Dr. phil. Sydney Dolan
E-mail address: sydney.dolan(at)tum.de
Biography
Dr Sydney Dolan is a postdoctoral associate at the Chair of Spacecraft Systems at the Technical University of Munich.
Sydney earned their PhD under the supervision of Professor Hamsa Balakrishnan in DINAMo in the AeroAstro Department at the Massachusetts Institute of Technology (MIT). Their doctoral area of expertise is in the development of autonomous collision avoidance and coordination algorithms for multi-agent systems like satellites. Prior to attending MIT, Sydney received a Bachelor’s in Aeronautics and Astronautics from Purdue University, and a Master 's in Aeronautics and Astronautics from MIT. Sydney’s work is broadly motivated by planning and perception problems for multi-agent systems in unstructured, uncertain environments.
Research Topics
- Event-based vision
- Multi-agent reinforcement learning
- Multi-agent systems and graph theory
Publications
Sydney Dolan, Siddharth Nayak, and Hamsa Balakrishan. “Satellite Coordination and Navigation with Limited Sensing.” Journal of Guidance, Control, and Dynamics, 2025.
Sydney Dolan, Siddharth Nayak, Jasmine Aloor, Hamsa Balakrishnan. “Asynchronous Cooperative Multi-Agent Reinforcement Learning with Minimal Communication.” International Conference on Autonomous Agents and Multi-Agent Systems, 2025.
Jasmine Jerry Aloor, Siddharth Nayak, Sydney Dolan, Hamsa Balakrishnan, “Cooperation and Fairness in Multi-Agent Reinforcement Learning.” Association for Computing Machinery Journal on Autonomous Transportation Systems, 2024.
Siddharth Nayak, Kenneth Choi, Wenqi Ding, Sydney Dolan, Karthik Gopalakrishnan, Hamsa Balakrishnan. “Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation” International Conference on Machine Learning, 2023
Sydney Dolan, Siddharth Nayak, Hamsa Balakrishnan. “Satellite Navigation and Coordination with Limited Information Sharing.” Learning for Dynamics and Control, 2023
2025
C. J. Juan Oliver, V. Messina, S. Dolan, and A. Golkar, “Autonomous Decision-Making for Large Satellite Constellations: a Multi-Agent Reinforcement Learning Approach to Space Situational Awareness in Partially Observable Dynamic Environments”, 11th European Conference for Aeronautics and Aerospace Sciences (EUCASS), 2025.
S. Dolan, L. Schuberth, R. Arge, R. M. G. Alarcia, V. Messina, C. J. Juan Oliver, F. Salmaso, J. Sindermann, F. Sofio Avogadro, A. Golkar, “Design and Analysis of an Event Camera Payload for Space-Based Object Detection on the EventSat 6U CubeSat Mission.” 15th IAA Symposium for Small Satellites for Earth System Observation, 2025
Teaching
Spacecraft Operations, Instructor, Grader |
Summer 2025 |
| Systems Engineering Advanced, Teaching Assistant | Summer 2025 |