causal inference , Jax, Pytorch, Neural ODEs, Bayesian deep learning, Foundation model fine-tuning, Graph neural networks, structural causal models, PINNs methodology, Bayesian experimental design, RL for scientific discovery, causal discovery, active learning acquisition function design, diffusion models

policy development , C, Optimization Algorithms, Tensorflow, Computer Vision, Pytorch, Python, LLMs, control theory, representation learning, 3D egocentric perception, deep learning frameworks, self-supervised learning, multimodal learning, reinforcement learning, Robotics, embodied AI

Rust, Pytorch, Python, C++, LLM pretraining, transformer architectures, Hugging Face ecosystem, RLVR-based approaches

Tensorflow, Jax, C, Pytorch, Python, Deep Learning, Generative AI

Machine Learning, Cnn, Deep Learning, Tensorflow, Rnn, Pytorch, Python, Transformer, LSTM, ViT, MxNet, Caffe, Model Compression

Pytorch, Cuda, Python, LLM and foundation models

Natural Language Processing, Pytorch, Computer Vision, C, Tensorflow, Python, Jax, Machine Learning, Large Language Modeling, reinforcement learning

pruning , Pytorch, Python, sim-to-real evaluation, domain adaptation, pre-training, quantisation, Physical AI, Embodied AI, TensorRT, knowledge distillation, edge devices, model compression, embedded platforms, ONNX, Robotics, Foundation Models, real-time AI inference pipelines, Multimodal AI, computational graph optimisation, synthetic data generation