Udit Gupta, an Indian American assistant professor of electrical and computer engineering at Cornell Tech, has received an inaugural AI and Climate Fast Grant to explore strategies to reduce energy use in AI industries and to integrate AI in environmental research.
He is one of eight Cornell research teams chosen to receive an inaugural round of $10,000 to $25,000 grant funding to support research at the intersection of AI and climate science under The 2030 Project: A Cornell Climate Initiative, according to a media release.
Recent work by Cornell Engineering researchers found that at the current rate of AI growth, by 2030, AI would contribute between 24 million and 44 million metric tons of carbon dioxide to the atmosphere and use between 731 million and 1.125 billion cubic meters of water.
The Cornell AI Initiative, launched in 2022, is a university-wide radical collaboration that seeks to inform basic research into AI and to leverage AI and machine learning technologies to solve problems across many fields.
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Gupta seeks to improve the sustainability, efficiency and scalability of AI with “EcoGPT,” a generative AI interface that will enable users to parlay minimally slower AI response times into smaller carbon footprints.
“Industry benchmarks show that relaxing output generation by small delays – even a couple hundred milliseconds – can improve overall system throughput and energy efficiency by 2.5 times, highlighting a steep trade-off between lowered response times and system efficiency,” Gupta said.
“Our EcoGPT user studies will produce the first quantitative dataset on user preferences for ‘green AI,’ providing companies with the empirical evidence needed to design practical and sustainable service tiers.”
His research lies at the intersection of computer architecture, systems, machine learning, and environmental sustainability. He focuses on co-designing solutions across the computing stack — including applications, algorithms, systems, architecture, circuits, and devices — to enhance the performance, efficiency, and sustainability of emerging technologies.
Gupta’s work emphasizes practical impact, interdisciplinary collaboration, and pathfinding. He led the characterization of industry-scale neural personalized recommendation models, shaping future AI hardware design and specialized systems research.
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His team has developed open-source benchmarks and tools, now standardized in community efforts like MLPerf. Using these benchmarks, he has co-designed hardware and software systems that enable high-performance, efficient, and scalable AI, resulting in significant industry-wide resource savings.
His research also underscores the importance of integrating environmental sustainability as a core principle in systems design, identifying key challenges and opening new research avenues.
His work has been featured in Bloomberg Green, the Guardian, and CNBC. He has received accolades, including IEEE Micro Top Picks in 2022 and 2023, as well as an Honorable Mention in 2021.
His research earned best paper nominations at PACT 2019 and DAC 2018. His dissertation was recognized with the SIGARCH Outstanding PhD Dissertation Honorable Mention in 2023 and the MICRO Outstanding PhD Dissertation Honorable Mention, the same year.
Gupta holds a PhD in computer science from Harvard University and a BSc in electrical and computer engineering from Cornell University.