We research Data Systems for Data Science (DS2). Our aim is to explore and build better systems software to sustain the requirements of next-generation data-intensive applications.
We are interested in addressing challenges existing in real-world distributed and storage systems. Our research is driven by the complexities of modern data-intensive computer systems, and the need for more efficient and flexible approaches to manage such complexities. We aim for innovation in systems technologies that range from large-scale distributed systems to cross-layer software-hardware co-design.
Our current efforts are focused on: (1) improving serverless computing using a full-stack approach spanning applications, middleware, and lower-level OS/hardware (watch this Youtube video summarizing our recent focus on serverless computing); and (2) building better (computing and storage) systems for distributed machine learning.
We are committed to training the next-gen of data systems researchers and developers. We are seeking Ph.D. students who are passionate about solving practical challenging problems in modern datacenter applications & systems. We are also open to working with Masters and undergrad students.Lab Members Our Research