About Me

I am a Research Scientist in the Software and Data Systems Research Lab at Nokia Bell Labs, where I work at the intersection of AI/ML systems, distributed infrastructure, and Web3 technologies. My current focus is on designing AI infrastructure and system abstractions for efficient deployment across heterogeneous compute environments.

I received my PhD from the University of Massachusetts Amherst, where I was advised by Professor Prashant Shenoy. My PhD thesis focused on enabling privacy and trust in edge AI systems. My prior research has spanned over building systems for machine learning that enable explainability and generalizability, building trustworthy and privacy-preserving ML systems, and designing machine learning solutions for ubiquitous computing.

Before graduate school, I was a software engineer at IBM, working on the z/OS mainframe. I hold a B.S. in Mathematics and Computer Science from the University at Albany, SUNY.

Research Interests

• Heterogeneity-aware AI — adapting models and systems to diverse, heterogeneous compute
• Distributed inference and serving — efficient, scalable model deployment across distributed infrastructure
• Trustworthy and privacy-preserving ML — protecting data and models from leakage, extraction, and misuse
• Edge AI — on-device learning and inference under tight resource constraints
• Applied machine learning — real-world ML for ubiquitous computing and networked systems

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