Four Indian American scientists awarded 2026 Sloan Research Fellowships for AI, cryptography, statistics, and quantum computing

Highlights:

• Four Indian American scholars named 2026 Sloan Fellows
• Each recipient receives a two-year $75,000 award
• Research spans AI, cryptography, statistics, and quantum computing
• Honors early-career scientific leadership and innovation
• Awards presented by the Alfred P. Sloan Foundation

Four Indian American researchers are among the 126 recipients of the 2026 Sloan Research Fellowships, one of the most respected honors for early-career scientists in the United States and Canada. The annual fellowships are awarded by the Alfred P. Sloan Foundation and recognize outstanding creativity, innovation, and research achievements.

The 2026 honorees include Aayush Jain, Arun Kumar Kuchibhotla, and Aditi Raghunathan from Carnegie Mellon University, and Anand Natarajan from Massachusetts Institute of Technology. Each fellow receives a two-year, $75,000 grant that can be used flexibly to advance their research.

“The Sloan Research Fellows are among the most promising early-career researchers in the U.S. and Canada, already driving meaningful progress in their respective disciplines,” said Stacie Bloom, president and CEO of the Alfred P. Sloan Foundation. She added that the foundation looks forward to seeing how these scholars continue to unlock scientific advancements and expand knowledge across fields.

Aayush Jain, an assistant professor in the Computer Science Department at Carnegie Mellon, focuses on theoretical and applied cryptography. His research explores the mathematical foundations that make modern encryption secure. Jain works to identify new and underexplored sources of computational hardness, the complex mathematical problems that form the backbone of secure digital communication. His work aims to strengthen long-term encrypted computation and address critical challenges in post-quantum cryptography, an emerging field that prepares security systems for the potential power of quantum computers. He also mentors graduate students in foundational cryptographic theory.

Arun Kumar Kuchibhotla, an associate professor in the Department of Statistics & Data Science at Carnegie Mellon, studies core challenges in statistical inference and predictive learning. His work has broad applications in artificial intelligence and machine learning. He develops robust, “assumption-lean” frameworks for measuring uncertainty in complex data settings. Kuchibhotla is known for advancing “honest inference” methods, including the Hull-based Confidence Method (HulC), which remains reliable in high-dimensional and irregular data environments where traditional statistical tools often fail. His research also contributes to financial forecasting and causal inference.

Aditi Raghunathan, also an assistant professor in Carnegie Mellon’s Computer Science Department, concentrates on AI safety and reliability. She studies how and why artificial intelligence systems fail and designs models that are safer, more accurate, and dependable in real-world applications. Raghunathan leads the AI Reliability Lab, where her team works to build aligned and trustworthy AI systems using rigorous analysis and principled methods. Her research has received recognition at major academic conferences and plays a key role in promoting responsible AI development.

Anand Natarajan, an associate professor of electrical engineering and computer science at MIT, specializes in quantum complexity theory. He is a principal investigator at MIT’s Computer Science and Artificial Intelligence Laboratory and the MIT-IBM Watson AI Lab. His research examines the limits of quantum computing, particularly the power of interactive proofs in quantum systems. Natarajan’s work seeks to better understand both the capabilities of quantum computers and how to verify the accuracy of their results. He earned his PhD in physics from MIT and previously conducted postdoctoral research at Caltech.

Together, these four scholars represent the next generation of scientific leaders pushing the boundaries of technology, mathematics, and computing.