I’m a first-year PhD student in Computer Science at Georgia Tech, where I’m advised by Anand Iyer in the NetSys Lab. My research interests lie at the intersection of systems and machine learning, with a current focus on building efficient and reliable agentic LLM systems for complex, distributed tasks.

Before joining Georgia Tech, I was an undergraduate research intern on several systems projects. At Carnegie Mellon’s Parallel Data Lab, I worked with Greg Ganger and Rashmi Vinayak on a theory-enhanced system for efficiently transitioning data across redundancy schemes. At Microsoft Research, I collaborated with Sid Sen, Chetan Bansal, and Gagan Somashekar to develop synthetic application request traces via AI behavior mimicry for system reliability testing.

I always enjoy learning from other students and researchers, and can be reached by emailing dax [at] gatech [dot] edu.

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