About

• I am a Ph.D. student at the University of Science and Technology of China (USTC), co-supervised by Prof. S. Kevin Zhou(Fellow of IEEE, AIMBE, NAI) and Dr. Peng Xiong.
• Prior to this, I received my bachelor degree from USTC in 2020 and obtained my master degree from Institute of Computing Technology (ICT) and University of Chinese Academy of Sciences (UCAS) in 2023.
• My research centers on AI for Science (AI4S), with a specific focus on fundamental challenges in computational biology, from structure prediction to sequence-structure-function applications, including:
  • RNA secondary structure and tertiary structure prediction.
  • Structure-guided RNA foundation model (LLM) for sequence understanding and structural prediction.
  • Functional applications such as identification of IRES, exploration of functional RNA motifs within non-coding genomic regions, and AI-driven drug discovery.
• Previously, I worked on medical imaging computing, where I developed universal models and few-shot learning methods for localizing anatomical landmarks.
• I am always welcoming discussions and collaborative opportunities, please feel free to contact me. :)
• I am actively seeking postdoctoral and research positions starting in Fall 2026. Here is my CV (中文简历). I would appreciate it if you would consider me for an opportunity.

News

• 2025.07:   BPfold has been published in Nature Communications.
• 2024.10:   We release BPfold, an effective tool for RNA secondary structure prediction.

Educations

• 2023.09 - present, Ph.D. student of Biomedical Engineering, Suzhou Institute for Advanced Research, University of Science and Technology of China (USTC), Suzhou, China
• 2020.09 - 2023.06, Master of Computer Applications, University of Chinese Academy of Sciences (UCAS) & Institute of Computing Technology (ICT), CAS, Beijing, China
• 2016.09 - 2020.06, Bachelor of Computer Science and Technology, University of Science and Technology of China (USTC), Hefei, China
  • Hua Xia Talent Program in Computer Science and Technology

Honors and Awards

• 2025, Suzhou Industrial Park Scholarship, USTC
• 2024, First Class Scholarship, USTC
• 2020-2023, First Class Scholarship, UCAS & ICT
• 2023, Merit Student Award, UCAS & ICT
• 2018-2019, Outstanding Student Award, USTC
• 2017, Institute of Chemistry Excellence Scholarship, USTC

Professional Experiences

• 2021.07 - 2021.11, Research Intern, Tencent Jarvis Lab, Shenzhen, China
• 2019.09 - 2020.04, Research Intern, Z2sky, Suzhou, China

Professional Services

• Journal Reviewers
  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
• Conference Reviewers:
  • International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)

Teaching & Volunteer Experiences

• 2024, Volunteer: Medical Augmented Reality Summer School, Suzhou
• Fall 2023, Teaching Assistant: Electronic information openness practices, USTC
• 2023, Volunteer: Dushu Lake Forum Dushu Lake Symposium on Medical lmage Computing, Suzhou

Publications

(# equal contribution, * corresponding authors. Selected publications | Full List)

RNA Secondary Structure Prediction

• Nat. Commun. 2025 Deep generalizable prediction of RNA secondary structure via base pair motif energy (Nature Communications)
  Heqin Zhu, Fenghe Tang, Quan Quan, Ke Chen, Peng Xiong*, S. Kevin Zhou*  [code][paper][poster]

Few-shot Learning

• MIA 2024 Which images to label for few-shot medical image analysis? (Medical Image Analysis)
  Quan Quan#, Qingsong Yao#, Heqin Zhu, Qiyuan Wang, S. Kevin Zhou   [code]
• MICCAI 2023 UOD: universal oneshot detection of anatomical landmark (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  Heqin Zhu, Quan Quan, Qingsong Yao, Zaiyi Liu, S. Kevin Zhou (early accept)   [code][arXiv][poster]

Anatomical Landmark Detection

• IJCARS 2024 PELE scores: pelvic X-ray landmark detection with pelvis extraction and enhancement (International Journal of Computer Assisted Radiology and Surgery)
  Zhen Huang#, Han Li#, Shitong Shao, Heqin Zhu, Huijie Hu, Zhiwei Cheng, Jianji Wang, S. Kevin Zhou   [code]
• BMEF 2022 Learning to localize cross-anatomy landmarks in x-ray images with a universal model (BME frontiers)
  Heqin Zhu, Qingsong Yao, Li Xiao, S. Kevin Zhou   [code][arXiv]
• MICCAI 2021 You Only Learn Once: Universal Anatomical Landmark Detection (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  Heqin Zhu, Qingsong Yao, Li Xiao, S. Kevin Zhou   [code][arXiv]

Unsupervised & Self-supervised Learning

• TMI 2024 IGU-Aug: Information-guided unsupervised augmentation and pixel-wise contrastive learning for medical image analysis (IEEE Transactions on Medical Imaging)
  Quan Quan#, Qingsong Yao#, Heqin Zhu, S. Kevin Zhou   [code][arXiv]
• MIDL 2024 Slide-SAM: medical SAM meets sliding window (Medical Imaging with Deep Learning)
  Quan Quan#, Fenghe Tang#, Zikang Xu, Heqin Zhu, S. Kevin Zhou   [code][arXiv]
• MICCAI 2024 Hyspark: Hybrid sparse masking for large scale medical image pre-training (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  Fenghe Tang, Ronghao Xu, Qingsong Yao, Xueming Fu, Quan Quan, Heqin Zhu, Zaiyi Liu, S. Kevin Zhou   [code][arXiv]

Others

• arXiv 2022 DFTR: Depth-supervised hierarchical feature fusion transformer for salient object detection
  Heqin Zhu, Xu Sun, Yuexiang Li, Kai Ma, S. Kevin Zhou*, Yefeng Zheng*  [code][arXiv]
• IJCARS 2021 Deep learning to segment pelvic bones: large-scale CT datasets and baseline models (International Journal of Computer Assisted Radiology and Surgery)
  Pengbo Liu, Hu Han, Yuanqi Du, Heqin Zhu, Yinhao Li, Feng Gu, Honghu Xiao, Jun Li, Chunpeng Zhao, Li Xiao, Xinbao Wu, S. Kevin Zhou   [link][arXiv]