For a detailed exploration of my professional journey, feel free to download the PDF version of my CV here.

Skills and Technologies

• Research Interests: Machine Learning algorithms, Optimization, Earth Mover’s Distance and Robotics
• Programming Languages: Python, C, C++, MATLAB, R, Java
• Technologies: LaTeX, Machine Learning, Mathematical Modelling, Git, Docker, MediaPipe, Webots, MMAction, ROS

Education

The Chinese University of Hong Kong, Shenzhen

• Location: Shenzhen, China
• Degree: Bachelor in Financial Engineering
• Enrollment Period: Sep. 2020 - Jul. 2024
• Coursework: Probability Theory, Stochastic Process, Calculus, Mathematical Modeling, Discrete Mathematics, Machine Learning, Advanced Machine Learning, Optimization in Data Science and Machine Learning, Data Structures and Algorithms, Computer Programming Paradigm
• Honor: Dean’s list (2020-2021)
• Scholarship: Bowen II Scholarship (2020-2024)
• TOEFL Score: 110 ($MyBest^{TM}$ R:30, L:27, S:24, W:29)

Research

Shenzhen Research Institute of Big Data (SRIBD)

• Estimation of Earth Mover’s Distance (EMD) calculation for incomplete 2D and 3D images (ongoing): Sept. 2022 - Now
  • Reviewed existing computation models focusing on EMD in point cloud data and boosting algorithms.
  • Performed comparative analyses between various EMD algorithms on sparse data sets.
  • Investigated computational complexity across different EMD algorithms.
• Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning: Feb. 2023 - May 2023
  • Formulated an intrinsic similarity matrix by extending the self-expressive learning (SEL) model.
  • Incorporated the $\ell_p$ norm $(0<p<1)$ to further boost the SEL framework.
  • Directed the formulation and coding of the suggested algorithm through optimization techniques such as ADMM.

Internship

Zhuhai Hanglok Interventional Robotics Co., Ltd

• Position: Algorithm Intern (in field of pose estimation and teleoperation)
• Time: Aug. 2023 - Now
  • Constructed a teleoperation platform that recognizes and predicts human motions in an inverse kinematics approach.
  • Designed a system where the robot mimics human movements in real-time through different mapping ways.
  • Enabled the robot to perform predefined actions upon detecting specific human gestures.

Projects

• Recommendation system with focus on user privacy and scalability Apr. 2023
  • Adopted hash encryption with Laplacian noise to encode data, ensuring customers’ privacy.
  • Designed an algorithm to maintain prediction accuracy in a noisy data environment and handle new inputs efficiently, achieving fast computation for different dataset sizes.
• Rumor Propagation Model Based on Continuous Time Markov Chain Dec. 2022
  • Summarized models in the field of infectious diseases and their performance in the field of rumor.
  • Designed a variant model of the SIRS model (SBRS model) and tested the performance of its prediction under the continuous time Markov chain (CTMC) framework.

Publications

1. Fangchen Yu, Runze Zhao, Zhan Shi, Yiwen Lu, Jicong Fan, Yicheng Zeng, Jianfeng Mao, Wenye Li. Boosting Spectral Clustering on Incomplete Data via Kernel Correction and Affinity Learning. (NeurIPS 2023 under revision)