Summary
As an algorithm engineer on the brink of receiving a PhD in deep learning and computer vision, brings a robust data-driven approach to problem-solving, complemented by strong engineering and research capabilities. Throughout the academic journey from 2017 to the present, successfully implemented machine and deep learning solutions tackling classification, segmentation, and reconstruction challenges. Proficiency spans over 7 years in Python, leveraging tools like NumPy, scikit-learn, Pandas, TensorFlow, and PyTorch to enhance data analysis workflows and automate pattern recognition processes. Additionally, Matlab has been applied for research purposes and industrial C programming for hardware design verification simulations. Experience extends to drafting research grant proposals, leading project management efforts, and fostering collaboration across interdisciplinary teams in both academic and commercial environments. With effective communication skills refined through tutoring, conference presentations, and collaborative engagements, well-equipped to drive innovation and deliver impactful solutions in the field of deep learning and computer vision.
Skills
- Computer Vision
- CUDA
- Deep learning (CNN)
- Docker
- GAN
- GIT
- Machine learning (SVM)
- NumPy
- Pandas
- Python (TensorFlow, PyTorch)
- Scikit-Learn
- SQL (MySQL, SQL Server, SQLite)
- Transformer
- XGBoost
Education
- 2020 - 2024 Doctor of Philosophy at University of New South Wales
- July 2021 - June 2022 Visiting Ph.D at ShanghaiTech University
- 2017 - 2020 Master of Engineering at Northwestern Polytechnical University
- 2013 - 2017 Bachelor of Engineering at Northwestern Polytechnical University