Kristen Grauman’s research focuses on designing the algorithms and learning processes that will allow computers to understand and organize visual information. In particular, she is interested in tackling the major scalability issues that surround visual recognition and search. The goal is to make it possible to efficiently index large volumes of visual data (images or videos) based on their content—a functionality that has the potential to greatly benefit a variety of users, from personal consumers to scientists and engineers.

Susan Hohenberger
Johns Hopkins University
Assistant Professor
Department of Computer Science

 

Susan Hohenberger focuses on cryptography: the art of securely communicating. She is interested in designing secure solutions for pervasive settings, where devices everywhere are constantly talking to their environments, which may require low energy, short overhead and the ability to quickly process a large number of incoming messages. Her research includes an emphasis on developing privacy-friendly technologies, such as anonymous communication and electronic cash.

Robert Kleinberg
Cornell University
Assistant Professor
Computer Science

 

Robert Kleinberg studies the theory of algorithm design under informational limitations. This means that he looks at practical questions in computer science—such as how to design more robust adaptive systems for web search, network routing, online auctions, and product recommendations—and address these questions using mathematically rigorous techniques that build on ideas from learning theory, game theory, and information theory.

Philip Levis
Stanford University
Assistant Professor
Departments of Computer Science and Engineering

 

Philip Levis researches software and networking for tiny, low-power, wireless sensors. He focuses on making these networks of sensors easier to deploy and maintain by researching ultra-simple algorithms that use robust local rules to achieve desirable global behaviors. Software he develops is used by hundreds of research groups worldwide and runs on millions of nodes.

Russell Tedrake
Massachusetts Institute of Technology
Assistant Professor
Electrical Engineering and Computer Science

 

Russell Tedrake works on computational and machine learning approaches to control system design for robots that walk, run, swim, and fly more like real animals. He believes that, to succeed, both the mechanical design of the robots and the algorithms for controller design must exploit the natural, nonlinear dynamics of locomotion. In the next few years, he aims to build bipedal robots that can walk and jump across piles of rocks, and robotic birds with flapping wings that can gracefully land on a perch.