Hi, I'm Abdeali Kothari - a.k.a Ali (if we're talking) or @AbdealiLoKo (if we're typing)
I graduated from IIT Madras and then worked with American Express, followed by Corridor Platforms where I am architecting a Decisioning platform for analytics in the Financial domain.

I've dabbled with Robotics, Operating System architectures, Machine Learning, Game Development, and Web Development a lot for a bunch of personal projects.
And worked mainly in Big Data, Machine Learning, and Analytics in the Financial Domain for enterprise-productional use-cases.

I'm a big fan of code hygiene and clean architecture. With a lot of Code Analytics experience under my belt.
And worked mainly in Python in all the above fields for about 13 years now (Back when the first blogpost telling us to stop using Python 2.x was written :D)

I'm extremely lazy - and hence an automation freak. And have created great automated test suites and CI/CD pipelines to help me remain lazy.

  • Monorepos with Python
Alejandro Saucedo

Alejandro is the Director of Engineering & Applied Science at Zalando where he leads a cross-functional technology organisation consisting of department heads, managers, principals and ICs across engineering and data science, and is responsible for the development of a large portfolio of (10+) products, the management of one of Zalando's large-scale central data platforms, and the productionisation of SOtA machine learning systems powering high-value & critical use-cases across the organisation. Alejandro is also the Chief Scientist at the Institute for Ethical AI & Machine Learning, where he contributes to policy and industry standards on the responsible design, development and operation of AI, and has led policy contributions including the EU's AI Regulatory Proposal, the Data Act, between others. With over 10 years of software development experience, Alejandro has held technical leadership positions across hyper-growth scale-ups and tech giants, with a strong track record of building cross-functional R&D and Product organisations. He is currently appointed as governing council Member-at-Large at the Association for Computing Machinery (ACM), and is currently the Chairperson of the ML Security Committee at the Linux Foundation.

Linkedin: https://linkedin.com/in/axsaucedo
Twitter: https://twitter.com/axsaucedo
Github: https://github.com/axsaucedo
Website: https://ethical.institute/

  • The State of Production Machine Learning in 2023
Aleksander Molak

For the last 6 years Alex worked as a machine learning consultant, engineer and researcher in the industry and academia. He helped designing and building machine learning systems for Fortune 100, Fortune 500 and Inc 5000 companies.

He’s an international speaker, blogger and author of a book on causality in Python. Interested in causality, NLP, probabilistic modeling, representation learning and graph neural networks.

Loves traveling with his wife, passionate about vegan food, languages and running.

Website: https://alxndr.io
LinkedIn: https://www.linkedin.com/in/aleksandermolak/

  • The Battle of Giants: Causality vs NLP => From Theory to Practice
Alexander CS Hendorf

Alexander Hendorf is responsible for data and artificial intelligence at the boutique consultancy KÖNIGSWEG GmbH. Through his commitment as a speaker and chair of various international conferences as PyConDE & PyData Berlin, he is a proven expert in the field of data intelligence. He's been appointed Python Software Foundation and EuroPython fellow for this various contributions. He has many years of experience in the practical application, introduction and communication of data and AI-driven strategies and decision-making processes.

  • 5 Things about fastAPI I wish we had known beforehand
Alexander Vosseler

Alexander Vosseler works as Principal Data Scientist at the Advanced Analytics Claims team of Allianz Germany - Chief Data Office in Munich. He has many years of industry experience as a data scientist and holds a PhD in Statistics with majors in Bayesian and Computational statistics. During his industry career as a data scientist he worked for companies such as Siemens AG, Allianz Global Corporate & Specialty SE and Allianz Germany.

His current methodological interests lies in probabilistic machine learning and uncertainty quantification with applications in time series methods, anomaly detection and NLP. In his spare time he likes to go jogging and play the drums.

  • BHAD: Explainable unsupervised anomaly detection using Bayesian histograms
Alicia Bargar

Alicia is a coding polyglot with over five years of professional engineering experience applied to R&D platform development and data engineering. As a Senior Data Developer at Shopify, Alicia works on the Machine Learning Platform team, working on designing and implementing data quality monitoring.

  • How to build observability into a ML Platform
Alina Bickel

Alina studies Data Science at University of Applied Sciences Karlsruhe and worked on the QA project within her internship semester at scieneers. Her passion lies in the extraction of knowledge using Data Science for the benefit of the public.

  • “Who is an NLP expert?” - Lessons Learned from building an in-house QA-system
Amit Verma

My name is Amit Verma, I have been working for Flixbus as Senior Data Engineer. I designed the dynamic pricing architecture which is currently being used in approximately 80% of market share. Before joining Flixbus, I worked in Cliqz: a Germany based search engine that was focused on user data privacy. Currently, this is used in brave search.

  • Dynamic pricing at Flix
Andreas Leed

As Head of Data Science at Oxford Global Projects, I have dedicated my career to improving project planning and decision making through the use of data-driven methods. In my role, I lead technical projects involving advanced techniques like natural language processing and machine learning, and am responsible for managing a database of project performance data from over 17,000 projects across all industries. This data is used to inform future projects and improve our understanding of project performance. In addition to my work at Oxford Global Projects, I serve as an external examiner for quantitative methods and data science courses at universities in Denmark.

My passion is to apply data science to the field of project management and help our clients achieve their objectives. I am constantly seeking new and innovative ways to do so and am excited to continue pushing the boundaries of what is possible. I have a strong track record of success, including leading external risk analysis on some of Europe's largest capital projects, contributing to project appraisal methodology for the UK Department for Transport, and presenting statistical analysis and results to senior management and high-level figures globally. I have also led work on a diverse range of projects, including the feasibility assessment of the first road between settlements in Greenland, the risk modeling of large scale nuclear new builds and decommissioning programs, and the development of an AI-based Early Warning System for the Development Bureau in Hong Kong. My expertise in data-driven project planning and risk analysis, as well as my ability to effectively communicate technical information to diverse audiences, have been key to my achievements in this field.

  • Accelerating Public Consultations with Large Language Models: A Case Study from the UK Planning Inspectorate
Anna Achenbach

After pursuing her PhD in Data Science Anna started her work at DPDHL back in 2018. With a background in Logistics from her Bachelor's and Master's studies Data Science at DPDHL combines what she enjoys most: Work with a group of talented
Machine Learning Experts and Analytics enthusiasts and develop projects to embed data (science)-
driven decision making deeply into our business processes. Besides regular project work Anna focuses on developing trainings for Non-Data Scientists ranging from data literacy to management trainings.

  • Delivering AI at Scale
Anna-Lena Popkes

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.

  • An unbiased evaluation of environment management and packaging tools
Antoine Toubhans

Python developer and Data-Scientist, I am Head of Science at Sicara since 2018.

I am also the organizer of the Paris Computer Vision Meetup.

Speaker at PyConUS22 and PyDataBerlin22.

  • Advanced Visual Search Engine with Self-Supervised Learning (SSL) Representations and Milvus
Antonia Scherz

Antonia Scherz is machine learning engineer and consultant at PD - Berater der öffentlichen Hand in Berlin. At PD she builds proof of concept tools and assists in software development for machine learning applications in public administration. She is passionate about making machine leanring and open software tools widely used by public administration and fascinated by how new tools can be integrated in old structures for the public good.

  • Unlocking Information - Creating Synthetic Data for Open Access.
Antonio Cuni

Dr. Antonio Cuni is a Principal Software Engineer at Anaconda. He is a core
developer of PyScript and PyPy, and one of the founders of the HPy project,
which aims to design a better and more modern C API for Python. He loves to
write tools from developers for developers, such as Pdb++, fancycompleter and
vmprof and he is creator/maintainer/contributor of numerous other open source
projects. He have also been very active in the Python community for years,
giving talks at various conferences such as EuroPython, EuroSciPy, PyCon
Italia, and many others. He regularly writes on the PyPy blog and on the HPy
blog. His main areas of interest are compilers, language implementation, TDD
and performance.

  • The CPU in your browser: WebAssembly demystified
Arnault Chazareix

Arnault Chazareix is a data scientist and engineering manager who has worked in the field of data science for more than 5 years. He has specialized in computer vision and natural language processing projects, and is passionate about working with unstructured data such as text and images. In addition to his professional work, Arnault is also passionate about Brazilian jiu-jitsu.

For the past 5 years, Arnault has been working at Sicara, a French start-up that helps customers build custom data solutions using data engineering and data science. Prior to working at Sicara, Arnault worked for Feedly, a Silicon Valley start-up that develops a news aggregation and curation software as a service (SaaS).

  • Visualizing your computer vision data is not a luxury, it's a necessity: without it, your models are blind and so do you.
Artem Kislovskiy

I am a software engineer based in Switzerland with a passion for data visualisation. This passion ignited as a student when I worked on various Computational Fluid Dynamics projects. After a few years of focusing on experimental physics in academia, I am now enjoying the opportunity to apply my skills in a real-world setting by building business analytics in my daily job.

  • The bumps in the road: A retrospective on my data visualisation mistakes
Asher Sterkin

Asher Sterkin is a 40-year industry veteran specializing in software architecture and technology. He currently serves as General Manager and Head of Engineering of BlackSwan Technologies’ BST LABS, which is developing the Cloud AI Operating System (www.caios.io), cloud infrastructure that incorporates Infrastructure from Code. Prior to this role, Asher served as a Distinguished Engineer at Cisco.

  • Cloud Infrastructure From Python Code: How Far Could We Go?
Avanindra Kumar Pandeya
  • FastAPI and Celery: Building Reliable Web Applications with TDD
Bruno Vollmer

I am the CTO of biped.ai, the AI Copilot for blind and visually impaired people that leverage advanced computer vision to guide them.

During my Masters at RWTH Aachen I worked at several Start-Ups as a software engineer. I've gained experience in Computer Vision and Machine Learning as well as general software engineering areas.

  • BLE and Python: How to build a simple BLE project on Linux with Python
Caner Turkmen

Caner Turkmen is a Senior Applied Scientist at Amazon Web Services, where he works on problems at the intersection of machine learning and forecasting, in addition to developing AutoGluon-TimeSeries. Before joining AWS, he worked in the management consulting industry as a data scientist, serving the financial services and telecommunications industries on projects across the globe. Caner’s personal research interests span a range of topics, including forecasting, causal inference, and AutoML.

  • AutoGluon: AutoML for Tabular, Multimodal and Time Series Data
Carsten Binnig

Carsten Binnig is a Full Professor in the Computer Science department at TU Darmstadt and a Visiting Researcher at the Google Systems Research Group. Carsten received his Ph.D. at the University of Heidelberg in 2008. Afterwards, he spent time as a postdoctoral researcher in the Systems Group at ETH Zurich and at SAP working on in-memory databases. Currently, his research focus is on the design of scalable data systems on modern hardware as well as machine learning for scalable data systems. His work has been awarded a Google Faculty Award, as well as multiple best paper and best demo awards.

  • Keynote - Towards Learned Database Systems
Cheuk Ting Ho

After having a career in data science, Cheuk now brings her knowledge of data and passion for the tech community as the developer advocate for Anaconda. Cheuk constantly contributes to the open-source community by giving free talks and tutorials and organising sprints to encourage diverse contributions.

  • Driving down the Memray lane - Profiling your data science work
Christian Bourjau

With a PhD in experimental particle physics, Christian has a passion for the intersection of
cutting-edge data science and modern software engineering. His work at QuantCo is centered
around creating efficient tools for data scientists with a clean and maintainable path toward
production. That pursuit has led him deep into ONNX and its related ecosystem over the last

  • Have your cake and eat it too: Rapid model development and stable, high-performance deployments
Christopher Prohm

Christopher is a data scientist and long-time Python user. Recently he started
using Rust for data projects and became interested in how to combine both

  • Pragmatic ways of using Rust in your data project
Clara Hoffmann

I'm a former ML Engineer in the geospatial domain and currently a Ph.D. student for trustworthy ML and Data Science at the RC Trust Ruhr. My main field of interest is Computer Vision and my guilty pleasure is assigning probability densities to all relevant variables in CV models. Application-wise I focus on Remote Sensing (Synthetic Aperture Radar) and Neuroscience (modeling trajectories of disease severity from MRI scans). I also collected a splash of experience in autonomous driving.
I'm classically trained in Bayesian Statistics and interested in combining Bayesian approaches with self-supervised learning and deterministic DNNs.

  • Honey, I broke the PyTorch model >.< - Debugging custom PyTorch models in a structured manner
Cole Bailey

I am leading a scrappy but growing team of ML engineers at Delivery Hero who aim to bridge the gap between software engineering, DevOps, data engineering, and data science. I hope to make data science easier without restricting the creativity and flexibility that data scientists need to make an impact in their role.

  • Cooking up a ML Platform: Growing pains and lessons learned
Corrie Bartelheimer

Corrie Bartelheimer first became interested in data when studying topological data analysis during her math Masters. After working a few years in Berlin and organizing the Berlin Bayesian meetups for a while, she moved to Brussels, Belgium where she now works as a Data Scientist in the hospitality industry. Her interests include, among others, Bayesian modelling, network analysis, data visualization and best practices for data science teams.
In her freetime, she enjoys cooking for friends and sampling new Belgium beers.

  • Code Cleanup: A Data Scientist's Guide to Sparkling Code
Damian Bogunowicz

Engineer, roboticist, software developer, and problem solver. Previous experience in autonomous driving (Argo AI), AI in industrial robotics (Arrival), and building machines that build machines (Tesla). Currently working in Neural Magic, focusing on the sparse future of AI computation.
Works towards unlocking creative and economic potential with intelligent robotics while avoiding the uprising of sentient machines."

  • Why GPU Clusters Don't Need to Go Brrr? Leverage Compound Sparsity to Achieve the Fastest Inference Performance on CPUs
Daryna Dementieva

I am a postdoctoral researcher at TUM. Currenlty, I am involved into the project of eXplainable AI. In 2022, I obtained my PhD under the supervision of Pr. Alexander Panchenko, Skoltech. My PhD research was connected with such important sociological issues as Fake News Detection and Texts Detoxification. More broadly, I am super interested in the NLP for Social Good research direction. Besides academical experience, I also was involved in several industrial projects in different companies: Visiology, Moscow, Russian Federation; Beiersdorf, Hamburg, Germany. Now, obtained industrial experience helps me a lot in my research.

  • Methods for Text Style Transfer: Text Detoxification Case
David Andersson

I started as a web developer after university with an Australian telco developing websites using Python and JavaScript. After a few years, I switched to product management looking after developer telco products such as an API for sending and receiving SMS where I overhauled the developer portal improving the developer experience. Then I switched back to engineering leadership looking after a team that was creating private and public cloud products where I launched a new private cloud product.

After a few years in the telco industry, I switched to Canonical where I lead a team of developer automating operations using and creating open source tooling.

  • Giving and Receiving Great Feedback through PRs
Dishant Sethi

I am a software engineer who loves being a problem solver. I am equipped with experience in web development, Cloud Engineering, and DevOps. I am self-motivated and able to work independently with minimal supervision. My experience in software development from open-source contributions, internships, and personal projects gives me confidence in my ability to be fit for the role.

I am passionate about supporting the education system and meeting new people. I believe in free and open information/internet access for everyone.

Interested in opportunities to contribute as:
♦ Web Developer
♦ System / Cloud Engineer
♦ DevOps

Talk to me about:
♦ Web Development Practices
♦ Free and Open Source Software (FOSS) Community
♦ Starting Software Engineering Journey

  • Introduction to Async programming
Dr. Thomas Wiecki

CEO and founder of PyMC Labs - the Bayesian consultancy that solves your most challenging data science problems. Co-author of PyMC, the industry standard Bayesian modeling library for Python.

  • Bayesian Marketing Science: Solving Marketing's 3 Biggest Problems
Ellen König
  • A concrete guide to time-series databases with Python
Emeli Dral

Emeli Dral is a Co-founder and CTO at Evidently AI, a startup developing open-source tools to evaluate, test, and monitor the performance of machine learning models.

Earlier, she co-founded an industrial AI startup and served as the Chief Data Scientist at Yandex Data Factory. She led over 50 applied ML projects for various industries - from banking to manufacturing. Emeli is a data science lecturer at GSOM SpBU and Harbour.Space University. She is a co-author of the Machine Learning and Data Analysis curriculum at Coursera with over 100,000 students.

  • Staying Alert: How to Implement Continuous Testing for Machine Learning Models
Erin Mikail Staples

Erin Mikail Staples is a very online individual passionate about facilitating better connections online and off. She’s forever thinking about how we can communicate, educate and elevate others through collaborative experiences.

Currently, Erin is a Senior Developer Community Advocate at Label Studio. At Label Studio — she empowers the open-source community through education and advocacy efforts. Outside of her day job, Erin is a comedian, graduate technical advisor, content creator, triathlete, avid reader, and dog parent.

Most importantly, she believes in the power of being unabashedly "into things" and works to help friends, strangers, colleagues, community builders, students, and whoever else might cross her path find their thing.

  • Improving Machine Learning from Human Feedback
Etzik Bega
  • Cloud Infrastructure From Python Code: How Far Could We Go?
Felix Wick

I received my PhD in high energy physics at the Karlsruhe Institute of Technology in 2011. Then I joined Blue Yonder, a provider of cloud-based predictive applications for the retail market, where I led the Machine Learning core team and developed, among other things, new methods for demand forecasting and shaping. In 2018, Blue Yonder got acquired by JDA (subsequently re-branded to Blue Yonder), a leading provider of supply chain management software, and in 2021, the merged company got, in turn, acquired by Panasonic. As Corporate Vice President and Blue Yonder fellow, I am now advising on overall Data Science strategies and driving research toward an autonomous supply chain powered by Artificial Intelligence. Moreover, I am lecturer for Machine Learning at the Karlsruhe Institute of Technology.

  • Exploring the Power of Cyclic Boosting: A Pure-Python, Explainable, and Efficient ML Method
Florian Wilhelm

Data Scientist and Python developer with a strong mathematical background. Always looking to apply mathematics to real-world problems and enthusiastic about everything math.

  • WALD: A Modern & Sustainable Analytics Stack
Gregor Riegler

I’m a Software Development Coach and Crafter on a lifelong journey to learn better ways to develop quality software. I like to practice with friends and teach and share what I learned. My goal is to help people find joy in their work and become better at developing software.

  • Data Kata: Ensemble programming with Pydantic #1
  • Data Kata: Ensemble programming with Pydantic #2
Guido Imperiale

I come from a 12 years career in orchestrating Monte Carlo simulations for finance, sized at 1500+ CPU hours each. For the last two years I've been an OSS engineer at Coiled, building up the foundations of the Dask library.

  • Data-driven design for the Dask scheduler
Guillem Borrell

PhD, MS, Aerospace Engineering. Previously researching on Turbulence Theory and Simulation. Now at BCG X helping clients take the most out of data and AI

  • Most of you don't need Spark. Large-scale data management on a budget with Python
Gunar Maiwald

Gunar Maiwald has a background in Computer Science. For the last 3 years he worked as an ML engineer at idealo.de. His professional programming path led him from Perl via TypeScript to Python.

  • Machine Learning Lifecycle for NLP Classification in E-Commerce
Heiner Tholen

Heiner leads the truck-IoT effort at alcemy GmbH, where he's responsible for hard- and software. He holds a PhD in Physics and has a knack for building things that open a new dimension for their users.

  • A concrete guide to time-series databases with Python
Hendrik Makait

Hendrik Makait is a data and software engineer building systems at the intersection of large-scale data management and machine learning. Currently, he works as an Open Source Engineer at Coiled improving Dask and its distributed execution engine.

  • Observability for Distributed Computing with Dask
Ines Montani

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

  • Incorporating GPT-3 into practical NLP workflows
Inga Janczuk

A data scientist with a background in economics and econometrics. Currently working at OLX Group in Berlin, focusing on designing and deploying solutions for marketing optimization and automation.

  • When A/B testing isn’t an option: an introduction to quasi-experimental methods
Jakub Bachurski

Currently studying Computer Science at the University of Cambridge, Jakub’s interests are primarily in algorithm design and programming languages. He put those interests to use designing the Spox framework for ONNX as a Software Engineer at QuantCo.

  • Have your cake and eat it too: Rapid model development and stable, high-performance deployments
Jens Agerberg

Jens is pursuing a PhD in Machine Learning and Topological Data Analysis at KTH Royal Institute of Technology in Stockholm, Sweden, while also working as a data scientist at Ericsson.
He believes that an important property that sets humans apart from other animals is that we have a sense of geometry and topology. Teaching computers a sense of geometrical recognition and reasoning is thus a promising direction if we want to develop more powerful AIs.

  • Teaching Neural Networks a Sense of Geometry
Jens Nie

A physicist who has filled a variety of roles in a leading service company in the oil and gas industry, currently tackling the development of embedded devices based on the Raspberry Pi, LinuX and Python with a Python history going back to version 1.4.

  • Accelerating Python Code
Jeremy Tuloup

Jeremy Tuloup is a Technical Director at QuantStack and a Jupyter Distinguished Contributor. Maintainer and contributor of JupyterLab, JupyterLite, Jupyter Notebook, Voilà Dashboards, and many projects within the Jupyter ecosystem.

  • The future of the Jupyter Notebook interface
  • Create interactive Jupyter websites with JupyterLite
John Sandall

John Sandall is the CEO and Principal Data Scientist at Coefficient.

His experience in data science and software engineering spans multiple industries and applications, and his passion for the power of data extends far beyond his work for Coefficient’s clients. In April 2017 he created SixFifty in order to predict the UK General Election using open data and advanced modelling techniques. Previous experience includes Lead Data Scientist at YPlan, business analytics at Apple, genomics research at Imperial College London, building an ed-tech startup at Knodium, developing strategy & technological infrastructure for international non-profit startup STIR Education, and losing sleep to many hackathons along the way.

John is also a co-organiser of PyData London, co-founded Humble Data in 2019 to promote diversity in data science through a programme of free bootcamps, and in 2020 was a Committee Chair for the PyData Global Conference. He is currently a Fellow of Newspeak House with interests in open data, AI ethics and promoting diversity in tech.

  • Postmodern Architecture: The Python Powered Modern Data Stack
Jonathan Brandt

Hi :)
I'm working as a Data Scientist since one year, mainly on topics of natural language processing and timeseries forecasting.
Before that I studied physics in Heidelberg.

  • Bringing NLP to Production (an end to end story about some multi-language NLP services)
Joris Van den Bossche

I am a core contributor to Pandas and Apache Arrow, and maintainer of GeoPandas. I did a PhD at Ghent University and VITO in air quality research and worked at the Paris-Saclay Center for Data Science. Currently, I work at Voltron Data, contributing to Apache Arrow, and am a freelance teacher of python (pandas) at Ghent University.

  • Pandas 2.0 and beyond
  • Apache Arrow: connecting and accelerating dataframe libraries across the PyData ecosystem
Jürgen Gmach

I am a software developer with a passion for Python and Linux, developing open source software both at my day job at Canonical, and at night as a maintainer of tox and many other projects.

  • Behind the Scenes of tox: The Journey of Rewriting a Python Tool with more than 10 Million Monthly Downloads
Katrin Reininger

With a background in physics, Katrin discovered her enthusiasm for data analysis while exploring laser-molecule interactions during her PhD. Hence, she left science to become a consultant at I-WUNDER. Since 2020 she mainly manages projects in the area of data science and software development. Besides, Katrin has a passion for exploring new (project) management techniques and running workshops.

  • How Chatbots work – We need to talk!
KIlian Kluge

My journey into Python started in a physics research lab, where I discovered the merits of loose coupling and adherence to standards the hard way. I like automated testing, concise documentation, and hunting complex bugs.

I completed a PhD on the design of human-AI interactions and now work to use Explainable AI to open up new areas of application for AI systems.

  • Grokking Anchors: Uncovering What a Machine-Learning Model Relies On
Kolja Maier

I love architecting & building data products that have business impact. Drilling into business domains and leveraging data to thrive the business excites me. Passionate about shaping company culture around and towards data.

  • Specifying behavior with Protocols, Typeclasses or Traits. Who wears it better (Python, Scala 3, Rust)?
Larissa Haas

I am a Senior Data Scientist working at sovanta AG in Heidelberg. With university degrees in Political Science and Data Science, I combine ethical and business views on NLP projects. My latest projects dealt with combining Machine Learning approaches with SAP technologies. Besides that, I care about AI in Science Fiction, Bullet Journaling, and bringing Roundnet to the Olympic Games.

  • Bringing NLP to Production (an end to end story about some multi-language NLP services)
Lea Petters

Data Scientist & Data PM @ inovex | PhD Behavioral Economics | special interests: data ethics, causality, mathematical modeling, data strategy

  • What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products
Leonard Püttmann

Leonard Püttmann studied economics at the Hochschule Düsseldorf. During a specialization course there he fell in love with all things ML, especially when it comes to natural language processing. After studying, he joined the company Kern AI as a data scientist and now works as a developer advocate, where he is connecting people to topics like ML and programming.

  • Contributing to an open-source content library for NLP
Lev Konstantinovskiy

Lev Konstantinovskiy is an experienced data science and software engineering team lead. Long time ago he used to maintain a python Natural Language Processing library gensim.

  • Prompt Engineering 101: Beginner intro to LangChain, the shovel of our ChatGPT gold rush."
  • Data Kata: Ensemble programming with Pydantic #1
  • Data Kata: Ensemble programming with Pydantic #2
Lisa Andreevna Chalaguine

Originally from Belarus, I currently live in London and work as a data scientist at ProcureAI. I did my PhD at University College London, where I used to develop algorithms for chatbots that can engage in argumentative dialogues, trying to persuade the user to accept the chatbot's stance. My expertise therefore mainly lies in knowledge acquisition/representation and, of course, natural language processing. I also have over 10 years of experience in teaching and tutoring. I am also a tutor at The Profs, and a member of the part-time tutor panel at the University of Oxford in the Department of Continuing Education.

  • How to teach NLP to a newbie & get them started on their first project
Luis Fernando Alvarez

Hi! I’m Luis Fernando Alvarez, Engineering Manager at Stack Builders. I’ve been working in the Software development industry for more than 15 years, both as a full-stack developer and tech lead in multiple projects, with a varied number of technologies and languages. I’m passionate about Software Development and helping younger engineers grow. I’m also a multi-instrumentalist musician, videogame lover, and cooking enthusiast.

  • How to connect your application to the world (and avoid sleepless nights)
Marcus Tedesco

Tech Lead at Briink, accelerating sustainable finance with machine learning!

Previously Senior Software Engineer at Babbel and Senior Software Engineer and Cloud Architect on the Emerging Technology team at Accenture.

  • Neo4j graph databases for climate policy
Maren Westermann

Dr Maren Westermann works as a machine learning engineer and holds a PhD in environmental science. She is a self taught Pythonista, an active open source contributor, especially to the library scikit-learn, and is a co-organiser of PyLadies Berlin where she hosts monthly open source hack nights.

  • How to increase diversity in open source communities
Marianne Stecklina

As a deep learning engineer at omni:us, I'm working on different NLP topics related to document understanding.

  • Using transformers – a drama in 512 tokens
Martin Christen

Martin Christen is a professor of Geoinformatics and Computer Graphics at the Institute of Geomatics at the University of Applied Sciences Northwestern Switzerland (FHNW). His main research interests are geospatial Virtual- and Augmented Reality, 3D geoinformation, Deep Learning, and interactive 3D maps.
Martin Christen is very active in the Python community. He teaches various Python-related courses and uses Python in most research projects. He organizes the PyBasel meet up - the local Python User Group Northwestern Switzerland. He also organizes the yearly GeoPython conference. He is a board member of the Python Software Verband e.V.

  • Geospatial Data Processing with Python: A Comprehensive Tutorial
Martin Grund

Martin Grund is a Senior Staff Software Engineer and Tech Lead at Databricks working at the intersection between query processing, data governance and security. He's currently leading the design and engineering efforts for Spark Connect as part of Apache Spark. Martin has previously led the engineering for Amazon Redshift Spectrum and worked on Cloudera Impala. He holds a PhD in computer science from the Hasso-Plattner-Institute in Germany.

  • Use Spark from anywhere: A Spark client in Python powered by Spark Connect
Martin Wistuba

Martin Wistuba is a researcher at Amazon Web Services where he works on automation of hyperparameter optimization and Neural Architecture Search. Earlier, he was at IBM Research, where he developed tools to automate deep learning.

  • Hyperparameter optimization for the impatient
Mathis Lucka

Building great products for NLP developers at deepset. Been a PM and NLP Engineer for 5 years. On a mission to make sure that every developer can incorporate NLP features into any product that needs it.

  • Building a Personal Assistant With GPT and Haystack: How to Feed Facts to Large Language Models and Reduce Hallucination.
Matthias Fey
  • Practical Session: Learning on Heterogeneous Graphs with PyG
Maxim Danilov

more than 24 years in development start with RISC assembler grows to python/Django/VueJs through C, VB, PHP, Jquery

  • What are you yield from?
Max Kahan

I'm a Python Developer Advocate and Software Engineer at Vonage (ex-IBM). I'm interested in communications APIs, machine learning, open-source, developer experience and dancing! My training is in Physics, and now I use my problem-solving skills daily, working on open-source projects and finding ways to make developers’ lives better.

  • Fear the mutants. Love the mutants.
Michael Gorkow

Michael is Field CTO for Datascience at Snowflake where he helps organisations to implement state of the art machine learning solutions. As a data science professional, he is passionate about sharing with others how to go beyond standard use cases and implement machine learning techniques for big data. 
He is based out of Munich, Germany.

  • Large Scale Feature Engineering and Datascience with Python & Snowflake
Michele Dallachiesa

Michele is a freelance data scientist based in Munich. He implemented solutions for Contact Center Forecasting, Marketing Attribution, Out-Of-Home Advertising, Natural Language Processing, Forecasting and Classification Models, Robots Autonomous Charging, Urban Traffic Optimisation, and other AI services for the governments of the United Kingdom and Hong Kong, and private clients including Google, NASA, Stanford University, Huawei, Taxfix, Wayfair, Telefónica, and others. He holds a Ph.D. in computer science earned for his research with the University of Trento, the IBM T.J. Watson Research Centre, and the Qatar Computing Research Institute on querying, mining, and storing uncertain data, with a particular interest in data series. He co-authored ten papers in top-tier publications on data management, including SIGMOD, VLDB, EDBT, KAIS, and DKE.

  • Accelerating Public Consultations with Large Language Models: A Case Study from the UK Planning Inspectorate
Mike Müller

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 and chair of the German Python Software Verband.

  • Aspect-oriented Programming - Diving deep into Decorators
Miroslav Šedivý

Miro is using Python to make the sun shine and the wind blow.

Born in Czechoslovakia, he has lived in France, Germany, and Austria and therefore understands a bunch of European languages. With 20+ years of Linux experience and coding with Python since version 2.5, Miro has dedicated most of his career building complex systems using open-source software and libraries to forecast, process, and analyze power generation and distribution data.

Miro is also a big fan of OpenStreetMap and helps fill in the gaps on the world map. As a reviewer of the books “Modern Vim” and “Fluent Python (2nd ed.)”, he loves sharing his expertise on the best tools for daily tasks. In 2021, Miro was named a Fellow of the Python Software Foundation.

  • Keynote - Lorem ipsum dolor sit amet
Nandana Sreeraj

Nandana is a data scientist at Censius AI. She had completed her bachelors degree from College Of Engineering, Trivandrum. She had previously worked in the e-commerce industry where she had to deal with real world problem statements including product ranking and recommendation systems. She had published a research paper in health care domain in an international journal. Currently, her research interests are aligned to the Explainable AI domain.

  • Thou Shall Judge But With Fairness: Methods to Ensure an Unbiased Model
Nico Kreiling

Nico is a Data Scientist at scieneers, co-organizer of PyData cologne meetup and host of the Techtiefen podcast. His passions are quick and simple solutions and the constant expansion of his and the communities' knowledge base.

  • “Who is an NLP expert?” - Lessons Learned from building an in-house QA-system
  • Raised by Pandas, striving for more: An opinionated introduction to Polars

As CTO of Heartex / Label Studio, I specialize in machine learning, data-centric AI, and innovative data labeling techniques. My expertise spans weak supervision, zero-shot and few-shot learning, and reinforcement learning to drive cutting-edge AI solutions.

  • Improving Machine Learning from Human Feedback
Nitsan Avni
  • Data Kata: Ensemble programming with Pydantic #1
  • Data Kata: Ensemble programming with Pydantic #2
Noa Tamir

Noa have been involved with the R and PyData communities for some time, with a focus on community building and DEI. They are a NumFOCUS member of the Board of Directors and DISC committee, PyLadies Organizer, and chaired the PyData Berlin 2022 conference. In addition, they are a Lead Data Science Coach at neue fische, contributing to pandas, and are currently developing the Contributor Experience Community and Handbook with Inessa Pawson and Melissa Mendonça.

  • Let's contribute to pandas (3 hours) #1
  • Keynote - How Are We Managing? Data Teams Management IRL
  • Let's contribute to pandas (3 hours) #2
Noé Achache

Noé is a lead data scientist at Sicara, and worked on various AI and data engineering related projects.
Speaker at the Paris Computer Vision Meetup.

  • Advanced Visual Search Engine with Self-Supervised Learning (SSL) Representations and Milvus
Oleksandr Shchur

Oleksandr Shchur is an Applied Scientist at Amazon Web Services, where he works on time series forecasting in AutoGluon. Before joining AWS, he completed a PhD in Machine Learning at the Technical University of Munich, Germany, doing research on probabilistic models for event data. His research interests include machine learning for temporal data and generative modeling

  • AutoGluon: AutoML for Tabular, Multimodal and Time Series Data
Paolo Melchiorre

I’m Paolo Melchiorre, a longtime Python backend developer who contributes to the Django project and gives talks at tech conferences.

I’ve been a GNU/Linux user for over 20 years and I use and promote Free Software.

I graduated in Software Engineering and I’m an alumnus of the University of Bologna, Italy.

I’ve been working in the web for 15 years and now I’m the CTO of 20tab, a pythonic software company, for which I work remotely.

  • Maps with Django
Pasha Finkelshteyn

Pasha Finkelshteyn is a developer advocate for data engineering at JetBrains with more than a
decade of experience in the industry. He has a passion for making big data processing
accessible to all and has spent most of his career working with the JVM. However, Pasha
switched to Data Engineering where he discovered the power of Python

  • The Spark of Big Data: An Introduction to Apache Spark
Patrick Blöbaum

Patrick Blöbaum is a Senior Applied Scientist at AWS, where he develops, implements and applies novel causal inference methods to business problems. He is also a main contributor to the open-source library DoWhy and the PyWhy organization. Prior to working at AWS, he got his PhD degree in the area of causality focusing on graphical causal models. His research interests include topics such as root cause analysis and causal discovery.

  • Performing Root Cause Analysis with DoWhy, a Causal Machine-Learning Library
Patrick Hoefler

I am a member of the pandas core team since early 2021. I am a regular contributor of pandas since early 2020. I am currently working at Coiled as a Senior Software Engineer. I hold a Masters degree in Mathematics and I am currently studying towards a Software Engineering degree.

  • Let's contribute to pandas (3 hours) #1
  • Pandas 2.0 and beyond
  • Let's contribute to pandas (3 hours) #2
Paula Gonzalez Avalos

Paula's love for working with Data brought her to the field of Data Science from her initial Natural Sciences background. Loving Teaching brought her to work as a Data Science Coach.Enjoying public speaking brought her to the PyData community - where she enjoys sharing and learning, and most recently organizing. Now she's working as Head of Data Science at Spiced Academy, although technically she's still on parental leave.

  • Workshop on Privilege and Ethics in Data
Paul Elvers

Dr. Paul Elvers is Head of AI/Data Science at Datadrivers, an IT Consulting Company in Hamburg. He graduated in Systematic Musicology & worked as a Research Fellow at the Max-Planck-Institute for empirical Aesthetics before transitioning into Data Science. He has worked for companies like Tchibo and Smartclip, before joining Datadrivers in 2021.

  • Maximizing Efficiency and Scalability in Open-Source MLOps: A Step-by-Step Approach
Pavel Zwerschke

Pavel is a data engineer at QuantCo who is currently studying Mathematics and Computer Science at KIT.

  • Shrinking gigabyte sized scikit-learn models for deployment
Ramona Bendias

I have a Master's degree in science and am currently working as a Applied Machine Learning Engineer at Kumo,ai, where I use my skills in machine learning and data analysis to solve challenging problems. In addition to my work at Kumo, I am also a contributor to PyG, a machine graph learning library in Python.

  • Practical Session: Learning on Heterogeneous Graphs with PyG
Robert Lange

I am a 3rd year PhD student working on Evolutionary Meta-Learning at the Technical University Berlin. My work is funded by the Science of Intelligence Excellence Cluster and supervised by Henning Sprekeler. Previously, I completed a MSc in Computing at Imperial College London, a Data Science MSc at Universitat Pompeu Fabra and an Economics undergraduate at University of Cologne. I also interned at DeepMind (Discovery team) & Accenture and maintain a set of open source tools.

  • evosax: JAX-Based Evolution Strategies
Robin Raymond

I have had a diverse career, starting out in academia as a mathematician and transitioning to work in startups as an engineer in the second half of my career. I thrive on wearing many hats and having a strong impact on the direction of the company. For the past two years, I have been working at Taktile, a series A startup with around 50 employees, where I serve as the lead technical engineer. My passion for programming has led me to work with a wide range of languages, including Haskell, Rust, C++, Typescript, and Python.

  • Rusty Python: A Case Study
  • Modern typed python: dive into a mature ecosystem from web dev to machine learning
Sanket Verma

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, government 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!

  • The Beauty of Zarr
Sarthika Dhawan

Sarthika Dhawan is a Software Engineer at Microsoft, where she has worked with a variety of technologies and teams. She is actively involved in the software development and research community, and has authored and presented a conference paper at IJCAI 2019. She is an ACM-W and AICTE-INAE scholarship recipient and has attended various conferences like GHCI and IJCAI. She has given technical talks, provided mentorships and volunteered as a tutor at NGOs to educate economically less fortunate kids in various disciplines. She has participated in multiple hackathons as she believes that’s an amazing way to keep yourself involved and updated.

  • You've got trust issues, we've got solutions: Differential Privacy
Severin Schmitt

Severin is a Senior Data Scientist at Deutsche Post DHL Group, leading the forecasting tech team, main
developer of DPDHL’s forecasting library and holds a PhD in mechanical engineering. He is passionate
about combining Data Science and Software Engineering for long lasting and maintainable machine
learning projects; he loves guiding the scoping of new projects as well as the change management
processes necessary to bring small and big solutions to life; he is curious about timeseries forecasting
and constantly looking for interesting discussions.

  • Delivering AI at Scale
Shahriyar Rzayev

Senior Software Engineer. Moving forward on Clean Code and Clean Architecture. Previous accomplishments include contributing to open source, providing technical direction, and sharing knowledge about Clean Code and Architectural patterns. An empathetic team player and mentor.
Azerbaijan Python Group Leader. Former QA Engineer and Bug Hunter.

  • Building Hexagonal Python Services
Simon Pressler
  • Getting started with JAX
Stephan Sahm

Stephan Sahm is founder of the Julia consultancy Jolin.io, full stack senior data/ml consultant, and organizer of the Julia User Group Munich.

Stephan Sahm's top interest are in green computing, probabilistic programming, real time analysis, big data, applied machine learning and in general industry applications of Julia.

Aside Julia and sustainable computing, he likes chatting about Philosophy of Mind, Ethics, Consciousness, Artificial Intelligence and other Cognitive Science topics.

  • Accelerate Python with Julia
Susan Shu Chang

Susan Shu Chang is the founder, Quill Game Studios and Principal data scientist at Elastic. Previously, she built machine learning at scale in the fintech, social, and telecom industries. At Quill Game Studios, she grew the company to 10+ developers and shipped 2 commercial releases on PC and consoles. The studio is currently developing the game “Autumn with the Shiba Inu”. She’s a five-time speaker at PyCons around the world and keynote speaker at the O’Reilly MLOps Superstream. You can find her machine learning career guides at Susanshu.com.

  • Keynote - A journey through 4 industries with Python: Python's versatile problem-solving toolkit
Suzin You

Suzin You is a Data Scientist based in New Delhi, India, working at IDinsight, an international development advisory. As do her colleagues, she strives to keep impact as her north star at work.

  • Ask-A-Question: an FAQ-answering service for when there's little to no data
Sven Oehler

I study Applied Artificial Intelligence at the Offenburg University of Applied Sciences and I am very interested in Data Science and AI. During my internship at the startup Bytefabrik.AI in Karlsruhe, I came in touch with the Apache StreamPipes software and became a committer for this project. I work on the python integration to enable easy access to live data streams that can be quickly connected by StreamPipes.

  • Apache StreamPipes for Pythonistas: IIoT data handling made easy!
Tereza Iofciu
  • Workshop on Privilege and Ethics in Data
  • Rethinking codes of conduct
Theodore Meynard

Theodore Meynard is a data scientist at GetYourGuide. He works on our ranking algorithm to help customers to find the best activities to book and locations to explore. He is one of the co-organisers of the Pydata Berlin meetup. When he is not programming, he loves riding his bike looking for the best bakery-patisserie in town.

  • Software Design Pattern for Data Science
  • MLOps in practice: our journey from batch to real-time inference
Thomas Bierhance

Thomas passion has been working with data since 25 years: from small databases for SMEs to large distributed systems for international enterprises and intelligent systems using machine learning. He graduated from the KIT in Karlsruhe, Germany and trained his first neural network while studying at UPC, Barcelona, Spain in 2002. Today he leads the Data Science & AI practice of BettercallPaul in Stuttgart and supports his customers and teams on their journey to generate added value from data.

  • Polars - make the switch to lightning-fast dataframes
Thomas Fraunholz

Thomas has a great fondness for science. Strictly speaking for numerics. After his doctorate, he went to the school of embedded programming. During this time he got to know and love DevOps. His enthusiasm for number crunching ultimately led him to the topic of artificial intelligence. He is currently in charge of publicly funded open source research programs. When he’s not trying to convince his colleagues to use DVC, he’s busy with MLOps, CML and his low-budget bark beetle detection drone – once you’ve done emdedded you just can’t get away from it.

  • From notebook to pipeline in no time with LineaPy
Thorsten Kranz

With a background in Physics and Neuroscience Research Thorsten has been working as a Data Scientist
for many industries. He is driving DPDHL’s efforts of increasing the efficiency for building productionquality, large scale Data Science solutions for the business together with his team. While working as a
Manager for many years now he has remained a nerd at heart – with a passion for data, algorithms and
Software Development in Python.

  • Delivering AI at Scale
Tim Bossenmaier

Tim Bossenmaier works as a Data Engineer at inovex. There he develops and builds modern data infrastructures in customer projects, from streaming ETL pipelines to data catalogs. He is also a developer and member of the project management committee of Apache StreamPipes, an open source solution for IoT data analysis.

  • Apache StreamPipes for Pythonistas: IIoT data handling made easy!
Tim Hoffmann

Tim Hoffmann is a physicist and software expert passionate to bring science and high-quality software together. He works as Simulation Architect Digital Twin at Carl Zeiss, where he covers all aspects from coding, architecture, training up to software strategy. Tim is an active contributor in the Python open source community. In particular, he is core developer and API lead for the visualization library matplotlib.

  • How Python enables future computer chips
Tobias Senst

Tobias Senst is a Senior Machine Learning Engineer at idealo internet GmbH. Tobias Senst received his PhD in 2019 from the Technische Universität Berlin under the supervision of Prof. Thomas Sikora. He has more than 10 years of experience in Computer Vision and Video Analytics research.

At idealo, he switched from the world of images and videos to Natural Language Processing and is responsible for the operation and development of machine learning models in a productive environment.

  • LinkedIn: https://linkedin.com/in/tobias-senst-08090b192
  • Github: https://github.com/tsenst
  • Machine Learning Lifecycle for NLP Classification in E-Commerce
Tobias Sterbak

Tobias Sterbak is a Data Scientist and Software Developer from Berlin. He has been working as a freelancer in the field of Machine Learning and Natural Language Processing since 2018. On the blog www.depends-on-the-definition.com he occasionally writes about these topics. In his private life he is interested in data privacy, open source software, remote work and dogs.

  • How to baseline in NLP and where to go from there
Travis Hathaway

I have been a practicing software engineer for just over 10 years now. I've done a lot of work in the past building and maintaining web applications but now develop CLI tools for the conda project. My interest in plugins was largely motivated by the work I've done at Anaconda for the conda project.

  • Writing Plugin Friendly Python Applications
Tvrtko Sternak

I am currently working as a Python developer at airt. In the past three years, I have gained valuable experience in the industry, including a year working on a microservice product that uses Apache Kafka for communication between services.

I am a strong believer in the power of open source software, and I enjoy learning from the open source community, hopefully also contributing more this year :). My interests in the field at the moment include machine learning, model deployment, Apache Kafka, and advanced Python programming.

In my free time, I enjoy reading fantasy books, staying active through biking and hitting the gym, and watching comedy-drama TV shows. I am always looking for new ways to expand my knowledge and skills, and I am excited to continue growing as a developer in the years ahead.

  • Introducing FastKafka
Vadim Nelidov

Vadim Nelidov is a Lead Data Science consultant at Xebia Data with diverse 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, Vadim 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.

Vadim 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 Vadim. 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.

  • Common issues with Time Series data and how to solve them
Valerio Maggio

Valerio Maggio is a Data scientist, a Developer Advocate at Anaconda. Valerio is well versed into open science and research software, advocating the use of best software development practice in Data Science. He is member of the Software Sustainability Institute (profile) where he has been awarded a fellowing to develop focusing on Privacy-Preserving Machine learning technologies. Valerio is an active member of the Python community. Over the last twelve years Valerio has contributed and volunteered to the organisation of many international conferences and local meet-ups like PyCon Italy, EuroPython, EuroSciPy and PyData. All his talks, workshop materials and open source contributions are publicly available on his Speaker Deck and GitHub profile pages.

  • Actionable Machine Learning in the Browser with PyScript
Vibha Vikram Rao

I am Vibha Vikram Rao.
I currently work as a (Senior)ML engineer at Climate Tech Startup --Briink based out of Berlin.
The reason I got into NLP was with the hope that someday every child would have access to an amazing tool which would be able to read books and would be able to explain it to the child even if they don't have access to good teachers.
So I started my NLP journey with text Summarization systems.
I have a total of around 4 years of experience in Applied NLP.

  • Haystack for climate Q/A
Victoria Slocum

Victoria is a Developer Advocate at Explosion, where she supports the Natural Language Processing community around the popular open-source library spaCy, the annotation tool Prodigy and other developer tools. Besides running marathons, learning new languages, and building fun machine learning projects about music and food, she loves learning about natural language processing and ensures that the open-source community has everything they need to do the same.

  • You are what you read: Building a personal internet front-page with spaCy and Prodigy
Vikram Waradpande

Vikram is a Computer Science master's student at Columbia University with a focus on Machine Learning. He completed his bachelor's in Computer Science and Mathematics in India from BITS Pilani. Before Columbia, he was a part of the engineering and strategy team at Goldman Sachs, where he built scalable and efficient trading tools. He has also had research experience working at TU Leibniz, Germany in the area of Reinforcement Learning and Parallel Programming. He presented his research at the International Conference on Mining and Learning on Graphs in 2020 in Vienna, Austria. He was a teaching assistant for three courses during his academic career, which involved conducting seminars (NumPy, Pytorch, etc.), organizing technical meetings and organizing research fairs. He has also tutored for the website 'Chegg' for more than two years where he taught Math and Programming to high school and university students.

  • You've got trust issues, we've got solutions: Differential Privacy
Wiktoria Dalach

Wiktoria Dalach is a Senior Software Developer, Security Engineer, a writer and a youtuber. She has been building apps for a decade. She has organized over 30 workshops for Webmuses, a community she co-founded in 2012. She's a RailsGirls mentor. Her interests focus on creativity, art and cybersecurity.

  • Great Security Is One Question Away
Yann Lemonnier

Yann Lemonnier is an experienced ML/Data Engineer with a strong background in data analysis, machine learning, and time-series predictions. He is currently focusing on enabling production machine learning projects with MLOps. Yann has a Master's degree in Physics from the Université de Sherbrooke in Canada and is a certified AWS Cloud Practitioner and GCP Professional Data Engineer. Yann is passionate about using his expertise to drive business value and innovation through data-driven insights. In his previous work experiences, he has worked as a Data Engineer, Tech Lead, Machine Learning Engineer, Flight Test Data Analyst and acoustic engineer. Yann has supervised data scientists teams, designed software solutions, and did project screening and reviews. Some of his past projects include L’Oréal supply chain ETL, tabular data AutoML for Aircraft design offices, Machine activity monitoring from vibration IoT, Aircraft Noise Classification, Aircraft Vibration Event Impact Assessment, Aircraft External Noise Cartography, and vibration flight test analysis. Yann has worked in companies like L’Oréal, Alteia, COREIoT, and Airbus Flight Test Center. He is now working at Adevinta in the ReCommerce (second hand marketplace) industry.

  • Enabling Machine Learning: How to Optimize Infrastructure, Tools and Teams for ML Workflows
Yasin Tatar

Yasin works as a Data Engineer at QuantCo and studies Computer Science at Karlsruhe Institute of Technology (KIT)

  • Shrinking gigabyte sized scikit-learn models for deployment
Yuichiro Tachibana

Yuichiro works as a professional software developer and also loves contributing to OSS projects. As a Pythonista, he has participated in various projects including web development, multimedia streaming, data management, computer vision, and machine learning.

  • Streamlit meets WebAssembly - stlite
Yuqiong Weng

Yuqiong recently received her master's degree in data science. She is now working as a junior data scientist at I-WUNDER GmbH, where she deals with data and develops machine learning models. NLP is one of the fields that catches her interest, out of which she developed a chatbot in the domain of E-Mobility to help with information-retrieval tasks.

  • How Chatbots work – We need to talk!