Biography
Greetings! I’m Yifan Zhang (中文: 张一凡, 日本語: チャン・イーファン, Русский: Ифань Чжан), a Research Scientist at Salesforce AI Research (SFR) in San Francisco/Palo Alto. I received my Ph.D. in Computer Science from Vanderbilt University (Vandy), where I was supervised by Prof. Kevin J. Leach and Prof. Yu Huang at the Institute for Software Integrated Systems (VU-ISIS). I am also pursuing an Online Master of Science in Computer Science at Georgia Institute of Technology (GaTech). Previously, I earned my B.A., B.Eng., and M.Eng. from China University of Petroleum (CUP) in Beijing and worked as a full-time MLE at JD.com. During my doctoral studies, I completed research internships at Google Research, Amazon AWS, IBM Research, Intel Corporation, and TikTok/ByteDance. My research focuses on leveraging AI for Programming Languages and Software Engineering (AI4Code), with a particular emphasis on combining program analysis and symbolic reasoning with interactive AI systems to improve neural code analysis, comprehension, and software engineering automation.
- Interactive and Agentic AI
- Neuro-Symbolic AI for PL/SE
- Data-Centric AI for Systems
- LLVM IR and Binary Code Analysis
- Compiler Optimization
- Applied NLP/ML
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
2026
[05/08/2026] Graduated from Vanderbilt University with a Ph.D. in Computer Science.
[04/15/2026] Invited as a reviewer for ICSE'27 Demo.
[04/06/2026] One paper got accepted to ACL'26 with AR of 19%.
[04/06/2026] One paper got accepted to ACL'26 Findings.
[04/05/2026] Received the Great Review Distinction for ACL ARR'26 in January.
[03/25/2026] One paper got accepted to FSE'26 with AR of 26.41%.
[03/24/2026] Invited as a reviewer for NeurIPS'26.
[03/11/2026] Passed my Ph.D. Dissertation Defense.
[01/19/2026] Invited as a reviewer for ACL ARR'26 in January.
[01/05/2026] Started my full-time RS at Salesforce AI Research in Palo Alto, CA, USA.
2025
[12/26/2025] One paper got accepted to ICPC'26 with AR of 26.8%.
[11/07/2025] One paper got accepted to AAAI'26 with AR of 17.6%.
[11/03/2025] Invited as a reviewer for LLM4Code@ICSE'26.
[10/27/2025] Attended LLVM Developers’ Meeting in Santa Clara, CA, USA.
[10/24/2025] Passed my Ph.D. Qualifying Examination.
[10/11/2025] One paper got accepted to TMLR.
[09/22/2025] Invited as a reviewer for ICLR'26.
[09/15/2025] Started my AS Intern at Amazon AWS in Arlington, VA, USA.
[07/12/2025] Invited as a reviewer for AAAI'26.
[06/22/2025] Attended FSE'25 in Trondheim, Trøndelag, Norway.
[06/01/2025] Received the NSF Student Travel Support for FSE'25/ISSTA'25.
[05/19/2025] Started my Research Intern at IBM Research in Yorktown Heights, NY, USA.
[05/15/2025] One paper got accepted to ACL'25 with apx. AR of 20%.
[05/06/2025] Received the C.F. Chen Best Paper Award from Vanderbilt University.
[04/27/2025] Attended ICSE'25 in Ottawa, ON, Canada.
[04/09/2025] Received ACM SIGSOFT CAPS Travel Grant for FSE'25/ISSTA'25.
[04/01/2025] Attended HotSoS'25 virtually hosted by NSA.
[03/31/2025] One paper got accepted to EuroS&P'25 with AR of 20%.
[03/13/2025] Invited as a reviewer for ACL'25 Industry.
[03/12/2025] One paper got accepted to FSE'25 IVR.
[02/19/2025] One paper got accepted to HotSoS'25 WIP hosted by NSA.
[02/17/2025] Invited as a reviewer for NeurIPS'25.
[02/13/2025] One paper got accepted to NAACL'25 Industry with apx. AR of 23.2%.
[01/13/2025] Started my Student Researcher at Google LLC in Sunnyvale, CA, USA.
[01/12/2025] One paper got accepted to ICPC'25 ERA.
2024
[12/11/2024] Invited as a reviewer 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 reviewer 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 reviewer for NeurIPS'24 D&B.
[05/30/2024] Invited as a reviewer for DMLR@ICML'24.
[05/24/2024] Invited as a reviewer for NeurIPS'24.
[04/23/2024] On paper got accepted to TOSEM with IF of 4.978.
[04/09/2024] Invited as a reviewer 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 reviewer 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 reviewer 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 reviewer 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 reviewer for MLSys'23 AE.
[03/02/2023] One paper got accepted to InteNSE@ICSE'23.
[02/06/2023] Invited as a reviewer for MICCAI'23.
[01/06/2023] Invited as a reviewer for DCAA@AAAI'23.
2022
[12/04/2022] Invited as a shadow reviewer 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 reviewer for AAAI'23.
[07/18/2022] One paper got accepted to CaPTion@MICCAI'22.
[07/02/2022] Invited as a reviewer for CaPTion@MICCAI'22.
[06/01/2022] Started my Ph.D. in Computer Science at Vanderbilt University.
Experience
AI Research Group, Enterprise Computer-Use Agent
Planned work focuses on an Action-as-Code paradigm to transition from fragile GUI-based interactions to robust programmatic execution.
Aims to develop autonomous agents capable of navigating fragmented enterprise environments with long-horizon consistency.
Automated Reasoning Group, Formal Methods and Programming Languages
- Planned to assist in research exploring LLM formal reasoning projects.
- Expected to contribute to the ongoing project with agentic workflow for system tasks.
- Will work with the team to build prototype and research on new topics.
AI Reasoning Group, Neuro-symbolic AI
- Architected a self-improving planning framework with the IBM Watson AI pillar that utilized a parallelized Monte Carlo Tree Search.
- Guided the search with a symbolic value function derived from a dynamically learned rule base.
- Used an LLM as an inductive learner to discover and refine strategic heuristics from successful plans, enabling efficient reasoning on complex agentic tasks.
Google TAO Team, Google CORE Developer
- Designed an automated pipeline with Google CORE/Google Research that uses LLMs to generate C++ code that simulates LLVM IR profiles.
- Enabled benchmarking and performance analysis of production code through the automated pipeline.
- The system supported AI models in learning compiler behavior and optimization strategies across diverse hardware platforms, with safeguards to preserve IP integrity.
Incubation and Disruptive Innovation (IDI) Group, Intel Silicon Valley
- 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, TikTok Applied Research Center
- 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, Duke University Medical Center
- 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 and prototyped in production environment.
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, Udacity China
- 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
- 2025 Zichen (Ryan) Zhu, undergraduate student in CS & Math & Political Science at Vanderbilt University
- 2024 Suad Mohamed, undergraduate student in CS & Psychology at Belmont University (co-mentored by Mr. Zachary Karas)
- 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 Committee Member and Conference Reviewer
- 2026 International Workshop on Large Language Models for Code (LLM4Code@ICSE'26)
- 2026 AAAI Conference on Artificial Intelligence (AAAI'26)
- 2025 Annual Meeting of the Association for Computational Linguistics (ACL'25) Industry Track
- 2025 Annual Conference on Neural Information Processing Systems (NeurIPS'25) Datasets & Benchmarks Track
- 2025 International Conference on Machine Learning (ICML'25)
- 2025 International Conference on Learning Representations (ICLR'25)
- 2024 Annual Conference on Neural Information Processing Systems (NeurIPS'24) Datasets & Benchmarks Track
- 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