Pytorch, Python, training data pipelines, training data curation, model training evaluation, reinforcement learning, large language model post-training

Tensorflow, Pytorch, C++, Python, Cuda

causal inference , Jax, Pytorch, physics-constrained loss function architecture, PINNs methodology design, Bayesian deep learning, ensemble uncertainty quantification, Bayesian experimental design, structural causal models, causal discovery, active learning acquisition function design

Machine Learning, Jax, Pytorch, structured prediction, uncertainty estimation, time-series modelling, representation learning, probabilistic forecasting, foundation models, multimodal learning

Machine Learning, Unsupervised Learning, agentic AI, adversarial machine learning, supervised learning, generative models, reinforcement learning, evaluating frontier AI systems, ML safety, ML interpretability, multi-object optimization, adversarial robustness