Locomotion, Humanoids, and Navigation
Model legged locomotion, whole-body control, and map-based navigation with hybrid contact dynamics, terrain uncertainty, and sim-to-real transfer.
Experienced analytics, AI, and technology leader with 13+ years of experience across data science, private equity, management consulting, entrepreneurship, and software engineering. Sharing thoughts on these topics.
Build a miniature planar pushing world model in Python: contact features, Ridge regressors, rollout error, random-shooting plans, and affordance maps.
Compare Atari, board games, and open worlds as learned game engines. Measure one-step prediction, recursive rollout drift, and model-predictive control.
VLA and world-action models fuse vision, language, and control, tokenize robot actions, and transfer across embodiments under closed-loop evaluation.
Examines NVIDIA's Cosmos world foundation models: video tokenization, physical AI data curation, conditional generation, guidance calibration, and simulation.
Explains how DINO-WM freezes a pretrained visual encoder, trains action-conditioned feature dynamics, and uses goal-image planning.

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Speaking with investors and operators about choosing problems worth solving, understanding what the technology can really do, and making it work in practice.
Commercial judgment · Technical depth
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Machine learning and math concepts explained step by step so you can understand how it works, without hours of digging through dense textbooks. Free to read online.
Read the World Models Handbook online for free. Learn latent dynamics, model-based reinforcement learning, planning, physical AI, evaluation, and deployment.
Build a small GPT-style language model in PyTorch. Follow each step from embeddings and attention through training, optimization, and text generation.
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