I’m a third-year PhD student at the University of Maryland, College Park, where I also earned my Bachelor’s degree in Computer Science. Advised by Dr. Bahar Asgari, my research operates at the intersection of computer architecture and machine learning, focusing on the development of self-adaptive systems. By leveraging machine learning as a foundational architectural mechanism rather than just a target workload, I aim to design systems that autonomously learn and adapt to changing demands throughout their lifecycle. My work moves beyond rigid, pre-defined design heuristics toward autonomous systems that proactively self-optimize for latency, throughput, and energy efficiency, ensuring architectural agility against the high-variance demands of modern computing.

This research philosophy is embodied in my work on Misam, an adaptive framework that earned me First Place at the ACM Student Research Competition at MICRO 2024. My contributions, including both Misam and the Boötes framework, have been featured at top-tier venues such as MICRO, and reflect my broader goal of treating intelligence as a first-class citizen within the hardware stack. By integrating adaptability directly into the architectural fabric, I continue to push the boundaries of how intelligent computing infrastructure can be effectively deployed in increasingly resource-constrained and dynamic environments.