10 Indian American scholars win Sloan Research Fellowships

Ten Indian American early-career scholars are among 126 outstanding early-career researchers across seven fields selected to receive a prestigious Sloan Research Fellowships in 2024.

Awarded annually since 1955, the fellowships honor exceptional US and Canadian researchers whose creativity, innovation, and research accomplishments make them stand out as the next generation of leaders, New York-based Alfred P. Sloan Foundation announced.

“Sloan Research Fellowships are extraordinarily competitive awards involving the nominations of the most inventive and impactful early-career scientists across the US and Canada,” says Adam F. Falk, president of the Alfred P. Sloan Foundation. “We look forward to seeing how Fellows take leading roles shaping the research agenda within their respective fields.”

READ: 11 Indian Americans among 2023 Sloan Research Fellows (February 20, 2023)

Fellows from the 2024 cohort are drawn from a diverse range of 51 institutions across the US and Canada, including large public university systems, Ivy League institutions, and small liberal arts colleges. Winners receive $75,000, which may be spent over a two-year term on any expense supportive of their research.

Indian Americans who won the Sloan Research Fellowship are:

Priyanka Raina, Stanford University (Computer Science)
Raina is an Assistant Professor of Electrical Engineering at Stanford University. She received her BTech in Electrical Engineering from IIT Delhi in 2011 and her SM and PhD in Electrical Engineering and Computer Science from MIT in 2013 and 2018.

Her research is on creating high-performance and energy-efficient architectures for domain-specific hardware accelerators in existing and emerging technologies and agile hardware-software co-design.

Her research has won best paper awards at VLSI, ESSCIRC and MICRO conferences and in the JSSC journal. She teaches several VLSI design classes at Stanford. She has also won the Intel Rising Star Faculty Award, Hellman Faculty Scholar Award and is a Terman Faculty Fellow.

READ: 9 Indian Americans awarded $50,000 Sloan Research Fellowships (March 16, 2015)

Arvind Satyanarayan, Massachusetts Institute of Technology (Computer Science)
Satyanarayan is an Assistant Professor of Computer Science at MIT, where he leads the Visualization Group at MIT CSAIL.

His research uses interactive data visualization as a petri dish to study intelligence augmentation, or how do computational representations and software systems help amplify our cognition and creativity while respecting our agency.

His work has been recognized with an NSF CAREER award, best paper awards at academic venues. He received my PhD from the Computer Science department at Stanford.

Dipti Nayak, University of California, Berkeley (Earth System Science).
Nayak is Assistant Professor in Molecular and Cell Biology at University of California, Berkeley. She received her PhD from the Department of Organismic and Evolutionary Biology at Harvard University in 2014.

She was a Simons Foundation Fellow of the Life Sciences Research Foundation /Carl R. Woese Postdoctoral Fellow at the University of Illinois Urbana-Champaign from 2015-2019.

She is broadly interested in the physiology and evolution of Archaea, specifically members within this domain that produce and consume the greenhouse gas methane.

READ: Seven Indian Americans amongst 126 awardees of the 2014 Sloan Research Fellowship (February 20, 2014)

She is a recipient of the Beckman Young Investigator Award, the Searle Scholars Award, the Packard Fellowship in Science and Engineering, a Rose Hills Innovator Grant and the Simons Foundation Early Career Investigator in Marine Microbial Ecology and Evolution. Outside of the lab, she enjoys hiking and pottery.

Aaditya Ramdas, Carnegie Mellon University (Mathematics)
Ramdas is an assistant professor at Carnegie Mellon University, in the Departments of Statistics and Machine Learning. He was one of the inaugural inductees of the COPSS Leadership Academy. His work is supported by an NSF CAREER Award, an Adobe Faculty Research Award, and an ARL Grant on Safe RL, amongst others.

His main theoretical and methodological research interests include selective and simultaneous inference, sequential uncertainty quantification, and distribution-free black-box predictive inference. His areas of applied interest include neuroscience, genetics and voting.

He has a PhD in Statistics and Machine Learning from Carnegie Mellon, and a Bachelors in Computer Science and Engineering, from IIT Research Institute, Chicago.

Ananth Shankar, Northwestern University (Mathematics)
Shankar is an assistant professor at Northwestern University.He graduated with a BSc in Mathematics and Computer Science from Chennai Mathematical Institute in August, 2012.

He was a PhD student at Harvard University, and graduated in May 2017. Before joining Northwestern, he was at MIT as a CLE Moore Instructor until July 2020, and an assistant professor at UW Madison until June 2023received his PhD from Harvard University in 2017.

His research is in arithmetic geometry and number theory, focusing mainly on Shimura varieties and abelian varieties. He has also worked on arithmetic differential equations.

Vineet Augustine, University of California, San Diego (Neuroscience)
Augustine is assistant professor of Neurobiology at the University of California, San Diego. He received his BS-MS from IISER, Kolkata (2013) followed by a PhD from the California Institute of Technology, Pasadena (2019).

As a result of his exemplary PhD work, he was awarded the prestigious Scripps Fellowship to skip the traditional postdoc and start his own lab at Scripps Research, La Jolla in 2019. His lab moved to UCSD in 2022.

His research has been covered by multiple news outlets including The New York Times, Scientific American and National Public Radio. The NIH Director has also written a personal blog about his work.

Vijay Mohan K Namboodiri, University of California, San Francisco (Neuroscience)
Namboodiri is the Scott Alan Myers Endowed Professor at University of California, San Francisco. He received his BTech in Engineering Physics from IIT-Bombay (Mumbai, India) in 2008, PhD in Neuroscience from The Johns Hopkins University School of Medicine in 2015.

He completed his postdoctoral research with Dr. Garret Stuber at UNC-Chapel Hill and University of Washington Schools of Medicine in 2020. His research focuses the biological algorithms and neuronal network mechanisms underlying associative learning, memory and decision-making.

Preeya Khanna, University of California, Berkeley (Neuroscience)
Khanna is assistant professor of electrical engineering and computer sciences at University of California, Berkeley.

She received a BSE in Bioengineering and Mathematics from the University of Pennsylvania in 2012, and a PhD in the Joint Graduate Group in Bioengineering from UC Berkeley and UCSF in 2017.

She completed her postdoctoral training in the Department of Neurology at UCSF. Her research combines sensorimotor systems neuroscience, network modeling, and neurotechnology development with the goal of uncovering principles of how distributed brain networks coordinate to control skilful dexterous movements.

Karan K. Mehta, Cornell University (Physics)
Mehta is assistant professor of Electrical and Computer Engineering at Cornell University. He received BS degrees from UCLA in Physics and Electrical Engineering in 2010, and completed his PhD in Electrical Engineering and Computer Science at MIT in 2017.

Following stints as a postdoctoral fellow and senior scientist in the physics department at ETH Zurich, he joined Cornell ECE in January 2022, where he leads a group working at the intersection of photonics, atomic physics, and quantum technologies.

Vikram Ravi, California Institute of Technology (Physics).
Ravi is assistant professor of Astronomy at California Institute of Technology. His professional focus is on exploring and understanding the ephemeral, unseen Universe.

He was educated at the Valley School, Bangalore, and Narrabri High School, NSW Australia. He studied physics as part of the Bachelor of Philosophy (PhB) at the Australian National University. He completed my PhD at the University of Melbourne.

He then spent a part of 2014-15 working with Prof. Matthew Bailes and his group at Swinburne University on the nascent upgrade of the Molonglo Observatory to form a fast transient, pulsar and wide-field imaging behemoth. He spent 2015-18 as a Millikan Fellow in Astronomy at Caltech, and 2018-19 as a Clay Fellow at the Center for Astrophysics, Harvard and Smithsonian.