Zhengzhi Liu
San Jose,USA
Summary
Zhengzhi, has a Ph.D. degree in advanced imaging from University of Tennessee and received postdoctoral training on medical image processing with machine learning/deep learning at Stanford University, has been working in industry for about 2 years on system simulation software development and medical image processing with deep learning, has an excellent knowledge of data structures and algorithms, machine learning, and deep learning, excels at C++ and Python programming with a proven record of researching and publication. Zhengzhi is an extremely careful, highly self-motivated, and goal-oriented person and a fast learner, who always tries his best to deliver impeccable work.
Overview
9
9
years of professional experience
Work History
Senior ADAS SYSTEM DEVELOPMENT ENGINEER
Audi Of America
05.2022 - Current
- Trained and mentored competent and flexible workforce to meet project needs and promote positive work environment.
- Performed preventative maintenance to keep tools and equipment functional.
- Read and interpreted blueprints, technical drawings, schematics, and computer-generated reports.
- Provided input to team lead regarding areas for process and procedural improvement.
Research scientist: Medical Imaging
RefleXion Medical
01.2020 - Current
- Build simulation software in C++/ Python for product validation and development, deep learning model for medical images processing
Postdoctoral Research Fellow: Molecular imaging
Stanford University
09.2018 - 01.2020
- Develop molecular imaging reconstruction methodology with machine learning/deep learning
Doctor of Philosophy: Industrial Imaging
The University of Tennessee
08.2014 - 08.2018
Education
Postdoctoral Research Fellow: Molecular imaging -
Stanford University
Stanford, CA01.2020
Doctor of Philosophy: Industrial Imaging -
The University of Tennessee
Knoxville, TN08.2018
Skills
- Data analysis
- Digital image processing
- Imaging reconstruction
- Machine learning
- Deep learning
- Object detection and tracking networks: Fater-RCNN, Mask-RCNN, YOLO, PointNet, Deep SORT
- Computer vision: camera, object tracking
- Advanced programming and acceleration
- C
- Python
- Keras
- TensorFlow
- PyTorch
- OpenCV
- Scikit-learn
- PyQt
- Linux system
- Docker
- Git
Publications
7, 8
Projects
Recommender system for online sales Natural language processing: translator between Chinese and English Car license plate detection Real time car lane, lines, and center detection, and surrounding vehicles detection (>30FPS) LaneNet + YOLO v3 Behavioral clone for self-driving - end to end learning Trained a CNN based model with car dam camera recording in Udacity self-driving car simulator, later use the trained model to predict steeling angle, braking and throttle based on real-time pictures to control the vehicle. Convolutional neural network visualization and reconstruction Gradient-weighted class activation mapping (Grad-CAM) and Guided Grad-CAM Reconstructing features in pretrained model Semantic segmentation for autonomous driving car Using FCN, U-Net, Mask RCNN with dataset from cityscape
Timeline
Senior ADAS SYSTEM DEVELOPMENT ENGINEER
Audi Of America
05.2022 - Current
Research scientist: Medical Imaging
RefleXion Medical
01.2020 - Current
Postdoctoral Research Fellow: Molecular imaging
Stanford University
09.2018 - 01.2020
Doctor of Philosophy: Industrial Imaging
The University of Tennessee
08.2014 - 08.2018
Postdoctoral Research Fellow: Molecular imaging -
Stanford University
Doctor of Philosophy: Industrial Imaging -
The University of Tennessee
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