As learning algorithms become increasingly capable of acting autonomously, it is important to better understand the behavior that results from their interactions. For example, a pervasive challenge in multi-agent learning […]
Understanding the dynamic behavior of complex biomolecules requires simplified models that not only make computations feasible but also reveal fundamental mechanisms. Coarse-graining (CG) achieves this by grouping atoms into beads, […]
Modern computing and communication technologies, such as supercomputers and the internet, are based on optically-linked networks of information processors operating at microwave frequencies. An analogous architecture has been proposed for […]
Team theory is a mathematical formalism for decentralized stochastic control problems in which a “team,” consisting of a number of members, cooperates to achieve a common objective. It was developed […]
The remarkable recent success of Machine Learning (ML) is driven by our ability to develop and deploy interactive models that can solve complicated tasks by understanding and adapting to the […]
Future emerging applications like extreme environment electronics, high-performance computing, space sensing, and brain-machine interfaces share a critical goal: massive bandwidth and deployment scalability. To this end, my research group is […]
Zoom link https://upenn.zoom.us/j/98220304722 Abstract We present computational tools for analyzing and designing first-order methods in parametric convex optimization. These methods are popular for their low per-iteration cost and warm-starting […]
Machine learning is transforming numerous aspects of modern society, and its expanding use in high-stakes applications calls for responsible development. In this talk, I will present my research on the […]
Over the past decade, large-scale pre-training followed by alignment has revolutionized natural language processing and computer vision. Yet, robotics remains constrained by the scarcity of real-world data. In this talk, […]
Zoom link: https://upenn.zoom.us/j/98220304722 Abstract: Modern ML models produce valuable predictions across various applications, influencing people’s lives, opportunities, and scientific advancements. However, these systems can fail in unexpected ways, generating unreliable […]
