Zhenya Huang  (黄振亚)


Ph.D, Associate Professor

School of Computer Science and Technology,    School of Arificial Intelligence and Data Science
University of Science and Technology of China (USTC)
State Key Laboratory of Cognitive Intelligence
Research Group: BASE Group (Bigdata and Artificial intelligence for Science and Education)

Email: huangzhy@ustc.edu.cn;   zheny.huang@gmail.com
Office: Room C309, No.1 Academic Building (1号学科楼), High-Tech Campus, USTC, Hefei, Anhui, China.
Lab: Room B708, Information&Intellgence Building (信智大楼), High-Tech Campus, USTC, Hefei, Anhui, China.

Biography

I am an Associate Professor at the School of Computer Science and Technology, University of Science and Technology of China (USTC), and a member of the BASE Group of the State Key Laboratory of Cognitive Intelligence.  
I received my Ph.D. in Applied Computer Technology from the Unversity of Science and Technology of China in July, 2020, co-supervised by Prof. Enhong Chen and Prof. Qi Liu, and received my Bachelor degree in Software Engineering from Shandong University in July, 2014.
In 2018-2019, I visited the TIMAN Group at the University of Illinois at Urbana-Champaign (UIUC), working with Prof. Chengxiang Zhai.

Research Interests

My general research interests include Data Mining and Knowledge Discovery, Artificial Intelligence. The main goal is to study how to learn, analyze and organize knowledge from data, as well as designing intelligent systems to help people manage and apply big data and knowledge for improving the service of real-world applications.

Education

Experience

Honors

Teaching

Selected Publications

[Google Scholar]    [DBLP]

( *, Corresponding author )

  1. Jiayu Liu, Zhenya Huang*, Qi Liu, Zhiyuan Ma, Chengxiang Zhai, Enhong Chen, Knowledge-Centered Dual-Process Reasoning for Math Word Problems with Large Language Models, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2025. accepted. [LINK]
  2. Zhiyuan Ma, Zhenya Huang*, Jiayu Liu, Minmao Wang, Hongke Zhao, Xin Li, Automated Creation of Reusable and Diverse Toolsets for Enhancing LLM Reasoning, The 39th Annual AAAI Conference on Artificial Intelligence (AAAI'2025): 24821-24830, Philadelphia, Pennsylvania, USA, February 25 – March 4, 2025. [PDF] [SLIDE] [CODE]
  3. Yuze Zhao, Tianyun Ji, Wenjun Feng, Zhenya Huang*, Qi Liu, Zhiding Liu, Yixiao Ma, Kai Zhang, Enhong Chen, Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment, The Thirteenth International Conference on Learning Representations (ICLR'2025), Singapore, April 24 – April 28th, 2025. [PDF] [POSTER] [CODE]
  4. Xin Xu, Tong Xiao, Zitong Chao, Zhenya Huang*, Can Yang*, Yang Wang, Can LLMs Solve Longer Math Word Problems Better?, The Thirteenth International Conference on Learning Representations (ICLR'2025), Singapore, April 24 – April 28th, 2025. [PDF] [POSTER] [CODE]
  5. Yanmin Dong, Zhenya Huang*, Zheng Zhang, Guanhao Zhao, Likang Wu, Hongke Zhao, Binbin Jin, Qi Liu, Enhancing Code Search Intent with Programming Context Exploration, The 18th International Conference on Web Search and Data Mining (WSDM'2025):596-605, Hannover, Germany, March 10-14, 2025. [PDF] [POSTER] [CODE]
  6. Xin Lin, Zhenya Huang, Zhiqiang Zhang, Jun Zhou, Enhong Chen, Explore What LLM Does not Know in Complex Question Answering, The 39th Annual AAAI Conference on Artificial Intelligence (AAAI'2025):24585-24594, Philadelphia, Pennsylvania, USA, February 25 – March 4, 2025. [PDF] [SLIDE] [CODE]
  7. Guanhao Zhao, Zhenya Huang, Cheng Cheng, Yan Zhuang, Qingyang Mao, Xin Li, Shijin Wang, Enhong Chen, Multi-Perspective Consolidation Enhanced Cognitive Diagnosis via Conditional Diffusion Model, The 39th Annual AAAI Conference on Artificial Intelligence (AAAI'2025):1174-1182, Philadelphia, Pennsylvania, USA, February 25 – March 4, 2025. [PDF] [POSTER] [CODE]

  1. Jiayu Liu, Zhenya Huang*, Tong Xiao, Jing Sha, Jinze Wu, Qi Liu, Shijin Wang, Enhong Chen*, SocraticLM: Exploring Socratic Personalized Teaching with Large Language Models, The 38th Annual Conference on Neural Information Processing Systems (NeurIPS'2024, Spotlight):85693-85721, Vancouver, Canada, December 10-15, 2024. [PDF] [DATA & CODE] [解读说明]
  2. Shangzi Xue, Zhenya Huang*, Jiayu Liu, Xin Lin, Yuting Ning, Binbin Jin, Xin Li, Qi Liu, Decompose, Analyze and Rethink: Solving Intricate Problems with Human-like Reasoning Cycle, The 38th Annual Conference on Neural Information Processing Systems (NeurIPS'2024, Oral): 357-385, Vancouver, Canada, December 10-15, 2024. [PDF] [SLIDE] [CODE]
  3. Guanhao Zhao, Zhenya Huang*, Yan Zhuang, Haoyang Bi, Yiyan Wang, Fei Wang, Zhiyuan Ma, Yixia Zhao, A Diffusion-Based Cognitive Diagnosis Framework for Robust Learner Assessment, IEEE Transactions on Learning Technologies (IEEE TLT), vol.17, pp.2227-2241, 2024. [PDF]
  4. Xin Lin, Tianhuang Su, Zhenya Huang*, Shangzi Xue, Haifeng Liu, Enhong Chen, A Knowledge-Injected Curriculum Pretraining Framework for Question Answering, The ACM Web Conference 2024 (WWW'2024):1986-1997, Singapore, May 13-17, 2024. [PDF] [POSTER]
  5. Haotian Zhang, Shuanghong Shen, Bihan Xu, Zhenya Huang*, Jinze Wu, Jing Sha, Shijin Wang, Item-Difficulty-Aware Learning Path Recommendation: From a Real Walking Perspective, The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2024):4167-4178, Barcelona, Spain, August 24-29, 2024. [PDF] [SLIDE] [POSTER]
  6. Yuze Zhao, Zhenya Huang*, Yixiao Ma, Rui Li, Kai Zhang, Hao Jiang, Qi Liu, Jinze Wu, Jing Sha, Shijin Wang, RePair: Automated Program Repair with Process-based Feedback, Findings of the 61th annual meeting of the Association for Computational Linguistics (ACL'2024-Findings):16415-16429, Bangkok, Thailand, August 11-16, 2024. [PDF] [POSTER] [DATA & CODE]
  7. Shangzi Xue, Zhenya Huang*, Xin Lin, Jiayu Liu, Longhu Qin, Tianhuang Su, Haifeng Liu, Qi Liu, Enhancing the Completeness of Rationales for Multi-Step Question Answering, The 33rd ACM International Conference on Information and Knowledge Management (CIKM'2024):2753-2763, Boise, Idaho, USA, October 21-25, 2024. [PDF] [SLIDE] [CODE]
  8. Cheng Cheng, Guanhao Zhao, Zhenya Huang*, Yan Zhuang, Zhaoyuan Pan, Qi Liu, Xin Li, Enhong Chen, Towards Explainable Computerized Adaptive Testing with Large Language Model, The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP'2024-Findings):2655-2672, Miami, Florida, November 12-16, 2024. [PDF]
  9. Tong Xiao, Jiayu Liu, Zhenya Huang, Jinze Wu, Jing Sha, Shijin Wang, Enhong Chen, Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning Process, The International Joint Conference on Artificial Intelligence (IJCAI'2024):6559-6568, Jeju, August 03-09, 2024. [PDF] [SLIDE] [CODE]
  10. Liyang He, Zhenya Huang, Chenglong Liu, Rui Li, Runze Wu, Qi Liu, Enhong Chen, One-bit Deep Hashing: Towards Resource-Efficient Hashing Model with Binary Neural Network, ACM MULTIMEDIA 2024 (ACM MM'2024): 7162-7171, Melbourne, Australia, October 28-November 1, 2024. [PDF] [POSTER]
  11. Liyang He, Zhenya Huang, Jiayu Liu, Enhong Chen, Fei Wang, Jing Sha, Shijin Wang, Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing, The ACM Web Conference 2024 (WWW'2024):1395-1406, Singapore, May 13-17, 2024. [PDF] [POSTER]
  12. Jiatong Li, Qi Liu, Fei Wang, Jiayu Liu, Zhenya Huang, Fangzhou Yao, Linbo Zhu, Yu Su, Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm, The ACM Web Conference 2024 (WWW'2024):3420-3431, Singapore, May 13-17, 2024. [PDF] [POSTER]
  13. Zheng Zhang, Qi Liu, Zirui Hu, Yi Zhan, Zhenya Huang, Weibo Gao, Qingyang Mao, Enhancing Fairness in Meta-learned User Modeling via Adaptive Sampling, The ACM Web Conference 2024 (WWW'2024):3241-3252, Singapore, May 13-17, 2024. [PDF]

  1. Zhenya Huang, Binbin Jin, Hongke Zhao, Qi Liu, Defu Lian, Tengfei Bao, Enhong Chen, Personal or General? A Hybrid Strategy with Multi-factors for News Recommendation, ACM Transactions on Information Systems (ACM TOIS), 41(2), Article 44, April, 2023. [Link] [PDF]
  2. Liyang He, Zhenya Huang*, Enhong Chen, Qi Liu, Shiwei Tong, Hao Wang, Defu Lian, Shijin Wang, An Efficient and Robust Semantic Hashing Framework for Similar Text Search, ACM Transactions on Information Systems (ACM TOIS), 41(4), Article 91, March, 2023 [Link] [PDF]
  3. Xin Lin, Zhenya Huang*, Hongke Zhao, Enhong Chen*, Qi Liu, Defu Lian, Xin Li, Hao Wang, Learning Relation-Enhanced Hierarchical Solver for Math Word Problems, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2023, Accepted. [Link]
  4. Jiayu Liu, Zhenya Huang*, Zhiyuan Ma, Qi Liu, Enhong Chen*, Tianhuang Su, Haifeng Liu, Guiding Mathematical Reasoning via Mastering Commonsense Formula Knowledge, The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2023): 1477–1488, Long Beach, CA, USA, August 6-10, 2023. [PDF] [SLIDE] [DATA & CODE]
  5. Bihan Xu, Zhenya Huang*, Jiayu liu, Shuanghong Shen, Qi Liu, Enhong Chen, Jinze Wu, Shijin Wang, Learning Behavior-oriented Knowledge Tracing, The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2023): 2789-2800, Long Beach, CA, USA, August 6-10, 2023. [PDF] [SLIDE]
  6. Jiayu Liu, Zhenya Huang*, Chengxiang Zhai, Qi Liu, Learning by Applying: A General Framework for Mathematical Reasoning via Enhancing Explicit Knowledge Learning, The 36th AAAI Conference on Artificial Intelligence (AAAI'2023): 4497-4506, WashingTon, DC, USA, Feb.7-14, 2023. [PDF] [SLIDE] [DATA & CODE]
  7. Longhu Qin, Jiayu Liu, Zhenya Huang*, Kai Zhang, Qi Liu, Binbin Jin, Enhong Chen, A Mathematical Word Problem Generator with Structure Planning and Knowledge Enhancement, The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2023): 1780-1784, Taipei, Taiwan, China, July 23-27, 2023. [PDF] [SLIDE]
  8. Guanhao Zhao, Zhenya Huang*, Yan Zhuang, Jiayu Liu, Qi Liu, Zhiding Liu, Jinze Wu, Enhong Chen, Simulating Student Interactions with Two-stage Imitation Learning for Intelligent Educational Systems, The 32nd ACM International Conference on Information and Knowledge Management (CIKM'2023): 3423-3432, Birmingham, UK, Oct. 21-25, 2023. [PDF] [SLIDE] [CODE]
  9. Fei Wang, Zhenya Huang, Qi Liu, Enhong Chen, Yu Yin, Jianhui Ma, Shijin Wang, Dynamic Cognitive Diagnosis: An Educational Priors-Enhanced Deep Knowledge Tracing Perspective, IEEE Transactions on Learnning Technologies (IEEE TLT), 16(3): 306-323, 2023. [Link] [PDF]
  10. Likang Wu, Hongke Zhao, Zhi Li, Zhenya Huang, Qi Liu, Enhong Chen, Learning the Explainable Semantic Relations via Unified Graph Topic-Disentangled Neural Networks, ACM Transactions on Knowledge Discovery from Data (ACM TKDD), Volume 17, Issue 8, Article 110, 2023, Accepted. [Link] [PDF]
  11. Ye Liu, Han Wu, Zhenya Huang, Hao Wang, Yuting Ning, Jianhui Ma, Qi Liu, Enhong Chen, TechPat: Technical Phrase Extraction for Patent Mining, ACM Transactions on Knowledge Discovery from Data (ACM TKDD), Volume 17, Issue 9, Article 129: 1–31, 2023. [Link] [PDF]
  12. Ye Liu, Kai Zhang, Zhenya Huang, Kehang Wang, Yanghai Zhang, Qi Liu, Enhong Chen, Enhancing Hierarchical Text Classification through Knowledge Graph Integration, Findings of the 61th annual meeting of the Association for Computational Linguistics (ACL'2023-Findings): 5797-5808, Toronto, Canada, July 9-14, 2023. [PDF] [SLIDE]
  13. Yan Zhuang, Qi Liu, GuanHao Zhao, Zhenya Huang, Weizhe Huang, Zachary Pardos, Enhong Chen, Jinze Wu, Xin Li, A Bounded Ability Estimation for Computerized Adaptive Testing, Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS'2023), New Orleans, USA, December 10-16, 2023. [PDF] [SLIDE]
  14. Zhiding Liu, Mingyue Cheng, Zhi Li, Zhenya Huang, Qi Liu, Yanhu Xie, Enhong Chen, Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective, Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS'2023), New Orleans, USA, December 10-16, 2023. [PDF] [SLIDE]
  15. Yuting Ning, Zhenya Huang, Xin Lin, Enhong Chen, Shiwei Tong, Zheng Gong, Shijin Wang, Towards a Holistic Understanding of Mathematical Questions with Contrastive Pre-training, The 36th AAAI Conference on Artificial Intelligence (AAAI'2023) 13409-13418, WashingTon, DC, USA, Feb.7-14, 2023. [PDF] [SLIDE]
  16. Yu Yin, Le Dai, Zhenya Huang, Shuanghong Shen, Fei Wang, Qi Liu, Enhong Chen, Xin Li, Tracking Knowledge Instead of Patterns: Stable Knowledge Tracing with Diagnostic Transformer, The Web Conference 2023 (WWW'2023): 855-864, Austin, Texas, USA, April 30-May 4, 2023. [PDF] [SLIDE] [CODE]
  17. Yin Gu, Kai Zhang, Qi Liu, Xin Lin, Zhenya Huang, Enhong Chen, Xin Li, MassNE: Exploring Higher-Order Interactions with Marginal Effect for Massive Battle Outcome Prediction, The Web Conference 2023 (WWW'2023): 2710-2718, Austin, Texas, USA, April 30-May 4, 2023. [PDF] [SLIDE]

  1. Qi Liu, Jinze Wu, Zhenya Huang*, Hao Wang, Yuting Ning, Ming Chen, Enhong Chen. Federated User Modeling from Hierarchical Information, ACM Transactions on Information Systems (ACM TOIS), 41(2), Article 46, April, 2023. [Link] [PDF]
  2. Jiayu Liu, Zhenya Huang*, Xin Lin, Qi Liu, Jianhui Ma, Enhong Chen, A Cognitive Solver with Autonomously Knowledge Learning for Reasoning Mathematical Answers, The 22nd IEEE International Conference on Data Mining (ICDM'2022): 269-278, Orlando, FL, USA, November 28-December 1, 2022. [PDF] [SLIDE] [DATA & CODE]
  3. Jiatong Li, Fei Wang, Qi Liu, Mengxiao Zhu, Wei Huang, Zhenya Huang*, Enhong Chen, Yu Su, Shijin Wang, HierCDF: A Bayesian Network-based Hierarchical Cognitive Diagnosis Framework, The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2022): 904-913, Washington, DC, USA, August 14–18, 2022. [PDF] [SLIDE]
  4. Song Cheng, Qi Liu, Enhong Chen, Kai Zhang, Zhenya Huang*, Yu Yin, Xiaoqing Huang, Yu Su, AdaptKT: A Domain Adaptable Method for Knowledge Tracing, The 15th ACM Conference on Web Search and Data Mining (WSDM'2022): 123-131, Phoenix, AZ, USA, February 21-25, 2022. [PDF] [SLIDE]
  5. 黄振亚, 刘淇, 陈恩红, 林鑫, 何理扬, 刘嘉聿, 王士进, 面向学科题目的文本分析方法与应用研究综述, 中文信息学报, 36(10), 2022年10月. . [PDF]
  6. Fei Wang, Qi Liu, Enhong Chen, Zhenya Huang, Yu Yin, Shijin Wang, Yu Su, NeuralCD: A General Framework for Cognitive Diagnosis, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 35(8): 8312-8327, 2023. [Link] [PDF]
  7. Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen, Model Inversion Attacks against Graph Neural Networks, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), accepted, 2022 [Link]
  8. Leyan Deng, Defu Lian, Zhenya Huang, Enhong Chen, Graph Convolutional Adversarial Networks for Spatiotemporal Anomaly Detection, IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 33(6): 2416-2428, 2022. [Link] [PDF]
  9. Jiayu Liu, Fei Wang, Haiping Ma, Zhenya Huang, Qi Liu, Enhong Chen, Yu Su, A Probabilistic Framework for Temporal Cognitive Diagnosis in Online Learning Systems, Journal of Computer Science and Technology (JCST), 2022. [Link] [PDF]
  10. Shiwei Tong, Jiayu Liu, yuting Hong, Zhenya Huang, Le Wu, Qi Liu, Wei Huang, Enhong Chen, Dan Zhang, Incremental Cognitive Diagnosis for Intelligent Education, The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2022): 1760-1770, Washington, DC, USA, August 14–18, 2022. [PDF] [SLIDE]
  11. Shuanghong Shen, Zhenya Huang, Qi Liu, Yu Su, Shijin Wang, and Enhong Chen, Assessing Student’s Dynamic Knowledge State by Exploring the Question Difficulty Effect, The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’2022): 427-437, Madrid, Spain, July 11-15, 2022. [PDF] [SLIDE]
  12. Kai Zhang, Qi Liu, Zhenya Huang, Mengdi Zhang, Kun Zhang, Mingyue Cheng, Wei Wu, Enhong Chen, Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification, The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’2022): 1566-1576, Madrid, Spain, July 11-15, 2022. [PDF] [SLIDE]
  13. Yan Zhuang, Qi Liu, Zhenya Huang, Zhi Li, Binbin Jin, Haoyang Bi, Enhong Chen, and Shijin Wang, A Robust Computerized Adaptive Testing Approach in Educational Question Retrieval, The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’2022): 416-426, Madrid, Spain, July 11-15, 2022. [PDF] [SLIDE]
  14. Yan Zhuang, Qi Liu, Zhenya Huang, Zhi Li, Shuanghong Shen, Haiping Ma, Fully Adaptive Framework: Neural Computerized Adaptive Testing for Online Education, The 36th AAAI Conference on Artificial Intelligence (AAAI'2022), Virtual Conference, February 22-March 1, 2022. [PDF] [SLIDE]

  1. Qi Liu, Shuanghong Shen, Zhenya Huang, Enhong Chen, Yonghe Zheng A Survey of Knowledge Tracing, arXiv version, 2021. [Link]
  2. Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen, Hui Xiong, Yu Su, Guoping Hu, EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 33(1): 100-115, January, 2021. (ESI Highly Cited Paper). [PDF] [SLIDE] [CODE]
  3. Zhenya Huang, Xin Lin, Hao Wang, Qi Liu, Enhong Chen, Jianhui Ma, Yu Su, Wei Tong, DisenQNet: Disentangled Representation Learning for Educational Questions, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2021): 696-704, Virtual Conference, August 14-18, 2021. [PDF] [SLIDE] [POSTER]
  4. Xin Lin, Zhenya Huang*, Hongke Zhao, Enhong Chen, Qi Liu, Hao Wang, Shijin Wang, HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem, The 35th AAAI Conference on Artificial Intelligence (AAAI'2021): 4232-4240, Virtual Conference, February 2-9, 2021. [PDF] [SLIDE] [CODE]
  5. Songtao Fang, Zhenya Huang*, Ming He, Shiwei Tong, Xiaoqing Huang, Ye Liu, Jie Huang, Qi Liu, Guided Attention Network for Concept Extraction, The 30th International Joint Conference on Artificial Intelligence (IJCAI'2021): 1449-1455, Virtual Conference, August 21-26, 2021. [PDF] [SLIDE]
  6. Ye Huang, Wei Huang, Shiwei Tong, Zhenya Huang*, Qi Liu, Enhong Chen, Jianhui Ma, Liang Wan, Shijin Wang, STAN: Adversarial Network for Cross-domain Question Difficulty Prediction, The 21st IEEE International Conference on Data Mining (ICDM'2021): 220-229, Auckland, New Zealand, December 7-10, 2021. [PDF] [SLIDE]
  7. Binbin Jin, Enhong Chen, Hongke Zhao, Zhenya Huang, Qi Liu, Hengshu Zhu, Shui Yu, Promotion of Answer Value Measurement with Domain Effects in Community Question Answering Systems, IEEE Transactions on Systems, Man and Cybernetics: Systems (IEEE TSMC-S), 51(5), May 2021. [PDF]
  8. Shuanghong Shen, Enhong Chen, Qi Liu, Zhenya Huang, Wei Huang, Yu Yin, Yu Su, Shijin Wang, Learning Process-consistent Knowledge Tracing, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2021): 1452-1460, Virtual Conference, August 14-18, 2021. [PDF] [SLIDE] [POSTER]
  9. Yuqiang Zhou, Qi Liu, Jinze Wu, Fei Wang, Zhenya Huang, Wei Tong, Huixiong, Enhong Chen, Jianhui Ma, Modeling Context-aware Features for Cognitive Diagnosis in Student Learning, The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2021): 2420-2428, Virtual Conference, August 14-18, 2021. [PDF] [SLIDE] [POSTER]
  10. Li Wang, Binbin Jin, Zhenya Huang, Hongke Zhao, Defu Lian, Qi Liu, Enhong Chen, Preference-Adaptive Meta-Learning for Cold-Start Recommendation, The 30th International Joint Conference on Artificial Intelligence (IJCAI'2021): 1607-1614, Virtual Conference, August 21-26, 2021. [PDF] [SLIDE]
  11. Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, Enhong Chen, GraphMI: Extracting Private Graph Data from Graph Neural Networks, The 30th International Joint Conference on Artificial Intelligence (IJCAI'2021): 3749-3755, Virtual Conference, August 21-26, 2021. [PDF] [SLIDE]
  12. Shiwei Tong, Qi Liu, Runlong Yu, Wei Huang, Zhenya Huang, Zachary Pardos, Weijie Jiang, Item Response Ranking for Cognitive Diagnosis, The 30th International Joint Conference on Artificial Intelligence (IJCAI'2021): 1750-1756, Virtual Conference, August 21-26, 2021. [PDF] [SLIDE]
  13. Weibo Gao, Qi Liu, Zhenya Huang, Yu Yin, Haoyang Bi, Mu Chun Wang, Jianhui Ma, Shijin Wang, Yu Su, RCD: Relation Map Driven Cognitive Diagnosis for Intelligent Education Systems, The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2021): 501-510, Virtual Conference, July 11-15, 2021. [PDF] [SLIDE]
  14. Jinze Wu, Qi Liu, Zhenya Huang, Yuting Ning, Hao Wang, Enhong Chen, Jinfeng Yi and Bowen Zhou, Hierarchical Personalized Federated Learning for User Modeling, The 30th International World Wide Web Conference (WWW'2021): 957-968, Ljubljana, Slovenia, April 19-23 2021. [PDF] [SLIDE]
  15. Yin Gu, Qi Liu, Kai Zhang, Zhenya Huang, Runze Wu, Jianrong Tao, NeuralAC: Learning Cooperation and Competition Effects for Match Outcome Prediction, The 35th AAAI Conference on Artificial Intelligence (AAAI'2021): 4072-4080, Virtual Conference, February 2-9, 2021. [PDF] [SLIDE]
  16. Jinze Wu, Zhenya Huang, Qi Liu, Defu Lian, Hao Wang, Enhong Chen, Haiping Ma and Shijin Wang, Federated Deep Knowledge Tracing, The 14th ACM Conference on Web Search and Data Mining (WSDM'2021): 662-670, Jerusalem, Israel, March 8-12 2021. [PDF] [SLIDE]
  17. Siqi Lei, Wei Huang, Shiwei Tong, Qi Liu, Zhenya Huang, Enhong Chen, Yu Su, Consistency-aware Multi-modal Network for Hierarchical Multi-label Classification in Online Education System, The 12th IEEE Internaltional Conference on Big Knowledge (ICBK'2021): 426-433. (Best Student Paper) [PDF]

  1. Zhenya Huang, Qi Liu, Yuying Chen, Le Wu, Keli Xiao, Enhong Chen, Haiping Ma, Guoping Hu, Learning or Forgetting? A Dynamic Approach for Tracking the Knowledge Proficiency of Students, ACM Transactions on Information Systems (ACM TOIS), 38(2), Article 19, February 2020. [PDF] [SLIDE] [CODE]
  2. Zhenya Huang, Qi Liu, Weibo Gao, Jinze Wu, Yu Yin, Hao Wang, Enhong Chen, Neural Mathematical Solver with Enhanced Formula Structure, The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2020): 1729-1732, Xi'an, China, July 25-30, 2020. [PDF] [SLIDE]
  3. Haoyang Bi, Haiping Ma, Zhenya Huang*, Yu Yin, Qi Liu, Enhong Chen, Yu Su, Shijin Wang, Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing, The 20th IEEE International Conference on Data Mining (ICDM'2020): 42-51, Sorrento, Italy, November 17-20 2020. [PDF][SLIDE]
  4. Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu, Enhong Chen, Cheekong Lee, ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction, The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2020): 731-739, San Diego, CA, USA, August 23-27 2020. [PDF] [SLIDE] [CODE]
  5. Fei Wang, Qi Liu, Enhong Chen, Zhenya Huang, Yuying Chen, Yu Yin, Zai Huang, Shijin Wang, Neural Cognitive Diagnosis for Intelligent Education Systems, The 34th AAAI Conference on Artificial Intelligence (AAAI'2020): 6153-6161, New York, USA, February 7-12 2020. [PDF][SLIDE][CODE]
  6. Xin Wang, Wei Huang, Qi Liu, Yu Yin, Zhenya Huang, Le Wu, Jianhui Ma, Xue Wang, Fine-Grained Similarity Measurement between Educational Videos and Exercises, The 28th ACM International Conference on Multimedia (ACM MM'2020): 331-339, Seattle, USA, October 12-16 2020. [PDF] [SLIDE]
  7. Shuanghong Shen, Qi Liu, Enhong Chen, Han Wu, Zhenya Huang, Weihao Zhao, Yu Su, Haiping Ma, Shijin Wang, Convolutional Knowledge Tracing: Modeling Individualization in Student Learning Process, The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'2020): 1857-1860, Xi'an, China, July 25-30, 2020. [PDF] [SLIDE]
  8. Shiwei Tong, Qi Liu, Wei Huang, Zhenya Huang, Enhong Chen, Chuanren Liu, Haiping Ma, Shijin Wang, Structure-based Knowledge Tracing: An Influence Propagation View, The 20th IEEE International Conference on Data Mining (ICDM'2020): 541-550, Sorrento, Italy, November 17-20 2020.[PDF][SLIDE]

  1. Zhenya Huang, Qi Liu, Chengxiang Zhai, Yu Yin, Enhong Chen, Weibo Gao, Guoping Hu, Exploring Multi-Objective Exercise Recommendations in Online Education Systems, The 28th ACM International Conference on Information and Knowledge Management (CIKM’2019): 1261-1270, Beijing, China, November 3-7 2019. [PDF] [SLIDE] [POSTER]
  2. Yu Yin, Qi Liu, Zhenya Huang, Enhong Chen, Wei Tong, Shijin Wang, Yu Su, QuesNet: A Unified Representation for Heterogeneous Test Questions, The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’2019): 1328-1336, Anchorage, AK, USA, August 4-8 2019. [PDF] [SLIDE] [POSTER]
  3. Chengqiang Lu, Qi Liu, Chao Wang, Zhenya Huang, Peize Lin, Lixin He, Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective, The 33rd AAAI Conference on Artificial Intelligence (AAAI’2019): 1052-1060, Honolulu, USA, January 27-February 1 2019. [PDF] [SLIDE]

  4. Yu Yin, Zhenya Huang, Enhong Chen, Qi Liu, Fuzheng Zhang, Xing Xie, Guoping Hu, Transcribing Content from Structural Images with Spotlight Mechanism, The 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2018): 2643-2652, London, UK, August 19-23 2018. [PDF] [SLIDE] [POSTER]
  5. Qi Liu, Zai Huang, Zhenya Huang, Chuanren Liu, Enhong Chen, Yu Su, Guoping Hu, Finding Similar Exercises in Online Education Systems, The 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2018): 1821-1830, London, UK, August 19-23 2018. [PDF] [SLIDE] [POSTER]
  6. Zhi Li, Hongke Zhao, Qi Liu, Zhenya Huang, Tao Mei, Enhong Chen, Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors, The 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'2018): 1734-1743, London, UK, August 19-23 2018. [PDF] [POSTER]
  7. Yu Su, Qingwen Liu, Qi Liu, Zhenya Huang, Yu Yin, Enhong Chen, Chris Ding, Si Wei, Guoping Hu, Exercise-Enhanced Sequential Modeling for Student Performance Prediction, The 32nd AAAI Conference on Artificial Intelligence (AAAI'2018): 2435-2443, New Orleans, Louisiana, USA, February 2-7 2018. [PDF] [SLIDE]
  8. Chao Wang, Qi Liu, Runze Wu, Enhong Chen, Chuanren Liu, Xunpeng Huang, Zhenya Huang, Confidence-aware Matrix Factorization for Recommender Systems, The 32nd AAAI Conference on Artificial Intelligence (AAAI'2018): 434-442, New Orleans, Louisiana, USA, February 2-7 2018. [PDF] [POSTER]
  9. Tianyu Zhu, Qi Liu, Zhenya Huang, Enhong Chen, Defu Lian, Yu Su, Guoping Hu, MT-MCD: A Multi-task Cognitive Diagnosis Framework for Student Assessment, The 23rd International Conference on Database Systems for Advanced Applications (DASFAA'2018): 318-335, Gold Coast Australia, May 21-24 2018. [PDF]
  10. 王超, 刘淇, 陈恩红, 黄振亚, 朱天宇, 苏喻, 胡国平, 面向大规模认知诊断的DINA模型快速计算方法研究, 电子学报, 46(5):1047-1055, 2018年5月. [PDF]
  11. 刘淇, 陈恩红, 朱天宇, 黄振亚, 吴润泽, 苏喻, 胡国平, 面向在线智慧学习的教育数据挖掘技术研究, 模式识别与人工智能, 31(1): 77-90, 2018. [PDF] [link]

  12. Zhenya Huang, Qi Liu, Enhong Chen, Hongke Zhao, Mingyong Gao, Si Wei, Yu Su, Guoping Hu, Question Difficulty Prediction for READING Problems in Standard Tests, The 31st AAAI Conference on Artificial Intelligence (AAAI'2017): 1352-1359, San Francisco, California USA, February 4-9, 2017. [PDF] [SLIDE]
  13. Yuying Chen, Qi Liu, Zhenya Huang, Le Wu, Enhong Chen, Runze Wu, Yu Su, Guoping Hu, Tracking knowledge Proficiency of Students with Educational Priors, The 26th ACM International Conference on Information and Knowledge Management (CKIM'2017): 989-998, Singapore, November 6-10, 2017. [PDF] [SLIDE]
  14. 朱天宇, 黄振亚, 陈恩红，刘淇，吴润泽，吴乐，苏喻，陈志刚，胡国平, 基于认知诊断的个性化试题推荐方法, 计算机学报, 40(1): 176-191，2017年1月. [PDF]
  15. 刘淇, 陈恩红, 黄振亚, 苏喻, 胡国平, 面向个性化学习的学生认知能力分析, 中国计算机学会通讯, 13(4), 2017年4月. [link]

  16. Le Wu, Yong Ge, Qi Liu, Enhong Chen, Bai Long, Zhenya Huang, Modeling Users’ Preferences and Social Links in Social Networking Services: a Joint-Evolving Perspective, The 30th AAAI Conference on Artificial Intelligence (AAAI'2016): 279-286, Phoenix, Arizona USA, February 12-17, 2016. [PDF]
  17. 黄振亚, 苏喻, 吴润泽, 刘玉苹, 刘淇, 陈志刚, 胡国平, 一种面向教育评估的智能教育辅助平台, 中国科学技术大学学报, 45(10): 846-854, 2015年10月. [PDF] [link]

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