About Me
I'm a Postdoctoral Associate in Computer Science at the University of Pittsburgh, working under the mentorship of Prof. Xiaowei Jia. I earned my Ph.D. in Computer Science from the University of Science and Technology of China (USTC) in 2023, under the supervision of Prof. Enhong Chen and the co-supervision of Prof. Qi Liu. Prior to that, I received my B.Eng. in Computer Science from USTC in 2017.
My primary research interest is to advance artificial intelligence and data science to solve real-world problems of great societal and scientific impact. A central focus of my research is developing machine learning models that adapt to dynamic environments while integrating scientific knowledge. This approach is gaining increasing attention across various scientific domains, including hydrology, limnology, climate science, and aquatic science.
My work has been published in top-tier journals such as IEEE TKDE and CACM, as well as in leading conferences such as KDD, ICDM, SDM, AAAI, IJCAI, PPSN, SIGIR, and CIKM. In total, I have authored seven peer-reviewed journal articles and 27 papers in highly selective conferences. My work has garnered over 370 citations, with an H-index of 11 (according to Google Scholar). Additionally, I have received numerous recognition for both research and leadership. As a team captain, I led my team to victories in several notable competitions. These achievements have been reported by media outlets such as Anhui Daily. To gain a more comprehensive understanding of my background, you can visit my Curriculum Vitae.
I am in the 2024-2025 academic job market for a tenure-track faculty position. Please kindly contact me if there is a good fit!
Research Interests
- Data Mining and Machine Learning: adaptive learning, feature selection, physics-guided machine learning, foundation model, spatiotemporal data mining, learning to rank, pairwise learning, sampling, graph embedding
- Evolutionary Computation: evolutionary learning, real-parameter optimization, evolution-based feature selection, Pareto optimization
- AI for Environmental Science: ecosystem modeling, aquatic science, freshwater systems, process-based modeling, carbon neutral
- Recommender Systems: user modeling, collaborative filtering, click-through rate prediction, intelligent marketing, fintech
Teaching
I am teaching CS 2756: Principles of Data Mining this semester!
- Lectures: Mondays & Wednesday, 6:00 - 7:15pm (@SENSQ 6110).
- The weekly schedule and office hours: Canvas Course Page.
I taught CS 1656 / CS 2056: Introduction to Data Science in Fall 2024.
- Lectures: Tuesdays & Thursdays, 1:00 - 2:15 pm (@IS 305).
- Recitations: Fridays, 2:00 - 2:50 pm (@SENSQ 5129) OR 3:00 - 3:50 pm (@SENSQ 6110).
- The weekly schedule and office hours: Canvas Course Page.
Honors and Awards
- [Sep. 2022] Outstanding Student Leadership Award
- [May 2022] Outstanding Student Award of "Six Good" College Students
- [Nov. 2021] Gold Medal of the 7th Anhui Province "Internet+" College Student Innovation Competition
- [Sep. 2021] USTC Postgraduate First-Class Scholarship
- [Jul. 2021] China Scholarship Council Scholarship
- [Jan. 2021] Champion of the CCF BDCI Fighting Epidemics Big Data Charity Challenge [Anhui Daily] [USTC News]
- [Jan. 2021] USTC Special Scholarship
- [Sep. 2020] USTC Postgraduate First-Class Scholarship
- [Dec. 2019] China National Scholarship
- [Sep. 2019] USTC Postgraduate First-Class Scholarship
- [Aug. 2019] KDD CUP Regular ML Track PaddlePaddle Special Award
- [Dec. 2018] The Third Runner-up of China (Hefei) Big Data and Artificial Intelligence Innovation Application Competition
- [Dec. 2018] Suzhou Industrial Park Scholarship
- [Oct. 2018] GDC Technology Scholarship
- [Sep. 2018] USTC Postgraduate First-Class Scholarship
- [Sep. 2017] USTC Postgraduate First-Class Scholarship
- [Oct. 2012] First Prize of Chinese Physics Olympiad
Selected Publications
Journal Articles:
Runlong Yu, Yiqun Xie, Xiaowei Jia. Environmental Computing as a Branch of Science, Communications of the ACM (CACM), accepted, to be published, 2025.
Runlong Yu, Qi Liu, Yuyang Ye, Mingyue Cheng, Enhong Chen, Jianhui Ma. Collaborative List-and-Pairwise Filtering from Implicit Feedback, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), v 34, n 6, pages 2667-2680, 2022.
Runlong Yu, Hongke Zhao, Zhong Wang, Yuyang Ye, Peining Zhang, Qi Liu, Enhong Chen. Negatively Correlated Search with Asymmetry for Real-Parameter Optimization Problems, Journal of Computer Research and Development (J-CRAD), v 56, n 8, pages 1746-1757, 2019. (in Chinese)
Yuyang Ye, Hengshu Zhu, Tianyi Cui, Runlong Yu, Le Zhang, Hui Xiong. University Evaluation through Graduate Employment Prediction: An Influence based Graph Autoencoder Approach, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), accepted, early access, doi: 10.1109/TKDE.2024.3402234, 2024.
Yuyang Ye, Zheng Dong, Hengshu Zhu, Tong Xu, Xin Song, Runlong Yu, Hui Xiong. MANE: Organizational Network Embedding with Multiplex Attentive Neural Networks. IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), v 35, n 4, pages 4047-4061, 2023.
Huijie Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Chunli Liu, Minglei Li, Qi Liu, Enhong Chen. A Hierarchical Interactive Multi-channel Graph Neural Network for Technological Knowledge Flow Forecasting, Knowledge and Information Systems (KAIS), v 64, n 7, pages 1723-1757, 2022.
Qixiang Shao, Runlong Yu, Hongke Zhao, Chunli Liu, Mengyi Zhang, Hongmei Song, Qi Liu. Toward Intelligent Financial Advisors for Identifying Potential Clients: A Multitask Perspective, Big Data Mining and Analytics (BDMA), v 5, n 1, pages 64-78, 2022.
Conference Articles:
Runlong Yu*, Shengyu Chen*, Yiqun Xie, Xiaowei Jia. A Survey of Foundation Models for Environmental Science, Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), accepted, to be published, 2025. (*equal contribution) Accepted to Data Science: Foundations and Applications (DSFA) Session
Runlong Yu, Yiqun Xie, Xiaowei Jia. What We Talk About When We Talk About AI for Science, SIAM International Conference on Data Mining (SDM), accepted, to be published, 2025.
Runlong Yu, Chonghao Qiu, Robert Ladwig, Paul Hanson, Yiqun Xie, Xiaowei Jia. Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science, AAAI Conference on Artificial Intelligence (AAAI), accepted, to be published, 2025.
Runlong Yu, Chonghao Qiu, Robert Ladwig, Paul C. Hanson, Yiqun Xie, Yanhua Li, Xiaowei Jia. Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations, IEEE International Conference on Data Mining (ICDM), pages 580-589, 2024.
Runlong Yu, Robert Ladwig, Xiang Xu, Peijun Zhu, Paul C. Hanson, Yiqun Xie, Xiaowei Jia. Evolution-based Feature Selection for Predicting Dissolved Oxygen Concentrations in Lakes, International Conference on Parallel Problem Solving from Nature (PPSN), pages 398-415, 2024.
Runlong Yu, Xiang Xu, Yuyang Ye, Qi Liu, Enhong Chen. Cognitive Evolutionary Search to Select Feature Interactions for Click-Through Rate Prediction, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pages 3151-3161, 2023.
Runlong Yu, Qi Liu, Yuyang Ye, Mingyue Cheng, Enhong Chen, Jianhui Ma. Collaborative List-and-Pairwise Filtering from Implicit Feedback (Extended Abstract), IEEE International Conference on Data Engineering (ICDE), pages 3801-3802, 2023.
Runlong Yu, Yuyang Ye, Qi Liu, Zihan Wang, Chunfeng Yang, Yucheng Hu, Enhong Chen. XCrossNet: Feature Structure-Oriented Learning for Click-Through Rate Prediction, Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pages 436-447, 2021.
Runlong Yu, Yunzhou Zhang, Yuyang Ye, Le Wu, Chao Wang, Qi Liu, Enhong Chen. Multiple Pairwise Ranking with Implicit Feedback, ACM Conference on Information and Knowledge Management (CIKM), pages 1727-1730, 2018.
Yiming Sun, Runlong Yu, Runxue Bao, Yiqun Xie, Ye Ye, Xiaowei Jia. Domain-Adaptive Continual Meta-Learning for Modeling Dynamical Systems: An Application in Environmental Ecosystems, SIAM International Conference on Data Mining (SDM), accepted, to be published, 2025.
Yingda Fan, Runlong Yu, Janet Rice Barclay, Alison P. Appling, Yiming Sun, Yiqun Xie, Xiaowei Jia. Multi-Scale Graph Learning for Anti-Sparse Downscaling, AAAI Conference on Artificial Intelligence (AAAI), accepted, to be published, 2025.
Yuyang Ye, Zhi Zheng, Yishan Shen, Tianshu Wang, Hengruo Zhang, Peijun Zhu, Runlong Yu, Kai Zhang, Hui Xiong. Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation, AAAI Conference on Artificial Intelligence (AAAI), accepted, to be published, 2025.
Xiang Xu, Hao Wang, Wei Guo, Luankang Zhang, Wanshan Yang, Runlong Yu, Yong Liu, Defu Lian, Enhong Chen. Multi-granularity Interest Retrieval and Refinement Network for Long-Term User Behavior Modeling in CTR Prediction, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), accepted, to be published, 2025.
Yin Gu, Kai Zhang, Qi Liu, Runlong Yu, Xin Lin, Xinjie Sun. ProCC: Programmatic Reinforcement Learning for Efficient and Transparent TCP Congestion Control, ACM International Conference on Web Search and Data Mining (WSDM), accepted, to be published, 2025.
Yuyang Ye, Lu-An Tang, Haoyu Wang, Runlong Yu, Wenchao Yu, Erhu He, Haifeng Chen, Hui Xiong. PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pages 6148-6157, 2024.
Yujie Chen, Runlong Yu, Qi Liu, Enhong Chen, Zhenya Huang. Using Entropy for Group Sampling in Pairwise Ranking from Implicit Feedback, International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pages 2496-2500, 2023.
Xiaojie Li, Runlong Yu, Guiquan Liu, Lei Chen, Enhong Chen, Shengjun Liu. Research on Multi-objective Optimization Algorithm for Coal Blending, China National Conference on Big Data and Social Computing (BDSC), pages 37-60, 2023.
Yang Yu, Qi Liu, Likang Wu, Runlong Yu, Lei Yu, Zaixi Zhang. Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense, AAAI Conference on Artificial Intelligence (AAAI), pages 4854-4863, 2023.
Zhikang Mo, Qixiang Shao, Likang Wu, Runlong Yu, Jiexin Xu, Hongmei Song, Enhong Chen. TGNN: A GNN-Based Method with Multi-entity Node for Personal Banking Time Prediction, Intelligent Networked Things: 5th China Conference (CINT), pages 68-79, 2023.
Yuren Zhang, Enhong Chen, Binbin Jin, Hao Wang, Min Hou, Wei Huang, Runlong Yu. Clustering based Behavior Sampling with Long Sequential Data for CTR Prediction, International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pages 2195-2200, 2022.
Zheng Gong, Shiwei Tong, Han Wu, Qi Liu, Hanqing Tao, Wei Huang, Runlong Yu. Tipster: A Topic-Guided Language Model for Topic-Aware Text Segmentation, International Conference on Database Systems for Advanced Applications (DASFAA), pages 213-221, 2022.
Huijie Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Chunli Liu, Qi Liu, Enhong Chen. Technological Knowledge Flow Forecasting through A Hierarchical Interactive Graph Neural Network, IEEE International Conference on Data Mining (ICDM), pages 389-398, 2021.
Mingyue Cheng, Fajie Yuan, Qi Liu, Shenyang Ge, Zhi Li, Runlong Yu, Defu Lian, Senchao Yuan, Enhong Chen. Learning Recommender Systems with Implicit Feedback via Soft Target Enhancement, International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), pages 575-584, 2021.
Shiwei Tong, Qi Liu, Runlong Yu, Wei Huang, Zhenya Huang, Zachary A Pardos, Weijie Jiang. Item Response Ranking for Cognitive Diagnosis, International Joint Conference on Artificial Intelligence (IJCAI), pages 1750-1756, 2021.
Yuyang Ye, Hengshu Zhu, Tong Xu, Fuzhen Zhuang, Runlong Yu, Hui Xiong. Identifying High Potential Talent: A Neural Network based Dynamic Social Profiling Approach, IEEE International Conference on Data Mining (ICDM), pages 718-727, 2019.
Mingyue Cheng, Runlong Yu, Qi Liu, Vincent W. Zheng, Hongke Zhao, Hefu Zhang, Enhong Chen. Alpha-Beta Sampling for Pairwise Ranking in One-Class Collaborative Filtering, IEEE International Conference on Data Mining (ICDM), pages 1000-1005, 2019.
Han Wu, Kun Zhang, Guangyi Lv, Runlong Yu, Weihao Zhao, Enhong Chen, Jianhui Ma. Deep Technology Tracing for High-tech Companies, IEEE International Conference on Data Mining (ICDM), pages 1396-1401, 2019.
Xianfeng Liang, Likang Wu, Joya Chen, Yang Liu, Runlong Yu, Min Hou, Han Wu, Yuyang Ye, Qi Liu, Enhong Chen. Long-term Joint Scheduling for Urban Traffic, KDD CUP, 2019.
Books & Chapters:
Tong Xu, Runlong Yu. Epidemic Prevention and Control Big Data Cloud Platform: Solutions for Major Public Health Emergencies, Annual Report on Development of Big Data Applications in China No.4 (2020) (Blue Book of Big Data Applications), Social Sciences Academic Press, ISBN 978-7-5201-7651-4, 2020. (in Chinese)
Selected Patents
Enhong Chen, Qi Liu, Runlong Yu, Mingyue Cheng, Yuyang Ye, Multiple pairwise personalized recommenders, CN109299370B, authorized.
Enhong Chen, Qi Liu, Runlong Yu, Mingyue Cheng, Yuyang Ye, Recommendation methods for products of interest to users, CN109934681B, authorized.
Enhong Chen, Qi Liu, Runlong Yu, Yuyang Ye, Negatively correlated search with asymmetry, CN110263906B, authorized.
Enhong Chen, Qi Liu, Runlong Yu, Yuyang Ye, Han Wu, Zhi Li, Ruijun Sun, Legal information recommendation method and device, storage medium and electronic equipment, CN109684470B, authorized.
Enhong Chen, Tong Xu, Runlong Yu, Han Wu, Zhi Li, Qiming Hao, Zhi Zheng, Epidemic forecasting method and device, CN112652403B, authorized.
Qi Liu, Enhong Chen, Han Wu, Kun Zhang, Guangyi Lv, Runlong Yu, Weihao Zhao, Jianhui Ma, Deep technology tracing for high-tech companies, CN110580261B, authorized.
Enhong Chen, Qi Liu, Zhikang Mo, Qixiang Shao, Likang Wu, Runlong Yu, Jiexin Xu, Hongmei Song, A GNN-based method for queuing time prediction in bank outlets, CN115640906A, substantively examined.
Enhong Chen, Yuren Zhang, BinBin Jin, Hao Wang, Min Hou, Runlong Yu. Method for product click-through rate determining, CN115018552A, substantively examined.
Enhong Chen, Qi Liu, Qixiang Shao, Runlong Yu, Mengyi Zhang, Hongmei Song, Intelligent financial management method to automatically identify potential customers, CN114297477A, substantively examined.
Huijie Liu, Enhong Chen, Qi Liu, Han Wu, Le Zhang, Runlong Yu, Ye Liu, Methods for predicting future technological knowledge flows, CN113989075A, substantively examined.
Enhong Chen, Qi Liu, Xianfeng Liang, Likang Wu, Zhuo Chen, Yang Liu, Runlong Yu, Min Hou, Han Wu, Yuyang Ye, A joint dispatch method based on urban public transportation resources, CN112417753A, substantively examined.
Invited Talks
[Aug. 2024] Adaptive Process-Guided Learning: An Application in Predicting Lake DO Concentrations in the KGML 2024 workshop, Minneapolis, MN, USA.
[Aug. 2023] Cognitive Evolutionary Search to Select Feature Interactions for Click-Through Rate Prediction in the KDD 2023 conference, Long Beach, CA, USA.
[May 2021] XCrossNet: Feature Structure-Oriented Learning for Click-Through Rate Predictions in the PAKDD 2021 conference, Delhi, India.
[Aug. 2019] Negatively Correlated Search with Asymmetry for Real-Parameter Optimization Problems in the CCFAI 2019 conference, Xuzhou, China.
Academic Services
Program Committee Member for the following conferences:
- WWW2025, AAAI2025, IJCAI2025, PAKDD2025, AAAI2024, IJCAI2024, AAAI2023, IJCAI2023, AAAI2022, IJCAI2022, AAAI2021, IJCAI2021, etc.
Reviewer for the following conferences:
- ICML2025, AISTATS 2025, ICLR2025, NeurIPS2024, ICLR2024, ICML2024, NeurIPS2023, ICML2023, NeurIPS2022, ICML2022, etc.
Reviewer for the following journals:
- IEEE Trans. KDE, IEEE Trans. BigData, ACM Trans. KDD, ACM Trans. RecSys, IEEE Trans. SMC: Systems, Communications of the ACM, Advanced Science, etc.
