🐰 About Me

• I am a third-year Ph.D. student in Management Science and Engineering (管理科学与工程专业) at the School of Management, University of Science and Technology of China (USTC) (中国科学技术大学), majoring in Information Systems, under the supervision of Prof. Hefu Liu (刘和福). Currently, I am a visiting student in the Department of Civil and Environmental Engineering at the National University of Singapore (NUS), where I am advised by Prof. Yang Liu.

• In addition, I am currently a deep learning research intern at Tiktok , Singapore. Previously, I worked as a research intern at DiDi and orange energy from November 2023 to July 2025, and at Xiaoan Tech from June 2023 to September 2023. During these internships, I developed some algorithms that have been successfully deployed in these companies.

• I have published papers at top Information Systems conferences, such as ICIS and PACIS, and in renowned journals. My work has been accepted by ACM Transactions on Knowledge Discovery from Data (TKDD, CCF-B), IEEE Transactions on Intelligent Transportation Systems (IEEE ITS, CCF-B), IEEE Transactions on Engineering Management (IEEE TEM), and Expert Systems with Applications (ESWA, CCF-B).
• 🔍 My current research interests involve:
  • Customer Behavior Analysis (Information Systems direction):
    • Recommendation, Purchase Prediction, Fraud Detection, and more.
    • Driving Behavior of Ride-Hailing Drivers.
  • Traffic Prediction & Scheduling (Intelligent Transportation direction):
    • Traffic Prediction, Large-Scale Scheduling, New Energy Vehicle Charging, and more.
  • Digital Commerce and Platform Economy (Operation Management):
    • EV Charging Station Configuration and Marketing.
• 🔦 Research Methods: I specialize in LLM, deep reinforcement learning approaches, traditional deep learning techniques (including Graph Neural Networks (GNN), Hyper-GNN), empirical methods (such as Difference-in-Differences (DID) and its variants), large-scale field experiments in companies. I also focus on the interpretability and causality of models.

💬 Contact Me

I am actively seeking collaborations. If you are interested in topics related to user behavior (e.g., fraud detection, opportunistic behavior, purchase prediction), intelligent transportation (e.g., new energy ride-hailing, demand prediction, driving behavior, charging behavior, charging stations), electricity trading, or data value assessment, or if you have innovative ideas, some datasets in these fields are avaiable.

If you are seeking any form of academic cooperation, please feel free to email me at: jiahuifeng@mail.ustc.edu.cn

🔥 News

• 2025.10:  🚗🚗 More works are on the road!

📝 Publications

🖥️ Informtion System Direction

• Beyond the Match: Predicting Bilateral-matching Satisfaction with Multi-view Heterogeneous Graph Neural Network, Jiahui Feng, Hefu Liu, Juntao Wu, Huiyu Liu, Peng Zhao, ICIS 2025
• Optimizing Restaurant Customer Flow and Revenue with Real-Time Coupon Allocation: A Deep Reinforcement Learning Approach, Jiahui Feng, Juntao Wu, Meng Chen, Juan Qin, ICIS 2024 Best Paper Nominee @ICIS2024
• When is AI Superior to Human? Unveiling the Effects of “Word-of-Machine” on Debt Collection Utilizing Different Types of Privacy: Randomized Field Experiment, Mengyao Ma, Ran Tan, Jiahui Feng, Qian Huang, Jiahong Xu, ICIS 2025
• Unraveling the Dual Effects of Online Contextual Information Disclosure on Offline Transactions, Yichang Shen, Jiahui Feng, Jie Fang, Hefu Liu, ICIS 2025

🚲 Intelligent Transportation Direction

• A Data-Driven Adaptive Spatial-Temporal Method for Docked Shared Bike Prediction, Jiahui Feng, Hefu Liu, IEEE Transactions on Intelligent Transportation Systems
• A Spatial-Temporal Aggregated Graph Neural Network for Docked Bike-sharing Demand Forecasting, Jiahui Feng, Hefu Liu, Jingmei Zhou, Yang Zhou, ACM Transactions on Knowledge Discovery from Data
• An end to end two-stream framework for station-level bike-sharing flow prediction, Xiaoyu Yao, Jiahui Feng, Expert Systems with Applications
• Service level optimizing and shared bike rebalancing based on multi-agent deep reinforcement learningc, Jiahui Feng, Yingbo Li, Hefu Liu, PACIS 2024

🤖 Operation Mangement

• Digital Transformation and Innovation Strategy Selection: The Contingent Impact of Organizational and Environmental Factors, Yangzhou, Jingjun Xu, Zhiying Liu, Jiahui Feng, IEEE Transactions on Engineering Management
• [Achieving sustainability through digital transformation: Innovation mechanisms and boundary conditions], Yang (Eric) Zhou, Wim Coreynen, Jiahui Feng, Liu, Zhiying, _ Industrial Management & Data Systems_

🎩 Educations

• 2025.08 - Now, Visiting Student, Department of Civil and Environmental Engineering, National University of Singapore, Singapore, advised by Yang Liu.
• 2021.07 - Now, PhD, School of Management, University of Science and Technology of China, Hefei, Anhui, advised by Hefu Liu.
• 2017.09 - 2021.06, Undergradate, School of Management, Hefei University of Technology, Hefei, Anhui, advised by Yezheng Liu.

👨‍💻 Internships

• 2025.8 - Now, TikTok , Deep Learning Engineer Intern.
  • More works are on the road!
• 2023.11 - 2025.7, DiDi Global, Hangzhou, Data Operations & Analysis Intern.
  • *2023.11, Developed a deep learning–based fraud detection algorithm leveraging in-app customer clickstream data to identify fraudster; the system is used by over 1 million customers daily.
  • *2024.04, Developed electric demand forecasting and intelligent trading algorithms using reinforcement learning to enhance energy management.
  • *2025.03, Developed a driver–passenger matching satisfaction prediction algorithm, aiming to improve overall user matching experiences.
  • *2025.07, Conducted large-scale on-site experiments to support data-driven operational analysis.
• 2023.06 - 2023.09, Xiaoan Tech, Wuhan.
  • Developed a shared bike prediction deep learning algorithm used to forecast the number of rented and returned bikes in over 200 regions in China.

📖 Academic Services

• Peer Reviewer for Journals and Conferences
  • Transportation Research Part B: Methodological
  • Industrial Management & Data Systems (IM&DS)
  • International Conference on Information Systems (ICIS)
  • Pacific Asia Conference on Information Systems (PACIS)
  • Summer Workshop on Information Management (CSWIM)
  • IEEE Transactions on Intelligent Transportation Systems (IEEE ITS)
  • ACM Transactions on Knowledge Discovery from Data (TKDD)