ZHANG Rushan

ZHANG Rushan

I am a first-year PhD student at the Georgia Institute of Technology (Georgia Tech). I am working with Prof. Qi Tang @ Georgia Tech on computational plasma physics.

During my undergraduate studies, I was fortunate to work with Prof. Hao Chen @ HKUST on deep learning-based medical image analysis, and our work was proudly published at CVPR. I also had the privilege of collaborating with Prof. Robert Katzschmann @ ETH on deep learning-based surrogate modeling for transient fluid-structure interaction and with Prof. Fu Lin @ HKUST on data-driven airfoil optimization.

My research interest lies in high-performance computing, scientific modeling and simulation, and artificial intelligence for scientific computing.

🔥 News

  • 2024 08 I graduated from the Hong Kong University of Science and Technology, and became a PhD student at the Georgia Institute of Technology.

📝 Publications

CVPR 2023
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DoNet: Deep De-Overlapping Network for Cytology Instance Segmentation

Hao Jiang*, Rushan Zhang*, Yanning Zhou, Yumeng Wang, Hao Chen

Google Scholar | Paper | Code |

  • In this work, we proposed a De-overlapping Network (DoNet) in a decompose-and-recombined strategy. A Dual-path Region Segmentation Module (DRM) explicitly decomposes the cell clusters into intersection and complement regions, followed by a Semantic Consistency-guided Recombination Module (CRM) for integration. To further introduce the containment relationship of the nucleus in the cytoplasm, we design a Mask-guided Region Proposal Strategy (MRP) that integrates the cell attention maps for inner-cell instance prediction. We validate the proposed approach on ISBI2014 and CPS datasets. Experiments show that our proposed DoNet significantly outperforms other state-of-the-art (SOTA) cell instance segmentation methods.

📖 Educations

  • 2024.08 - Present The Georgia Institute of Technology (Georgia Tech)
    • PhD in Machine Learning
  • 2020.09 - 2024.06 The Hong Kong University of Science and Technology (HKUST)
  • 2022.08 - 2022.12 The Georgia Institute of Technology (Georgia Tech)
    • Exchange Student

🎖 Honors and Awards

💻 Previous Projects

  • 2023.09 - 2024.06 Designing a high-performance airfoil by advanced CFD and machine-learning methods (Final year design project for aerospace engineering, Prof. Fu Lin@HKUST)
    • 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 (Final year project for computer science, Prof. Dit-Yan YEUNG@HKUST)
    • 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 (Summer research, Prof. Dr. Robert Katzschmann@ETH Zurich)
    • 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 (Undergraduate research, Prof. Chen Hao@HKUST)
  • 2021.06 - 2021.09, Digitalization of wet lab project (Student helper, WeShare Tech Limited)
    • Implementing the hazard warning feature with pop-up windows
    • Role:
      • Front-end development with Vue.js

💬 Invited Talks