Research & projects
Selected work in machine learning research and research-oriented engineering.
Research experience
Stochastic optimization for discrete world models
Intelligent Dynamics Lab · Advisor: Roy Fox
Developed a PyTorch library of gradient estimators and control variates. I also replaced straight-through estimators in DreamerV3 with Gumbel-Softmax relaxations for discrete latents and actions.
Double descent and model merging
Machine Learning Research Group · Advisor: Alexander Ihler
Studied how scale, distillation, and regularization affect minima flatness and generalization. I also merged pruned CNNs by combining similar filters and evaluating unique filters through grouped convolutions.
Surrogate models for thermal simulation
California Institute for Telecommunications and Information Technology
Developed physics-informed neural networks as efficient surrogates for finite-element simulations used to evaluate thermal-storage systems.
Selected projects
Molecular generation
Deep generative models · 2026
Built a graph variational autoencoder with a property-prediction head, inverse autoregressive flow, and autoregressive transformer decoder to generate drug-like molecules.
Result: Fréchet ChemNet Distance of 1.81 on ZINC-250k.
Semi-supervised code translation
Programming language translation · 2026
Fine-tuned CodeT5 for Python–C++ translation using paired examples alongside backtranslation and denoising autoencoding on unpaired code.
Result: Approximately 76% CodeBLEU and 20% HumanEval-X.