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Ankur Moitra And Yogesh Surendranath Of MIT Named 2016 Sloan Research Fellows

Press Release
03/10/2016

Venkat Chandrasekaran of the California Institute of Technology, Abhinav Gupta of Carnegie Mellon, Ankur Moitra and Yogesh Surendranath of the Massachusetts Institute of Technology, Devi Parikh of Virginia Tech, and Surjeet Rajendran and Nikhil Srivastava of the University of California, Berkeley are among the selection of 126 outstanding U.S. and Canadian researchers as recipients of the 2016 Sloan Research Fellowships announced by The Alfred P. Sloan Foundation.  
 
Awarded annually since 1955, the fellowships honor early-career scientists and scholars whose achievements and potential identify them as rising stars, the next generation of scientific leaders. Fellows receive $55,000 to further their research. 

An assistant professor in the Computing and Mathematical Sciences Department at the California Institute of Technology, Chandrasekaran's research focuses on mathematical optimization and, specifically, developing an understanding of the power and limitations of convex optimization.

His thesis work studied convex optimization in the context of questions related to statistical modeling, and received the Jin-Au Kong Outstanding Doctoral Thesis Prize for the best Ph.D. thesis in electrical engineering at MIT. Additionally, he received the Young Researcher Prize in Continuous Optimization for his work on matrix decomposition.

Gupta is an assistant professor at Carnegie Mellon University’s Robotics Institute. His research focuses on how humans interact with their environment and how their perception of visual world depends on these interactions and their abilities.

Building upon Gibson's idea of affordances, he and his team have recently proposed the concept of human centric scene understanding, developing representation and reasoning approaches for deeper understanding.

Moitra is an assistant professor in the Department of Mathematics at MIT and a member of the Computer Science and Artificial Intelligence Lab. Prior to that, he was an NSF CI Fellow at the Institute for Advanced Study, and also a senior postdoc in the Computer Science department at Princeton University.

He has worked in numerous areas of algorithms, including approximation algorithms, metric embeddings, combinatorics and smoothed analysis, but lately has been working on the intersection of algorithms and machine learning.

Surendranath’s lab is focused on addressing global challenges in the areas of chemical catalysis, energy storage and utilization, and environmental stewardship. Fundamental and technological advances in each of these areas require new methods for controlling the selectivity and efficiency of inner-sphere reactions at solid-liquid interfaces.

The strategy for his team emphasizes the bottom-up, molecular-level, engineering of functional inorganic interfaces with a current focus on electrochemical energy conversion.

Parikh, who leads the Computer Vision Lab at Virginia Tech, is the 2014 recipient of the Allen Distinguished Investigator Award from the Paul G. Allen Family Foundation. She is using the money to help computers "read" complex images with the use of cartoon clip art scenes.

She believes that the best way to do so would be by using hundreds of thousands of Amazon Mechanical Turk workers online to showcase the visual world with clip art.

Rajendran graduated from Caltech in 2004 with a degree in mathematics and subsequently pursued a Ph.D. in Physics from Stanford. He has broad interests in theoretical physics with a strong focus on physics beyond the standard model.

While the standard model of particle physics has repeatedly withstood many experimental tests, it leaves many questions unanswered. Rajendran is interested in inventing new experimental avenues to help answer these questions and discover new physics.

Srivastava is an assistant professor in the mathematics department at UC Berkeley. He received his Ph.D. in computer science from Yale in 2010, and his BS from Union College in 2005.

After postdocs at the IAS, Princeton, and MSRI, he spent two and a half years as a researcher at Microsoft Research India, before coming to Berkeley. He is currently interested in algorithms, spectral graph theory, random matrices, and the geometry of polynomials.



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