Biography
I received my Ph.D. in Computing and Robotics from the University of Utah under the supervision of Dr. Tucker Hermans. My dissertation investigated skill planning under state and goal uncertainty for robot manipulation tasks.
I have hands-on experience with a variety of robot platforms, sensors, and simulators. I am passionate about open source software development for robotics, particularly for the ROS framework and Linux.
I am currently a Senior Software Engineer on the Applications team at Berkshire Grey.
In my spare time, I am playing around with learning Rust. I enjoy reading, playing guitar, and doing crossword puzzles. When I’m not injured, you can find me out trail running and cycling.
Interests
- Robotics
- Artificial Intelligence
- Deep Learning
- Multisensory Perception
- Reinforcement Learning
- Embodied Cognition
Education
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PhD Computing and Robotics, 2022
University of Utah
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MS Computer Science, 2016
DePaul University
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BS Mathematics and Philosophy, 2011
Carnegie Mellon University
Experience
Senior Software Engineer
Berkshire Grey
Robotics Machine Learning Research Scientist
I was technical lead and a core developer for a team creating new capabilities for undersea autonomous systems. I worked at the intersection of robotics, machine learning, perception, and autonomous decision-making to deliver autonomy capabilities to client platforms.
Research Assistant
I worked under the supervision of Dr. Tucker Hermans to complete research for my PhD dissertation regarding skill planning under state and goal uncertainty for robot manipulation tasks.
Research Scientist Intern - Advanced Robotics
I implemented an end-to-end robotic system for performing a material handling task using ROS and C++. I additionally developed a Python application from scratch for performing discrete event simulation, visualization, and timing analysis.
Associate Software Engineer
I was an Agile Scrum developer in the Health and Public Service division of Accenture. I created new features for state healthcare systems ranging from frontend interfaces to backend batch operations and utilized technologies such as Java, Oracle SQL, and Oracle Policy Automation.
Patent Examiner - Computer Science
I was a patent examiner in computer science in the art of compilers and software development tools. I determined the patentability of a claimed invention in view of discovered references and issued official decisions as to whether or not the patent was to be granted.
Student Researcher
I led an effort to improve the search efficiency of an automated theorem prover called AProS. I also explored syntactical abbreviations to make generated proofs more intelligible to humans, a key contribution to the project’s expansion into set theory and metamathematics.
Publications
Transformer-based neural network that predicts object-environment relations for latent space planning of multi-object manipulation tasks.
A graph neural network approach to multi-object manipulation from partial-view point clouds.
A probabilistic planning framework for planning under uncertainty to goal distributions.
A high-level vision for learning robot behaviors in a lifelong learning setting leveraging multisensory observations.
Projects
Motion-planned manipulation behaviors using MoveIt and IsaacGym to collect data for learning algorithms.
Tool for rviz that enables user to select the region over which pointcloud segmentation will be performed.
Robot control framework for simulations in Gazebo. Designed to be extensible for easily adding new controllers. Works in conjunction with my robot interface package to decouple the controllers from any particular robot.
Abstraction layer for controlling robots in a unified manner while accounting for robot platform-specific needs.
Real-time Orocos controllers for the KUKA LBR4+ robot. Includes a controller switching framework for safely swapping controllers at runtime, and a simulated FRI component that allows Orocos components to be tested Gazebo.
An actuated version of the ReFlex TakkTile hand and Gazebo plugins for simulating contact and pressure sensors on the fingers.
A lightweight simulator with force rendering created with rviz and DART. Provides a training ground for learning robust policies from demonstration with a haptic input device.
A demonstration recorder for the Baxter robot utilizing the button and display interfaces to make it easier to record demonstrations when operating Baxter in gravity compensation mode.
Package for generating trajectory visualizations in rViz, including dynamic real-time visualizations showing a customizable trace of the robot’s end-effector.
