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Lightning Talk Intermediate MIT License

DeepChem is one of the biggest Open-Source Frameworks connecting Chemistry, Biology and ML

Proposal status is Rejected
Session Description

Every year it costs a lot of money to perform experiments in the space of Physical Sciences. If there were only a way Researchers could simulate and perform experiments to find proper candidates for an experiment, then it could save a lot of resources and that is the exact bridge that DeepChem tries to build between Machine Learning and Physical and Life Sciences.

DeepChem is one of the largest Open-Source Machine Learning Frameworks with over 6.8k Stars mainly for work related to Molecular Science. It combines Chemistry, Biology, Physics and modern Deep Learning into a single ecosystem, allowing Researchers and Developers to build models for Drug Discovery, Material Science, Protein Engineering and Quantum Chemistry, all in one place instead of doing everything from scratch.

A big portion of Developers and Researchers are still unaware of DeepChem and that is what this talk is aimed to do. I want to make more people aware of the work we do at DeepChem. I will cover how DeepChem is used to tasks related to Chemistry, Biology and Physics and why is having one big framework integrating all operations for Life Sciences important and why scattered approaches can be bad.

I will also briefly touch on how to contribute to DeepChem since the workflow for contributing to DeepChem is a bit different and we need many more contributors to help us.

By the end of this talk, the public will have an understanding of what DeepChem is, why Machine Learning is transforming Computational Chemistry and how an Open-Source Framework is powering Research across different Life Sciences applications.

Key Takeaways
  1. Learn what DeepChem is.
  2. Understanding how ML is transforming Life Science tasks.
  3. See how Open Source accelerates scientific Research.
  4. Gain Practical Insights into contributing to DeepChem.

References

https://github.com/deepchem/deepchem
https://deepchem.readthedocs.io/en/latest/development_guide/scientists.html
https://deepchem.io/

Session Categories

Introducing a FOSS project or a new version of a popular project
Talk License: MIT License

Which track are you applying for?

Main track

Speakers

Shubhang Sinha
Shubhang Sinha Machine Learning Engineer | Open Source Contributor @Pandas, DeepChem, MLLAM | DeepChem, Talent Angels (LFDT)

I am Shubhang Sinha, a 4th year Undergrad working as a Google Summer Of Code Mentee with DeepChem and a LFX Mentee with Talent Angels (LFDT) and also an Open-Source Contributor in Pandas. I was also the Smart India Hackathon ‘25 Winner.

I happen to run a big Open-Source Community (around 400 members) with my friends with a sole goal of educating India’s youth about Open Source and preventing them from making the mistakes that we have often seen them doing and make them aware of the proper practices to follow in Open Source and do it for the love of the game.

I have been doing stuff related to Machine Learning since my first year and I don’t restrict myself to one space. I have worked on Compilers, Obfuscators, Reverse Engineering, DevOps and have done research on Translational Models. I also delivered a talk on my GSoC Project in the PyTorchxRedHat Bengaluru Meetup which was my first talk.

https://www.linkedin.com/in/shubhangsinha/