Dongheon Lee

Autonomous Systems Research Engineer

Master’s student working on UAV systems, multi-agent coordination, and end-to-end autonomous algorithms

📍 West Lafayette, IN, U.S.A.

✉️ Get in Touch 📄 Download CV

Expertise

Skills and technologies I work with

Robotics & Autonomous Systems

Building autonomous UAV systems from simulation to real-world deployment

ROS 1/2 PX4 Autopilot MAVLink QRB-5165 Gazebo Isaac Sim OpenAI Gym

Programming & Development

Developing robust software for robotics and embedded systems

C/C++ Python Java MySQL CMake Bash Git Docker

Machine Learning

Applying ML and CV to robotics and sensing applications

TensorFlow PyTorch Object Detection Gaussian Splatting Reinforcement Learning Federated Learning

Hardware & Integration

Integrating custom hardware for autonomous systems

Pixhawk VOXL (ModalAI) STM32 FPV Drones 3D Printers Microhard DoodleLabs

Projects

Featured work and projects

Evaluating Trade-offs Between LiDAR Specifications and Autonomy Performance

Built a closed-loop autonomy evaluation framework to quantify how LiDAR specifications impact drone navigation and replanning performance

ROS 1/2 Sensor Fusion LiDAR RRT Path Planning Collision Avoidance Simulation

Multi-Agent UAV Systems with Mesh-Based Communication

Designed and implemented a scalable multi-agent UAV system using mesh networking for robust real-time coordination

ROS 2 PX4 Multi-Agent Systems Mesh Networking Swarm Robotics Distributed Systems

GPS-Denied Indoor Navigation – NIST 5.0 3D Mapping Challenge

Implemented advanced 3D mapping using Gaussian Splatting for GPS-denied environments

ROS 1 Gaussian Splatting 3D Mapping 3D Object Detection VOXL PX4

BeyondGrip – Physics-Informed RL for Slip Recovery

Team project on using physics-informed reinforcement learning to recover racecars from loss of tire grip

Reinforcement Learning Vehicle Dynamics Assetto Corsa SAC TD3

Automated Shot Group Measurement System

IEEE-published vision-based system for remote and contactless shot group measurement with 91.8% accuracy

OpenCV YOLO Image Processing IoT Raspberry Pi LoRa

Experience

Professional career history

Graduate Research Assistant

Networked Control Systems Lab, Purdue University • Sep 2025 – Present

📍 West Lafayette, IN, U.S.A.

Developed MPPI- and MPC-based control frameworks for 4-channel fixed-wing UAV enabling aggressive pylon navigation
Designed cost functions and tuning strategies, performing simulation-to-flight transfer with real-world flight validation
Analyzed controller robustness and failure modes under wind and sensing uncertainty

Software Engineer

Applied Intuition • Nov 2024 – Jul 2025

📍 Seoul, South Korea

Migrated EpiSci's 3D mapping stack from ROS 1 to ROS 2 within Applied Intuition's simulation platform
Evaluated LiDAR specification trade-offs on drone autonomy performance with Tier-1 sensor supplier
Delivered simulation training workshops for Korean automotive OEM and airline R&D center

Software Engineer

EpiSci (Acquired by Applied Intuition) • Oct 2023 – Nov 2024

📍 Seoul, South Korea

Developed autonomous multi-agent UAV systems enabling efficient data exchange and swarm coordination
Applied computer vision and machine learning techniques including 3D Gaussian Splatting for enhanced visualization
Led sim-to-real deployment from Gazebo to real drones using ROS 2, PX4, and VOXL
Demonstrated UAV applications to NIST, U.S. Army, and DARPA

Software Engineering Intern

EpiSci (Acquired by Applied Intuition) • Sep 2022 – Sep 2023

📍 Poway, CA, U.S.A.

Evaluated visual-inertial odometry and obstacle avoidance algorithms on indoor drones using ROS 1
Developed frontier-based exploration and object detection modules for PX4-based drones
Built ATAK Android plugin for drone control and monitoring
Earned FAA Part 107 certification

Education

Academic background

Purdue University

M.S. in Electrical and Computer Engineering

Aug 2025 – Present

GPA: 3.61 / 4.0
Specializing in automatic control with interests in reinforcement learning, autonomous systems, and distributed robotics

Chungnam National University (CNU)

B.E. in Computer Science and Engineering

Mar 2017 – Feb 2023

GPA: 3.88 / 4.0 (3rd out of 102 students)
Strong foundation in computer science and software engineering

Publications

Research papers and articles

Feasibility of Measuring Shot Group Using LoRa Technology and YOLO V5

Dongheon Lee, et al.

IEEE Sensors Applications Symposium (SAS) • 2022

View DOI Download PDF

A Case Study on Scenario-Based Mobile Application UI Action Test

Dongheon Lee, et al.

Korean Institute of Information Scientists and Engineers (KIICE) • 2021

Awards & Honors

Recognition and achievements

Engineer of the Year

2022

Dean, College of Engineering, CNU

Recognized for outstanding academic and research achievements

Sponsor's Award

2022

2022 Software Talent Competition, IITP Korea

Awarded by competition sponsor for excellence

Encouragement Award

2021

KIICE Poster Session

For poster presentation on mobile application testing

Full Scholarship

2020

Sejong City Foundation

Foundation scholarship for academic achievement

Full Scholarship

4 semesters

Department of CSE, CNU

Academic excellence award for 4 semesters

Partial Scholarship

3 semesters

Department of CSE, CNU

Academic excellence award for 3 semesters