Biography

I am an Associate Researcher at the School of Computer Science and Technology, USTC. I am also affiliated with the State Key Laboratory of Cognitive Intelligence at the side of USTC, working under the leadership of Prof. Enhong Chen and Prof. Qi Liu. Previously, I obtained my Ph.D. degree under the supervision of Prof. Qi Liu.

Research Interests

My research focuses on structured data analysis and LLM-based reasoning & agents, with applications in AI for Science and Recommender Systems.

• Structured Data Mining: Building foundation models and agentic frameworks for time series, spatio-temporal, and tabular data — covering forecasting, classification, anomaly detection, and universal data representation.
• LLM-based Reasoning and Agent: Advancing LLM capabilities via reinforcement learning and training-free methods, toward autonomous agents with long-chain reasoning, memory, tool use, and multi-agent collaboration.
• AI for Science: Leveraging structured data mining and LLM agents for scientific discovery — including scientific table/time-series understanding, literature reasoning, and automated report generation.
• Recommender Systems: Context-aware personalized recommendation via sequential modeling, one-class collaborative filtering, and LLM-driven reasoning for dynamic user preference understanding.

Latest News

• [Mar. 2026] 🚀 We open-sourced TabClaw, an GitHub framework for agentic table reasoning, designed to enable LLM agents to understand, analyze, and interact with large-scale tabular data through structured reasoning and tool-augmented workflows.
• [Mar. 2026] 🚀 We open-sourced Claw-R1, an GitHub framework for agentic reinforcement learning, extending RL training environments for reasoning and tool-using LLM agents.
• [Feb. 2026] 🎉 We released a Position Paper on arXiv: "Beyond Model-Centric Prediction — Agentic Time Series Forecasting".
• [Jan. 2026] 🎉 Congratulations to Li Li on her paper being accepted to DASFAA 2026!
• [Jan. 2026] 🎉 Congratulations to Qingyang Mao and Zirui Liu on their paper being accepted to ICLR 2026!
• [Jan. 2026] 🎉 I will serve as a Senior Program Committee (SPC) member for IJCAI2026.
• [Jan. 2026] 🎉 Congratulations to Huajian Zhang, Shuo Yu, Qingchuan Li and Zhiding Liu on their paper being accepted to WWW 2026!
• [Dec. 2025] 🎉 I will serve as a AE for IEEE SMC2026.
• [Nov. 2025] 🎉 Congratulations to Xiaoyu Tao on her paper being accepted to ACM TIST!
• [Nov. 2025] 🎉 Congratulations to Qingchuan Li and Yupeng Li on their paper being accepted to AAAI 2026!
• [Oct. 2025] 🎉 Congratulations to Chuang Jiang, Jiahao Wang, and collaborators on their paper being accepted to ACM WSDM2026!
• [Sep. 2025] 🎉 Congratulations to Zhiding Liu on his paper being accepted to NeurIPS 2025!
• [Aug. 2025] 🎉 Congratulations to Shuo Yu and Jiahao Wang on their paper being accepted to CIKM 2025!

• [Jul. 2025] 🎉 Congratulations to Mingfan Pan and Yue Chen for their paper acceptance at RecSys 2025!
• [Jun. 2025] 📊 We released ChemTable, a large-scale dataset and benchmark for evaluating MLLMs on real-world chemical tables. [GitHub] [arXiv]
• [Jun. 2025] 🚀 We released Time-R1, the first time series reasoning model with reinforcement fine-tuning, now available on Hugging Face and GitHub.
• [May. 2025] 🎉 Congratulations to Jie Ouyang and Junhao Yu on their paper being accepted to ACL 2025!
• [May. 2025] 🎉 Congratulations to Daoyu Wang and Zirui Liu on their paper being accepted to ICML 2025!
• [Apr. 2025] 🎉 Congratulations to Jintao Zhang, Yitong Zhou, and Hao Zhang for having their paper accepted by IJCAI 2025!
• [Apr. 2025] 📄 We preprinted a new survey: A Comprehensive Survey of Time Series Forecasting on TechRxiv.
• [Apr. 2025] 📄 Our survey A Survey on Table Mining with Large Language Models released on TechRxiv.
• [Mar. 2025] 🚀 Our Agent R1 project officially released on GitHub.
• [Mar. 2025] 📄 Our survey A Survey on Knowledge-Oriented Retrieval-Augmented Generation released on arXiv.
• [Dec. 2024] 🏆 Congrats to our students on winning the Gold Award in the 2024 Ascend AI Innovation Competition finals!

Open Source Projects

TabClaw 2026.03 GitHub ⭐ …

TabClaw is an agentic table reasoning framework that empowers LLMs to understand, analyze, and interact with complex tabular data through structured reasoning, tool use, and multi-step decision workflows.

Claw-R1 2026.03 GitHub ⭐ …

An agentic reinforcement learning framework extending RL training environments for reasoning and tool-using LLM agents.

Mind2Report 2025 GitHub ⭐ …

A cognitive deep research agent for synthesizing expert-level commercial and strategic reports from massive web sources with citation-grounded outputs.

Science-Star 2025 GitHub ⭐ …

An open-source framework for building scientific AI agents — ReAct engine, tool orchestration, memory & reflection, HLE dataset integration.

Agent-R1 2025 GitHub ⭐ …

A large-model agent training framework supporting reinforcement fine-tuning (GRPO), multi-tool orchestration, long-term memory, and reflective reasoning.

📘 Preprint and Under Review

1. Mingyue Cheng, Jie Ouyang, Shuo Yu, Ruiran Yan, Yucong Luo, Zirui Liu, Daoyu Wang, Qi Liu, Enhong Chen, Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning. (Preprint) [PDF] [Code]
2. Mingyue Cheng, Daoyu Wang, Qi Liu, Shuo Yu, Xiaoyu Tao, Yuqian Wang, Chengzhong Chu, Yu Duan, Mingkang Long, Enhong Chen, Mind2Report: A Cognitive Deep Research Agent for Expert-Level Commercial Report Synthesis. (Preprint) [PDF] [Code]
3. Mingyue Cheng, Xiaoyu Tao, Huajian Zhang, Qi Liu, Enhong Chen, InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement. (Preprint) [PDF] [Code]
4. Xiaohan Zhang, Tian Gao, Mingyue Cheng*, Bokai Pan, Ze Guo, Yaguo Liu, Xiaoyu Tao, AlphaCast: A Human Wisdom-LLM Intelligence Co-Reasoning Framework for Interactive Time Series Forecasting. (Preprint) [PDF] [Code]
5. Yitong Zhou, Yucong Luo, Mingyue Cheng*, Jiahao Wang, Daoyu Wang, Tingyue Pan, Jintao Zhang, Qi Liu, Enhong Chen, Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs. (Preprint) [PDF] [Code]
6. Xiaoyu Tao, Mingyue Cheng*, Ze Guo, Shuo Yu, Yaguo Liu, Qi Liu, Shijin Wang, MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning. (Preprint) [PDF]
7. Xiaoyu Tao, Shilong Zhang, Mingyue Cheng*, Daoyu Wang, Tingyue Pan, Bokai Pan, Changqing Zhang, Shijin Wang, From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization. (Preprint) [Code]

📘 Released Benchmark and Survey

1. Mingyue Cheng, Xiaoyu Tao, Qi Liu, Ze Guo, Enhong Chen, Position: Beyond Model-Centric Prediction — Agentic Time Series Forecasting. (Preprint) [arXiv] [PDF]
2. Mingyue Cheng, Zhiding Liu, Xiaoyu Tao, Qi Liu*, Jintao Zhang, Tingyue Pan, Shilong Zhang, Panjing He, Xiaohan Zhang, Daoyu Wang, Jiahao Wang, Enhong Chen, A Comprehensive Survey of Time Series Forecasting: Concepts, Challenges, and Future Directions. (Preprint) [PDF] [Code]
3. Mingyue Cheng, Qingyang Mao, Qi Liu*, Yitong Zhou, Yupeng Li, Jiahao Wang, Jiaying Lin, Jiawei Cao, Enhong Chen, A Survey on Table Mining with Large Language Models: Challenges, Advancements and Prospects. (Preprint) [PDF] [Code]
4. Mingyue Cheng, Yucong Luo, Jie Ouyang, Qi Liu*, et al., A Survey on Knowledge-Oriented Retrieval-Augmented Generation. (Preprint) [PDF] [Code]
5. Daoyu Wang, Mingyue Cheng*, Shuo Yu, Zirui Liu, Ze Guo, Qi Liu, PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature. (Preprint) [PDF] [Code]
6. Yitong Zhou, Mingyue Cheng*, Qingyang Mao, Yucong Luo, Qi Liu, et al., Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tables. (Preprint) [PDF] [Code]

🐎 Year of the Fire Horse (Bing Wu Year, 2026)

1. Huajian Zhang, Mingyue Cheng*, Yucong Luo, Xiaoyu Tao, STaR: Towards Cognitive Table Reasoning via Slow-Thinking Large Language Models. (ACM WWW2026) [PDF] [Code]
2. Zhiding Liu, Ben Chen, Mingyue Cheng*, Enhong Chen, Li Li, Chenyi Lei, Wenwu Ou, Han Li and Kun Gai, Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce. (ACM WWW2026) [PDF]
3. Shuo Yu, Mingyue Cheng*, Daoyu Wang, Qi Liu, Zirui Liu, Ze Guo, Xiaoyu Tao, MemWeaver: A Hierarchical Memory from Textual Interactive Behaviors for Personalized Generation. (ACM WWW2026) [PDF]
4. Qingchuan Li, Jiatong Li, Zirui Liu, Mingyue Cheng, Yitong Zhou, Yuting Zeng, Qi Liu and Tongxuan Liu, Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts? (ACM WWW2026)
5. Li Li, Mingyue Cheng*, Yuyang Ye, Zhiding Liu, Enhong Chen, Preference Trajectory Modeling via Flow Matching for Sequential Recommendation. (DASFAA2026)
6. Zirui Liu, Xianquan Wang, Yan Zhuang, Jiatong Li, Qi Liu, Shuanghong Shen, Mingyue Cheng, Shijin Wang, Fewer Battles, More Gain: An Information-Efficient Framework for Arena-based LLM Evaluation. (ICLR2026) [PDF]
7. Qingyang Mao, Qi Cai, Yehao Li, Yingwei Pan, Mingyue Cheng, Ting Yao, Qi Liu, Tao Mei, Visual Autoregressive Modeling for Instruction-Guided Image Editing. (ICLR2026)
8. Mingyue Cheng, Jiahao Wang, Daoyu Wang, Xiaoyu Tao, Qi Liu*, Enhong Chen, Can Slow-Thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting, ACM WSDM2026: 99–110, Feb 2026. [PDF] [Code]
9. Mingyue Cheng, Xiaoyu Tao, Zhiding Liu, Qi Liu*, Hao Zhang, Rujiao Zhang and Enhong Chen, TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked Autoencoders, ACM WSDM2026: 498–508, Feb 2026. [PDF] [Code]
10. Chuang Jiang, Mingyue Cheng*, Xiaoyu Tao, Qingyang Mao, Jie Ouyang and Qi Liu, TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning, ACM WSDM2026: 260–270, Feb 2026. [PDF] [Code]
11. Qingchuan Li, Mingyue Cheng*, Zirui Liu, Daoyu Wang, Yuting Zeng, Tongxuan Liu, From Hypothesis to Premises: LLM-based Backward Logical Reasoning with Selective Symbolic Translation. (AAAI2026)
12. Yupeng Li, Mingyue Cheng*, Yucong Luo, Yitong Zhou, Qingyang Mao, Shijin Wang, BLADE: A Behavior-Level Data Augmentation Framework with Dual Fusion Modeling for Multi-Behavior Sequential Recommendation. (AAAI2026)
13. Xian Guo, Ben Chen, Siyuan Wang, YingYang, Mingyue Cheng, Chenyi Lei, Yuqing Ding, Han Li, OneSug: The Unified End-to-End Generative Framework for E-commerce Query Suggestion. (AAAI2026)

🐍 Year of the Wood Snake (Yi Si Year, 2025)

1. Mingyue Cheng, Jiqian Yang, Tingyue Pan, Qi Liu*, Zhi Li, ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis, ACM WWW2025, Sydney, 2025. [PDF] [Code] — Included in sktime
2. Xiaoyu Tao, Tingyue Pan, Mingyue Cheng*, Yucong Luo, Qi Liu, Enhong Chen, Hierarchical Multimodal LLMs with Semantic Space Alignment for Enhanced Time Series Classification. (ACM TIST) [PDF] [Code]
3. Mingyue Cheng, Yiheng Chen, Qi Liu*, Zhiding Liu, Yucong Luo, Enhong Chen, InstrucTime: Advancing Time Series Classification with Multimodal Language Modeling, ACM WSDM2025 (Best of WSDM): 792–800, Hannover, 2025. [PDF] [Code] [Poster]
4. Mingyue Cheng, Xiaoyu Tao, Qi Liu*, Hao Zhang, Yiheng Chen, Defu Lian, Cross-Domain Pre-training with Language Models for Transferable Time Series Representations, ACM WSDM2025: 175–183, Hannover, 2025. [PDF] [Code] [Poster]
5. Daoyu Wang, Mingyue Cheng*, Zhiding Liu, Qi Liu, TimeDART: A Diffusion Autoregressive Transformer for Self-supervised Time Series Representation, ICML 2025, Vancouver, PMLR 267, 2025. [PDF] [Code]
6. Jie Ouyang, Tingyue Pan, Mingyue Cheng*, Ruiran Yan, Yucong Luo, Jiaying Lin, Qi Liu, HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on RAG, ACL 2025: 6036–6063, Vienna, 2025. [PDF] [Code]
7. Mingyue Cheng, Jintao Zhang, Zhiding Liu, Chunli Liu*, A Hybrid Multi-Factor Framework for Dynamic Intraoperative Hypotension Prediction, IJCAI 2025: 4923–4931, Montreal, 2025. [PDF]
8. Jintao Zhang, Mingyue Cheng*, Xiaoyu Tao, Zhiding Liu, Daoyu Wang, Conditional Denoising Meets Polynomial Modeling: A Flexible Decoupled Framework for Time Series Forecasting, IJCAI 2025: 6993–7001, Montreal, 2025. [PDF] [Code]
9. Yitong Zhou, Mingyue Cheng*, Qingyang Mao, Feiyang Xu, Xin Li, Enhancing Table Recognition with Vision LLMs: A Benchmark and Neighbor-Guided Toolchain Reasoner, IJCAI 2025: 2503–2511, Montreal, 2025. [PDF] [Code]
10. Hao Zhang, Mingyue Cheng*, Qi Liu, Zhiding Liu, Linbo Zhu, Yu Su, Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems, IJCAI 2025: 3624–3632, Montreal, 2025. [PDF] [Code]
11. Jiahao Wang, Mingyue Cheng*, Qingyang Mao, Qi Liu, Feiyang Xu, Xin Li, Enhong Chen, TableTime: Reformulating Time Series Classification as Zero-Shot Table Understanding via LLMs, ACM CIKM 2025. [PDF] [Code]
12. Shuo Yu, Mingyue Cheng*, Jiqian Yang, Jie Ouyang, et al., Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study, ACM CIKM 2025.
13. Zhiding Liu, Mingyue Cheng, Guanhao Zhao, Jiqian Yang, Qi Liu, Enhong Chen, Improving Time Series Forecasting via Instance-aware Post-hoc Revision. (NeurIPS2025) [PDF]
14. Huijie Liu, Shulan Ruan, Qi Liu, Mingyue Cheng, Zhenya Huang, Yu Liu, Enhong Chen, You He, Global Structure-aware and Feature-augmented Graph Neural Network for Heterophilic Graphs, ACM TOIS. [PDF]
15. Junhao Yu, Yan Zhuang, Yuxuan Sun, Weibo Gao, Qi Liu, Mingyue Cheng, Zhenya Huang, Enhong Chen, TestAgent: An Adaptive and Intelligent Expert for Human Assessment. (ACL2025) [PDF]
16. Zirui Liu, Jiatong Li, Yan Zhuang, Qi Liu, Shuanghong Shen, Jie Ouyang, Mingyue Cheng, Shijin Wang, am-ELO: A Stable Framework for Arena-based LLM Evaluation, ICML 2025, PMLR 267, 2025. [PDF]
17. Mingfan Pan, Qingyang Mao, Xu An, Jianhui Ma, Gang Zhou, Mingyue Cheng, Enhong Chen, Tag-augmented Dual-target Cross-domain Recommendation, RecSys 2025, Prague, 2025.
18. Yue Chen, Susen Yang, Tong Zhang, Chao Wang, Mingyue Cheng, Chenyi Lei, Han Li, Lasso: Large Language Model-based User Simulator for Cross-Domain Recommendation, RecSys 2025, Prague, 2025.

🐉 Year of the Wood Dragon (Jia Chen Year, 2024)

1. Jie Ouyang, Yucong Luo, Mingyue Cheng*, Shuo Yu, Daoyu Wang, Qi Liu, Enhong Chen, Revisiting the Solution of Meta KDD Cup 2024: CRAG. (KDD Cup Workshop, 2nd Place in Task 2 & Task 3) [Slides] [Poster]
2. Mingyue Cheng, Qi Liu*, Wenyu Zhang, Zhiding Liu, Hongke Zhao, Enhong Chen, A General Tail Item Representation Enhancement Framework for Sequential Recommender Systems, Frontier of Computer Science (FCS), 2024, 18(6): 1–12. [PDF] [Code]
3. Rujiao Zhang, Hao Zhang, Yucong Luo, Zhiding Liu, Mingyue Cheng, Qi Liu, Enhong Chen*, Learning the Dynamics in Sequential Recommendation by Exploiting Real-time Information, ACM CIKM2024: 4288–4292, Oct 2024. [PDF]
4. Jie Wang, Fajie Yuan, Mingyue Cheng, et al., TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback, APWeb-WAIM2024: 193–208, Aug 2024. [PDF]
5. Zhiding Liu, Jiqian Yang, Mingyue Cheng*, Yucong Luo, Zhi Li, Generative Pretrained Hierarchical Transformer for Time Series Forecasting, ACM SIGKDD2024: 2003–2013, Barcelona, 2024. [PDF]
6. Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu, Enhong Chen*, Unlocking the Potential of Large Language Models for Explainable Recommendations. (DASFAA2024) [PDF] [Code]
7. Junzhe Jiang, Shang Qu, Mingyue Cheng*, Qi Liu, et al., Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling. (DASFAA2024) [PDF] [Code]
8. Mingyue Cheng, Hao Zhang, Qi Liu*, Fajie Yuan, Zhi Li, Zhenya Huang, Enhong Chen, Longfei Li, Jun Zhou, Empowering Sequential Recommender Systems from Mixture of Collaborative Signals and Semantic Relatedness. (DASFAA2024) [PDF] [Code]
9. Hao Zhang, Mingyue Cheng*, Qi Liu, Yucong Luo, Rui Li, Enhong Chen, Learning Recommender Systems with Soft Target: A Decoupled Perspective. (DASFAA2024) [PDF] [Code]
10. Mingyue Cheng, Hao Zhang, Jiqian Yang, Qi Liu*, Li Li, Xin Huang, Liwei Song, Zhi Li, Zhenya Huang, Enhong Chen, Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform. (WWW2024)
11. Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, et al., Exploring Adapter-based Transfer Learning for Recommender Systems, ACM WSDM'2024: 208–217, Mar 2024. [PDF] [Code]

📘 2023 and Before

1. 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, NeurIPS'2023: 36, New Orleans, 2023. [PDF] [Code]
2. 耿杰, 刘春丽*, 魏雪梅, 程明月, 袁昆, 李洋, 刘业政, 基于用户重购行为的产品推荐方法, 计算机研究与发展 2023, 60(8): 1795–1807.
3. Mingyue Cheng, Qi Liu*, Zhiding Liu, Zhi Li, Yucong Luo, Enhong Chen, FormerTime: Hierarchical Multi-scale Representation for Multivariate Time Series Classification, ACM WWW'2023: 1437–1445, Austin, 2023. [PDF] [Code]
4. Wenqiang He, Mingyue Cheng, Qi Liu*, Zhi Li, ShapeWordNet: An Interpretable Shapelet Neural Network for Physiological Signal Classification, DASFAA'2023: 353–369, Tianjin, 2023.
5. Mingyue Cheng, Zhiding Liu⁺, Qi Liu*, Shenyang Ge, Enhong Chen, Towards Automatic Designing of Deep Hybrid Network Architecture for Sequential Recommendation, ACM WWW'2022: 1923–1932. [Code]
6. Zhiding Liu, Mingyue Cheng, Zhi Li, Qi Liu, Enhong Chen*, One Person, One Model — Learning Compound Router for Sequential Recommendation, IEEE ICDM'2022. [Code]
7. Junzhe Jiang, Mingyue Cheng, Qi Liu*, Zhi Li, Enhong Chen, Nested Named Entity Recognition from Medical Texts: A Multi-task Learning Approach, CAAI CICAI'2022: 248–259.
8. Runlong Yu, Qi Liu*, Yuyang Ye, Mingyue Cheng, Enhong Chen, Jianhui Ma, Collaborative List-and-Pairwise Filtering from Implicit Feedback, IEEE TKDE'2022: 34(6): 2667–2680.
9. Kai Zhang, Qi Liu*, Zhenya Huang, Mingyue Cheng, Kun Zhang, Mengdi Zhang, Wei Wu, Enhong Chen, Graph Adaptive Semantic Transfer for Cross-domain Sentiment Classification, ACM SIGIR'2022: 1566–1576.
10. Mingyue Cheng, Fajie Yuan⁺, Qi Liu*, Xin Xin, Enhong Chen, Learning Transferrable User Representations with Sequential Behaviors via Contrastive Pre-training, IEEE ICDM'2021: 51–60.
11. 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, ACM SIGIR'2021: 575–584.
12. Linan Yue, Qi Liu*, Han Wu, Kai Zhang, Yanqing An, Mingyue Cheng, Biao Yin, Dayong Wu, NeurJudge: A Circumstance-aware Neural Framework for Legal Judgment Prediction, ACM SIGIR'2021: 973–982.
13. Yanqing An, Qi Liu*, Han Wu, Kai Zhang, Linan Yue, Mingyue Cheng, Hongke Zhao, Senchao Yuan, Enhong Chen, LawyerPAN: A Proficiency Assessment Network for Trial Lawyers, ACM SIGKDD'2021: 5–13.
14. Mingyue Cheng, Runlong Yu, Qi Liu*, Hongke Zhao, Hefu Zhang, Enhong Chen, Alpha-Beta Sampling for Pairwise Ranking in One-Class Collaborative Filtering, IEEE ICDM'2019: 1000–1005.
15. 程明月, 刘淇*, 李徵, 于润龙, 高维博, 陈恩红, 多重对级贝叶斯个性化排序算法. (南京信息工程大学学报自然科学版, 2019(03): 302–308)

AI System Development

我们团队致力于研发高效且实用的AI系统，以下为一些我们团队研发的部分系统成果：

• 冰鉴·大模型评测平台：冰鉴大模型评测平台，大模型认知能力评测工具。
• 科言·智能助写平台：科言智能助写平台，提升写作效率与技能。
• 科小研·学位论文辅助审查：文阅学位论文辅助审查，研究生学位论文辅助审阅。

Working Experiences

• Jun. 2023 ~ Present, Associate Researcher, School of Computer Science and Technology, USTC, Hefei, China
• Jan. 2021 ~ Jun. 2023, Research Assistant, Research Center for Big Data in Intelligent Healthcare, USTC, Hefei, China
• Jun. 2019 ~ Oct. 2019, Research Intern, Data Service Center (DSC), Platform and Content Group (PCG), Tencent, Shenzhen, China
• Jul. 2018 ~ Sep. 2018, Engineer Intern, Lab of Big Data, Core Technology R&D Platform, iFLYTEK, Hefei, China

Education

• Sep. 2017 ~ Jun. 2023, Major: Data Science (Computer Science and Technology), Ph.D Degree, University of Science and Technology of China (USTC), China
• Sep. 2013 ~ Jul. 2017, Major: Marketing Management, Bachelor of Management, Hefei University of Technology (HFUT), China

Honors and Awards

• Aug. 2025, 中国科学技术大学红专青年人才
• Mar. 2025, Best of WSDM2025（优秀论文奖）
• Dec. 2024, 昇腾人工智能创新大赛全国总决赛金奖（指导教师）
• Aug. 2024, Second Place of Task2 & Task3 in KDD Cup'2024
• Jan. 2024, 中国科学技术大学雄鹰创新创业基金（指导教师）
• Dec. 2023, 2023年中国国际大学生创新大赛国家级银奖（教育部）
• Jul. 2023, 全国"互联网+"大学生创新创业大赛安徽省金奖（安徽省教育厅）
• Mar. 2023, 中国科学技术大学优秀毕业生
• May. 2022, 2022年中国科学技术大学"创新创业"基金
• Jan. 2022, 中国科学技术大学2022年"优秀博士生出国留学支持计划"
• Dec. 2021, "创青春"中国青年创新创业项目支持——大学生创业"金种子"计划（团中央）
• Sep. 2021, 博士研究生国家奖学金（教育部）
• Sep. 2021, 全国"互联网+"大学生创新创业大赛安徽省金奖（安徽省教育厅）
• Jul. 2021, 中国科学技术大学"庆峰杯"创新创业大赛二等奖
• Sep. 2019, 腾讯科技平台与事业群实习生Mini项目卓越奖
• Jul. 2018, 全国大学生"创青春"创新创业大赛安徽省金奖（安徽省教育厅）

Teaching

• Introduction to Data Science（数据分析及实践）, Undergraduate Course, Spring 2024.
• Introduction to Data Science（数据分析及实践）, Undergraduate Course, Spring 2025.
• Introduction to Data Science（数据分析及实践）, Undergraduate Course, Spring 2026.
• Introduction to Systems Programming（系统程序设计基础）, Undergraduate Course, Spring 2026.

Professional Activities

Research Grants

• 2026.01–2028.12, the Natural Science Foundation of China
• 2025.01–2027.12, USTC New Medicine Joint Fund Cultivation Project (Double First-Class Initiative Special Project)
• 2024.09–2026.08, Anhui Provincial Natural Science Foundation
• In addition, my research has been partially supported by industrial grants from leading companies such as iFlyTek, Huawei and Kuaishou.

Related Links

• Prof. Qi Liu (USTC)
• Prof. Enhong Chen (USTC)
• Prof. Fajie Yuan (WU)
• Prof. Hongke Zhao (TJU)