CV
Education
Michigan Technological University
- August 2021 – August 2025: BS in Robotics Engineering
Experience
Research Assistant
Michigan Technological University
Houghton, MI
Aug 2022 – Present
- Conducted research in various topics spreading from legged robotic control to perception and path planning systems in autonomous vehicles
- Assisted graduate student peers in additional research topics
Research Areas
- 8/2024 - Present: Winter Snow dataset for LiDAR systems and neural network training for vehicle detection in heavy snow environments
- 6/2023 - Present: Automated bat counting system for White Nose Disease population study with DNR (See Fat Bat Project)
- 6/2023 - 9/2024: ARPA-E NextCar II, road surface analyzation and data collection
- 1/2023 - 5/2023: (main researcher) Bipedal locomotion and gate correction on low mu surfaces
- 8/2022 - 8/2023: (main researcher) Calculating fractional order calculus through the usage of symmetric neural networks
Software Developer
Steelhead Technologies
Calumet, MI
Sep 2025 – Nov 2025
- Implemented improved UI design for web-based applications
- Improved admin/user communication and interaction through back-end SQL data
Autonomous Simulations Intern
Hexagon - Manufacturing Intelligence Division
Novi, MI
June 2024 – Aug 2024
- Developed interfaces between simulation software and major autonomous vehicle software
- Developed automotive simulations for autonomous vehicle testing and development
- Produced documentation for customer support
- Supported and assisted in customer usage of simulation software
Undergraduate Class Grader - Neuromorphics
Michigan Technological University
Houghton, MI
March 2025 – April 2025
- Rewrote labs to provide proper content information and proper formatting
- Assisted students in asynchronous learning labs
- Graded students on given tasks
Undergraduate Lab Assistant - ROS
Michigan Technological University
Houghton, MI
Sept 2023 – Dec 2023
- Transferred labs from ROS Melodic to Noetic
- Re-wrote labs to provide better flow and ease of knowledge acquisition for students
- Assisted students in learning and understanding beginning topics for ROS
- Started creation of new lab curriculum for students in up-coming years
IT Operations Student - Tier 1
Michigan Technological University IT
Houghton, MI
Oct 2021 – Dec 2022
Additional Projects
AutoDrive Challenge II
The AutoDrive II Challenge is a GM and SAE sponsored event in which universities receive a stock Chevy EUV Bolt and make it autonomous over 5 years. This challenge began in 2021 and ends in June 2026. Scored challenges progressively get harder as each year passes with topics including base-level object detection, and spanning to non-gps-based localization in an area. Teams then meet in June of each year to compete at the University of Michigan’s test track, M-City.
Roles: Michigan Tech AutoDrive Team Captain, Robotics Systems Enterprise Director, Enterprise Assistant Director, Outreach Coordinator, Lab manager, Team Lead
Personal Contributions:
- Computer vision through usage of a neural network and a camera
- Object detection and tracking through a lidar sensor
- Autonomous Vehicle simulation through for subsystem testing
- Implementation of feature level sensor fusion
- Creation of vehicle behavior management system
- Creation of mapping and path planning system using a standard planning algorithm
- Built LiDAR based localization system from scratch
Major AutoDrive Contributions:
- LiDAR Object Detection}
- In my first year on the team, and in my first year working with this system, I worked on basic Euclidean Clustering and plane-ground filtering. Both of these implementations were done through use of PCL Libraries.
- Vehicle Navigation, Path Planning, and Behavioral Subsystems
- In Year 3 of the AutoDrive II Challenge, I implemented a D* Lite path planner for basic vehicle navigation through GPS-defined map infrastructure.
- LiDAR Based Localization System (See github.com)
- In year 4 of the AutoDrive II Challenge, teams were put to the task of navigating through an environment with intermittent GPS signal drops. With this challenge in mind, I was assigned the task of building the new localization system from scratch for our team. To do this, I worked on making an adaptation of KISS-ICP, which is a simple ICP based localization system, as a way to solve this challenge. The aim was to make a lightweight localization system so that we can successfully detect where we are within our environment and navigate to our end-goal location safely.
Technologies
Languages:
C++, C, Python, Matlab
Software:
ROS, Linux, PyTorch, Virtual Test Drive, Carla, Unreal, Matlab DSD and RoadRunner, Simulink, Inventor, NX
Topics of Interest:
Perception, Mapping and Planning, SLAM, Simulation, Autonomous Vehicles, LiDAR, Camera Vision, Artifical Intelligence