News

Radhika Nagpal approved for promotion to tenured full professor

Computer scientist applies inspirations from biological multi-agent systems to computer and robotic systems

Radhika Nagpal's research draws on inspiration from social insects and multicellular biology, with the goal of creating globally robust systems made up of many cooperative parts.

Cambridge, Mass. - April 16, 2012 - Harvard President Drew Faust has approved Radhika Nagpal for promotion to the role of full professor with tenure at the Harvard School of Engineering and Applied Sciences (SEAS).

Nagpal, the Thomas D. Cabot Associate Professor of Computer Science at SEAS and a Core Faculty Member at the Wyss Institute for Biologically Inspired Engineering at Harvard, heads the Self-Organizing Systems Research Group in the study of collective behavior in biological systems and how such behaviors can be applied to computing and robotics.

Her research draws on inspiration from social insects and multicellular biology, with the goal of creating globally robust systems made up of many cooperative parts. Nagpal also investigates complex biological systems through mathematical and computational models. Discoveries in these areas have applications in computer networking, robot swarms, and sensor networks.

A study by her Self-Organizing Systems Research Group recently resulted in the Kilobots, tiny, inexpensive robots that are designed as a tool for understanding complex, distributed systems. The Kilobots' design allows researchers to manage large numbers of the tiny bots, where previous research was limited to smaller numbers or computer simulations.

Nagpal completed her S.B., S.M. (1994) and Ph.D. (2001) in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. She came to Harvard in 2003 as a Research Fellow in the Department of Systems Biology at Harvard Medical School and remains an affiliated faculty member of that department today.

Nagpal is a recipient of the 2010 Borg Early Career Award and the 2007 National Science Foundation (NSF) Career Award. 

Topics: Computer Science, Bioengineering, AI / Machine Learning