IDEAS/STAT Optimization Seminar: “Foundations of Deep Learning: Optimization and Representation Learning”
Deep learning’s success stems from the ability of neural networks to automatically discover meaningful representations from raw data. In this talk, I will describe some recent insights into how optimization […]
IDEAS/STAT Optimization Seminar
ESE Spring Seminar – “AI as a Lens: Expanding Vision for Scientific Discovery”
Conventional approaches to scientific discovery often prioritize building larger sensors, gathering more data, and scaling up computational power. In this talk, I will present a complementary perspective: extracting insights hidden […]
ESE Spring Seminar – “Machine Learning: Algorithmic and Economic Perspectives”
Algorithms are increasingly integrated into various societal applications, often directly interacting with people and communities. This highlights the importance of understanding the interplay between algorithmic decisions and economic incentives when […]
ESE Seminar – “A changing grid powered by the new generations of power conversion, control, and energy management”
The electric grid is undergoing a transformative paradigm shift, driven by sweeping changes in generation, demand, and energy storage. By 2035, solar PV alone is expected to supply 40% of […]
ESE Ph.D. Thesis Defense: “Wave Interaction with Nonreciprocal Swift-Electron Platforms and Reconfigurable Metasurfaces”
The study of electromagnetic wave interactions with various media is of fundamental significance in both theoretical and applied sciences. Understanding how electromagnetic waves propagate, reflect, refract, and scatter when encountering […]
ESE PhD Thesis Defense: “A Dynamical Systems Perspective on Optimization Algorithms”
The intersection of machine learning (ML) and dynamical systems and control (S&C) has become a prominent area of research in recent years. While most work applies ML to S&C problems, […]
ESE PhD Thesis Defense: “Software-like Incremental Refinement on FPGA using Partial Reconfiguration”
To improve FPGA design productivity, our goal is to create a development experience for FPGAs that aligns closely with widely accepted software design principles. Software programmers quickly test their minimally completed […]
ESE Ph.D. Thesis Defense: “Learning-based Model Predictive Control for Aerial Vehicles”
Learning-based model predictive control (MPC) is an increasingly prominent control paradigm in recent years. One primary approach in learning-based MPC is to leverage machine or deep learning tools to construct […]