Rushan Zhang

rzhangbq@gatech.edu
rzhangbq@gmail.com
Homepage: https://rzhangbq.github.io
Github: rzhangbq

Education

2024.08 - Present The Georgia Institute of Technology (Georgia Tech)
- PhD in Computational Science and Engineering
- Advisor: Prof. Qi Tang
2024.08 - 2026.08 The Georgia Institute of Technology (Georgia Tech)
- MS in Mathematics
2020.09 - 2024.06 The Hong Kong University of Science and Technology (HKUST)
- BEng in Aerospace Engineering and BSc in Computer Science
- Awardee of the Academic Achievement Medal (Approx. top 1%)
2022.08 - 2022.12 The Georgia Institute of Technology (Georgia Tech)
- Exchange Student

Publication

Structure-Preserving Transfer of Grad-Shafranov Equilibria to Magnetohydrodynamic Solvers (Paper, Presentation, Code)
- Rushan Zhang, Golo Wimmer, Qi Tang
- Journal of Computational Physics
- Presented at MFEM Workshop 2025
DoNet: Deep De-overlapping Network for Microscopy Instance Segmentation (Paper, Code)
- Hao Jiang*, Rushan Zhang*, Yanning Zhou, Yumeng Wang, Hao Chen
- Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Experience

2023.09 - 2024.06 Designing a high-performance airfoil by advanced CFD and machine-learning methods (Prof. Fu Lin@HKUST, Final Year Design Project for Aerospace Engineering)
- Designing, implementing and evaluating machine-learning-based methods for airfoil shape optimization, and comparing results with numerical adjoint methods and experimental results
- Inspiration:
  - Machine learning methods excel in identifying coarse global optima, while numerical adjoint methods excel in refining local optima
  - Combining these two methods could potentially yield improved results
2023.09 - 2024.06 Adversarial or reinforcement learning-based closed-loop training strategy for PINN-based fluid simulators that generalize (Prof. Dit-Yan YEUNG@HKUST, Final Year Project for Computer Science)
- Designing, implementing and evaluating a closed-loop training strategy for PINN-based fluid simulator with adversarial or reinforcement learning, to achieve enhanced generalizability
- Inspiration:
  - Closed-loop strategy can more efficiently explore the solution space
  - Training strategies like RL and AL can be used to form a closed-loop process
2023.06 - 2023.08 Iterative surrogate model optimization for transient fluid structure interaction (Prof. Dr. Robert Katzschmann@ETH Zurich, Summer Research Internship)
- Designing, implementing and evaluating surrogate models for fluid structure interaction, conducting optimization with the resultant surrogate models
- Inspiration:
  - Modeling transient fluid flow as a Markov process to enable single-step prediction of flow evolution
  - Introducing shape representation from the field of computer vision to enable monolithic modeling of fluid-structure interaction
  - Introducing active learning techniques to reduce the number of samples required for optimization
2022.02 - 2023.08 Deep learning for medical image analysis (Prof. Chen Hao@HKUST, Undergraduate Research Opportunity Program)
- Designing, implementing and evaluating a novel de-overlapping strategy for semi-transparent cervical cell segmentation
- Inspiration:
  - Using extra information from the overlapping area and the non-overlapping area to guide the segmentation of the whole cell
- Publication: CVPR2023: DoNet: Deep De-overlapping Network for Microscopy Instance Segmentation
2021.06 - 2021.09, Digitalization of wet lab project (WeShare Tech Limited, Student Helper)
- Implementing the hazard warning feature with pop-up windows
- Role:
  - Front-end development with Vue.js

Extracurricular Activities

Aerial robot development team member, HKUST ENTERPRIZE Robo Master Team — 2020 Fall - 2022 Spring
- Collaborating in a team for mechanical design and manufacturing of robots
Hackathon, hackUST 2022 — 2022 Spring
- Collaborating in a team for the development of a webapp called School Application Helper, helping students to manage school application requirements and timelines
- Github repository; Video demo
Research assistant, Prof. Ki Ling CHEUNG@HKUST — 2022 Summer - 2022 Winter
- MySQL database maintenance and data washing with Dask
- Providing technical support for researchers from different technical backgrounds
Peer mentor, COMP & CPEG Mentor-Mentee Scheme — 2023 Fall
- Providing mentoring to second-year students admitted to the computer science and engineering department
Exchange buddy, Exchange Buddy Program — 2023 Spring, 2023 Fall
- Helping exchange students navigate the HKUST campus

Skills

C/C++: C++(intermediate), C(elementary); notes: C++ basic notes, C++ OOP notes
Python: PyTorch(master), NumPy(master), TensorFlow(intermediate), Django(intermediate), Pandas(intermediate)
CAD: SolidWorks(master)
Documentation: Markdown(master), LaTeX(master)
Webapp Development: Vue.js(intermediate), React.js(elementary), MySQL(intermediate), Google Firebase(elementary)
Soft Skills: Collaboration and leadership, self-learning, self-motivation, time management