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Hello! I am Smit Chaudhary. A physicist, ML Developer, and a full-time nerd. I enjoy training large neural networks to get them to solve problems they have not seen before.
What I’ve Been Up To
- PASQAL - Machine Learning 🤝 Quantum Computing
 Built Scientific ML systems. Trained Neural Networks. Minimized losses. Shipped APIs that let others use our Quantum Neural Networks to minimize their losses.
- Menten AI - Research Intern
 Built Generative Adversarial Networks in JAX. Made them quantum. Taught them discrete data. Published the results.
- TU Delft - Master’s in Applied Physics
 Built optimization algorithms in Quantum Machine Learning group. Implemented GANs for quantum states. Researched barren plateaus. Learned Physics. Applied Physics.
- IIT Kanpur - Bachelor’s in Physics
 Learned a lot. Forgot a lot. Learned to learn again. Learned to forget only some. Still reaping the benefits of those fundamentals.
More About Me
- Grew up in India, now live in Rotterdam, The Netherlands.
- Stop-Motion Animation
 I enjoy the process of meticulously crafting each frame where hours worth of effort bears a small (often satisfying) few-seconds long clip.
- Open Source
 Always looking for open source alternatives to everything. Yes, everything. And you should also sponsor your favorite open source projects. Goes a long way.
- Build From Scratch
 Building something from ground up is my usual way of, uhm, scratching the itch. Not just now on weekend(s) projects but also during academic projects.
- I Self-Host by the way
 Ok. I am not annoying about it (yet) but I am starting to move more and more of my stuff off someone else’s cloud and my own VPS. Hetzner and Coolify for the win.
- Languages and Etymology
 I am fortunate to be part of a diverse set of friends, which means many discussions about the similarities and differences in our languages. Have many unfounded theories.
Publications
- 
    Solving Fluid Dynamics Equations with Differentiable Quantum Circuits 
 Proceedings of the 35th Parallel CFD International Conference 2024 (2025)
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    Quantum Circuit Training with Growth-Based Architectures 
 arXiv preprint (2024)
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    Towards a scalable discrete quantum generative adversarial neural network 
 Quantum Science and Technology (2023)
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    Quantum Machine Learning: A Review and Current Status 
 Springer Singapore (2020)
