Musad Haque Print



:   AI Scientist specializing in spacecraft autonomy; swarming; multiagent systems

:  Earth

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Degree Field of Study Year Attained Institution Name
PhD Electrical and Computer Engineering 2010 Georgia Institute of Technology
MS Electrical and Computer Engineering 2008 Georgia Institute of Technology
BS Electrical Engineering 2006 University of Texas at Arlington

I study distributed artificial intelligence, particularly its application to space, from Earth science to planetary exploration. My research focuses on strategic coordination, onboard algorithms, and constellation design considerations, such as heterogeneity and team compositions. I work on the Double Asteroid Redirection Test (DART) mission, NASA’s first test mission for planetary defense. I’m currently a member of DART’s Integration and Testing team, having previously been a part of the mission’s Autonomy, Fault Management, and SMART Nav/GNC teams. My background is in swarm robotics. As part of that training, I’ve researched how to transition collective behaviors found in nature to artificial, networked systems. The swarming work has appeared in leading venues, such as the IEEE Transactions on Automatic Control, Automatica, European Conference on AI, and the Conference on Intelligent Robots and Systems. I was the PI of an Office of Naval Research project investigating self-organizing systems. My current research projects range from providing hyper-local situational awareness in the aftermath of disasters, predicting the outbreak of waterborne diseases, to the coordination of sensor platforms. A common thread in my work is an interest to connect novel remotely-sensed products, analytics, and multiagent systems.

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Start Year End Year Description
2017 Current Autonomy and Intelligent Systems Development Section Embedded Applications Group Space Exploration Sector Johns Hopkins University Applied Physics Laboratory
2020 Current Lecturer (Artificial Intelligence) Department of Computer Science Johns Hopkins University
2018 Current Adjunct Professor Department of Computer Science and Electrical Engineering University of Maryland, Baltimore County
2015 2017 Postdoctoral Research Scholar Human-Machine Teaming Lab Vanderbilt University
2007 2010 Graduate Research Assistant Georgia Robotics and Intelligent Systems Lab Georgia Institute of Technology
Year Description
2021 APL Sabbatical Fellowship and Professorship
2017-2020 Mentor ASPIRE High School Interns APL STEM Program Management Office
2019 AGU
2017 IEEE
The following publication information was downloaded from

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, (2020), Continuum: A New Observing Strategies-Based Framework for Hyper-Local Situational Awareness, American Geophysical Union (AGU)

, (2020), Waterborne Disease Outbreaks in the Post-Disaster Scenario: Can High-Resolution Earth Observations and Smallsat Imagery Enhance Cholera Forecasting?, American Geophysical Union (AGU)

, (2019), A Swarming-based New Observing Strategy using Intelligent, Heterogeneous Satellites for Disasters and Public Health Emergencies, American Geophysical Union (AGU)

, (2019), Onboard Artificial Intelligence and Machine Learning for Enhancing Smallsat Constellations, IAC/IAF Space Operations Symposium

, (2018), Small-Body Maneuvering Autonomous Real-Time Navigation (SMART NAV): Guiding A Spacecraft to Didymos for NASA’s Double Asteroid Redirection Test (DART), Advances in the Astronautical Sciences: Guidance, Navigation, and Control Conference

Musad Haque, Connor McGowan, Yifan Guo, Douglas Kirkpatrick, Julie A. Adams, (2018), Communication ModeltextendashTask Pairing in Artificial Swarm Design, IEEE Robotics and Automation Letters, 3, 4, 3073--3080,

Musad Haque, Waseem Abbas, Abigail Rafter, Julie A. Adams, (2017), Efficient topological distances and comparable metric ranges, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS),

, (2016), Analysis of swarm communication models, European Conference on Artificial Intelligence

Musad Haque, Amir Rahmani, Magnus Egerstedt, Anthony Yezzi, (2014), Efficient Foraging Strategies in Multi-Agent Systems Through Curve Evolutions, IEEE Transactions on Automatic Control, 59, 4, 1036--1041,

M. Haque, M. Egerstedt, A. Rahmani, (2013), Multilevel Coalition Formation Strategy for Suppression of Enemy Air Defenses Missions, Journal of Aerospace Information Systems, 10, 6, 287--296,

G. Notarstefano, M. Egerstedt, M. Haque, (2011), Containment in leadertextendashfollower networks with switching communication topologies, Automatica, 47, 5, 1035--1040,

Musad Haque, Amir Rahmani, Magnus Egerstedt, Anthony Yezzi, (2011), Biologically motivated shape optimization of foraging fronts, Proceedings of the 2011 American Control Conference,

Musad A. Haque, Amir R. Rahmani, Magnus B. Egerstedt, (2011), Biologically inspired confinement of multi-robot systems, International Journal of Bio-Inspired Computation, 3, 4, 213,

Musad Haque, Amir Rahmani, Magnus Egerstedt, Anthony Yezzi, (2011), Optimization of foraging multi-agent system front: A flux-based curve evolution method, 2011 IEEE International Conference on Robotics and Biomimetics,

, (2010), Sustainable Group Sizes for Multi-Agent Search-and-Patrol Teams, Mathematical Theory of Networks and Systems (MTNS)

, (2010), Biologically Inspired Coalition Formation of Multi-Agent Systems, Autonomous Agents and Multi-agent Systems (AAMAS)

Musad Haque, Amir Rahmani, Magnus Egerstedt, (2010), Geometric foraging strategies in multi-agent systems based on biological models, 49th IEEE Conference on Decision and Control (CDC),

Musad A. Haque, Magnus Egerstedt, (2009), Coalition formation in multi-agent systems based on bottlenose dolphin alliances, 2009 American Control Conference,

Musad Haque, Amir Rahmani, Magnus Egerstedt, (2009), A Hybrid, Multi-Agent Model of Foraging Bottlenose Dolphins, IFAC Proceedings Volumes, 42, 17, 262--267,

G. Notarstefano, M. Egerstedt, M. Haque, (2009), Rendezvous with multiple, intermittent leaders, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference,

, (2008), Decentralized formation selection mechanisms inspired by foraging bottlenose dolphins, Mathematical Theory of Networks and Systems (MTNS)

Musad A. Haque, Magnus Egerstedt, Clyde F. Martin, (2008), First-order, networked control models of swarming silkworm moths, 2008 American Control Conference,