Radhika Nagpal, Ph.D.
Founding Core Faculty Member
Platform Co-Lead, Bionspired Robotics
Radhika is developing programming paradigms that enable new types of robotic systems to mimic the collective behaviors of living creatures. Inspired by bee swarms and termite colonies, she is applying nature's approach to decentralized cooperation to engineer new collective systems that meet real-world challenges. Biological systems, from embryos to social insects, depend upon the coordinated behavior of large numbers of individual agents to achieve highly complex outcomes--termites build skyscrapers and embryonic cells develop into healthy babies. Radhika is building new types of distributed systems -- from multi-modular robots and robot swarms, to vast sensor networks -- that have similar capabilities. Her research spans theory (e.g., mathematical models of programmable self-assembly), engineering (e.g., building self-adapting modular robots), and biology (e.g., models of multicellular development). Current projects include developing control policies that enable efficient pollination by a swarm of robotic bees, creating self-balancing tables and other structures that adapt to changing circumstances, and developing termite-inspired robots to help automate human construction. One of her group's goals is to create a framework for the design and analysis of self-organizing, multi-agent systems by formalizing natural collective behavior. In the future, such frameworks could facilitate the development of new robotic applications to assist society.
Radhika is the Fred Kavli Professor of Computer Science at the Harvard School of Engineering and Applied Sciences. She received the 2010 Borg Early Career Award from the Committee on the Status of Women in Computing Research, a 2007 National Science Foundation Career Award, and the 2005 Microsoft New Faculty Fellowship Award.
Modeling and Inferring Cleavage Patterns in Proliferating Epithelia
Cell division is one of the key mechanisms driving organismal growth and morphogenesis. Yet many aspects of the relationship between local cell division (how a cell chooses an orientation to divide) and global tissue architecture (e.g. regular vs irregular cells) remain poorly understood.