Three Indian American scientists — Kiran Kumar Yalamanchi, FNU Shilpika, and Krishna Teja Chitty-Venkata — are among the winners of Argonne National Laboratory’s 2025 Outstanding Postdoctoral Performance Awards recognizing researchers supporting critical national energy and security missions.
These awards by Argonne, a Department of Energy science and engineering research laboratory, celebrate early-career researchers who demonstrate exceptional leadership, collaborative spirit, and measurable impact in their respective fields.
For these scientists, the road to the forefront of American exascale computing began with foundational academic training in India.
Engineering digital molecules: Kiran Kumar Yalamanchi
Kiran Kumar Yalamanchi serves as an Associate Research Scientist at Argonne, where he integrates physics-based understanding with machine learning. His work focuses on developing “multimodal foundation models” that help predict the behavior of complex fluid dynamics and design novel fuel molecules.
Yalamanchi’s academic journey started at the Indian Institute of Technology (IIT) Madras, where he completed 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 using AI to automate “inverse molecular design,” Yalamanchi is helping industry partners create more efficient and sustainable energy systems.
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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 research ensures that as supercomputers grow more complex, their operations remain transparent and predictable for scientists.
Shilpika is particularly recognized for developing a “digital twin” of Aurora, one of the world’s most powerful exascale supercomputers. This virtual replica allows operators to monitor system health and detect inefficiencies in real time.
Shilpika, who holds an MS from Loyola University Chicago and a PhD from UC Davis, exemplifies the global reach of Indian computer science, moving from initial training to managing the infrastructure of America’s most advanced computing machines.
Efficient AI for a greener future: Krishna Teja Chitty-Venkata
Krishna Teja Chitty-Venkata has focused his research on the intersection of deep learning and hardware optimization.
Recognizing that Large Language Models (LLMs) are often restricted by massive memory requirements, he developed open-source tools like LLM-Inference-Bench to measure and improve how efficiently these models run on supercomputers.
Chitty-Venkata began his engineering education at 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, focused on “pruning” and “quantizing” neural networks, aims to make AI faster and less energy intensive. Chitty-Venkata recently transitioned to a senior role at Red Hat, continuing his work on AI infrastructure.
The recognition of these three researchers underscores the vital role of the Indian diaspora in driving the next generation of American scientific innovation.