Yifan Zhang

Yifan Zhang

Ph.D. Student at Vanderbilt University

Vanderbilt University


Yifan Zhang (中文: 张一凡, 日本語: チャン・イーファン, Русский: Ифань Чжан) is a Ph.D. student in Computer Science at Vanderbilt University (Vandy), under the supervision of Prof. Kevin J. Leach and Prof. Yu Huang at the Institute for Software Integrated Systems (ISIS). He is also jointly pursuing the Online Master of Science in Computer Science (OMSCS) at Georgia Institute of Technology (GaTech). Before joining Vanderbilt & GaTech, he earned his B.A., B.Eng., and M.Eng. from China University of Petroleum (CUP) at Beijing and worked as a machine learning engineer at the Intelligent Risk Management Lab at JD.COM. He has also worked as a research associate at the University of Hong Kong (HKU) and Duke University (Duke). His research interests lie in AI for programming languages (AI4Code), code representation learning, cognitive process in software engineering, binary code analysis, and medical imaging.

  • AI for Programming Languages (AI4Code)
  • Code Representation Learning
  • Cognitive Process in Software Engineering
  • Binary Code analysis
  • Medical Imaging
  • Vanderbilt University, 2022-2026

    Ph.D. in Computer Science, AI for Software Engineering

  • Georgia Institute of Technology, 2022-2025

    M.Sc. in Computer Science, Machine Learning

  • China University of Petroleum, 2012-2019

    B.A., B.Eng., M.Eng. in English & Petroleum Engineering

  • University of Calgary, 2015-2016

    Undergraduate Exchange Program in Petroleum Engineering



  • [06/10/2024] Started my GenAI Intern at Intel Corporation in Santa Clara, CA, USA.

  • [06/02/2024] Invited as a PC member for NeurIPS'24 D&B.

  • [05/30/2024] Invited as a PC member for DMLR@ICML'24.

  • [05/24/2024] Invited as a PC member for NeurIPS'24.

  • [05/02/2024] Started my remote visiting at Yale University in New Haven, CT, USA.

  • [04/23/2024] On paper got accepted to TOSEM with IF of 4.978.

  • [04/09/2024] Invited as a PC member for CCS'24 AE.

  • [03/15/2024] Selected as a top reviewer for DMLR@ICLR'24 with TR of 9.41%.

  • [01/25/2024] Invited as a PC member for MICCAI'24.

  • [01/23/2024] One paper got accepted to WWW'24 with AR of 20.2%.

  • [01/22/2024] One paper got accepted to FSE'24 with direct AR of 11.59%.

  • [01/11/2024] Invited as a PC member for DMLR@ICLR'24.

  • [01/04/2024] One paper got accepted to ICPC‘24 RENE.



  • [12/04/2022] Invited as a Junior PC member for MSR'23.

  • [11/28/2022] Attended NeurIPS'22 physically in New Orleans, LA, USA.

  • [10/10/2022] Attended ASE'22 physically in Detroit, MI, USA and presented one paper.

  • [09/22/2022] Attended MICCAI'22 virtually in Singapore and presented one paper.

  • [08/05/2022] One paper got accepted to ASE'22 DS.

  • [08/01/2022] Invited as a PC member for AAAI'23.

  • [07/18/2022] One paper got accepted to CaPTion@MICCAI'22.

  • [07/02/2022] Invited as a PC member for CaPTion@MICCAI'22.

  • [06/01/2022] Started my Ph.D. in Computer Science at Vanderbilt University.



Yifan Zhang, Haoyu Dong, Nicholas Konz, Hanxue Gu, Maciej Mazurowski: REPLICA: Enhanced Feature Pyramid Network by Local Image Translation and Conjunct Attention for High-Resolution Breast Tumor Detection. Preprint.

Submitted & Working Papers

Yichang He, Yifan Zhang, Yunpeng Fan, U-Xuan Tan,: Real-time Vibration Compensation with Long Short-term Memory Recurrent Neural Network and Adaptive Filter, Under Review by IEEE-TMech.

Yifan Zhang, Chen Huang, Yueke Zhang, Kevin Cao, Scott Thomas Anderson, Huajie (Jay) Shao, Kevin Leach, Yu Huang: Pre-Training Representations of Binary Code Using Contrastive Learning. Under Review.

Yifan Zhang, Junwen Yang, Haoyu Dong, Qingchen Wang, Huajie (Jay) Shao, Kevin Leach, Yu Huang: ASTRO: An AST-Assisted Approach for Generalizable Neural Clone Detection. Accepted by ICSEW 2023.

Haoyu Dong, Yifan Zhang, Hanxue Gu, Nicholas Konz, Maciej Mazurowski: SWSSL: Sliding-Window based Self-Supervised Learning Framework for Anomaly Detection. IEEE-TMI.

Haoyu Dong, Yifan Zhang, Nicholas Konz, Hanxue Gu, Maciej Mazurowski: Localized Semi-Supervised Anomaly Detection for Breast Tomosynthesis Lesion Screening. Under Review by CMPB.

Chen Huang, Yifan Zhang, Kevin Leach, Yu Huang, Wenqiang Lei, Jiancheng Lv: Cross-Domain Filters for Graph Convolutional Networks by Multiple Kernel Learning. Under Review by AAAI 2024.

Journal & Conference Papers

(2022). Lightweight Transformer Backbone for Medical Object Detection. In MICCAIW 2022.

PDF Cite Poster Slides Video

(2017). Thickness and Stability of Water Film Confined Inside Nanoslits and Nanocapillaries of Shale and Clay. IJCG 2017.

PDF Cite


Intel Corporation
Generative AI Research Intern
Jun 2024 – Dec 2024 Santa Clara, CA, USA

Emerging Growth Incubation Group

  • Ongoing
Yale University
Visiting Student Researcher
May 2024 – May 2024 New Haven, CT, USA

Rigorous Software Engineering Group

  • Ongoing
Research Scientist Intern
May 2023 – Aug 2023 San Jose, CA, USA

Infrastructure Systems Lab

  • Enhancing the SQL pipeline with a hint recommendation system based on representation learning.
  • Optimizing data processing efficiency and query performance.
  • This is an ongoing project expected to complete by the end of this year.
Duke University
Research Associate
Jul 2021 – Jun 2022 Durham, NC, USA

Duke Center for AI in Radiology

  • Designed a pipeline for tumor detection using ViT and FPN, achieving a 13.1% improvement in AP50.
  • Introduced anomaly detection methods for high-resolution medical images with domain generalization.
  • Both methods achieved state-of-the-art results, with work accepted by MICCAIW'22 and IEEE-TMI.
The University of Hong Kong
Senior Research Assistant
Mar 2021 – Sep 2021 Hong Kong SAR

HKU Business School

  • Developed an intelligent debt collection system using data-driven deep reinforcement learning.
  • Utilized transformers and policy gradient models for long-term decision making.
  • Explored GNN applications for finance, leading to a paper on code clone detection accepted by ICSEW'23.
Machine Learning Engineer
Dec 2018 – Mar 2021 Beijing, CN

Intelligent Risk Management Lab, JD Technology

  • Developed DeepFM models for predicting credit use rate and profit, achieving a 21.4% increase.
  • Built a heterogeneous graph and GNN models to improve credit score classification by 5%.
  • Invented a GAN-styled model with differential privacy, leading to 10 CN patents, and awarded in the JD Discovery Cup Patent Competition (Top 0.1%).
Data Science Mentor
May 2018 – Apr 2019 Shanghai, CN

Institute for Data Science

  • Taught VIP students Python, statistics, machine learning and data mining
  • Organized online community activities and created instructional materials
  • Awarded Oustanding Mentor of Udacity China (Top 1%)

Funds & Awards

Research Fellowship from Defense Advanced Research Projects Agency (DARPA)
Fellowship for Ph.D. study at Vanderbilt University (32500$/year)
Research Fellowship from National Institutes of Health (NIH)
Fellowship for research at Duke University ($36000/year)
First Runner-up in the 3rd JD.COM Patent Competition
Employee award for distinguished profit-making technical innovation at JD.COM (Top %0.1 company-wide)
Silver Medal Award of Distinguished JD.COM Technical Recruiter
Employee award for distinguished interviewers at JD.COM (Top %5 company-wide)
Bronze Medal Award of Certified JD.COM Technical Instructor
Employee award for certified JD.COM technical instructor
Beijing Outstanding Graduate Award
Student award for outstanding graduates at Beijing (Top 0.1% nationwide)
Roberto Roca Education Fellowship
Fellowship for outstanding graduate students in China (Top 10 nationwide)
Chinese National Fellowship
Fellowship for undergraduate students in overseas study (CA$6000/4 months)
Dean’s List for the Best Undergraduate Students
Student award for the best undergraduates (Top 4 university-wide)
Schlumberger Engineering Fellowship
Fellowship for outstanding undergraduate students (Top 8 university-wide)
Chinese National Scholarship
Scholarship for top undergraduate students in China (Top 0.2% nationwide)


Academic Mentorship

  • 2024 Manish Acharya, undergraduate student in CS & Math at Vanderbilt University
  • 2023 Jieyu Li, bachelor in EEE at Shanghai Jiaotong University, master in ECE at Vanderbilt University
  • 2023 Luka Mushkudiani, undergraduate student in CS & Math at Vanderbilt University
  • 2022 Eric Li, undergraduate student in CS & Math at Vanderbilt University

Program Comittee (PC) Member

  • 2024 Data-centric Machine Learning Research Workshop at ICML (DMLR@ICML'24)
  • 2024 Annual Conference on Neural Information Processing Systems (NeurIPS'24)
  • 2024 ACM Conference on Computer and Communications Security (CCS'24) Artifact Evaluation Track
  • 2024 Data-centric Machine Learning Research Workshop at ICLR (DMLR@ICLR'24)
  • 2024 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'24)
  • 2024 AAAI Conference on Artificial Intelligence (AAAI'24)
  • 2023 Annual Conference on Machine Learning and Systems (MLSys'23) Artifact Evaluation Track
  • 2023 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'23)
  • 2023 AAAI Workshop on DL-Hardware Co-Design for AI Acceleration (DCAA@AAAI'23)
  • 2023 International Conference on Mining Software Repositories (MSR'23)
  • 2023 AAAI Conference on Artificial Intelligence (AAAI'23)
  • 2022 MICCAI Workshop on Cancer Prevention through early detecTion (CaPTion@MICCAI'22)

External Conference Reviewer

  • 2024 International Conference on Very Large Data Bases (VLDB'24)
  • 2023 USENIX Security Symposium (USENIX'23)
  • 2022 Computer Vision and Pattern Recognition Conference (CVPR'22)