Nisar R. Ahmed, Ph.D.
Research and Engineering Center for Unmanned Vehicles (RECUV)
Department of Aerospace Engineering Sciences
University of Colorado Boulder
Office: ECAE 175
Office hours: Tuesday, 9-10am; 4:30- 5:30pm
My research focuses on developing algorithms and models that promote cooperative intelligence in mixed teams of humans and autonomous robotic vehicles. I currently work in three problem areas:
-cooperative sensing and perception in human-robot teams
-modeling and prediction of human decision making and task performance
-robust fusion of complex information in dynamic sensor networks
Click on the links on the left to find out more. Also check out this link for related research at CU Boulder
MS students Matthew Aitken and Nicholas Sweet successfully defended their MS Theses on July 19 and 20, respectively.
Matt's thesis: "Assured Human-Autonomy Interaction through Machine Self-Confidence"
Nick's thesis: "Semantic Likelihood Models for Bayesian Inference in Human-Robot Interaction"
We all wish them both the very best as they kick off exciting futures in robotics!
Girish Chowdhary, Soumik Sarkar, Luca Bertucelli and I organized this workshop in early July -- click here to see the slides from all of the great speakers who participated. Thanks to all participants for making this workshop a great success!
"Structured Synthesis and Compression of Semantic Human Sensor Models for Bayesian Estimation," by Nicholas Sweet and Nisar Ahmed (IEEEXplore link to final paper)
"Deep Value of Information Estimators for Collaborative Human-Machine Information Gathering," by Kin Gwn Lore, Nicholas Sweet, Kundan Kumar, Nisar Ahmed and Soumik Sarkar (arXiv pre-print version)
"Scalable Decentralized Target Localization with Ownship Uncertainties," by Nisar Ahmed, William Whitacre, Sangwoo Moon and Eric Frew (AIAA ARC link)
"Event-based Cooperative Localization using Implicit and Explicit Measurements," by Michael Ouimet, Nisar Ahmed, and Sonia Martinez (final paper)
"What's One Mixture Divided by Another?: A Unified Approach to High-fidelity Distributed Data Fusion with Mixture Models," by Nisar Ahmed (final paper)
I am also co-organizing a full-day MFI 2015 workshop on Large-scale Bayesian Data Fusion and Consensus
Paper Accepted to RSS 2015 Workshop on Model Learning for Human-Robot Communication
I also co-organized the RSS 2015 Workshop on Realistic, Rapid and Repeatable Robot Simulation
"Unified Mixture-Model Based Terrain Estimation with Markov Random Fields," by Rina Tse, Nisar Ahmed, and Mark Campbell published in IEEE Transactions on Robotics (final paper)
"Fully Bayesian Learning and Spatial Reasoning with Flexible Human Sensor Networks," by N. Ahmed, M. Campbell, D. Casbeer, Y. Cao, and D. Kingston presented in Seattle, WA, April 14-16, 2015 (final paper)
"Bayesian Hidden Markov Models for UAV-Enabled Target Localization on Road Networks with Soft-Hard Data," by N. Ahmed, D. Casbeer, Y. Cao, and D. Kingston presented in Baltimore, MD, April 20-24, 2015 (final paper)
"Decentralized Bayesian Fusion in Networks with Non-Gaussian Uncertainties", by Nisar R. Ahmed, Simon J. Julier, Jonathan R. Schoenberg, and Mark E. Campbell to be published in forthcoming book Multisensor Data Fusion: From Algorithm and Architecture Design to Applications (CRC Press, H. Fourati and K. Iniewski, Eds.) (final unformatted draft)
"Conditionally Factorized DDF for General Distributed Bayesian Estimation" to be presented at Tsinghua University, Beijing China, September 28-30, 2014 (download paper)
I have been selected to the ASEE Summer Faculty Fellowship Program, and will be spending the summer working with Dr. Derek Kingston, Dr. David Casbeer, and other members of the Control Science Center of Excellence at the Air Force Research Lab at Wright-Patterson AFB in Dayton, OH.
I am co-organizing a workshop at the RSS Conference in Berkeley this July on "Distributed Control and Estimation for Robotic Vehicle Networks" -- we have lots of great speakers lined up, please check the link for more information and updates as they occur. Hope to see you there!
AES grad student Nicholas Sweet joins the research group -- welcome Nick! (check out his webpage)