Curriculum Vitae

General Information

Full Name Justin M. Kottinger
Date of Birth 23rd October 1997
Languages English

Education

  • 2024
    Ph.D in Robotics
    University of Colorado Boulder, CO
    • Department of Robotics
  • 2024
    M.S in Aerospace Engineering
    University of Colorado Boulder, CO
    • Concentration in Autonomous Systems / Robotics
  • 2019
    B.A in Physics
    Whittier College, Whittier, CA
    • Minor in Mathematics
    • Member of Sigma Pi Sigma and Pi Mu Epsilon

Skills

  • Programming Languages
    • C++
    • Python
    • MATLAB
    • Julia
  • Modeling and Simulation
    • ROS / ROS 2
    • Gazebo
    • Simulink
  • Operating Systems
    • Mac OS
    • Linux
    • Windows
  • Workflow
    • Git
    • GitHub
    • Bitbucket
    • Jira

Relevant Coursework

  • Core Courses
    • Linear Control Theory
    • Mathematical Statistics
    • Statistical Estimation
    • Decision Making Under Uncertainty
    • Spacecraft Attitude, Dynamics, and Control
  • Research Specific Courses
    • Algorithmic Motion Planning
    • Statistical Learning
    • Verifcation and Synthesis of Stochastic Systems
    • Coordination and Control of Multi-Agent Systems
    • Hybrid Control Systems

Experience

  • 2023-present
    Robotic Navigation Software Engineer Graduate Intern
    Trimble Corporation, Westminster, Colorado, USA
    • Conceptualized and developed a containerized physics-based simulator using Docker, ROS2, and Gazebo to test GNC service product.
    • Implemented motion planning algorithms for line acquisition of autonomous agricultural vehicles.
    • Enabled autonomous line acquisition in reverse and validated on-vehicle.
  • 2022-2023
    Fault Identification of Autonomous Systems via Bayesian Inference
    University of Colorado Boulder, Colorado, USA
    • Utilized Bayesian hypothesis testing to accurately identify faults and unknown anomalies within autonomous robots.
    • Implemented statistical estimation algorithms such as Kalman Filter, Extended Kalman Filter, and Unscented Kalman Filter in C++.
    • Conceptualized and implemented moving time-windows and fault-partitioning to improve the baseline approach by 20%.
    • Delivered a final product that identified faults and unknown anomalies with over 95% success.
  • 2021-2022
    Autonomous Systems Software Engineer Graduate Intern
    The Aerospace Corporation, El Segundo, California, USA
    • Assisted in design, control, and system identification of an omni-directional octocopter.
    • Implemented advanced algorithms and data structures to create novel flight software in Python and C++.
    • Validated custom flight modules inside simulation using ROS and Gazebo, and tested them onboard the vehicle.
    • Assisted in the development of a Risk-Aware framework for Uber ATG's self-driving vehicle stack.
    • Formulated probabilistic dynamics propagation and intent models for self-driving vehicle and pedestrian models.
    • Implemented probabilistic models in Python and C++ using Bayesian derived statistics.

Presentations

Achievements

  • 2021
    • Recipient, Graduate Assistantships for Areas of National Need (GAANN) Fellowship
  • 2019
    • Recipient, Undergraduate Award for Outstanding Academic Performance in the Major
    • Recipient, Magna Cum Laude Honors
  • 2018
    • 2nd Place, Research Presentation Competition at NSF funded REU
    • Captain, Whittier College NCAA Baseball Team

Open Source Projects