Research at MCS



Robotics researchers at the Department of Mathematical & Computational Sciences are envisioning interactive robotics systems of the future. We develop cutting-edge robotics methodology and systems with a broad set of ideas in the following areas: mechanical design, continuum & soft robots, computer vision & 3D perception, robot learning, reasoning & planning, optimal control & reinforcement learning, and state estimation. Our research has applications in mobile manipulation, field & service robotics, medical & surgical robotics, legged locomotion, and human-robot interaction.



Robot Vision & Learning Lab
Intelligent systems lab



Computer Science Education

The CS Education Research Group of researchers focuses on the application and empirical assessment of modern learning principles in the context of undergraduate computing education. Recent projects have focused on peer instruction, blended and online teaching, teamwork in programming courses, and educational data mining. The group also develops and maintains software in support of computing classrooms.


Active Learning Classroom



Machine Learning



Computer Science Theory






Geometric Function Theory

Ilia Binder


Complex Dynamics

Ilia Binder

Mathematical Physics

Ilia Binder

Luis Seco

Algebraic Geometry

Michael Groechenig

Symplectic Geometry

Yael Karshon

Ergodic Theory

Konstantin Khanin

Statistical Mechanics

Konstantin Khanin


Geometric Analysis

Yevgeny Liokumovich

Metric Geometry

Yevgeny Liokumovich

Harmonic Analysis

Luis Seco

Mathematical Finance

Luis Seco


Number Theory

Arul Shankar

Arithmetic Statistics 

Arul Shankar

Relativity Theory

Yakov Shlapentokh-Rothman

Set Theory and Measurable Combinatorics

Spencer Unger


Mathematics Education





Theoretical Statistics

Dehan Kong

Stanislav Volgushev

Statistics Interdisciplinary Research

Dehan Kong


Statistics Education