the co-founder and CEO of Explosion and a core developer of spaCy, a popular open-source library for Natural Language Processing in Python, and Prodigy, a modern annotation tool for creating training data for machine learning models.

As a clean code enthusiast, Women in Tech advocate, DevOps engineer, and mathematician, I have worked in multiple tech fields. My journey has taken me from roles as a data scientist and machine learning engineer to MLOps, culminating in my current position as the lead DevOps engineer of a computer vision platform with hundreds of active users. I possess a broad range of experience in multiple programming languages, creating fast and structured CI/CD pipelines, deploying entire platforms to Kubernetes, and working with various cloud providers. I am passionate about efficient, well-readable, and easily maintainable code and strongly believe that machine learning products should be developed with the same standards as good software.

Iryna is a data scientist and co-founder of DataForce Solutions, a company specialized in delivering end-to-end data science and AI services. She contributes to several open-source libraries, and strongly believes that open-source products foster a more inclusive tech industry, equipping individuals and organizations with the necessary tools to innovate and compete.

Isabel Drost-Fromm was up to recently the Chair of the board of directors of the InnerSource Commons Foundation, as well as (former board) member of the Apache Software Foundation. Interested in all things search and text mining with a thorough background in open source collaboration, she is working at Europace AG as Open Source Strategist. True to the nature of people living in Berlin she loves giving friends a reason for a brief visit - as a result she co-founded and is still one of the creative heads behind Berlin Buzzwords, a tech conference on all things search, scale and storage and FOSS Backstage.

I am the Lead of the Data Science Group at the Max Planck Institute for Astronomy in Heidelberg, Germany and an editor for the Journal of Open Source Software (JOSS). My scientific work focuses on galaxy evolution. I get my thrills from gravitational lenses, spectra, databases and well-documented APIs.

I am a Machine Learning Engineer at H&M Group, former Data Scientist at Lidl Sweden, as a professional I am designing Machine Learning services, extracting insights and arranging meaningful stories for my clients by conducting high-quality modeling, engineering, data mining and analytics.

I have a Bachelor degree in Statistics and Probability theory from Uppsala University of Sweden. Because I am a Statistician at core I have good experience with Data Sciencr, Python, R, time series modeling, simulations, machine learning algorithms, SQL, Excel, Spark and database technologies, as well as good communication skills.

You’ll find two comprehensive Python libraries I have open-sourced. One is based on an emerging modern statistical hypothesis testing framework using e-values and martingales based on game-theoretic statistics. The other is for computational Supply Chain and Logistics. The first one is called ’expectation’ and the second one is called ’supplyseer’ and you can find both on my GitHub.

I am a Machine Learning Engineer with 4 years of Python and PyTorch development experience. I've provided ML expertise to startups and the UK government, and I'm particularly interested in beneficial AI applications. My background is in Physics and Atmospheric Physics, where I interpreted large tropical cyclone datasets at Imperial College London.

My previous talks are:
EuroPython Prague 2022 - 🐍 Large Language Model Zen
PyCon/PyData DE Berlin 2023 - Mojo 🔥 - Is it Python's faster cousin or just hype?

Completing my language trilogy: I recently began exploring Rust 🦀.

2008
M.Sc. Physics and Computer Science at Osnabrück University

2012
PhD in Physics at Osnabrück University

2013 - now
Sensor Developer at ROSEN Group

2020 - now
Volunteer operative in the Federal Agency for Technical Relief (THW, Germany)

Javier is a Research Engineer at Hopsworks, where he actively contributes to advancing the Hopsworks AI Lakehouse. He is currently pursuing his Ph.D. at KTH Royal Institute of Technology in Sweden with a primary focus on large-scale machine learning systems.

A physicist currently tackling the development of embedded devices at Rosenxt for various use cases. My journey with Python began a long, long time ago, when the interpreters version string said 1.4.

Besides my current efforts I can rely on great experience from various other roles in my prior career as a scientist, technology manager and department head.

Jesper Dramsch works at the intersection of machine learning and physical, real-world data. Currently, they're working as a scientist for machine learning in numerical weather prediction at the coordinated organisation ECMWF.

Jesper is a fellow of the Software Sustainability Institute, creating awareness and educational resources around the reproducibility of machine learning results in applied science. Before, they have worked on applied exploratory machine learning problems, e.g. satellites and Lidar imaging on trains, and defended a PhD in machine learning for geoscience. During the PhD, Jesper wrote multiple publications and often presented at workshops and conferences, eventually holding keynote presentations on the future of machine learning in geoscience.

Moreover, they worked as consultant machine learning and Python educator in international companies and the UK government. They create educational notebooks on Kaggle applying ML to different domains, reaching rank 81 worldwide out of over 100,000 participants and their video courses on Skillshare have been watched over 128 days by over 4500 students. Recently, Jesper was invited into the Youtube Partner programme creating videos around programming, machine learning, and tech.

I'm the Co-Founder of pi_optimal, where we're working to democratize reinforcement learning and make it usable for real-world decision-making. My passion lies in building AI systems that don't just work in theory, but actually solve meaningful problems in practice.

Before that, I was Lead Data Scientist at Stellwerk3 GmbH, where I led the development of a model-based reinforcement learning project for campaign control. I also had the chance to represent the company at Cyber Valley Incubator events and build a strong, collaborative data team.

My academic journey brought me to the Max Planck Institute for Intelligent Systems, where I focused on challenges in autonomous learning — from sparse rewards in model-free RL to structured world models and graph networks in model-based approaches. Earlier on, I also worked in digital advertising technology at Gruner + Jahr, developing deep learning models for ad click prediction.

Across all these experiences, one thing has stayed the same: I love taking complex machine learning concepts and turning them into impactful, real-world applications.

Software Engineer since 2018, Data Engineer at inovex since 2022 – happy to get the job done, but prefers beautiful solutions.

I am a core contributor to Pandas and Apache Arrow, and one of the maintainers of GeoPandas and Shapely. I did a PhD at Ghent University and VITO in air quality research, worked at the Paris-Saclay Center for Data Science and at Voltron Data contributing to Apache Arrow. I am a freelance open source software developer and teacher.

I'm Josef, an econometrician turned ML engineer. With a strong background in statistics and causal inference, I have developed my skills through rigorous work at institutions such as the University of Bonn and UC Berkeley, but also through the design and implementation of ML solutions at the Rewe Group. My passion lies in reducing model and ecosystem complexity, enhancing interpretability, and bridging the gap between academia and production settings in the context of machine learning. I believe that if we do not establish reliable machine learning systems, we risk failing to harness the immense potential they offer for humanity.

Jose Moreno Ortega (aka Pepe) is a GenAI Lead at E.ON Digital Technology, shaping AI strategy and driving enterprise adoption. With extensive experience in NLP and GenAI, he has worked as both a consultant and developer, building scalable AI solutions and fostering innovation in the field.

Juan Cruz Martinez is a curious software engineer who loves building things. From web apps to AI integrations, he enjoys crafting solutions that make a difference. He's always learning and experimenting with new tech.

Cloud Platform Engineer @ inovex, I specialize in designing scalable cloud infrastructure solutions. My expertise spans cloud architecture, container orchestration, and infrastructure automation. Beyond my core work, I maintain active interests in web technologies and mobile app development, exploring solutions that bridge the gap between platforms

Software developer and data scientist at heart, with an inclination to teach others. Public speaker, working in DevRel.

Kat is a Senior Machine Learning Engineer at Malt, the freelancer marketplace, where she works in the relevancy and matching team. She has a background in bioinformatics and passionate about beautiful code.

Katharine Jarmul is a privacy activist and an internationally recognized data scientist and lecturer who focuses her work and research on privacy and security in data science and machine learning. You can follow her work via her newsletter, Probably Private (https://probablyprivate.com) or in her recently published book, Practical Data Privacy (O'Reilly 2023) now also available in German as Data Privacy in der Praxis.

Katie Richardson is a Staff Data Scientist at Blue Yonder, where she currently works on demand forecasting. Before joining Blue Yonder, she was primarily focused on the domain of search, ranking, and recommendation. With a background in Anthropology and several years experience working with geographical data, she's passionate about exploring spatial inequalities using open data. In her free time, she's an avid tap dancer.

Kristian Kersting is co-director of the Hessian Center for AI (hessian.AI), head of research at the German Research Center for AI / Darmstadt, and professor of AI and machine learning at TU Darmstadt. After his PhD at the Univrsity of Freiburg in 2006, he was with the MIT, Fraunhofer IAIS, the University of Bonn and the TU Dortmund. He is an AAAI, EurAI and ELLIS Fellow, coauthor of the popoular science book “Wie Maschinen Lernen”, winner of the “German AI Prize”, member of the Mainz Academy of Sciences and Literature and seed investor at Aleph Alpha, one of Europe's AI hopes. in collaboration with Aleph Alpha Research, he also runs the collaboration lab 1141 at TU Darsmtadt on safe and transparent generative AI. He had a regular AI column in the Welt (am Sonntag).

I'm Squad Lead for Automation & Analytics, coordinating Process Automation projects and drafting solutions for intelligent enterprises. Within projects, I work as a Senior Data Scientist and Cloud Solution Architect, combining various SAP BTP services with Artificial Intelligence.

In our sovanta Innovation Factory I drive innovation and automation with traditional Artificial Intelligence and fancy Generative AI services, to facilitate business processes on SAP BTP and make SAP as easy as it never was before.

So if you like to chat about Artificial Intelligence, Science Fiction, bots gone rogue and seeking for world domination, or the Art of Python you're more than welcome to contact me!

Laura is a very technical designer™️, working at Pydantic as Lead Design Engineer. Her side projects include Sweet Summer Child Score (summerchild.dev) and Ethics Litmus Tests (ethical-litmus.site). Laura is passionate about feminism, digital rights and designing for privacy. She speaks, writes and runs workshops at the intersection of design and technology.

Leandro von Werra is the head of research at Hugging Face. He promotes open science and works on building large high-quality datasets and training of open LLMs. He lead the BigCode project, is a co-author of the “Natural Language Processing with Transformers” book published at O’Reilly and the creator of the popular Python library TRL, which combines transformers with reinforcement learning and other effective fine-tuning methods.

AI Engineer at xtream by day, and open source maintainer by night. I strive to be an active part of the Python and PyData communities - e.g. as an organiser of PyData Milan. Feel free to reach out!

Malte is a seasoned Data Engineer with over 10 years at Blue Yonder, where he recently worked on company's forecasting service. Holding a PhD from the University of Hertfordshire's Adaptive Systems Research Group, he explored Information Theory in the context of Multi-Agent Systems. Beyond tech, Malte is passionate about great UX, typography, and baking the perfect loaf of bread.

Marcelo Trylesinski, known as "The FastAPI Expert", is a passionate software engineer from Brazil 🇧🇷 (half 🇺🇾, half 🇮🇹).

Currently based in Utrecht, Netherlands 🇳🇱, he actively maintains Starlette 🌟 and Uvicorn 🦄, contributing significantly as a senior engineer at Pydantic 🤓. Marcelo also shares insights about Python and FastAPI via his YouTube channel 🎥.

Principal Data Scientist at Merck KGaA Darmstadt, Germany
Interested in combining machine learning, data science, computational natural science, and cheminformatics.

Martin Seeler is the approachable tech enthusiast from next door who effortlessly bridges the gap between cutting-edge AI and practical customer solutions. As a Senior Staff Engineer at Blue Yonder, he spearheads Generative AI initiatives, crafting solutions that genuinely benefit customers rather than just riding the hype train. With a rich background in software development across various industries, Martin thrives as a tinkerer who delves into research papers and develops proof-of-concepts. His passion lies in harmonizing customer needs with state-of-the-art Generative AI solutions, ensuring technology serves as a tool for meaningful progress.

Martin is a data-scientist/engineer at QuantCo. He is mainly working on developing the software packages that Quantco uses for insurance risk modeling and pricing. This includes QuantCo's open-source generalized linear modeling package, glum.

He has a background in economics, and has previously worked at the Central Bank of Hungary as an applied researcher. He also taught a number of 'Programming for Economists' courses for college and PhD students.

Matthias Niehoff works as Head of Data and Data Architect for codecentric AG and supports customers in the design and implementation of data architectures. His focus is on the necessary infrastructure and organization to help data and ML projects succeed.

I’m a Senior Software Developer in the team behind SAP’s huge CI/CD infrastructure for SAP HANA.
We design, implement, operate and maintain it's cloud native graph-based task execution framework leveraging 2000 compute nodes in multiple data centers and cloud provider regions.
In my spare time, I like to play Dungeons & Dragons.

Software tinkerer, stumbling through software creation, with a deep enthusiasm for history and understanding human migration.

Mia Chang is a GenAI/ML Specialist Solutions Architect for Amazon Web Services. She shares best practices for running GenAI/ML workloads through customer engagements, public speaking, blog posts, and authoring books. She works in a multi-culture environment with customers in EMEA, which brings her to see technology with different culture lens. In her free time, Mia spends time mentoring aspired data scientists, and she enjoys traveling, hiking, board games, and meditation.

Michael co-founded MOSTLY AI in 2017, led the company as CEO until 2020, and then transitioned to the CTO role. Michael is a world class data scientist who held leading positions at Microsoft and Nokia before founding MOSTLY AI. He was awarded with the Global Marketing Research Award by the American Marketing Association. He holds a PhD degree from the Vienna University of Economics and Business and a Master degree from the Vienna University of Technology. Michael is a proud dad of two daughters and passionate for all kinds of sports including running, biking and baseball.

Mihail Douhaniaris is a Senior Data Scientist at GetYourGuide, where he specializes in improving the marketplace ranking algorithms to improve search relevance. His work helps travelers find experiences that match their preferences more effectively. Beyond his role, Mihail is deeply interested in responsible AI, ML observability, and the challenges of deploying machine learning at scale.

Mika is a Berlin-based lifeform mostly working with devops, distributed systems and Apache Flink. She also loves Rust, making ceramics and baking bread.

I've been a Python user since 1999, teaching Python professionally since 2004.
I am also active in the community, organizing Python conferences such as
PyCon DE, EuroSciPy, and BarCamps.
I am a PSF Fellow, PSF Community Service Award winner,
and chair of the German Python Software Verband.

Machine Learning Engineer at Schwarz IT, Germany, where I'm passionate about harnessing the power of AI to revolutionize the retail industry

I currently work as a Software Engineer at Aleph Alpha. Before joining Aleph Alpha, I founded WeGlide and worked on error back-propagation in Spiking Neural Networks. I enjoy spending time outdoors and flying gliders.

Natalie co-founded Lavrio.solutions, a company specializing in AI implementation. Since then, she has helped numerous organizations integrate AI into their processes and optimize their workflows. She has also conducted AI training sessions for businesses and professionals, bridging the gap between technical innovation and real-world usability.

Nico works as a Senior Machine Learning Engineer at Merck, focusing on developing applications powered by LLMs. His background bridges software engineering and data science, with experience spanning classical data science, computer vision, and discrete optimization, where he has deployed several machine learning solutions in production environments.

I am a Data Scientist primarily focused on Deep Learning and MLOps. In my spare time I contribute to several open-source python libraries.

For the past 3 years, I have been working on machine learning and data engineering and QuantCo. Previously, I studied computer science at the Technical University of Munich, focusing on machine and deep learning.

A researcher in Topological Data Analysis (TDA) working on both its theoretical aspects and applications. I have completed my PhD at ISTA in Austria and then moved to Inria in France to apply the TDA methods to spatial transcriptomics data.

Freelance backend software and data engineer. I try to make data behave the way it needs to by finding data quality problem and building custom software solutions to automate data processing.

I’m a wholehearted explorer and community-driven developer, advocating for FOSS while blending art, technology, and inclusion.

Data Nerd & Python Pydata community lover. AI education specialist with five years of experience shaping data science and AI educational offers. Currently leading the AI Academy at the appliedAI Institute for Europe.

Paul studies Computer Science at the KIT in Karlsruhe.
Alongside his studies, he works part-time at QuantCo.

Pavithra Eswaramoorthy is a Developer Advocate at Quansight, where she works to improve the developer experience and community engagement for several open source projects in the PyData community. Currently, she maintains the Bokeh visualization library, and contributes to the Nebari (adjacent to the Jupyter community), and conda-store (part of the conda ecosystem).

Pavithra has been involved in the open source community for over 5 years, notable as an emeritus contributor to the Dask library and Wikimedia Foundation projects. In her spare time, she enjoys a good book and hot coffee. :)

Hacker-maker, specialising in system infiltration and enhancement. Expert in reverse engineering, distributed systems architecture, and AI integration. Proven track record in high-stakes technical operations and system security.

Hey, I am Raana!

Some days, I am a Data Scientist with a passion for patterns, and other days, I am a Data Engineer with a love for code refactoring. I am also interested in methods for team building.

Besides the nerdy stuff, I enjoy board games, bouldering, and singing in a choir!

Rahkakavee Baskaran studied Political Science and Social and Economic Data Science at the University of Konstanz. At &effect, she works as a Data Scientist, Machine Learning Engineer, and Backend Developer, with over four years of experience in Natural Language Processing (NLP).
Her work focuses on leveraging data science and software development to create social impact, particularly in projects related to social sciences and the public sector.

Hello! I am Raphael Hviding, a Postdoctoral Researcher in the Data Science Department at the Max-Planck Institute for Astronomy.
Scientifically I am interested in studying the lives of galaxies beyond our own Milky Way, how they formed, and the role that supermassive black holes play in governing galaxy evolution.
Computationally my skills are in workflow management for complex data processing pipelines and in data-driven Bayesian modelling of astronomical data.

Just another Python nerd with a freshly gained enthusiasm for image gen AI. I'm working as a Data Engineer for nearly three years with focus on computer vision topics.

I earned both my Bachelor's and Master's degrees in Physics from the University of Heidelberg, specializing in Condensed Matter Physics and Computational Physics. During my Master's thesis in 2020, I advanced existing NLP Transformer architectures for timeseries applications where I worked extensively with uncertainty quantifications and normalizing flows. Since the beginning of 2021, I have been employed at Paretos, where the primary focus of my work lies in Timeseries Forecasting, specifically demand forecasting. Since 2023, Im leading the AI team at paretos which is giving me a good opportunity to combine my leadership skills with our super interesting research in scalable time series forecasting & optimization applications.

I speak & write about my experiences in the world of data & AI. This comes from the perspective of having worked across data science, data engineering and ML engineering in start-ups, scale-ups and enterprises.

My first pieces of code ran on Atari ST machines. I had the chance to see the Internet baby say its first words while I was starting to get interested in building software. I'm a proud Software Craftsman and Open-Source Software advocate. I spend a few of my other lifes playing afro-cuban & jazz music, or playing some go games.

Rostislaw, a data architect at RATIONAL AG, specializes in distributed databases, the Apache Hadoop ecosystem and Azure cloud. He leverages his expertise to oversee the company's Data & Analytics platform, where his daily work involves reconciling diverse stakeholder perspectives to deliver optimal solutions.

Rotem Tamir (39), father of two. Co-founder and CTO of Ariga, creator of Atlas, an open-source database schema as code tool.

After studying robotics and working in the field for some years, I've noticed that package management was one of the bigger unsolved issues in Robotics, so I joined prefix.dev to solve that issue!
Currently, I'm a core maintainer of pixi and take on a big part of the community management.

Born in Iran, I have embraced diverse roles throughout my career, ranging from founding a startup and software development to consulting companies on cloud migrations and integrating machine learning technologies into their operations. My professional journey has been shaped by a passion for problem-solving and innovation across various domains.

Academically, I hold a Ph.D. in particle physics, specializing in Higgs boson precision measurements as part of the CMS experiment at CERN's Large Hadron Collider. This experience honed my analytical skills and gave me a deep appreciation for collaboration in high-stakes, cutting-edge environments.

Today, I draw on my multidisciplinary background to create solutions at the intersection of software, data science, and high-performance computing, continually seeking to bridge theory and practice in impactful ways.

Sanket is a data scientist based out of New Delhi, India. He likes to build data science tools and products and has worked with startups, governments, and organisations. He loves building community and bringing everyone together and is Chair of PyData Delhi and PyData Global.

Currently, he's taking care of the community and OSS at Zarr as their Community Manager.

When he’s not working, he likes to play the violin and computer games and sometimes thinks of saving the world!

Sebastian Folz works as a machine learning engineer at DB Systel GmbH. His tasks also include project management and contributing in works groups around AI topics. He also has contributed to open source projects in the past. Sebastian can often be found at meet-ups around Python and machine learning in Karlsruhe.

Semona is a Developer Advocate at Okta. She enjoys chatting about OpenID Connect, OAuth 2.0, and web security, but most of all, learning how developers learn best. Outside work, Semona is a Pythonista, loves kombucha, and plays board/role-playing games and Ultimate!

Dr. Silke Horn is a Mathematical Optimization QA Engineer with the Gurobi Optimizer team. She began her journey at Gurobi in 2018 in the technical support team and transitioned to R&D in 2024. She holds a Ph.D. in Mathematics from TU Darmstadt (Germany) and has many years of experience in academic teaching and software development.

Dr.-Ing. Simonas Černiauskas is the founder and CTO of tisix.io, specializing in developing practical LLM solutions for media and publishers. With a doctorate from RWTH Aachen and experience as a principal researcher at Research Center Jülich, he combines deep technical expertise with hands-on implementation experience. His work focuses on multi-modal content generation and media processing. Drawing from his background in mechanical engineering, quality assurance and machine learning engineering, Simonas develops scalable AI solutions while maintaining a strong focus on quality assurance and risk management. He regularly shares insights through speaking engagements and technical publications, helping organizations navigate the complexities of AI implementation with practical, business-focused approaches.

Trained as a mathematician, I quickly delved into the world of machine learning and computational statistics to learn about more about cancer dynamics in molecular biology and patient data.
I currently work as a Machine Learning Engineer in the domains of Med-Tech, optics, and semi-conductors at Carl Zeiss AG.

Sohan is a Lead Developer Advocate at AuthZed, based in the Netherlands. He started his career as a developer building mobile apps and has worked in the developer relations space since 2013, in companies such as Amazon, Fermyon and Gupshup. He has always been interested in emerging technologies and how it shapes the world around us.

His interests outside work include visual arts, trivia, and playing frisbee.

Sonam is the creator of the open-source library called Embed-Anything, which helps to create local and multimodal embeddings and index them efficiently to vector databases, it’s built in rust and thus it’s more greener and efficient. She works as the GenerativeAI Evangelist at Articul8, spun-off of Interl, Articul8 is the go-to generativeAI platform for enterprise.

Experienced platform engineer and architect with a passion for open source and developer tools. The author of Cadwyn -- a sophisticated API Versioning framework based on FastAPI. A contributor to numerous projects such as CPython and tortoise-orm. Currently building the future of finance at Monite.

Tanu is a Software Engineer at Bloomberg on the BQL (Bloomberg Query Language) team. BQL provides intelligent query suggestions to empower users for efficient data exploration. A passion for crafting clean, maintainable, and efficient software solutions fuels her work in this role and throughout her career. She has a Master's degree in Distributed Systems and 6 years of industry experience building scalable systems. She is a tech writer for Medium, has organized hands-on workshops and delivered technical presentations internally for 100+ people . She is passionate about staying on top of tech and sharing knowledge at conferences. In her free time, Tanu enjoys traveling and playing music.

Tereza Iofciu is data leadership coach and a data practitioner She has more than 15 years of experience in Data Science, Data Engineering, Product Management and Team Management. Alongside that she spent most of those years volunteering in the Python Community and wears many hats: PyLadies Hamburg organizer, Python Software Verband board member, Python Software Foundation Code of Conduct team member, Diversity & Inclusion working group member, PyConDE & PyData Berlin organizer, Python Pizza Hamburg organizer, and PyPodcats co-leader. In 2021 Tereza was awarded the Python Software Foundation community service award.

Theodore Meynard is a data science manager at GetYourGuide.He leads the evolution of their ranking algorithm, helping customers to find the best activities to book and locations to explore. Beyond work, he is one of the co-organizers of the Pydata Berlin meetup and the conference.
When he is not programming, he loves riding his bike, looking for the best bakery-patisserie in town.

Hi, I’m Thomas Berger! I work as a Machine Learning Engineer at a FinTech company and also teach part-time as a lecturer. I’ve been working with Python for over six years, starting during my studies, where I focused on machine learning. For the last three years, I’ve been applying these skills professionally in my full-time role as a Machine Learning Engineer. I’ve been diving deep into Python for things like machine learning, reinforcement learning, and high-performance computing. I love finding ways to make Python run faster and more efficiently, especially when tackling big data or complex models.

At PyCon, I’ll be talking about high-performance Python and sharing tips and tricks to help you optimize your code for demanding tasks. I’m excited to share what I’ve learned and connect with others in the Python community!

Thomas Mayer holds a PhD in Quantitative Language Comparison and brings a profound background in Machine Learning and Natural Language Processing (NLP) to his work. As Team Lead in the Data Intelligence team at HolidayCheck, Thomas combines his passion for data-driven insights with his expertise in linguistics and AI to drive innovation in the travel industry. With a deep understanding of both technical and business challenges, he plays a pivotal role in leveraging data to enhance customer experiences and inform strategic decisions.

Thomas is an expert in tech transfer and startup development, with a career focused on fostering innovation and bridging the gap between research and industry. He has led initiatives like accelerator programs, innovation networks, and hackathons. A Generative AI enthusiast and co-founder of neunzehn innovations, Thomas helps companies leverage AI technologies. He holds a doctorate from the University of Basel and is a dedicated advisor, educator, and speaker in the startup ecosystem.

I'm a data scientist, machine learning engineer, AI developer, or whatever else you want to call it. After finishing my PhD I am now working as a consultant at Dataciders ixto, where I'm helping our customers to never make wrong decisions again.

Tim is a Data Engineer at Cloudflight, based in Innsbruck. There he architects and builds modern data infrastructures in customer projects, ranging from streaming ETL pipelines to data catalogs and entire data platforms. His focus areas include software engineering, cloud technologies, data platform engineering, and DataOps. Tim is also a passionate Open Source contributor, actively working on projects like Apache StreamPipes and DataHub, among others.

I am a scikit-learn core maintainer and work at NVIDIA.

Before working on scikit-learn I helped build mybinder.org and worked on JupyterHub.

Many years ago I was a particle physicist at CERN in Geneva.

I am currently working as a Senior Data Scientist at Ailio. My focus is on helping improve organizations by better utilizing their data. I contribute to these transformation projects by bringing in my broad expertise in data related topics ranging from data engineering and cloud-development (AWS, Azure) over data science and machine learning to communication and leadership skills.

After completing my masters in chemistry, I really started my journey in the data science and machine learning field during my PhD studies in theoretical chemistry. The next step for me was a role as a data scientist in a company developing software in the IT-Security field. For five years, I worked on a system to detect suspicious e-mail traffic using machine learning. Set aside the technical aspect of the job, I also built a small team. From this experience I learnt a lot about leadership and developing software products on a larger scale.

I strongly believe that using the right data to inform important decisions helps organizations of all kinds improve. However, often this is easier said than done. I am always curios to discover and tackle these interesting challenges. Also, I am more than happy to sharing my knowledge and learnings.

Tuhin Sharma is Senior Principal Data Scientist at Redhat in the Data Development Insights & Strategy AI team. Prior to that, he worked at Hypersonix as an AI architect. He also co-founded and has been CEO of Binaize (backed by Techstars), a website conversion intelligence product for e-commerce SMBs. Previously, he was part of IBM Watson where he worked on NLP and ML projects featured on Star Sports and CNN-IBN. He received a master's degree from IIT Roorkee and a bachelor's degree from IIEST Shibpur in Computer Science. He loves to code and collaborate on open-source projects. He is one of the top 20 contributors of pandas. He has 4 research papers and 5 patents in the fields of AI and NLP. He is a reviewer of the IEEE MASS conference, Springer nature and Packt publication in the AI track. He writes deep learning articles for O'Reilly in collaboration with the AWS MXNET team. He is a regular speaker at prominent AI conferences like O'Reilly Strata & AI, ODSC, GIDS, Devconf, Datahack Summit etc.

I’m a data scientist and consultant specializing in Bayesian modeling in Civil Engineering, currently focusing on applying machine learning to anomaly detection in mechanical systems. My work also explores how machine learning and Bayesian methods can provide clearer insights in engineering applications. When I’m not working with data, you’ll probably find me swimming, cooking, or listening to anything from black metal to Japanese jazz.

Vince Nelidov is a Staff Data Science at Blue Yonder with diverse consulting experience in the data domain in a variety of industries from energy sector and banking to skincare and agriculture. Throughout his years in the data world, Vince has been combining advanced data science with business insights to make data work with an impact. He aspires to see far beyond what is on the surface and get to the essence of the problems, discovering robust and scalable long-term solutions rather than temporary fixes.

Vince is passionate about sharing his knowledge and insights, believing that Data literacy should not be a privilege of a few. And his goal is to be there to make this a reality. Making the intricacies of data science intelligible and uncovering the regularities hiding in the data is a major source of inspiration for Vince. With this goal in mind, he combines his years of experience in consulting with his background in statistics, research and teaching to make this knowledge accessible to businesses and individuals in need.

A results-driven data professional – focused on hype-free solutions tailored to business needs.

I am currently creating value at the National Institute of Geophysics and Volcanology (INGV), where I develop machine learning models in the Space Weather domain. My job is complemented by finding the hidden stories in data and make them accessible to stakeholders. I studied Physics in Italy (Napoli) and Germany (Frankfurt am Main), previously worked on Analytics in the strategic division of the world's largest professional services network, and in the Data Science department of the leading Italian publisher.

When not at work, I enjoy theatre, talking about finance or learning a new language.

Wolf Vollprecht has been active in the Python open source community for the past 5 years. He is a core member of conda-forge and the conda steering council, and the original author of the mamba package manager. He also has extensive experience in high-performance C++ and Rust. 2 years ago he started prefix.dev where the team is focusing all efforts on making cross-platform, language independent package management great (on top of the conda ecosystem).

Versatile data scientist with 3+ years of experience building AI-products at the service of the industry. I believe that the key for success revolves around embracing shared best practices, upholding high quality standards for code development and having a team composed of complementary skill sets.

Over the last five years living in Germany, during which I have gained a diverse range of experiences in the tech industry. My expertise spans from developing web applications in Python to constructing AWS cloud solutions. I have a good understanding of design patterns, Object-Oriented Programming (OOP), event-driven architecture, and microservices architectures, REST API design and database technologies. I have hands-on experience with creating a web application as part of Cloud Foundation framework to manage and secure AWS accounts and creating a lightweight web application to quickly generate and provide results to users.