Dylan Shell

Dylan Shell is a Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on distributed AI, multi-robot systems, and autonomous planning. He holds a B.Sc. from the University of the Witwatersrand and advanced degrees from the University of Southern California.

Education:

• PostDoc in Robotics, University of Southern California (2009)
• Ph.D. Computer Science, University of Southern California (2008)
• MSc Computer Science, University of Southern California (2006)
• B.Sc. (Hons) Computer Science, University of the Witwatersrand (2001)
• B.Sc. Computational & Applied Mathematics and Computer Science, University of the Witwatersrand (2000)

Research Interests:

• Distributed AI and multi-robot coordination
• Biologically-inspired systems for robotics
• Autonomous planning and decision-making
• Crowd modeling and multi-agent systems

Recent Research Trends:

His work emphasizes sensor-based planning, resilient systems, and privacy-preserving robotics. Recent papers explore optimal planning under uncertainty, combinatorial filter reduction, and multi-robot task allocation. His research often bridges theory and practice, with applications in autonomous systems, disaster response, and human-robot interaction.

Awards:

• Montague-CTE Scholar for teaching excellence (2013–2014)
• Faculty Service Excellence Award (2010)

Advising and Grants:

Shell advises a diverse cohort of graduate and undergraduate students in the Distributed AI Robotics Lab. He has led NSF-funded projects on adaptive sampling, contact models, and privacy-aware multi-robot systems. His lab collaborates with industry partners like Intelligent Automation, Inc.

Labs & Teams:

He directs the Distributed AI Robotics Lab, which develops algorithms for autonomous systems and experiments in multi-robot coordination. The lab emphasizes interdisciplinary work, blending robotics, AI, and control theory.