Research Interests: Machine Learning, Data Mining, Information Retrieval, Recommender Systems, Natural Language Processing, ML Systems, AI Agents, Explainable, Fair and Personalized AI, AI for Science and Social Good
Contact: Department of Computer Science, 110 Frelinghuysen Road, Rutgers University, Piscataway, NJ 08854, USA
2020 Distinguished Editor for ACM Transactions on Information Systems (TOIS)
2018 Rutgers CS Best Professor Award for Teaching and Mentoring
2017 AIRS Best Paper Award
2017 THU and CAAI Best PhD Dissertation Award
2015 Microsoft PhD Fellowship
2015 Siebel Scholar
2014 Baidu Scholarship
2014 IBM PhD Fellowship
2012 Google Scholarship
Recent Talks:
Trustworthy AI for Human and Science at Rutgers CS Colloquium. [Slides]
Tutorial on Large Language Models for Recommendation at RecSys 2023. [Slides][Website]
Large Language Models for Generative Recommendation, Keynote speech on WWW 2023 ISIR-eCom Workshop, Keynote speech on KDD 2023 OARS Workshop, Amazon Research Seminar. [Slides]
Towards Trustworthy Recommender Systems: From Shallow Model to Deep Model to Large Model, Microsoft Research Summit 2022, CNCC 2022, AAAI 2023. [Slides]
Explainable AI for Science at Rutgers CQB Seminar. [Abstract][Slides]
From Kepler to Newton: Explainable AI for Science Discovery at ICML 2022. [Video and Slides]
Human-centered Explainable AI at UMass Amherst, USC, Brandeis U., U. of Delaware, Megagon Labs, Salesforce, Instacart, RUC, U. of North Texas, IEEE BigData Special Section on XAI (Keynote). [Slides][Video in English][Video in Chinese]
Explainable AI: From Human to Nature at Rutgers University. [Slides]
Towards Explainable Artificial Intelligence at Infinia ML Tech Talk. [Slides]
Tutorial on Fairness of Machine Learning in Recommender Systems at SIGIR 2021, CIKM 2021. [Slides][Website]
Tutorial on Conversational Recommendation Systems at RecSys 2020, WSDM 2021, IUI 2021. [Slides][Video][Website]
Tutorial on Explainable Recommendation and Search at WWW 2019, SIGIR 2019, ICTIR 2019. [Slides][Website]
Recommender Systems: an Interdisciplinary Perspective at Rutgers University. [Slides]
Recent News:
2024-08-26 Congratulations to Wenyue Hua for her successful PhD Thesis defense "Towards Trustworthy Large Language Models"!
2024-08-23 Congratulations to Jianchao Ji for his successful PhD Thesis defense "Integrate Learning and Reasoning for Large Language Model and Recommender Systems"!
2024-03-27 Congratulations to Zelong Li for his successful PhD Thesis defense "Automated Machine Learning for Intelligent Systems"!
2024-03-15 Congratulations to Runhui Wang for his successful PhD Thesis defense "Large Language Model for Data Driven Applications"!
2024-03-13 Congratulations to Shuyuan Xu for his successful PhD Thesis defense "Causal Collaborative Filtering"!
2024-03-13 Congratulations to Yunqi Li for her successful PhD Thesis defense "Fairness in Recommender Systems"!
2024-02-26 Survey on Trustworthy Recommendation accepted by ACM Transactions on Recommender Systems.
2024-02-25 Survey on LLM-based Generative Recommendation accepted by COLING 2024.
2024-02-01 Papers on LLM for Graph Learning and LLM for Fairness-aware Recommendation accepted by EACL 2024.
2023-12-15 Papers on LLM for Generative Recommendation and LLM for News Recommendation accepted by ECIR 2024.
2023-12-05 Congratulations to Juntao Tan for his successful PhD Thesis defense "Counterfactual Explainable AI for Human and Science"!
2023-10-17 Congratulations to Yingqiang Ge for his successful PhD Thesis defense "Towards Trustworthy Recommender Systems"!
2023-10-07 Paper on VIP5: Towards Multimodal Foundation Models for Recommendation accepted by EMNLP 2023.
2023-09-22 Paper on OpenAGI: When LLM Meets Domain Experts accepted by NeurIPS 2023.
2023-09-10 Paper on How to Index Item IDs for Recommendation Foundation Models accepted by SIGIR-AP 2023.
2023-08-06 Give a keynote speech Large Language Models for Generative Recommendation at KDD 2023 The 3rd International Workshop on Online and Adaptive Recommender Systems (OARS 2023).
2023-08-05 Paper on Prompt Distillation for Efficient LLM-based Recommendation accepted to CIKM 2023.
2023-05-16 Paper on Explainable AI for Science (ExplainableFold: Understanding AlphaFold Prediction with Explainable AI) accepted to KDD 2023.
2023-05-01 Give a keynote speech "Generative Recommendation with Foundation Models" at WWW 2023 The 2nd International Workshop on Interactive and Scalable Information Retrieval Methods for E-commerce (ISIR-eCom 2023).
2023-04-08 Paper on using explainable AI in responsible ways accepted to SIGIR 2023.
2023-02-13 Give a keynote speech "Towards Trustworthy Recommender Systems: From Shallow Model to Deep Model to Large Model" at AAAI 2023 AI for Web Advertising Workshop.
2023-01-20 Paper on RL-based recommendation in latent action space accepted to WWW 2023.
2023-01-20 Paper on Vision-Language Pre-training accepted to ICLR 2023.
2022-11-23 Congratulations to Shijie Geng for his successful PhD Thesis defense "Personalized Foundation Models for Decision Making"!
2022-10-18 Paper on Counterfactual Logical Reasoning accepted by WSDM 2023.
2022-10-06 Papers on Neural-Symbolic Reasoning and Commonsense Explanation Generation accepted by EMNLP 2022.
2022-09-15 Congratulations to Shuchang Liu for his successful PhD Thesis defense "Multi-Dimensional Federated Learning in Recommender Systems" co-advised with Prof. Amélie Marian!
2022-09-01 Grateful to recieve NSF-NIH Smart Health grant as co-PI to work on Explainable AI for Healthcare together with Dr. Lanjing Zhang.
2022-08-05 Papers on Auto Machine Learning and Causal Machine Learning accepted by CIKM 2022.
2022-07-12 Congratulations to Pavan Velaga for his successful MS Thesis defense "Logical Reasoning Models for Graphs and Vision"!
2022-06-28 Papers on Universal Recommendation Engine (P5) and Federated Fairness accepted by RecSys 2022.
2022-05-11 Give a talk Towards Trustworthy and Responsible Recommender Systems: Explainability, Fairness and Beyond at Microsoft Research.
2022-05-01 Papers on Automatic Loss Function Generation and Explainable Fairness accepted to SIGIR 2022.
2022-03-25 Congratulations to Hanxiong Chen for his successful PhD Thesis defense "Neural Logic Reasoning and Applications"!
2022-03-15 Paper on Causal Factorization Machine accepted to JCDL 2022.
2022-03-09 Give an invited talk Human-centered Explainable AI at Renmin University of China. [Slides]
2022-02-28 Paper on Personalized Explanation Generation accepted to ACL 2022.
2022-02-25 Give an invited talk Human-centered Explainable AI at Megagon Labs. [Slides]
2022-02-18 Give an invited talk Human-centered Explainable AI at University of Southern California. [Slides][Video]
2022-01-20 Two papers on Graph Language Models and Explainable Graph Neural Networks accepted to WWW 2022.
2021-11-30 What is the role of Explainable AI in Science Discovery? Can Kepler's and Newton's groundbreaking works be rediscovered by AI based on Tycho Brahe's ancient observation data? Check out paper From Kepler to Newton: Explainable AI for Science Discovery.
2021-11-05 Give an invited talk Human-centered Explainable AI at Brandeis University. [Slides]
2021-10-16 Papers on Graph Collaborative Reasoning and Fairness-Utility Trade-off accepted to WSDM 2022.
2021-09-17 Congratulations to Zuohui Fu for his successful PhD Thesis defense "Towards Human-centered Recommender System"!
2021-09-15 How can AI machines have Free Will, why does it help, and how to achieve it in a responsible way? Check out paper Problem Learning: Towards the Free Will of Machines.
2021-09-12 Grateful to receive Facebook Faculty Research Award as PI "Towards a Sustainable Social Platform based on Explainable and Fairness-aware Recommendation" to support our research.
2021-08-26 Grateful to receive NSF grant IIS-2127918 as co-PI "RI: Small: Enabling Interpretable AI via Bayesian Deep Learning" to support our research. Details can be found on NSF award abstract.
2021-08-16 Papers on Counterfactual Explainable Recommendation, Unbiased Conversational Recommendation, and Causal Recommendation accepted to CIKM 2021.
2021-07-28 Grateful to receive NSF grant IIS-2046457 as PI "CAREER: Towards Conversational Recommendation Systems: Explainability, Fairness, and Human-in-the-Loop Learning" to support our research on Conversational AI and Human-in-the-Loop AI. Details can be found on NSF award abstract and our Project Homepage.
2021-07-10 Grateful to receive NSF grant CCF-2124155 as co-PI "FMitF: Track I: Synthesis and Verification for Programmatic Reinforcement Learning" to support our research on Neural-Symbolic AI and Explainable AI. Details can be found on NSF award abstract and our Project Homepage.
2021-07-08 Paper on Explainable Recommendation in collaboration with Amazon accepted to RecSys 2021.
2021-05-06 Paper on Personalized Transformer accepted to ACL 2021.
2021-04-15 Papers on Fairness, Federated Learning, Counterfactual Recommendation, Conversational Recommendation, and Explainable Recommendation accepted to SIGIR 2021.
2021-04-10 Congratulations to Yikun Xian for his successful PhD Thesis defense "Neural Graph Reasoning for Explainable Decision-Making"!
2021-03-26 Give an invited talk Human-centered Explainable AI at the CIIR Talk Series. [Slides][Video]
2021-03-24 Congratulations to Yujia Fan for her successful MS Thesis defense "Neural Logic Analogy Learning"!
2021-01-19 Give an invited talk Human-centered Explainable AI at the Salesforce Research Speaking Session. [Slides]
2021-01-16 Papers on Reasoning, Fairness, Generative Recommendadtion, Knowledge Graph Embedding and Explainable Recommendation accepted to WWW 2021.
2020-12-17 Give an invited talk Human-centered Explainable AI at Instacart Algorithms Research Seminar. [Slides]
2020-12-10 Give an invited keynote speech Human-centered Explainable AI at the 2020 IEEE BigData Speical Session on Explainable Artificial Intelligence in Safety Critical Systems. [Slides]
2020-10-16 Our research on Long-term Fairness is accepted as a full paper to the WSDM 2021 conference.
2020-09-10 Grateful to receive NSF grant IIS-2007907 as PI "III: Small: Collaborative Research: Scrutable and Explainable Information Retrieval with Model Intrinsic and Agnostic Approaches", to support our research on Explainable Search. Details can be found on NSF award abstract and our Project Homepage.
2020-08-10 Our research on Neural Logic Reasoning, Neural Symbolic Reasoning, Generating Natural Language Explanations, and Economic Recommendation are accepted as four long papers to the CIKM 2020 conference.
2020-07-08 Give an invited talk Towards Explainable Artificial Intelligence at Infinia ML Tech Talk. [Slides]
2020-06-20 Our research on Risk-aware Recommendation, Fairness-aware Recommendation, Echo Chamber Analysis, and Learning to Hash are accepted as long papers on the SIGIR 2020 conference.
2019-09-20 Our research on Pareto-efficient and Fairness-aware Learning to Rank was awarded a Best Paper Honorable Mention at the ACM RecSys 2019 conference. Check out the research which improves the Pareto efficiency and fairness of recommender systems.
2019-09-03 Grateful to receive NSF grant IIS-1910154 as PI "III: Small: Towards Explainable Recommendation Systems" to support our research on Explainable Recommendation. Details can be found on NSF award abstract and our Project Homepage.
2019-08-20 Three long papers accepted by CIKM 2019, including our recent research on Conversational Search, Conversational QA, and Recommendation Systems.
2019-04-15 Five long papers and one short paper accepted by SIGIR 2019, including our recent research on Knowledge-enhanced machine learning, visually explainable recommendation, and conversational question answering.
2019-03-12 We are organizing the 2nd International Workshop on ExplainAble Recommendation and Search (EARS 2019) on July 25, to be co-located with SIGIR 2019 in Paris, France. More information and call for papers will be released soon.
2019-03-11 We are organizing the 2019 International Workshop on Recommendation in Multistakeholder Environments (RMSE 2019) on September 19-20, co-located with RecSys 2019 in Copenhagen, Denmark. More information and call for papers will be released soon.
2019-01-20 Three research papers accepted by the Web Conference 2019 (WWW 2019), including our recent research on bridging machine learning and economic principles for economic analysis of web-based systems.
2018-08-06 Our research paper on Towards Conversational Search and Recommendation: System Ask, User Respond got accepted by CIKM 2018 as a full paper.
2018-06-22 Give an invited talk "Explainable Recommendation and Search" at Guangzhou University, Guangzhou, China
2018-06-18 Give an invited talk "Explainable Recommendation and Search" at the Software College, Northeastern University, Shenyang, China.
2018-06-15 Give an invited talk "Economics of Recommendation and Search Systems" at Alibaba incorporation.
2018-06-14 Give an invited talk "Conversational Search in E-commerce" at the Department of Computer Science, Tsinghua University.
2018-06-14 Give an invited talk "Explainable Recommendation and Search" at Institute of Computing Technology, Chinese Academy of Sciences.
2018-05-31 Give an invited talk "From Textual to Visual Explainable Recommendation" at Microsft Research Asia.
2018-03-15 We are organizing the 2018 Workshop on ExplainAble Recommendation and Search (EARS 2018), to be co-loacted with SIGIR 2018 at Ann Arbor, Michigan. Please check out the call for papers at https://ears2018.github.io/.
2017-12-15 Please check out the accepted papers and schedule of the second International Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization (IFUP 2018), by clicking here.
2017-10-24 Paper on Sequential Recommendation with Memory Networks got accepted by WSDM 2018.
2017-08-15 We are organizing the Second International Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization (IFUP 2018) co-located with WSDM 2018 at Los Angeles, please checkout the workshop website by clicking here, and kindly consider a contribution!
2017-08-06 Two papers about Joint Representation Learning for Recommendation and Visibility Issues in Recommendation got accepted by CIKM 2017 as full papers, our Joint Representation Learning (JRL) algorithm got 2~3 times improvement than shallow baselines for top-N recommendation, check out the papers and source codes!
2017-04-10 Our two papers about Personalized Product Search and Personalized Key Frame Recommendation got accepted by SIGIR 2017, check out these new research tasks!
2017-01-26 Will give a talk Unstructured Data Mining for Web Personalization in Boston University.
2016-10-17 See how machine learninhg can help to quantity essential economic concepts and model the online economy in our paper “Multi-Product Utility Maximization for Economic Recommendation” accepted as a full paper in WSDM 2017.
2016-06-05 We are organizing the Tsinghua University Forum on Intelligent Recommendation, with distinguished keynote speakers Prof. Jian-Yun Nie from UMontreal, Dr. Xing Xie from MSRA, Dr. Quan Yuan from Alibaba, and Dr. Yading Yue from Tencent. Welcome to join!
2016-06-01 Will give a talk Personalized Recommendation based on Internet Surplus Maximization in Renmin University of China.
2016-05-18 Gave a talk Internet Welfare Economics in School of Computer Science, Beijing University of Technology.
2015-12-16 Let's promote the Web Intelligence towards Social Good! See our paper “Economic Recommendation with Surplus Maximization” accepted as a full paper in WWW 2016.
2015-04-17 Nearly driven crazy by the countless and continuously emerging approachs of shilling attach in practical recommender systems? See our paper “Catch the Black Sheep: Unified Framework for Shilling Attack Detection based on Fraudulent Action Propagation” in IJCAI 2015.
2015-01-18 Leverage the rather mature time series analysis techniques for business intelligence. See our paper “Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis” accepted as a full paper by WWW 2015.
2014-11-21 It's time to care about the role of textual reivews in recommender systems! See our research proposal “Incorporating Phrase-level Sentiment Analysis on Textual Reviews for Personalized Recommendation” accepted by WSDM 2015.
2014-11-10 Our paper “SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering” is accepted as a full paper by AAAI 2015.
2014-08-09 Our paper entitled “Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables” is accepted as a long paper by CIKM 2014.
2014-07-07 My research proposal “Browser-Oriented Universal Cross-Site Recommendation and Explanation based on User Browsing Logs” is accepted by the Doctoral Symposium of the RecSys 2014 conference.
2014-04-12 Our paper “Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis” is accepted as a long paper by SIGIR 2014.
2014-04-12 Our paper entitled “Do Users Rate or Review? Boost Phrase-level Sentiment Labeling with Review-level Sentiment Classification” has been accepted as a short paper by SIGIR 2014.
2013-12-08 I am visiting as a research assistant at the School of Computing (SoC) in the National University of Singapore (NUS).
2013-09-15 Our paper entitled “Towards the Adaption to the Open Texture of Law” was accepted by CSMES 2013.
2013-08-18 Our paper entitled “A Unified Framework for Emotional Elements Extraction based on Finite State Matching Machine” was accepted as a long paper by NLPCC 2013.
2013-04-05 Our paper “Improve Collaborative Filtering Through Bordered Block Diagonal Form Matrices” was accepted as a long paper by SIGIR 2013.
2013-02-08 Our paper entitled “Localized Matrix Factorization for Recommendation based on Matrix Block Diagonal Forms” was accepted as a long paper by WWW 2013.
2013-02-05 Our paper “A General Collaborative Filtering Framework based on Matrix Bordered Block Diagonal Forms” was accepted as a short paper by ACM Hypertext 2013.
2013-01-10 Our paper entitled “Is Fengshui Science or Superstition? A New Criterion for Judging the Value of Knowledge Systems” is published in Vol.3 No.1 in Journal of Literature and Art Studies.
2012-10-08 I gave a talk about “Framework of Distributed Recommender Systems“ in State Key Laboratory of Intelligent Technology and Systems of CS Dept. at Tsinghua University.
2012-04-23 I gave a talk about “A Suervey of Recommender Systems“ in State Key Laboratory of Intelligent Technology and Systems of CS Dept. at Tsinghua University.
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Associate Professor, Department of Computer Science, Rutgers University
Director, AIOS Foundation
Research Interests: Machine Learning, Data Mining, Information Retrieval, Recommender Systems, Natural Language Processing, ML Systems, AI Agents, Explainable, Fair and Personalized AI, AI for Science and Social Good
Contact: Department of Computer Science, 110 Frelinghuysen Road, Rutgers University, Piscataway, NJ 08854, USA
Education and Experience:
Honors and Awards:
Recent Talks:
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