About me
I am Maria Gabriela Mendoza, a Ph.D. student in Mechanical Engineering at UC Berkeley. I am fortunate to be advised by Prof. Shankar Sastry and mentored by Prof. Chinmay Maheshwari and Dr. Victoria Tuck (Postdoctoral Researcher at Upenn).
My research focuses on the design and control of multi-agent systems operating in complex environments (highly uncertain and dynamic) environments with applications in Advanced Air Mobility, humanitarian robotics, and strategic coordination of robots.
Prior to UC Berkeley, I worked for five years as a Research Scientist at Lockheed Martin, contributing to projects ranging from hypersonic aerothermal design earlier in my career to AI and robotics research in later years, often in collaboration with academic partners. I am also deeply committed to mentoring and inclusive engineering education, and previously served as engineering faculty at Cañada College.
I hold a B.S. in Mechanical Engineering from the University of Southern California (USC) and a M.S. in Aeronautics and Astronautics from Purdue University.
Research Interests
My research focuses on the design of algorithms for modeling, analyzing, and controlling complex interactions in societal-scale multi-agent systems. I develop frameworks for coordination and decision-making in cyber-physical systems where physical dynamics, communication constraints, uncertainty, and strategic interactions are tightly coupled.
I emphasize modeling and simulation approaches that reflect real-world operating conditions, incorporating contextual information, uncertainty, low observability or communication among heterogeneous agents, and system-level constraints rather than idealized assumptions.
My interests lie in humanitarian and safety-critical applications such as disaster response, transportation, resource allocation, and planning for underserved populations. This spans in domains such as autonomous aerial mobility, human-robot interaction, and multi-robot systems.
Methods I study include learning-based approaches (AI) with control theory, optimization, and game-theory, mechanism design. However, I emphasize selecting methods that are appropriate to the system and task at hand. My goal is to design systems that are effective, reliable, and principled, with safety, interpretability, and performance guarantees where possible.
News
- May 25-29 - I'll be presenting my work on "Decentralized Ergodic Coverage Control in Unknown Time-Varying Environments" at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS) in Paphos, Cyprus
- April 23-27 - I'll be presenting my work on "Hierarchical Generative Agents For Simulating Sequential Human Behavior" at the International Conference on Learning Representations (ICLR) in Rio de Janerio, Brazil
- Oct 2025 - Presented my work on "Coordinated Autonomous Drones for Human-Centered Fire Evacuation in Partially Observable Urban Environments" at the IEEE Global Humanitarian Technology Conference (GHTC) (AAMAS) in Boulder, Colorado
Publications
For an updated list, please see my Google Scholar.
Teaching
- Learning-enabled multi-agent systems - EL ENG 290, teaching assistant, UC Berkeley, Spring 2026
- Introduction to Engineering - ENGR 100, instructor, Cañada College (San Mateo Community College District), Fall 2022, Spring 2023
- Computational Methods for Engineers and Scientists - ENGR 215, instructor, Cañada College (San Mateo Community College District), Fall 2022, Spring 2023
Professional Experience
Research Scientist, Lockheed Martin, 2017-2022
Engineering Faculty, Cañada College, 2022-2023
Ongoing Projects
More information coming soon, website under construction, please look at my CV for more information