People

Principal Investigator

Naomi Ehrich Leonard
Office: D-234 E-Quad
Email: naomi@princeton.edu
Phone: (609) 258-5129
MAE Faculty Profile
Full Bio
Teaching

Prof. Leonard’s background includes feedback control theory, nonlinear dynamics, geometric mechanics, and robotics, where she has made contributions both to theory and to application. She studies and designs complex, dynamical systems comprised of many interacting agents, including, for example, animals, robots, and/or humans that move, sense, and decide together. Her research program emphasizes the development of analytically tractable mathematical models of collective dynamics that provide the systematic means to examine the role of feedback (responsive behavior), interconnection (who is communicating with whom), heterogeneity (individual differences) in the behavior, learning, and resilience of groups in changing environments.

Leveraging mathematical models, Leonard has studied mechanisms of collective behavior in fish schools, bird flocks, honeybee swarms, and ant colonies, and she has designed rules for distributed robotic vehicles to perform collaborative tasks ranging from adaptive ocean sampling to trash collection in human-populated spaces. A former student of dance and life-long dance enthusiast, she has grown increasingly interested in intersections with dance and composition.

Current Post-docs

Christine Allen-Blanchette
Department: MAE
Office: H-116 E-Quad
Email: ca15 [at] princeton.edu
Personal Webpage

My research interests lie at the intersection of deep learning, geometry and dynamical systems.

MarĂ­a Santos
Department: MAE
Office: H-116 E-Quad
Email: maria.santos [at] princeton.edu
Personal Webpage

My research focuses on the distributed coordination of multi-robot systems, with a particular focus on modeling heterogeneous capabilities within large swarms of robots. I am also very interested on exploring how to use swarm robotics in various forms of artistic expression, including theatre or painting.

Current Graduate Students

Giovanna Amorim
Department: MAE
Office: H-120 E-Quad
Email: giamorim [at] princeton.edu

TBD

Anastasia Bizyaeva
Department: MAE
Office: H-120 E-Quad
Email: bizyaeva [at] princeton.edu
Student Profile

I am interested in emergent complex phenomena in multi-agent dynamical systems such as formation of opinions and spatiotemporal patterns on networks, synchronization, and swarming. My current research involves modeling and control of collective decision making, and application of this work to distributed coordination of multi-robot teams. Beyond my academic pursuits, I am passionate about and actively participates in volunteer work aimed at broadening participation in STEM, making education more accessible, and inspiring future generations of scientists and engineers.

Charlotte Cathcart
Department: MAE
Office: H-120 E-Quad
Email: cathcart [at] princeton.edu
Student Profile

Broadly interested in feedback control, robotics, and people, my research focuses on what processes and control strategies can be used to aid human-robot interactions and encourage collaboration. I am currently exploring the use of opinion dynamics to dictate reactive motion control and collision avoidance for on-ground robots to safely pass by humans.

Isla Xi Han
Department: Architecture
Office: H-120 E-Quad
Email: xihan [at] princeton.edu

TBD

Mari Kawakatsu
Department: APC
Office: Fine 218
Email: mk28 [at] princeton.edu
Student Profile
Personal Website

As a mathematical biologist and an applied mathematician, I use tools from evolutionary game theory, dynamical systems, and network science to explore mathematical and computational models of collective and emergent behavior in social systems. I am especially interested in understanding how inter-individual differences and population structures influence and are influenced by collective dynamics. My recent and current projects have focused on self-organized division of labor in ant colonies, hierarchies in adaptive networks, and cooperation and polarization in group-structured populations, among others.

Justin Lidard
Department: MAE
Office: H-120 E-Quad
Email: jlidard [at] princeton.edu
Student Profile
Personal Webpage

My research interests lie at the intersection of machine learning, optimization, multi-agent systems, and control theory, primarily in (deep) multi-agent reinforcement learning (MARL) and efficient decentralized decision-making. I am currently working on new algorithms that allow learning agents to solve game-theoretic tasks while using communication to promote coordination and cooperation.

Udari Madhushani
Department: MAE
Office: H-120 E-Quad
Email: udarim [at] princeton.edu
Student Profile
Personal Webpage

I am broadly interested in the problems at the intersection of machine learning, control theory and robotics.

Justice Mason
Department: MAE
Office: H-120 E-Quad
Email: jjmason [at] princeton.edu
Student Profile

My research interests are at the intersection of robotics, control, and machine learning. I’m interested in questions about how robots perform cooperative tasks, specifically in space applications. Currently, I am working on using learning techniques to predict the dynamics of 3D rigid-body objects for the purposes of model-based control.

Anthony Savas
Department: MAE
Office: H-120 E-Quad
Email: asavas [at] princeton.edu
Student Profile

My research investigates the problem of distributed estimation and control in networked multi-agent systems. I am also interested in studying the role of the network structure as well as how the distribution of sensing and control authority throughout the network affects the performance of the distributed algorithms

Yenan (Daniel) Shen
Department: MAE
Office: H-120 E-Quad
Email: yenan.shen [at] princeton.edu

I am interested in designing and controlling of physics-based deformable structures and soft robotics. Specifically, my research interest is using topological optimization and inverse learning to use physics-based mechanisms in designing soft robotics. In addition, I am passionate about controlling the soft robotics and using reinforcement learning to achieve controllable locomotion.

Current Undergraduate Students

  • Ken Nakamura, MAE
  • Lucy Norton, MAE
  • Christine Ohenzuwa, MAE
  • Ritika Ramprasad, ECE
  • Sarah Witzman, MAE

Former Graduate Students 

(*co-advised, **visiting)

Former Post Docs

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