I work across the full lifecycle of perception systems, including model integration,
GPU-accelerated inference, system optimization, and deployment under real-time and
safety-critical constraints. My experience spans ROS 2-based system design,
CUDA/TensorRT acceleration, and automotive-grade software development practices.
| Isuzu Technical Center of America (ITCA) |
Jan. 2021 – Present |
| Lead Engineer, Autonomous – Advanced Engineering |
Jun. 2024 – Present |
| – Deployed perception components on NVIDIA TensorRT, including: |
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| FCOS object detection,
FCOS segmentation,
SORT tracker, and
SCNN lane detection |
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| for autonomous driving applications. |
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| – Conducted research on Transformer-based perception architectures. |
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| – Conducted research on manifold (matrix Lie group) methods for vehicle localization. |
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| Sr. Engineer, Autonomous and AI – Advanced Engineering |
Jan. 2022 – May 2024 |
| – Led development of perception components: object detection, tracking, and visualization. |
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| Implemented ROS visualization for MVXNet: MVXNet demo. |
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| Developed structure-aware single-stage 3D object detection. |
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| Developed LiDAR object detection and tracking: 3D-LiDAR multi-object tracking. |
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| Developed multi-object tracking: Multi-object tracking demo. |
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| – Developed localization components: wheel odometry, GNSS/IMU processing, and Fast-LOAM. |
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| Developed Visual SLAM: Visual SLAM demo. |
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| – Acting scrum master; contributed to software architecture design and stack integration. |
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| – Provided technical mentorship and supervised interns. |
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| Autonomous Driving Engineer – Powertrain and Vehicle R&D |
Jan. 2021 – Dec. 2021 |
| – Developed core sensor components for centralized sensor fusion (cameras and LiDARs). |
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| – Curb detection using 3D LiDAR point clouds: Moriyama dataset demo. |
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| – Object detection using 3D LiDAR point clouds: Moriyama dataset demo. |
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| – Point cloud 3D map construction using Fast LOAM and OctoMap: Moriyama dataset demo. |
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| – Software stack management with release tags and version control via git submodules. |
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| – Component integration and testing in simulation and on the real truck. |
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| APTIV |
Jul. 2018 – Jan. 2021 |
| Algorithm Engineer – Scene Perception Algorithm Team |
Oct. 2020 – Jan. 2021 |
| – Developed unit test cases in vectorCAST for perception components. |
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| Algorithm Engineer – Fused Road Model (FRM) Team |
Sep. 2018 – Sep. 2020 |
| – Developed fusion algorithms for object trail processing: |
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| Road shape estimation and lane centerline prediction. |
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| – Designed FRM state machine and mode manager. |
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| – Implemented error handling for vision, object fusion, and vehicle state inputs. |
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| – Developed FRM analysis pipeline and dashboard. |
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| – Coverity static analysis (AUTOSAR and MISRA C++); developed unit tests in Google Test. |
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| Algorithm Engineer – Autonomous Driving Behavior Team |
Jul. 2018 – Aug. 2018 |
| – Developed prediction and cost function algorithm for cooperative social behavior. |
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| – Contributed to Ottomatika code migration from urban pilot to highway pilot. |
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| Programming Languages: C++ (advanced), Python (advanced) |
| Robotics & Middleware: ROS 2 (custom packages, ament/CMake, rviz, rosbag workflows) |
| Model Deployment & Acceleration: TensorRT (engine build, ONNX import, C++/Python inference), CUDA |
| Computer Vision & 3D Perception: OpenCV, Point Cloud Library (PCL), Ceres Solver, g2o |
| Machine Learning Frameworks: PyTorch, ONNX ecosystem |
| Operating Systems: Linux/Unix (extensive experience with Ubuntu, shell and system commands) |
| Software Quality & Standards: AUTOSAR C++, MISRA C++, CERT C++ static analysis and compliance |
| Testing & Benchmarking: Google Test, pytest, Google Benchmark |
| High-Performance Computing: HPC clusters using SLURM |
| Documentation: LaTeX, TikZ |
| Build & Tooling: CMake, colcon, git |
