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Decision & Optimization
Dynamical Systems
Generative AI
Multimodal Learning
Learning for Dynamical Systems
Research focuses on developing machine learning methods to model, analyze, and control complex dynamical systems across engineering and scientific
Multimodal Sensing, Perception & Representation Learning
This research area explores how machines learn from multiple sensory modalities such as vision, audio, and sensor data to
Optimization & Decision-Making Under Uncertainty
We study algorithms for optimal decision-making in uncertain environments, combining machine learning, optimization, and probabilistic modeling.
Generative Models for Simulation & Design
Research focuses on generative AI models that enable simulation, design automation, and creative problem-solving in engineering and scientific domains.
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