Nisar Ahmed

About

Nisar Ahmed is an Associate Professor in the Ann and H.J. Smead Aerospace Engineering Sciences at the University of Colorado Boulder, where he also serves as the Director of the Research and Engineering Center for Unmanned Vehicles (RECUV). His educational background includes a PhD and MS in Mechanical Engineering with a focus on Dynamics, Systems, and Controls from Cornell University, and a BS in Engineering from The Cooper Union for the Advancement of Science and Art. His research interests encompass collaborative human and autonomous robot vehicle systems, dynamic state estimation and sensor fusion, supervisory control and decentralized coordination in networked systems, as well as the application of statistical system identification, machine learning, and artificial intelligence to aerospace challenges. He has held various roles at CU Boulder, including Site Director for the NSF IUCRC Center for Aerial Autonomy, Mobility, and Sensing, and has been recognized with awards such as the H. Joseph Smead Faculty Fellow and the AIAA Guidance, Navigation and Control Conference Best Paper Award.

Research topics

• Artificial Intelligence
• Computer Science
• Machine Learning
• Mathematics
• Physics
• Human–computer interaction
• Psychology
• Neuroscience
• Geography
• Engineering

Selected publications

• Designing Sun–Earth L2 Halo Orbit Stationkeeping Maneuvers via Reinforcement Learning

  Journal of Guidance Control and Dynamics · 2022 · 23 citations

  Reinforcement learning (RL) is used to design impulsive stationkeeping maneuvers for a spacecraft operating near an [Formula: see text] quasi-halo trajectory in a Sun–Earth–Moon point mass ephemeris model with solar radiation pressure. This scenario is translated into an RL problem that reflects the desired stationkeeping goals, variables, and dynamical model. An algorithm from proximal policy optimization is used to train a policy that generates stationkeeping maneuvers while transfer learning…

  PublisherDOI

• Collaborative human-autonomy semantic sensing through structured POMDP planning

  Robotics and Autonomous Systems · 2021 · 21 citations

  DOI

• COMPASS: Computations for Orientation and Motion Perception in Altered Sensorimotor States

  Frontiers in Neural Circuits · 2021 · 18 citations

  Reliable perception of self-motion and orientation requires the central nervous system (CNS) to adapt to changing environments, stimuli, and sensory organ function. The proposed computations required of neural systems for this adaptation process remain conceptual, limiting our understanding and ability to quantitatively predict adaptation and mitigate any resulting impairment prior to completing adaptation. Here, we have implemented a computational model of the internal calculations involved in…

  DOI

• Observation-Augmented Contextual Multi-Armed Bandits for Robotic Search and Exploration

  IEEE Robotics and Automation Letters · 2024-08-22 · 5 citations

  articleSenior author

  We introduce a new variant of contextual multi-armed bandits (CMABs) called observation-augmented CMABs (OA-CMABs) wherein a robot uses extra outcome observations from an external information source, e.g. humans. In OA-CMABs, external observations are a function of context features and thus provide evidence on top of observed option outcomes to infer hidden parameters. However, if external data is error-prone, measures must be taken to preserve the correctness of inference. To this end, we deriv…

  PublisherDOI

• “A Good Bot Always Knows Its Limitations”: Assessing Autonomous System Decision-Making Competencies through Factorized Machine Self-Confidence

  ACM Transactions on Human-Robot Interaction · 2025-04-28 · 4 citations

  article

  How can intelligent machines assess their competency to complete a task? This question has come into focus for autonomous systems that algorithmically make decisions under uncertainty. We argue that machine self-confidence—a form of meta-reasoning based on self-assessments of system knowledge about the state of the world, itself, and ability to reason about and execute tasks—leads to many computable and useful competency indicators for such agents. This article presents our body of work, so far,…

  PublisherDOI

Frequent coauthors

• Mark Campbell

  29 shared

• Alan E. Willner

  University of Southern California

  28 shared

• Yongxiong Ren

  Robert Bosch (Germany)

  28 shared

• Guodong Xie

  24 shared

• Nicholas Conlon

  University of Colorado Boulder

  24 shared

• Eric W. Frew

  22 shared

• Moshe Tur

  Tel Aviv University

  21 shared

• Hao Huang

  21 shared

Education

• Ph.D., Mechanical Engineering (Dynamics, Systems and Controls)

  Cornell University

  2012

• M.S., Mechanical Engineering (Dynamics, Systems and Controls)

  Cornell University

  2009

• B.S.

  The Cooper Union for the Advancement of Science and Art

  2006

Awards & honors

• H. Joseph Smead Faculty Fellow (2021)
• Aerospace Control and Guidance Systems Committee (ACGSC) Dav…
• ASEE Air Force Summer Faculty Fellowship (2014)
• AIAA Guidance, Navigation and Control Conference Best Paper…

Similar researchers at University of Colorado Boulder

• James Brasseurh-49
• John Evansh-42
• Dennis Akosh-33