Saransh Chopra
AI Engineering Intern at Logitech
Lausanne, Vaud, Switzerland
Summary
🤩
Rockstar🎓
Top SchoolSaransh Chopra is an AI engineering intern and computational science master’s student at EPFL with about five years’ experience building research-grade software across HPC, DevOps, and scientific machine learning. He has served as a research software engineer at CERN and UCL, contributing GPU and auto-differentiation support to large-scale simulations, migrating services to Kubernetes, and teaching Research Software Engineering curricula. An active open-source maintainer, he has improved usability and infrastructure across notable projects like Flux.jl, PyBaMM, and zarr-python, including documentation, CI modernization, and physics-informed ML examples. His background spans theoretical work in functional programming and Agda proofs to practical efforts like CUDA-enabled histogramming and battery modeling, reflecting a rare blend of formal methods and high-performance implementation. Passionate about open science, he repeatedly bridges research and production—building developer tooling, docs, and reproducible teaching infrastructure. Based in Lausanne, he describes himself as a generalist who deliberately pursues grad school to deepen expertise after broad hands-on impact.
5 years of coding experience
2 years of employment as a software developer
University of DelhiMaster of Science - MS Computational Science and Engineering, Master of Science - MS Computational Science and Engineering at EPFLSwiss National Supercomputing Centre Summer University Effective High-Performance Computing and Data Analytics, Swiss National Supercomputing Centre Summer University Effective High-Performance Computing and Data Analytics at ETH ZürichHigh School Diploma, High School Diploma at ASN Senior Secondary School - India
Github Skills (28)
dependency-management10
github-ci10
python10
testing10
machine-learning10
refactor10
numpy10
deep-learning10
flux10
fluxor10
refactoring10
githubaction-workflow10
scientific-machine-learning10
documentation10
data-science9
Programming languages (23)
Github contributions (5)
FluxML/Flux.jl
Mar 2022 - Oct 2022
Relax! Flux is the ML library that doesn't make you tensor
Role in this project:
Data Scientist / ML Engineer
Data Scientist / ML EngineerContributions:59 reviews, 114 commits, 24 PRs in 7 months
Contributions summary:Saransh primarily contributed to improving the documentation and examples within the Flux.jl library, specifically concerning the use of MLUtils and fixing docstrings for various functions. They also resolved merge conflicts, updated dependencies, and turned off doctests during documentation builds. Their changes indicate a focus on enhancing the usability and clarity of the library, including the addition of examples and better documentation practices for key features.
ml-librarythe-human-braindata-sciencedeep-learningneural-networks
pybamm-team/PyBaMM
Feb 2021 - Dec 2022
Fast and flexible physics-based battery models in Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:7 releases, 727 reviews, 175 commits in 1 year 10 months
Contributions summary:Saransh primarily focused on refactoring the code related to the cell capacity parameter in the PyBaMM simulation library. This involved renaming the parameter and updating its usage across various files, including simulation scripts, test files, and example notebooks. Moreover, they introduced error messages and deprecation warnings to guide users towards the updated parameter name, promoting code maintainability and preventing future errors. They also fixed testing issues around the deprecation warning of "Cell capacity [A.h]".
chemical-engineeringphysicspower-systemspythonbattery
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