Bowen Yu

I’m a first-year Ph.D. student at the School of Data Science at City University of Hong Kong. I am very fortunate to be advised by Prof. Xiangyu Zhao. I obtained my Master’s degree from CityU and my Bachelor’s degree from Nantong University.

My research interests lie at the intersection of machine learning, signal processing, and robotics, with a focus on developing innovative solutions for real-world challenges. I have a strong foundation in both hardware and software, with hands-on experience in circuit design, control systems, and data analysis.

Email / WeChat (WeChat ID: ybw2636839047) / Github

Education

• City University of Hong Kong (Sept 2024 - June 2025)
  • MSc in Venture Creation
  • Role: CAI Class Representative, Data Science Department RA at AML Lab (Prof. Zhao)
• Nantong University (Sept 2020 - June 2024)
  • B.Eng in Electrical Engineering and Automation
  • Coursework: Artificial Intelligence, Linear Algebra, Microcontroller Technology, Power Electronics Technology, Principles of Automatic Control, PLC Technology

Research Experience

• ConFact: Multi-dimensional Signal Processing with Deep Dimension-specific Convolutional Tensor Factorization (Submitted to IJCAI 2025, co-first author)
  • Developed a unified solution for multi-modal data with missing entries and noise.
  • Achieved state-of-the-art performance in image, video, seismic, and audio data reconstruction and denoising.
• Graduation Project: Wind-Storage Integrated Voltage Signal Acquisition and Filtering Design
  • Designed and implemented an analog voltage signal acquisition and conditioning circuit.
  • Utilized an improved wavelet threshold denoising algorithm in MATLAB to effectively remove noise from signals.
  • Successfully reduced the Total Harmonic Distortion (THD) from 9.07% to 5.52% through harmonic filtering.

Publications

• Design of an Automatic Afforestation and Grass Planting Vehicle for Desert Conditions
  • Science and Technology and Innovation, CN14-1369/N (Accepted for publication, Sep 2024)
  • Authors: Bowen Yu, Haiyang Gong, Haiyang Gong, Sen Wang

Patents

• A High-Economy Laser Shock Strengthening Method for Anode Targets
  • Application Number: 2023103522746
• A Robot for Assisting Feeding
  • Patent Number: 202320541893.5

Projects

• “DotGreen” - Multi-functional Automated Grass Grid Laying Vehicle
  • Solar-powered mechanical system for automated grass planting.
  • Utilized Arduino for intelligent control, achieving 95% coverage and a 10% efficiency improvement.
  • Awarded 2nd Prize in the College Student Mechanical Design Innovation Competition, Jiangsu Province.
• “Smart Eyes” - Intelligent Assisted Feeding Robot
  • Developed a height-adjustable smart feeding system for elderly care, leveraging Raspberry Pi and OpenMV for vision and voice control.
  • Secured a national patent for the design.

Internships

• Semiconductor Engineer Intern, Zhuhai Lingyange Chip Technology Co., Ltd. (July 2023 - Aug 2023)
  • Gained foundational knowledge of the semiconductor industry.
  • Applied PDCA project management methods.
  • Tested signal processing using visual signal software and explored GPGPU acceleration with OpenCL, achieving a 20% reduction in energy consumption.
• Firmware Engineer Intern, Seyond (Suzhou), China (July 2022 - Sep 2022)
  • Managed LiDAR data processing on a Linux platform.
  • Developed Python scripts that improved point cloud processing efficiency by 200%.
  • Led log analysis efforts to resolve LiDAR errors.

Skills

• Programming: Python, MATLAB, C, Linux
• Software: CAD, Solidworks, Microsoft Office, Visio
• Technical Skills: Signal Processing, Control Systems, Machine Learning, Deep Learning, Recommender Systems
• Languages: English (CET-6: 531)

Awards and Honors

• 2nd Prize, College Student Mechanical Design Innovation Competition, Jiangsu Province
• 2nd Prize, 14th Higher Education Cup National College Students Advanced Drawing Technology and Product Information Modeling Competition
• 3rd Prize, 12th Jiangsu Province College Students Robot Competition
• Nantong University 2024 Excellent Graduation Thesis (Design)