Engineer Intern Software

HaoTsung Lee

*********@*****.*** 734-***-**** Salt Lake City, UT LinkedIn: https://www.linkedin.com/in/hao-tsung-lee-3b39b11aa/ WORK EXPERIENCE

Altitude AI Salt Lake City, UT

Software Engineer – AI/ Robotics Jan 2023 - Present

Designed and constructed multi-class semantic segmentation models using Tensorflow, incorporating data augmentation techniques to enhance performance in food processing automation

Developed end-to-end robotics manipulator infrastructure, including perception, planning, and control

Conducted high-resolution camera calibration and integrated depth maps for improved perception Argo AI Palo Alto, CA

Software Engineer Intern May - Nov 2022

Formulated LiDAR detection association as a graph-based Multi-Object Tracking (MOT) problem; applied Minimum Cost Flows (MCF) solver for accurate frame-to-frame associations

Enhanced MOTChallenge Official Evaluation Kit to support 3D cuboids, and created a tracklet visualizer to evaluate resulting tracker performance, achieving 97% MOTA and HOTA

Devised occlusion modeling and linkage recommendation strategies to connect fragmented tracklets belonging to the same objects

Intel Taipei, Taiwan

Software Engineer Intern Jun - Aug 2021

Developed a full-stack application to extract critical error messages from 20+ hardware components on Chromebooks, reducing hardware engineers' debugging cycle by 50% and deploying to OEM partners SKILLS

Computer programming: C/C++, Python, MATLAB(Simulink)

Applications & Platform: ROS, OpenCV, LiDAR, camera, Linux, Keras, Pytorch, Git, LaTex, Protobuf EDUCATION

University of Michigan Ann Arbor, MI

Master of Science in Electrical and Computer Engineering Dec 2022 With a concentration in Robotics (GPA: 3.9/4.0)

Coursework: Deep Learning Computer Vision, Mobile Robotics, Robotics System Lab, Machine Learning National Taiwan University (NTU) Taipei, Taiwan

Bachelor of Science in Engineering Science (GPA: 3.7/4.0) June 2019 ACADEMIC PROJECTS

University of Michigan Ann Arbor, MI

Robotics System Lab SLAM project Sep - Oct 2021

Modeled the motion and trajectory controllers of a mobile robot with feedback from encoders and IMU

Implemented Monte Carlo Localization, mapping on occupancy grids with a 2D LiDAR while the robot driving through a maze in C++, which reduced the errors of pose estimation to 3%.

Designed frontier exploration for autonomous SLAM in an unknown map with A* path planning, and won the first place in the class competition.

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