Portfolio

Systems, research, and things that work.

A portfolio of difficult problems made inspectable—from agent architecture and cybersecurity research to the infrastructure beneath them.

Each case study follows the problem, constraints, approach, architecture, outcomes, and next questions.

4 selected projectsResearch · Software · Infrastructure

experimentcomplete
Transformer-augmented reinforcement learning in the Unity Food Collector environment
Can a transformer beat the MLP inside PPO and SAC? A three-way study placing the transformer on the actor, the critic, or both, with a CoordConv-ResNet encoder, the failure modes that shaped it, and held-out results across five agents.
- Unity ML-Agents Food Collector (5×40×40 grid sensor, hybrid action space)
- Gymnasium wrapper over the Unity binary
- PyTorch
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