Explore the science and philosophy of intelligence itself. From foundational theory to cutting-edge research in deep learning, reinforcement learning, and generative AI — this department is for those who want to push the boundaries of what machines can do.
4-year program blending theory with practice — from logic and algorithms to neural networks and RL.
2-year research-intensive graduate program for those aiming to push the frontiers of AI.
History, philosophy, and core paradigms — from symbolic AI to modern deep learning.
MDPs, Q-learning, policy gradients, actor-critic methods, and deep RL.
VAEs, GANs, Diffusion Models, Flow Models — theory and implementation.
Self-attention, BERT, GPT, fine-tuning, RLHF, and prompt engineering.
TRPO, PPO, SAC, model-based RL, offline RL, and multi-agent RL research.
AutoML, NAS algorithms (DARTS, ENAS), hardware-aware design, and efficient AI.