Ziyu Su

Ziyu Su

PhD candidate

PhD candidate in AI & Medcine
Center for Artificial Intelligence
Wake Forest University, Winston Salem, NC
Virginia Tech-Wake Forest University School of Biomedical Engineering and Sciences

About Me

I’m a 4th year PhD student at Center for Artificial Intelligence, Wake Forest University, where I’m focusing on Deep learning and Medical Image Analysis. I’m currently advised by Dr. Metin Gurcan and Dr. M. Khalid Khan Niazi. I’m also a PhD student in the joint BMES school of Virginia Tech and Wake Forest. Before that, I worked as a research associate at Rensselaer Polytechnic Institute with Dr. Fenglei Fan and Dr. Ge Wang. I received a Master’s degree in Electrical Engineering from Rensselaer Polytechnic Institute in 2020, and a Bachelor’s degree in Electronic&Information Science from Shandong University in 2018.

Research Interests

Weakly/Self-Supervised Learning, Attention Mechanism, Visual Language Model, Medical Image Analysis, Digital Pathology

Highlights

  • [Nov 2023] We have four paper accepted in the oral sessions of SPIE Medical Image 2024!
  • [Oct 2023] Our paper entitled “Attention2Minority: A salient instance inference-based multiple instance learning for classifying small lesions in whole slide images.” is accepted in Computers in Biology and Medicine.
  • [Sep 2023] Our paper entitled “One label is all you need: Interpretable AI-enhanced histopathology for oncology.” is accepted in Seminars in Cancer Biology.
  • [Aug 2023] My mentee Amanda Rosen (Duke) and Preston Leigh (Arizona) won 2nd and 3rd places in the final presentions of WFBMI REU summer research program. Congratualations!
  • [July 2023] I am delighted to share that I have successfully defended my thesis proposal titled “Improved Breast Cancer Diagnosis and Prognosis with Interpretable Deep Learning in Histopathology Images.” I extend my gratitude to Dr. Gurcan, Dr. Niazi, and all members of my committee!
  • [June 2023] Our paper entitled “NRK-ABMIL: Subtle Metastatic Deposits Detection for Predicting Lymph Node Metastasis in Breast Cancer Whole-Slide Images” is accepted in Cancers.
  • [May 2023] I make a lecture about Imaging Informatics and Artificial Intelligence in WFBMI CALIBIR Informatics Bootcamp.
  • [May 2023] Our paper received the top scientific paper award during the Internal Medicine Research Day Grand Rounds of WFUSOM-Atrium Health. This award recognizes outstanding scientific papers published by students and faculty members from WFUSOM and Atrium Health in 2022.”
  • [April 2023] Our pilot study about Oncotype-DX prediction, “BCR-Net: A deep learning framework to predict breast cancer recurrence from histopathology images”, is accepted in PLOS ONE.
  • [Feb 2023] Our conference paper entitled “Predicting obstructive sleep apnea severity from craniofacial images using ensemble machine learning models” is accepted in SPIE Medical Imaging: Computer-Aided Diagnosis, 2023.
  • [July 2022] Our paper entitled “Attention2majority: Weak multiple instance learning for regenerative kidney grading on whole slide images” is accepted in Medical Image Analysis.