Projects
Research sprints at the intersection of learning, causality, and dynamical systems.
Zero-Shot Coordination in Multi-Agent RL
Convention emergence via IPPO in grid environments. Analyzing when ad-hoc teamwork fails and what structural symmetry-breaking enables coordination without prior agreement.
Causal State-Space Models for Time Series
Structural causal models integrated with SSM architectures for counterfactual forecasting. Granger-causal baselines compared against do-calculus interventions in finance and climate data.
Port-Hamiltonian Neural Networks
Energy-preserving neural ODEs constrained to Hamiltonian structure. Enforcing symplectic symmetry as inductive bias for learning conservative physical systems from trajectory data.
Generative Social Network Simulation
LLM-driven agent simulation of graduate student archetypes. Evaluating opinion dynamics and belief propagation across synthetic social graphs under heterogeneous prior distributions.
Personality-Aligned Vision-Language Model
Fine-tuning VLMs with RLHF to align visual description style with Myers-Briggs personality dimensions. Studying whether personality-conditioned reward signals improve downstream task coherence.