I am a PhD student at the University of Michigan advised by Professor Dmitry Berenson. I started in the fall of 2018 after I completed my Bachelors in Robotics Engineering and Bachelors in Computer Science at WPI.
My research interests include planning and deep learning for robotics. In my personal time, I enjoy rock climbing, woodworking, and a wide variety of music.
During my PhD, I have studied deep learning and motion planning and have a particular interest in deformable object manipulation. Two key research questions that I have focused on are (1) when/where should the robot trust its dynamics models? and (2) what should the robot do when it cannot? I have designed and implemented several dynamics learning methods, as well as planning methods which use learned models. For deformable object manipulation, our methods for planning with learned models must be aware of modeling inaccuries, and I have explored a number of ways for doing this. I also have experience working with real robot hardware. This includes working with low-level control and sensors, embedded systems, and dealing with real data collection and experiments on real robots.
As a freshman at WPI, I worked as a research assistant for Russell Torris, under Professor Sonia Chernova. I also worked with Professor Chernova for a summer at Georgia Tech. My project focused on using demonstration to improve indoor robot navigation.
I have worked with Professor Carlo Pinciroli on a swarm robotics project. We are studing the space of possible behaviors for memoryless computeless robots, specifically showing that they are capable of n-class segregation with a single primitive sensor and no communication. You can learn more by reading the paper we wrote for the project as a part of the Swarm Intelligence course at WPI.
I also worked with Professor Scott Barton on the intersection of machine learning and music. As a musician myself, this is an interesting application of machine learning.
Learning Where to Trust Unreliable Models in an Unstructured World for Deformable Object Manipulation. Under Review for Science Robotics
Learning When to Trust a Dynamics Model When Planning With Physical Constraints . Accepted for the ICRA 2020 Workshop MLPC
Learning When to Trust a Dynamics Model for Planning in Reduced State Spaces . ICRA 2020
A Minimalistic Approach to Segregation in Robot Swarms. The 2nd IEEE International Symposium On Multi-Robot and Multi-Agent Systems
Using Recurrent Neural Networks to Judge Fitness in Musical Genetic Algorithms. The 5th International Workshop on Musical Metacreation (MUME)
Worcester Polytechnic Institute - BS in Computer Science, BS in Robotics Engineering
I worked on the problem of predicting future paths of actors detected by the autonomous vehicle. My work consisted mostly of software engineering.
At OSRF, I worked on the Gazebo robot simulator. I worked on getting Gazebo running on windows, and on allowing high school students in the FIRST Robotics Competition to use Gazebo as a simulator for their robots.
Inspiration for website design from here.