Research Interests

• Parallel and Heterogeneous computing

• GPU computing

• Design automation

• Graph partitioning

About Me

I am a fourth-year Ph.D. student in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. I obtained my B.S. in Chemical Engineering from Brigham Young University. I am currently working on the graph partitioning problem. Graph partitioning is an important topic in many fields, including scientific computing, data analysis, and VLSI design. My research focuses on developing novel algorithms for both regular graphs and hypergraphs, leveraging the computational power of GPUs to accelerate these processes.

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Achievements

Education

  1. Ph.D. Electrical and Computer Engineering

    University of Wisconsin - Madison, WI Aug 2023 — Jul 2026(expected)

    • GPU-accelerated regular and hypergraph partitioning

    • GPU-accelerated incremental graph partitioning

    • Large Language Model-powered code generation assistant for graph partitioning workloads

  2. B.S. Chemical Engineering

    Brigham Young University, Provo, UT Jan 2017 — Aug 2020

    • GPA: 3.7/4.0

    • Accurately predicted the behavior of molten salt mixtures using molecular simulation

Experience

  1. Computer Engineering Research Assistant

    Department of Electrical and Computer Engineering, UW – Madison Jan 2022 — Present

    • Developed a GPU-based graph partitioning algorithm, achieving a 9x speedup over state-of-the-art CPU partitioners

    • Implemented a GPU-accelerated hypergraph partitioning algorithm, delivering a 4x performance boost compared to leading CPU tools

    • Designed a GPU-based incremental hypergraph partitioner, enabling real-time partition updates with minimal computational overhead

  2. Summer Intern

    Cadence Design Systems, San Jose, CA May 2025 – Aug 2025 (expected)

    • Developed GPU-accelerated solutions to enhance the performance of emulation workloads, targeting critical bottlenecks in existing hardware acceleration pipelines

    • Benchmarked GPU-based accelerators against CPU baselines and proposed optimization strategies based on performance profiling

  3. Computer Engineering Teaching Assistant

    Department of Electrical and Computer Engineering, UW – Madison Sep 2024 – May 2025

    • Assisted in teaching a 100-student course focused on parallel programming with OpenMP and CUDA

    • Conducted weekly office hours and discussion sessions to support students on performance tuning, debugging, and understanding parallel computing concepts

    • Provided one-on-one feedback and guidance to students on their final HPC projects, evaluating proposed methods for feasibility, performance potential, and alignment with course principles.

  4. Summer Internship

    Synopsys, Mountain View, CA May 2022 — July 2022

    • Conducted performance analysis on the Synopsis timing tool to identify bottlenecks

    • Researched opportunities to apply GPU acceleration to the timing calculation

    • Replaced heavy calculations with GPU implantation

  5. Software Developer

    Secumax Technology, Taipei, Taiwan Sep 2020 — May 2021

    • Constructed a SQL database to store and handle application data efficiently and securely

    • Utilized QT to create a cross-platform application which allows users to control remote monitors and perform different functionalities such as zoom in and playback

    • Implemented a new user interface to improve the user experience

  6. Software Developer Internship

    WeCare Insurance Company, Provo, UT Apr 2020 — Aug 2020

    • Led a team of three and mentored team progress

    • Utilized Selenium in Java script to accomplish website automation

    • Reorganized SQL database for easier access

  7. Chemical Engineering Teaching Assistant

    Brigham Young University, Provo, UT Jan 2020 — Apr 2020

    • Aided 45 students in Environmental Safety concepts

    • Led review sessions for class exams

  8. Chemical Engineering Research Assistant

    Brigham Young University, Provo, UT Sep 2017 — Jan 2020

    • Wrote Python and C++ scripts to generate complex formatted files from data

    • Utilized bash commands to run molecular simulations on a supercomputer

    • Evaluated molten salt structure for nuclear reactors through molecular dynamics simulation

Publications

  1. G-kway: Multilevel GPU-Accelerated k-way Graph Partitioner using Task Graph Parallelism

    ACM Transactions on Design Automation of Electronic Systems (TODAES) 2025

    Wan Luan Lee, Dian-Lun Lin, Shui Jiang, Cheng-Hsiang Chiu, Yibo Lin, Bei Yu, Tsung-Yi Ho, and Tsung-Wei Huang.

  2. iG-kway: Incremental k-way Graph Partitioning on GPU

    Design Automation Conference (DAC), San Francisco, California 2025

    Wan Luan Lee, Shui Jiang, Dian-Lun Lin, Che Chang, Boyang Zhang, Ulf Schlichtmann, Tsung-Yi Ho, and Tsung-Wei Huang.

  3. Scalable Code Generation for RTL Simulation of Deep Learning Accelerators with MLIR

    International European Conference on Parallel and Distributed Computing (Euro-Par), Dresden, Germany 2025

    Jie Tong, Wan Luan Lee, Umit Yusuf Ogras, and Tsung-Wei Huang.

  4. SimPart: A Simple Yet Effective Replication-aided Partitioning Algorithm for Logic Simulation on GPU

    International European Conference on Parallel and Distributed Computing (Euro-Par), Dresden, Germany 2025

    Yi-Hua Chung, Shui Jiang, Wan Luan Lee, Yanqing Zhang, Haoxing Ren, Tsung-Yi Ho and Tsung-Wei Huang.

  5. HyperG: Multilevel GPU-Accelerated k-way Hypergraph Partitioner

    Asia and South Pacific Design Automation Conference (ASP-DAC), Tokyo, Japan 2025

    Wan Luan Lee, Dian-Lun Lin, Cheng-Hsiang Chiu, Ulf Schlichtmann, and Tsung-Wei Huang

  6. G-kway: Multilevel GPU-Accelerated k-way Graph Partitioner

    Design Automation Conference (DAC), San Francisco, California 2024

    Wan Luan Lee, Dian-Lun Lin, Tsung-Wei Huang, Shui Jiang, Tsung-Yi Ho, Yibo Lin, and Bei Yu

  7. G-PASTA: GPU Accelerated Partitioning Algorithm for Static Timing Analysis

    Design Automation Conference (DAC), San Francisco, California 2024

    Boyang Zhang, Dian-Lun Lin, Che Chang, Cheng-Hsiang Chiu, Bojue Wang, Wan Luan Lee, Chih-Chun Chang, Donghao Fang, and Tsung-Wei Huang

  8. Complexation of Mo in FLiNaK Molten Salt: Insight from Ab Initio Molecular Dynamics

    The Journal of Physical Chemistry 2020

    Austin David Clark, Wan Luan Lee, Andrew Russell Solano, Tyler Bruce Williams, Gabriel Scott Meyer, Granite J Tait, Ben C Battraw, and Stella D Nickerson



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