Udit Gupta

Assistant Professor
Cornell Tech

[ECE] [CSL]
[Jacobs Technion-Cornell Institute]
[Atkinson Center for Sustainability]

ugupta@cornell.edu


I am an Assistant Professor in the Department of Electrical and Computer Engineering at Cornell Tech. My research interests lie at the intersection of computer architecture, systems, machine learning and environmental sustainability. The central theme to my research is co-designing solutions across the computing stack (applications, algorithms, systems and architecture, circuits and devices) to design and implement computer systems and hardware in new ways to improve the performance, efficiency, and environmental sustainability of emerging applications.

Through research, I am driven to realizing practical impact, building interdisciplinary research communities, and pathfinding. I led the characterization of industry scale neural personalized recommendation models, outlining paths for future AI hardware design and academic research into specialized systems for AI. Based on the key insights we built open-source systems' benchmarks and tools that have been standardized as part of the community efforts such as MLPerf Using these benchmarks I developed specialized hardware/software systems by co-designing solutions across the computing stack to enable high performance, efficient, and scalable AI at-scale; these solutions have evaluated in real-world industry scenarios saving significant AI cycle and infrastructure resources. Going beyond performance and efficiency, my research also demonstrates the critical need to incorproate environmental sustainability as a first-order design principle in systems design, development, and deployment. My research identifies fundamental bottlenecks towards enabling environmentally sustainability computing, opening new research opportunities across the computing stack from applications to algorithms and from systems and hardware to circuits and devices.

Honors/Awards: My work has been featured in venues such as Bloomberg Green, The Guardian, and CNBC. My work has been awarded an IEEE MICRO Top Picks (2022 and 2023) and IEEE MICRO Top Picks Honorable Mention (2021), as well as receieved Best Paper Nominations at the Parallel Architectures and Compilation Techniques (PACT 2019) and Design Automation Conference (DAC 2018). My dissertation received the SIGARCH Outstanding Ph.D. Dissertation Honorable Mention in 2023 as well as the MICRO Outstanding Ph.D. Dissertation Honorable in 2023. I received my Ph.D. in Computer Science at Harvard University and BSc in Electrical and Computer Engineering from Cornell University.

Prospective students: I am actively looking for motivated, ambitious, and passionate graduate students, postdoctoral scholars, and undergraduate. If you are interested in working with me please read the following page.

Research Interests


My current research interests include:

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