Institute for Data, Intelligent Systems, and Computation

Artificial Intelligence & Machine Learning

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Artificial Intelligence & Machine Learning

Research Focus Area

The new Artificial Intelligence and Machine Learning (AI/ML) research group will mostly focus on applying AI/ML methodologies in various engineering applications, including civil engineering, material science, physics and computational chemistry to name a few.

  • AI/ML: One of the methodologies we are focusing on is on how to train AI/ML models efficiently in problems coming from physics and engineering applications. Some of the challenges includes interpretability and fast inference.

  • Reinforcement learning is a machine learning paradigm for sequential decision making in which an agent(s) learns to adapt to changing environmental conditions while performing a task. Studying methodological advances in the state of the art including hierarchical reinforcement learning, function approximation for reinforcement learning, and optimization algorithms that can be used to accelerate training RL agent(s). Applications of reinforcement learning in a variety of areas including transportation networks, autonomous robotics, block chain and fintech. 

Recent Research

"Multi-Agent Image Classification via Reinforcement Learning". 
A video explaining our recent paper is available here >

Research Focus Group Members

Activities include weekly seminars attended by faculty and PhD students across a number of Rossin College of Engineering Arts & Science Departments.