The Institute for Systems Research
Maryland Robotics Center
He is Professor of Electrical Engineering in the Electrical and Computer Engineering Department of the University of Maryland, where he also holds a joint appointment with the Institute for Systems Research. He was Director of the Maryland Robotics Center from 2012 until 2014.
He served as Associate Editor for Systems and Control Letters (Elsevier), Automatica and the IEEE Control Systems Society Conference Editorial Board. He was also a program Vice-Chair for the IEEE Conference on Decision and Control in 2013 and 2014.
Honors and awards
His research interests are in control theory, distributed control, team decision, optimization, networked control and communications, estimation and information theory.
- AFOSR: Air Force Center of Excellence on Nature-Inspired Flight Technologies and Ideas (NIFTI)
- NSF CPS Collaborative Research: Designing semi-autonomous networks of miniature robots for inspection of bridges and other large infrastructures
- NSF: Optimal Distributed Estimation over Shared Networks
- Remote Imaging of Community Ecology via Animal-borne Wireless Networks
- Distributed Learning and Information Dynamics in Networked Autonomous Systems
- NSF CPS: Ant-Like Microrobots—Fast, Small, and Under Control
- NSF Optimal Reference Tracking, the Next Step in the Design of Controllers for Markovian Jump Linear Systems
- NSF CAREER: Distributed control of dynamic systems using a wireless communcation medium: two new paradigms
- Monitoring Multiple Systems over Channels with Usage-Dependent Performance
- Semi-Autonomous Networks of Miniature Robots for Inspection of Large Infrastructures
- Reaching a Target inside a Denied Area: What is the Optimal Control Strategy?
- Optimal estimation over shared networks
- W-Crittercam system: Animal-borne wireless camera networks
- Optimal remote estimation: Managing a human operator's workload
- Distributed Decision Theory Group
- CPS: Ant-Like Microrobots
- Optimal Distributed State Estimation with Communication Cost: A Majorization Theory Approach
- A Convex Parameterization of All Stabilizing Controllers for Non-strongly Stabilizable Plants, under Quadratically Invariant Sparsity Constraints
- Gene Network Detection using Directed Mutual Information