I build networked systems. My current research focuses on mitigating unfair network flows and preventing incast traffic bursts in a datacenter, from the receiver's point of view. Previously, I architected transport protocols for hybrid packet/circuit networks, built machine learning systems for processing streaming video data at the edge, and developed new software architectures for big data analytics that put performance clarity first. I have a longstanding collaboration with Meta's Host Networking team.

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Summer 2023: I'm thrilled to return for a third internship with Meta's Host Networking team, this time working on network congestion control for Meta's AI training clusters.

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Summer & Fall 2022: I worked on delay-based congestion control and mitigating incast microbursts in datacenter networks with Meta's Host Networking team.

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Fall 2021: I was a full instructor (with Professor Peter Steenkiste) for CMU's 15-441/641 Networking and the Internet course. I gave seven lectures, created the homework assignments, managed the three projects, and supervised the four teaching assistants.

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Summer & Fall 2021: I worked on microburst congestion control for datacenter networks with Meta's Host Networking team.

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From 2016-2019, I managed a student team in the Intel Science and Technology Center for Visual Cloud Systems, where we built systems for machine learning on edge devices under the guidance of Professor Dave Andersen and Michael Kaminsky. From 2014-2016, I built big data analytics systems with Kay Ousterhout and Professors Sylvia Ratnasamy and Scott Shenker in the NetSys Lab. I earned a B.S. in Electrical Engineering and Computer Science from UC Berkeley in 2015 and an M.S. in Computer Science from CMU in 2021.

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I am from San Diego, CA.