Three Columbia Engineering Professors Win Sloan Fellowships

Matei Ciocarlie, Roxana Geambasu, and Daniel Hsu have been honored by the Alfred P. Sloan Foundation as rising stars.

Feb 23 2016 | By Holly Evarts and Kim Martineau

Three Columbia Engineering professors—Matei Ciocarlie (Mechanical Engineering), Roxana Geambasu (Computer Science), and Daniel Hsu (Computer Science)—have won 2016 Sloan Research Fellowships. They are among 126 outstanding young scientists and scholars announced today by the Alfred P. Sloan Foundation.

Awarded annually since 1955, the Sloan Fellowships honor early-career scientists and scholars whose achievements and potential identify them as rising stars, the next generation of scientific leaders. The 2016 fellows, who receive $50,000 to further their research, have been drawn from 52 colleges and universities in the United States and Canada, and represent a wide range of research interests.

Matei Ciocarlie —Photo by Eileen Barroso

Matei Ciocarlie’s research is focused on developing versatile manipulation and mobility in robotics, in particular on building dexterity into robotic hands, and he sees robotic manipulation in unstructured environments as a critical research area. “We aim to discover how artificial mechanisms can interact with the world as skillfully as biological organisms,” he notes. So far, robotic applications that have had significant impact (especially in industrial domains) have done it by being fast, precise, and tireless. In order to advance to less constrained domains, robots need to become more versatile and learn to handle variability, or be more intelligent in their environment interaction. “True dexterity in interacting with the world will play a role in the more general problem of developing cognitively advanced computers and machines,” Ciocarlie adds. His Robotic Manipulation and Mobility Lab is working on a range of applications, from versatile automation in manufacturing and logistics to mobile manipulation in unstructured environments to assistive and rehabilitation robotics in healthcare. He is a member of the Data Science Institute and has won numerous prestigious honors, including the 2013 IEEE Robotics and Automation Society Early Career Award, a 2015 Young Investigator Program grant from the Office of Naval Research, a 2015

Roxana Geambasu —Photo by Eileen Barroso

Computer Science Professor Roxana Geambasu is working to ensure data security and privacy in an era of cloud computing and ubiquitous mobile devices—technologies upon which billions of users rely to access and host sensitive data and which have become easy targets for theft, espionage, hacking, and legal attacks. Our mobile devices are packed with confidential information under operating systems that never securely erase data. And at the other end, cloud services not only accumulate endless logs of user activity, such as searches, site visits, and locations, but also keep them for extended periods of time, mine them for business value, and at times share them with others—all without the user’s knowledge or control. Geambasu, a member of the Data Science Institute, is working to identify the security and privacy risks inherent in current mobile and web technology and designs, and constructing systems to address those problems. Her research spans broad areas of systems research, including cloud and mobile computing, operating systems, and databases, all with a focus on security and privacy. She integrates cryptography, distributed systems, database principles, and operating systems techniques and works collaboratively in developing cross-field ideas in order to solve today’s data privacy issues.

Daniel Hsu —Photo by Ryan John Lee

A computer science professor at Columbia Engineering and a member of the Data Science Institute, Daniel Hsu develops machine learning algorithms that have been used in automated language translation, personalized medicine, and privacy transparency systems. His work making computers smarter was recently recognized in IEEE’s Intelligent Systems magazine. Hsu specializes in a branch of machine learning called interactive learning, which turns an algorithm loose on a small set of hand-labeled data. When the algorithm encounters a term it doesn’t recognize, it requests a label, massively speeding up the training process. As a graduate student in the late 2000s, Hsu helped develop an active learning method that was later applied to electrocardiograms, reducing the amount of training data needed by 90 percent. His work on Hidden Markov Models has been applied in genomics to understand the role of gene regulation in disease, and how the chromatin packaging a cell’s DNA may be implicated. More recently, he helped develop a tool to bring greater transparency to how personal data is used on the Web.

The Sloan Fellowships are awarded in eight scientific and technical fields—chemistry, computer science, economics, mathematics, computational and evolutionary molecular biology, neuroscience, ocean sciences, and physics. Candidates are nominated by their fellow scientists and winning fellows are selected by an independent panel of senior scholars.

For a complete list of winners, visit:

For more information on the Alfred P. Sloan Foundation, visit: