Sonia MartÃnez
Benjamin W. Zweifach Endowed Chair
Professor of Mechanical and Aerospace Engineering
Autonomy Collaboratory, Contextual Robotics Institute
University of California, San Diego
Benjamin W. Zweifach Endowed Chair
Professor of Mechanical and Aerospace Engineering
Autonomy Collaboratory, Contextual Robotics Institute
University of California, San Diego
I received my PhD degree in Engineering Mathematics from
the University Carlos III of Madrid, Spain, in May
2002. After this, I spent two years as a Fulbright
Postdoctoral Scholar at the University of Illinois at
Urbana-Champaign and the University of California, Santa
Barbara. I started as an Assistant Professor at the
University of California, San Diego in 2006; and became a
Full Professor in Mechanical and Aerospace Engineering in
2014, being affiliated there ever since. I was honored to
become a Jacobs Faculty Scholar in 2019. She is a Fellow of
the IEEE, class 2018.
My research interests span all aspects of the control of
networked, multi-agent systems, including robotic teams
and cyber-physical systems. I have particularly focused
on the analysis and design of distributed coordination
algorithms for groups of autonomous robots, by leveraging
nonlinear control, distributed optimization, and
game-theoretic approaches. Current topics of interest
include the resilient, safe and robust coordination of
mixed multi-agent systems subject to adversarial action.
For an extended biography please click
here.
Available Openings for Ph.D. students interested in innovative research in systems-related areas such as dynamic systems and controls, networked systems, robotics and machine learning. See more details here
Honored to be the recipient of this generous gift and proud to be part of the faculty group cohort of new 18 endowed chairs at UC San Diego
See the new Special Sections on the Intersection of Machine Learning and Control, and Safe Motion Planning and Control for Autonomous Driving
Please visit my Publications link for a list of published papers, and Google Scholar for more recent preprints. See below some publication highlights.
We compute so-called maximal controlled recurrent sets for continuous-time nonlinear systems, emphasizing the relationship between these sets and the control invariant set of its discretization. These concept is applied for safe robotic navigation …
Optimization problems where the objective function is given as the solution to a maximization problem, for which neither its values nor its gradients are available in closed form, benefits from this gradient sampling approach. We look into applications to coverage control problems …
We propose a scalable, distributed probabilistic inference algorithm that applies to continuous variables, intractable posteriors and large-scale real-time data in sensor networks. This is done via a Distributed ELBO (DELBO) approach, and apply to distributed mapping …