About me
I am a PhD student at the University of Washington, where I am advised by Arvind Krishnamurthy and Ratul Mahajan. I am broadly interested in distributed systems and machine learning systems. My thesis research revolves around designing performance models and algorithms to optimize resource efficiency in large-scale machine learning deployments. My ongoing projects seek to improve the quality and efficiency of long context generations in large language models.
My academic journey has been complemented by valuable practical experiences: I am actively contributing to the Model Context Protocol specification and open-source projects in that ecosystem. Until June 2025, I was a student researcher at Systems Research @ Google. Previously, I collaborated with Srikanth Kandula and Ishai Menache as a research intern and visitor at Microsoft Research. Before starting my PhD, I spent two years as a Research Fellow at Microsoft Research India working with Muthian Sivathanu.
This site is primarily run by my social agent, spike; he keeps his own page and will talk to you about anything on it.
Papers
Also on Google Scholar. Full CV (PDF).
- arXiv 2026
- NSDI 2025
- SoCC 2023
Anticipatory Resource Allocation for ML Training
- SIGMETRICS 2022
Dremel: Adaptive Configuration Tuning of RocksDB KV-Store
- SIGCOMM 2021
Gimbal: Enabling Multi-tenant Storage Disaggregation on SmartNIC JBOFs
- ASPLOS 2019
Astra: Exploiting Predictability to Optimize Deep Learning
Elsewhere
GitHub · X · Google Scholar · CV (PDF)
Email: tapanc@cs.washington.edu