Three Indian American scientists — Kiran Kumar Yalamanchi, FNU Shilpika, and Krishna Teja Chitty-Venkata — are among the many winners of Argonne National Laboratory’s 2025 Outstanding Postdoctoral Performance Awards recognizing researchers supporting crucial nationwide power and safety missions.
These awards by Argonne, a Department of Energy science and engineering analysis laboratory, have a good time early-career researchers who show distinctive management, collaborative spirit, and measurable influence of their respective fields.
For these scientists, the street to the forefront of American exascale computing started with foundational tutorial coaching in India.
Engineering digital molecules: Kiran Kumar Yalamanchi
Kiran Kumar Yalamanchi serves as an Associate Research Scientist at Argonne, the place he integrates physics-based understanding with machine studying. His work focuses on creating “multimodal foundation models” that assist predict the conduct of complicated fluid dynamics and design novel gasoline molecules.
Yalamanchi’s tutorial journey began on the Indian Institute of Technology (IIT) Madras, the place he accomplished a Dual Degree (BTech and MTech) in Mechanical Engineering in 2017. He later earned his PhD from King Abdullah University of Science and Technology. By utilizing AI to automate “inverse molecular design,” Yalamanchi helps trade companions create extra environment friendly and sustainable power programs.
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The digital twin of Aurora: FNU Shilpika
At the Argonne Leadership Computing Facility (ALCF), FNU Shilpika is a pioneer in “Explainable AI” (XAI). Her analysis ensures that as supercomputers develop extra complicated, their operations stay clear and predictable for scientists.
Shilpika is especially acknowledged for creating a “digital twin” of Aurora, one of many world’s strongest exascale supercomputers. This digital reproduction permits operators to observe system well being and detect inefficiencies in actual time.
Shilpika, who holds an MS from Loyola University Chicago and a PhD from UC Davis, exemplifies the worldwide attain of Indian pc science, transferring from preliminary coaching to managing the infrastructure of America’s most superior computing machines.
Efficient AI for a greener future: Krishna Teja Chitty-Venkata
Krishna Teja Chitty-Venkata has centered his analysis on the intersection of deep studying and {hardware} optimization.
Recognizing that Large Language Models (LLMs) are sometimes restricted by large reminiscence necessities, he developed open-source instruments like LLM-Inference-Bench to measure and enhance how effectively these fashions run on supercomputers.
Chitty-Venkata started his engineering training on the University College of Engineering, Osmania University in Hyderabad. He subsequently moved to the US to earn his PhD in Computer Engineering from Iowa State University.
His work at Argonne, centered on “pruning” and “quantizing” neural networks, goals to make AI sooner and much less power intensive. Chitty-Venkata lately transitioned to a senior position at Red Hat, persevering with his work on AI infrastructure.
The recognition of those three researchers underscores the important position of the Indian diaspora in driving the subsequent era of American scientific innovation.