Biography
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
News
2024
[12/11/2024] Invited as a PC member for ICML'25.
[12/10/2024] One paper got accepted to ICSE'25 JF.
[10/15/2024] One paper got accepted to TMech with IF of 6.38.
[08/23/2024] Invited as a PC member for ICLR'25.
[07/15/2024] Attended FSE'24 in Porto de Galinhas, PE, Brazil.
[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.
[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.
2023
[12/19/2023] Passed my Ph.D. Preliminary Examination.
[09/05/2023] One paper got accepted to TMI with IF of 11.037.
[07/13/2023] Invited as a PC member for AAAI'24.
[07/07/2023] One paper got accepted to ASE'23 NIER.
[05/22/2023] Started my RS intern at ByteDance in San Jose, CA, USA.
[03/19/2023] Invited as a PC member for MLSys'23 AE.
[03/02/2023] One paper got accepted to InteNSE@ICSE'23.
[02/06/2023] Invited as a PC member for MICCAI'23.
[01/06/2023] Invited as a PC member for DCAA@AAAI'23.
2022
[12/04/2022] Invited as a Junior PC member for MSR'23.
[11/28/2022] Attended NeurIPS'22 in New Orleans, LA, USA.
[10/10/2022] Attended ASE'22 in Detroit, MI, USA.
[09/22/2022] Attended MICCAI'22 virtually in Singapore.
[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.
Experience
AI Reasoning Group
- Planned to assist in research exploring AI techniques for solving complex problems.
- Expected to contribute to the development and evaluation of innovative solutions in AI.
- Will support the team in designing and testing scalable systems for practical applications.
Compiler and Learning Theory Group
- Planned to participate in research projects focused on advancing AI and systems optimization.
- Expected to explore methods to improve the performance and applicability of cutting-edge tools.
- Will collaborate with the team to analyze and enhance existing frameworks.
Incubation and Disruptive Innovation (IDI) Group
- Automated and enhanced construction scheduling for semiconductor projects using LLM-based systems.
- Integrated rule-based knowledge and in-context learning, improving efficiency by 2.8x compared to GPT-4o.
- Designed a novel DPO pipeline for better alignment of context and preference in construction automation.
Infrastructure Systems Lab
- Implementing a hint recommendation system by applying representation learning on SQL execution trees.
- Optimizing query performance by identifying patterns in execution trees and reranking SQL hints.
- Enhancing data processing efficiency based on insights from execution tree representation.
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.
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.
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%).
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
Services
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)
Contact
- yifan.zhang.2@vanderbilt.edu
- +1 919 638-0501
- 1400 18th Ave S, Nashville, TN 37212
- DM Me on Twitter