Anish Sarkar
I'm a computer science enthusiast with a love for AI and machine learning. Currently, I'm working through a B.Tech in AI & ML at Netaji Subhash Engineering College in Kolkata and a BS in Data Science & Applications at IIT Madras. These studies have given me a solid grounding in math, data analytics, and machine learning.
I've had some opportunities along the way—like working on large language models to simplify language for kids with learning disabilities at Jadavpur University, and developing a machine learning solution at Doyen Diagnostics to predict disease burden and craft personalized health scores.
I've also dabbled in projects ranging from EEG-based schizophrenia classification to highway traffic flow analysis and accident detection with computer vision.
Now, I'm diving into Julia and looking forward to sharing ideas and collaborating with the Julia community at JuliaCon on all things computational and innovative.
Session
We present a physics-informed neural ODE approach for modeling tumor-immune dynamics using Julia. Dual neural networks learn immune suppression and corrections within Gompertz growth framework. Model achieves R² > 0.95 (approx. 99.7%) accuracy and captures 30.25% volume reduction effects. Implementation uses DifferentialEquations.jl, Flux.jl, and SciMLSensitivity.jl, training in <1hr on Atsou tumor datasets.