Deep Learning for Tabular Data
Learning with Insufficient Data and Labels
Uncertainty-Aware Learning and Inference
Training-Free and Data-Free Model Improvement
Active Data Acquisition and Exploration
Data-Driven Optimization
Autonomous Materials Development (Materials Design, Synthesis, Characterization, Optimization, etc.)
Autonomous Manufacturing (Process Control, Machine Vision, Quality Inspection, Fault & Anomaly Detection, etc.)
AI Agents for Scientific and Industrial Applications