My research is primarily in the area of systems and networking, with an emphasis on enhancing networked systems using practical machine learning (ML) techniques. To achieve this, I work with students to build real-world systems, design ML-based policies to optimize system performance, and develop mechanisms to make ML more readily deployable.

Given the interdisciplinary nature of my research, I encourage applications from students with expertise in either systems and networking or ML. I mostly publish in systems and networking conferences such as USENIX NSDI and ACM SIGCOMM, but I am open to other top-tier venues.

In my group, you will receive guidance to sharpen your research and communication skills, along with my full support for your career development. For instance, when there is a good fit, I will be glad to recommend you for summer internships at Microsoft Research, SystemsResearch@Google, or other research labs. My goal is to help you succeed in your academic and professional pursuits. You are welcome to reach out to any of my current or former students to learn about the experience of working with me.

I am committed to fostering an inclusive and respectful research environment where everyone feels welcome and valued. Any form of misconduct, including but not limited to discrimination, harassment, and intimidation, will not be tolerated.