Weiqi Lu

Weiqi Lu

PhD Candidate in Computer Science & Engineering @ HKUST

Weiqi Lu (卢伟奇)

I am Weiqi (William) Lu, a fourth-year Ph.D. candidate in CASTLE (Code AnalysiS, Testing and LEarning) Lab at The Hong Kong University of Science and Technology (HKUST), supervised by Prof. S. C. Cheung (IEEE Fellow, Chair Professor) and Prof. Yongqiang Tian (Monash University), and supported by the Hong Kong PhD Fellowship Scheme (HKPFS). Prior to this, I earned my B.Sc. in Computer Science and Mathematics at HKUST.

My research focuses on software engineering, particularly the algorithmic search, pattern recognition, and anomaly detection in data analytics systems. I am interested in combining mathematical modeling, theory and algorithms, and engineering practice to improve the quality and reliability of data-driven systems. Additionally, I enjoy exploring mathematics and machine learning, with a specific interest in artificial intelligence for software engineering (AI4SE) and large language models for software engineering (LLM4SE).

I am also drawn to data structures and algorithms and their engineering implementation. I have solved 1,480+ problems on LeetCode in C++ and Python, including 230+ hard problems, with a global rank under 8,200. Recently, I achieved an all-kill (AK) in a LeetCode weekly contest, ranking 837 (top 2%). Beyond research, I enjoy listening to music, playing acoustic guitar, photography, jogging, hiking, and playing video games.

Publications

Education

The Hong Kong University of Science and Technology

  • Ph.D. in Computer Science and Engineering | 2023.09 - Present
    GPA: 4.050/4.30

  • B.Sc. in Computer Science and Mathematics | 2019.09 - 2023.07
    First Class Honors · GPA: 4.109/4.30 · 2023 Academic Achievement Medal · Top 2%

Georgia Institute of Technology

  • Undergraduate Exchange Program | 2022.01 - 2022.05
    GPA: 4.00/4.00

University of California, Berkeley

  • Berkeley Summer Sessions | 2021.06 - 2021.08
    GPA: 4.00/4.00

Projects

  • Automated Testing of Data Visualization Libraries | arXiv
    Engineered VIZDETOUR, an automated testing framework for stateful systems driven by novel endpoint-preserving mutations and automated visual oracles. Evaluated the framework across major visualization libraries (matplotlib, bokeh, and plotly) to expose deep state-management vulnerabilities. Discovered 47 previously unknown bugs, of which 39 were confirmed and 18 were fixed.
  • Uncovering Causal Relationships in Co-location Patterns | UROP Proceedings 2021-22 | Short Paper
    Proposed a scalable framework for mining causal relationships among co-location patterns using Granger causality. Designed an algorithm that approximates direct causes from Granger causes using unique causal information, addressing limited use of temporal information in prior causal-mining models. Evaluated the approach on real-world datasets.
  • Language-Guided Dense Prediction for Scene Understanding | UROP Proceedings 2022-23
    Proposed OpenCLIP, a CLIP-guided approach for open-world semantic segmentation, to recognize novel classes without pixel-level annotations. Addressed the class bias of incremental learning by leveraging the semantic representations of CLIP image and text encoders.
  • JoJo Manga Style Transfer Model | Report | Demo
    Engineered and trained a generative image-to-image translation model using CartoonGAN to stylize real-world video frames into the distinctive high-contrast art style of JoJo’s Bizarre Adventure. Preprocessed and aligned 18,000+ CelebA human face photos with 4,000 face-cropped anime frames, applying Canny edge-detection and Gaussian smoothing for edge-promoting adversarial loss.
  • Multiplayer Dou Dizhu (Landlord) Game | GitHub
    Architected a full-stack, multi-player Dou Dizhu game in C++ using Qt, featuring integrated GUI elements, automated AI players, and real-time multiplayer support via TCP sockets. Implemented rule-based AI heuristics for strategic hand evaluation, alongside an event-driven user interface complete with dynamic card distribution effects, hint generation, and audio feedback.

Selected Coursework

Statistics: MATH5431 Advanced Mathematical Statistics I (A+) · MATH2431 Honors Probability (A+) · MATH2411 Applied Statistics (A+)

ML & Data: COMP5212 Machine Learning (A+) · MATH4432 Statistical Machine Learning (A+) · COMP4331 Data Mining (A+) · COMP3311 Database Management Systems (A+)

Algorithms: COMP5711 Introduction to Advanced Algorithmic Techniques (A+) · COMP4421 Image Processing (A+) · COMP3711 Design and Analysis of Algorithms (A+)

Mathematics: MATH4223 Differential Geometry (A+) · MATH3343 Combinatorial Analysis (A+) · MATH3121 Abstract Algebra (A+) · MATH2352 Differential Equations (A+)

Business: ISOM1380 Technology and Innovation: Social and Business Perspectives (A+)

Technical Skills

Programming Languages: C++, Python, Java, SQL, R, JavaScript, HTML5, Bash

Libraries & Frameworks: NumPy, Pandas, PyTorch, Pytest, Soot, STL, Qt, JavaFX

Domains: Data Structures & Algorithms, Static/Dynamic Program Analysis, Test Automation, Machine Learning

Honors and Awards

  • 2026: #10 at HKUST, Hong Kong Joint Collegiate Programming Contest (HKJCPC 2026).
  • 2025: ACM SIGSOFT CAPS Award.
  • 2023 - 2027: Hong Kong PhD Fellowship Award (Hong Kong’s top PhD scholarship).
  • 2023: HKUST RedBird PhD Award.
  • 2023: HKUST Academic Achievement Medal (highest academic honor at graduation).
  • 2022: The 17th Epsilon Fund Honorable Mention (outstanding mathematical scholarship).
  • 2022: Tin Ka Ping Scholarship (Exchange).
  • 2022: HKUST Alumni Endowment Fund High Flyers Program Scholarship.
  • 2020 - 2023: Chiaphua Industries Limited Scholarship for Chinese Undergraduate Students.
  • 2020 - 2023: University’s Scholarship Scheme for Continuing Undergraduate Students.
  • 2019 - 2023: Dean’s List for the School of Engineering.

Teaching and Service

  • 2025 Spring, 2026 Spring: COMP5111 Fundamentals of Software Testing and Analysis.
  • 2024 Spring: COMP2211 Exploring Artificial Intelligence.
  • 2025 - 2026: Reviewer for top-tier (CCF-A / CORE A*) software engineering venues, including ICSE 2026, FSE 2026, ASE 2025-2026, and ISSTA 2025-2026.