Projects

Completed Projects:

• Accelerated materials development for manufacturing (AMDM), A*STAR Programmatic Grant, 2018-2024 (5.5 years)

  • WP 1: Core of accelerated materials development, Role: Co-Principal Investigator (Co-PI)

  • WP 2: ML-guided failure identification in advanced nanoscale semiconductors, Role: Co-Principal Investigator (Co-PI)

AI techniques: generative models, online learning, multi-agent systems, reinforcement learning, and optimization.

Generative models: generative autonomous clustering, generative continual learning, generative inverse model, generative oversampling, generative domain adaptation

Online learning: online classification, online clustering, online regression 

Optimization: metaheuristic optimization, stochastic optimization, Bayesian optimization, multi-objective optimization, discrete optimization (learn-to-optimize - transformer)

Reinforcement learning: Q-Network, SARSA, DQN, DRL-PSO, Interpretable RL, Gated Convolutional Network-based RL, Offline RL.

Multi-agent systems: multi-agent optimization (stochastic, metaheuristic, game theory, team theory), multi-agent learning (online learning, reinforcement learning)

AI for Science: semiconductors, material informatics, and satellite/UAV remote sensing.