Autonomous & Intelligent Robotics Laboratory (AIR Lab)
Developing theoretical & computational foundations to achieve long-term robot autonomy
Catastrophe Modeling
A rigorous probabilistic approach to the study of natural disasters, and their consequences. Recent trends have seen CatModeling applied to rare events like financial crises, political unrest, and pandemics.
Computer Vision
Developing novel computationally efficient computer vision algorithms for visual understanding, forensic analysis, real/fake image/video detection, and AI-assisted healthcare
Explainable Graph Learning
Focus on problems in the smart electric grid where much of the data infrastructure is in place & evaluation of developed methodologies
FinTech and Blockchain
Advancing blockchain technology for business-scale performance with attention to privacy, transparency, and regulatability.
Human Centered Computing
As humans face a growing reliance on computer-mediated behaviors of all sorts, the need for smarter human-technology interfaces is growing
Machine Learning in Materials Science
Use of machine learning & deep learning for modeling complex physical systems of materials & chemical processes
Mathematical Optimization & Data Science (MODS)
Research on mathematical optimization, which involves the development of mathematical & computational tools that facilitate discovery, design, and decision-making throughout science, engineering & business
Quantum Computing & Optimization Lab (QCOL)
Quantum Computing has the potential to solve problems faster than classical supercomputers. This capability can change our world by enabling new methods to decrypt data, faster molecular analysis to design better drug treatments and to solve complex optimization problems rapidly.
Scalable Systems & Software
Developing software & hardware to maximize performance and reduce energy consumption in multi-core & distributed systems