Learning-Augmented Algorithm Design
This project seeks to develop algorithms that are theoretically robust and take advantage os advice from machine learning in decision-making.
Fairness in Online Optimization and Learning
In this project, our goal is to develop fair and competitive algorithms for some classic online problems and explore the benefit of ML advice to achieve better performance for both fairness and efficiency.
Carbon Intelligent Computing Systems
This project seeks to develop cooperative online learning algorithms in distributed and heterogeneous networks.
Bitrate and View Adaptation Algorithms for Video Streaming
The goal of this project is to design better adaptive bitrate (ABR) algorithms for high-performance video delivery and evaluate their performance in the field.
Data-driven Algorithms for Equitable Emissions Reduction in Transportation Systems
In this project, we develop data-driven algorithms for reducing the emissions of the ride sharing platforms.
Robust Cooperative Learning in Distributed Networks
This project seeks to develop cooperative online learning algorithms in distributed and heterogeneous networks.
CarbonFirst
The CarbonFirst Project focuses on making cloud and edge computing sustainable and carbon-free.