Assistant Professor
Department of Information Technology and Management (ITM)Director of the Center for Decision Making and Optimization (DMO)
Director of the PhD Program in the ITM Department
ITM Curriculum Coordinator for Data Analytics
Ph.D., Computer and Information Sciences, DePaul University, USA
M.E., Computer and Its Application, Nanjing University of Posts & Telecommunications, China
B.E., Computer Science and Technology, Jiangnan University, China
| Office: | Perlstein Hall Room 221, 10 W 33rd St, Chicago, IL |
| Telephone: | 312.567.3575 |
| Fax: | 312.567.5248 |
| Email: | yzheng66 [at] iit.edu |
| Snail Mail: | Dr. Yong Zheng Perlstein Hall RM 221
10 W 33rd Street
Chicago, IL, 60616-3792, USA
|
| Social Media: | |
| Résumé/Vitae: |
Messages from Dr. Yong Zheng:
- Call for PhD students: information about our PhD program, admission guidelines for domestic students and international students. The application deadline for the prospective PhD students starting in the upcoming Fall semester is Jan 31. Note that you need to mention me as your preferred PhD advisor in the application form and/or cover letter.
- Dr. Zheng is looking for self-motivated PhD and Master students to conduct research in the area of data science and AI, paraticularly in recommender systems, user modeling, decision making and optimization, AI for Education, and large language models (LLMs). Interested students please feel free to drop me an email with your CV, TOEFL/GRE, transcript (and I can not reply to every individual email).
About
Dr. Yong Zheng is currently a tenure-track Assistant Professor at Department of Information Technology and Management, College of Computing, Illinois Institute of Technology, Chicago, USA, and he also served as the Director of the PhD Program in the ITM Department. He obtained his PhD degree in computer and information sciences from DePaul University in Chicago. Prior to IIT-Chicago, he worked with Dr. Bamshad Mobasher and Dr. Robin Burke on Recommender Systems and User Modeling.
Dr. Zheng is the director of the Center for Decision Making and Optimization (DMO) at Illinois Institute of Technology. His primary research focus encompasses the realm of Data Science and AI, with a specific emphasis on User Modeling, Personalization, and Recommender Systems. Additionally, he is engaged in cross-disciplinary investigations within Human-Centric Computing, Technology-Enhanced Learning, and FinTech. Notably, his scholarly contributions have found their way into premier conferences and journals, including KDD, ICDM, CIKM, RecSys, UMAP, IUI, SAC, UMUAI, Neurocomputing, etc. He maintains an active presence in professional engagement. His expertise has led to invitations to serve as organizational roles in prominent ACM conferences, such as ACM RecSys, ACM UMAP, ACM IUI, ACM Hypertext, and ACM SIGITE. Furthermore, he has played editorial roles for journals like JIIS, FIBD and IJEntTM. Serving as both a Program Committee member and reviewer, he has contributed his insights to distinguished academic journals and conferences, including IJCAI, KDD, SIGIR, WWW, RecSys, UMAP, TOIS, TIST, TiiS, TKDE, UMUAI, and more.
Experience
- 08/2018 – Present, Tenure-Track Assistant Professor, Illinois Institute of Technology, USA
- 08/2016 – 08/2018, Senior Lecturer, Illinois Institute of Technology, USA
- 06/2015 – 11/2015, Data Scientist at Pandora Media, Inc., USA
Latest News
- 2023 - 2024
- 11/2023, Call for PhD students: information about our PhD program, admission guidelines for domestic students and international students. The application deadline for the prospective PhD students starting in the upcoming Fall semester is Jan 31. Note that you need to mention me as your preferred PhD advisor in the application form and/or cover letter.
- 10/2023, I was invited to serve as a NSF Panelist for the Division of Information and Intelligent Systems at US NSF
- 10/2023, CFP: International Workshop on Decision Making and Optimization in Education (DMO-EDU) at LAK 2024
- 10/2023, I will give an invited Keynote Speech on the topic of "Personalized Learning: Adaptive Learning and Educational Recommendation Technologies" at the 4th Workshop on Eliciting Adaptive Sequences for Learning @ LAK 2024, Mar, 2024
- 10/2023, I started to serve as the Director of the PhD Program in the ITM Department
- 10/2023, I will serve as the Student Support Co-Chair at ACM UMAP, Italy, July, 2024
- 10/2023, Best Paper Nominee (Finalist) at ACM SIGITE 2023
- 09/2023, I served as the Workshop Chair for the Hands-on Workshop on Academic Writing by Using Latex at ACM SIGITE 2023
- 08/2023, I was invited to serve as a consultant and panelist at the Workshop on Recommender Systems in Education held by AI.EDU Research Lab at the FernUniversität in Hagen, Germany on Nov 3, 2023
- 08/2023, PI, NSF Grant (#2333695) to support participations in ACM IUI 2024
- 07/2023, PI, Seed Grant (GPU Computing Resources) by Argonne National Laboratory
- 06/2023, CFP: Special Issue on "Multi-Criteria/Multi-Objective Decision Making and Recommender Systems"
- 05/2023, I was given the Angela Jarka Service Award by the ITM department at IIT
- 05/2023, I was promoted to Associate Editor at Frontiers in Big Data (FIBD)
- 04/2023, PI, Industry Grant (#230342) by Morningstar, Inc. (Featured News)
- 03/2023, I served as sponsor chair at ACM IUI 2024 to be held in USA.
- 02/2023, I was one of the selected speakers at INFORMS Business Analytics Conference, 2023
- 02/2023, CFP, Special Issue on "Challenges and New Opportunities in Next-Generation Recommender Systems" at Electronics
- 01/2023, ITM-Rec: An Open Data Set for Educational Recommender Systems, is released on Github and Kaggle
- 01/2023, PI, NSF grant to support participations at ACM IUI 2023
- 01/2023, I will give a tutorial on "Multi-Criteria Decision Making and Recommender Systems" at ACM IUI 2023
- 11/2023, Call for PhD students: information about our PhD program, admission guidelines for domestic students and international students. The application deadline for the prospective PhD students starting in the upcoming Fall semester is Jan 31. Note that you need to mention me as your preferred PhD advisor in the application form and/or cover letter.
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2021 - 2022
2021 - 2022
- 12/2022, PI, ACM SIGAI Travel Fund for ACM IUI 2023
- 11/2022, I will serve as Sponsor Co-Chair at ACM IUI, Australia, Mar, 2023
- 10/2022, I will serve as Publicity Chair at ACM RecSys, Singapore, Sep, 2023
- 09/2022, I will give a tutorial on "Multi-Objective Optimization and Recommendations" at IEEE ICDM 2022
- 08/2022, I served as the Lead Guest Editor for the special issue on "Information Technology Education" to be published at Education and Information Technologies, Springer
- 07/2022, PI, AWS Cloud Credit Award to support Research on Deep Recommender Systems
- 07/2022, I was invited to deliver a Keynote Speech, "Multi-Objective Optimization and News Recommendations", at the International Workshop on News Recommendation and Analytics (INRA) @ ACM SIGIR 2022, July 2022
- 06/2022, PI, Industry Grant (#220300) by Morningstar, Inc. (Featured News)
- 05/2022, PI, ACM SIGCHI Development Fund
- 04/2022, I served as the Workshop Co-Chair for the 3rd Workshop on Personalization & Recommender Systems in Financial Services (FinRec) at ACM RecSys 2022
- 04/2022, I served as the guest editor for the topic on "Rising Stars in Recommender Systems 2022" at Frontiers in Big Data
- 03/2022, I will serve as Program Chair at ACM SIGITE 2022 to be held in September, 2022
- 02/2022, I served as a panelist for the Joint Panel Discussion on Data Science organized by IIT and Rust College
- 01/2022, I joined the Editorial Board of the Journal of Intelligent Information Systems (JIIS), Springer
- 01/2022, PI, Google Cloud Credit Award to support Research on Deep Recommender Systems
- 01/2022, I will serve as student support chair at ACM UMAP 2022 and ACM Hypertext 2022
- 12/2021, CFP: Special Issue on "Affective Computing and Recommender Systems" at Applied Sciences
- 12/2021, I will give an invited talk, "Recommender Systems Using Multi-Objective Optimization: An Overview", at IECI 2021.
- 11/2021, I was given the Excellence in Research Award by College of Computing at Illinois Institute of Technology, USA.
- 09/2021, I will give an invited talk (with Shlomo Engelson Argamon @ CS department), "Demystifying Data Science for Business Intelligence: Understanding Its Landscape and Deploying It Effectively", at AT&T, Inc.
- 08/2021, I will attend the training workshop "Data-Driven Cybersecurity"
- 05/2021, I will give a tutorial on "Multi-Objective Recommendations" at KDD 2021
- 05/2021, PI, ACM SIGCHI Development Fund
- 04/2021, I joined the Editorial Board of Frontiers in Big Data (FIBD), Frontiers
- 01/2021, Serve as student support chair at ACM UMAP 2021 and ACM IUI 2021
- 01/2021, Track Chair, Track on Recommender Systems @ ACM SAC 2021
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2019 - 2020
2019 - 2020
- 08/2020, I will give a Keynote talk at CARS workshop @ ACM RecSys 2020
- 05/2020, Serve as Student Volunteer Co-Chair at ACM IUI, Texas, USA, 2021
- 04/2020, PI, NSF grant to support students in ACM UMAP 2020 & 2021
- 02/2020, Collaboration with Digby's Detective & Security Agency, Inc. to predict crimes over Chicago Transit Authority (CTA) services
- 01/2020, Serve as student support chair at ACM UMAP 2020
- 12/2019, Invited talk on "Multi-Stakeholder Recommendations" at Morningstar, Inc.
- 06/2019, Track Chair, Track on Recommender Systems @ ACM SAC 2020
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2017 - 2018
2017 - 2018
- 10/2018, Serve as student support chair at ACM UMAP 2019
- 05/2018, Track Chair, Track on Recommender Systems @ ACM SAC 2019
- 04/2018, PI, NSF grant to support students in ACM UMAP 2018 & 2019
- 03/2018, Workshop Chair, Workshop on RecSysKTL @ ACM RecSys 2018
- 10/2017, Serve as publicity chair for ACM RecSys 2018, ACM IUI 2018 and ACM IUI 2019
- 10/2017, Serve as student support chair at ACM UMAP 2018
- 09/2017, Honored as a distinguished reviewer by ACM Transactions on Interactive Intelligent Systems
- 07/2017, Invited talk on "Context-Aware Recommendations" at The University of Glasgow, UK
- 05/2017, Track Chair, Track on Recommender Systems @ ACM SAC 2018
- 04/2017, Distinguished Student Supervisor Nominee, IIT, Chicago, USA
- 02/2017, Workshop Chair, Workshop on RecSysKTL @ ACM RecSys 2017
Teaching Interests
- Data Science & AI: Database, Data Analytics, Data Mining, Machine Learning, Artificial Intelligence
- Web Intelligence: Information Retrieval, Recommender Systems, Natural Language Processing, Decision Making
Teaching History
Year
Spring Semester (Jan to May)
Summer Semester (May to Aug)
Fall Semester (Aug to Dec)
2016
ITMD 510 (OOP)
ITMD 523 (Data Management)
ITMD 525 (Data Science)
2017
ITMD 523 (Data Management)
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
ITMD 523 (Data Management)
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
2018
ITMD 525 (Recommender Systems)
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
ITMT 597 (Independent Research)
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
ITMT 597 (Independent Research)
2019
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
ITMT 597 (Independent Research)
ITMD 527 (Data Analytics)
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
ITMT 597 (Independent Research)
2020
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
ITMT 597 (Independent Research)
ITMD 527 (Data Analytics)
ITMT 597 (Independent Research)
ITMD 525 (Data Science)
ITMD 527 (Data Analytics)
2021
ITMD 525 (Data Science)
ITMT 595 (Applied AI)
ITMT 597 (Independent Research)
ITMD 522 (Data Science)
ITMD 524 (Applied AI)
ITMT 597 (Independent Research)
2022
ITMD 321 (Data Management)
ITMD 522 (Data Science)
ITMT 597 (Independent Research)
ITMD 514 (Data Analytics)
ITMT 597 (Independent Research)
ITMD 522 (Data Science)
ITMD 523 (Data Management)
ITMT 597 (Independent Research)
2023
ITMD 522 (Data Science)
ITMD 523 (Data Management)
ITMT 597 (Independent Research)
ITMD 514 (Data Analytics)
ITMT 597 (Independent Research)
ITMD 514 (Data Analytics)
ITMD 522 (Data Science)
ITMD 523 (Data Management)
ITMT 597 (Independent Research)
2024
ITMD 522 (Data Science)
ITMD 523 (Data Management)
ITMT 597 (Independent Research)
ITMT 597 (Independent Research)
Research Interests
- General Areas: Data Science, Machine Learning, Artificial Intelligence
- Web Intelligence: Personalization, Recommender Systems, etc.
- HCI and Users: User Modeling, Human-Centric Computing, Behavior Analysis, etc.
- Education: Learning Analytics, Educational Data Mining, AI for Education, Technology-Enhanced Learning, etc.
- FinTech: AI in Finance, portfolio optimization, financial recommender systems, etc.
Honors, Grants & Awards
-
- 2023, NSF Merit Review Panelist for programs in NSF CISE/IIS
- 2023, Best Paper Nominee (Finalist) at ACM SIGITE 2023
- 2023, PI, NSF Grant (#2333695) to support participations in ACM IUI (2024)
- 2023, PI, Seed Grant (GPU Computing Resources) by Argonne National Laboratory
- 2023, PI, ACM SIGAI Travel Fund for ACM IUI 2024
- 2023, Angela Jarka Service Award by the ITM department at IIT
- 2023, PI, Industry Grant (#230342) by Morningstar, Inc.
- 2023, CCCC Professional Equity Project Grant
- 2023, IEEE EDUCON Registration Waiver
- 2023, ACM IUI Registration Waiver
- 2023, PI, NSF Grant (#2309142) to support participations in ACM IUI (2023 - 2024)
- 2022, PI, ACM SIGAI Travel Fund for ACM IUI 2023
- 2022, PI, ACM SIGCHI Development Fund for ACM IUI 2023
- 2022, PI, ACM SIGCHI Development Fund for ACM UMAP 2023
- 2022, PI, ACM SIGCHI Development Fund for ACM UMAP 2022
- 2022, PI, Industry Grant (#220300) by Morningstar, Inc.
- 2022, PI, AWS Cloud Credit Award for Research
- 2022, PI, Google Cloud Credit Award for Research
- 2022, ACM RecSys Registration Waiver
- 2022, ACM UMAP Registration Waiver
- 2022, IEEE ICDM Registration Waiver
- 2021, Excellence in Research Award by College of Computing at Illinois Institute of Technology
- 2021, ACM RecSys Registration Waiver
- 2021, ACM SIGKDD Registration Waiver
- 2021, AWS Educate Credit
- 2021, PI, ACM SIGCHI Development Fund for ACM UMAP 2021
- 2020, ACM RecSys Registration Waiver
- 2020, Project on "Predictive Staffing Model for Transit Security" for Chicago Transit Authority (CTA)supported and collaborated with Digby’s Detective & Security Agency, Inc.
- 2020, PI, Industry Grant #20-0195 by Morningstar, Inc. (approved but cancelled due to Covid-19)
- 2020, PI, NSF Grant (#2022227) to support students in ACM UMAP (2020 - 2024)
- 2019, ACM RecSys Registration Waiver
- 2019, ACM CIKM Registration Waiver
- 2018, PI, NSF Grant (#1830908) to support students in ACM UMAP (2018 - 2019)
- 2018, Distinguished reviewer by ACM Transactions on Interactive Intelligent Systems
- 2017, Distinguished Student Supervisor Nominee, Illinois Institute of Technology, Chicago, USA
- 2017, Distinguished reviewer by ACM Transactions on Interactive Intelligent Systems
- 2015, Best paper award at SOCRS, Chicago, USA
- 2015, Finalist at ACM Student Research Competition@ACM SAC, Spain
- 2014-2016, Being selected to participate in ACM Student Research Competition @ ACM SAC
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Sponsors & Collaborators
Academic & Professional Services
University Services
- Director of the PhD Program in ITM Department, 2023 - Present
- ITM Grant Search Coordinator, 2023 - Present
- ITM Tenure Track Faculty Search Committee, 2023 - 2024
- IIT Research Council (ITM Representative), 2023 - Present
- Teaching Faculty Search Committee, 2022 - 2023
- Strengthening Research Committee, College of Computing, 2021 - 2022
- Graduate Studies Committee, Illinois Institute of Technology, 2018 - 2021
- ITM Chair Search Committee, 2021
- Committee for Joint Statistics Course, 2020
- Academic Grievance Committee member, 2016
- Thesis Defense Committee for ITM-Spain Joint Master Program, 2016 - Present
- ITM Tenured/Tenure-Track Faculty Committee, 2018 - Present
- ITM Curriculum Coordinator for Data Analytics, 2016 - Present
- ITM Curriculum Committee, 2016 - Present
- ITM Faculty Committee, 2016 - Present
Conference Organizations
- Student Support Co-Chair, ACM UMAP, Italy, July, 2024
- Sponsor Chair, ACM IUI, USA, Mar, 2024
- Publicity Co-Chair, ACM RecSys, Singapore, Sep, 2023
- Sponsor Chair, ACM UMAP, Cyprus, June, 2023
- Sponsor Chair, ACM IUI, Australia, Mar, 2023
- Program Chair, ACM SIGITE, USA, Sep, 2022
- Proceedings Chair, ACM SIGITE, USA, Sep, 2022
- Student Support Co-Chair, ACM Hypertext, Spain, July, 2022
- Student Support Co-Chair, ACM UMAP, Spain, July, 2022
- Student Support Co-Chair, ACM UMAP, Netherlands, June, 2021
- Student Volunteer Co-Chair, ACM IUI, USA, April, 2021
- Student Support Co-Chair, ACM UMAP, Italy, July, 2020
- Student Support Co-Chair, ACM UMAP, Cyprus, June, 2019
- Publicity Co-Chair, ACM IUI, USA, March, 2019
- Student Support Co-Chair, ACM UMAP, Singapore, July, 2018
- Publicity Co-Chair, ACM RecSys, Canada, Oct, 2018
- Publicity Co-Chair, ACM IUI, Japan, March, 2018
Track | Workshop Organizations
- Workshop Co-Chair, Optimizing Human Learning. 4th Workshop eliciting Adaptive Sequences for Learning (WASL 2024) at LAK 2024
- Workshop Co-Chair, The International Workshop on Decision Making and Optimization in Education (DMO-EDU) at LAK 2024
- Workshop Co-Chair, The International Workshop on Decision Making and Optimization in Intelligent Information Systems (DMO-IIS) at AINA 2024
- Workshop Chair, Hands-on Workshop on Academic Writing by Using Latex at ACM SIGITE 2023
- Track Co-Chair, Track on Recommender Systems with Decision Making at the 23rd International Conference on Group Decision and Negotiation, 2023 (cancelled due to insufficient submissions)
- Workshop Co-Chair, The 3rd Workshop on Personalization & Recommender Systems in Financial Services (FinRec) at ACM RecSys 2022
- Track Co-Chair, Track on Recommender Systems at ACM SAC 2017, 2018, 2019, 2020, 2021, 2022
- Track Co-Chair, Track on Recommender Systems at AAAI FLAIRS 2018
- Workshop Co-Chair, The 2nd Workshop on Intelligent Recommender Systems by Knowledge Transfer and Learning (RecSysKTL) at ACM RecSys 2018
- Workshop Co-Chair, The 1st Workshop on Intelligent Recommender Systems by Knowledge Transfer and Learning (RecSysKTL) at ACM RecSys 2017
- Workshop Co-Chair, The Workshop on Web Personalization & Social Media at IEEE/WIC/ACM WI 2017
- Session Chair, IEEE/WIC/ACM Conference on Web Intelligence 2017
- Track Co-Chair, Track on Recommender Systems at AAAI FLAIRS 2017
- Workshop Co-Chair, The Workshop on Educational Recommender Systems at IEEE/WIC/ACM WI 2016
- Session Chair, The Workshop on Emotions and Personality in Personalized Systems at ACM RecSys 2016
Senior Program Committee Member
- ACM Conference on Information and Knowledge Management (CIKM): 2023 (Demo Track)
Technical Program Committee Member (Selected)
- International Joint Conference on Artificial Intelligence (IJCAI): 2022
- International World Wide Web Conference (WWW): 2024, 2023, 2022, 2021, 2020, 2019, 2018, 2017
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD): 2023, 2022, 2021
- ACM Conference on Web Search and Data Mining (WSDM): 2024, 2023, 2022, 2021
- ACM Conference on Information Retrieval (SIGIR): 2023, 2022, 2021, 2020, 2019, 2018
- ACM Conference on Recommender Systems (RecSys): 2023, 2022, 2021, 2020, 2019, 2018, 2017
- ACM Conference on User Modeling, Adaptation & Personalization (UMAP): 2023, 2022, 2021, 2018, 2017, 2016, 2015
- ACM Conference on Intelligent User Interfaces (IUI): 2019, 2018, 2017, 2016
- ACM Symposium on Applied Computing (SAC): 2014
- ACM Conference on Human Information Interaction & Retrieval (CHIIR): 2017
- ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE): 2022
- ACM Global Computing Education Conference (CompEd): 2019
- ACM Conference on Information Technology Education (SIGITE): 2023, 2018
- European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD): 2023
- SIAM International Conference on Data Mining (SDM): 2023
- European Conference on Information Retrieval (ECIR): 2018
- International Conference on Weblogs and Social Media (ICWSM): 2018, 2017, 2014
- Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD): 2018, 2017
- International Conference on Electronic Commerce and Web Technologies (EC-WEB): 2013
Grant Proposal Reviewer | Panelist
- 2023, NSF Panelist, Division of Information and Intelligent Systems at NSF
- 2019, External reviewer, Netherlands Organisation for Scientific Research (NWO)
- 2016, Ad Hoc Reviewer, US National Science Foundation (NSF)
Editorial Services
- Editorial Board
- 2023 - Present, Associate Editor at Frontiers in Big Data (FIBD), Frontiers
- 2021 - 2023, Review Editor at Frontiers in Big Data (FIBD), Frontiers
- 2022 - Present, Editorial Board, Journal of Intelligent Information Systems (JIIS), Springer
- 2020 - Present, Editorial Board, International Journal of Entertainment Technology and Management (IJEntTM)
- Journal Guest Editor
- 2023 - 2024, Lead Guest Editor, Special Issue on "Multi-Criteria/Multi-Objective Decision Making and Recommender Systems" at Applied Sciences, MDPI
- 2022 - 2023, Lead Guest Editor, Special Issue on "Information Technology Education" at Education and Information Technologies, Springer
- 2023, Guest Editor, Special Issue on "Challenges and New Opportunities in Next-Generation Recommender Systems" at Electronics, MDPI
- 2022, Guest Editor, Topic on "Rising Stars in Recommender Systems 2022" at Frontiers in Big Data, Frontiers
- 2022, Lead Guest Editor, Special Issue on "Affective Computing and Recommender Systems" at Applied Sciences, MDPI
- 2021 - 2022, Lead Guest Editor, Special Issue on "Advances in Recommender Systems" at Journal of Intelligent Information Systems, Springer
Invited Speakers & Panelist
- Invited Consultant and Panelist, at the Workshop on Recommender Systems in Education held by AI.EDU Research Lab at the FernUniversität in Hagen, Germany on Nov 3, 2023
- Selected Speaker, at INFORMS Business Analytics Conference, Aurora, CO, USA, April 16-18, 2023
- Invited Keynote Speaker, at the International Workshop on News Recommendation and Analytics (INRA) @ ACM SIGIR 2022, July 2022
- Invited Panelist, at the International Workshop on News Recommendation and Analytics (INRA) @ ACM SIGIR 2022, July 2022
- Invited Conference Speaker, at the 1st International Electronic Conference on Information (IECI 2021), December, 2021
- Invited Keynote Speaker, at the International Workshop on Context-Aware Recommender Systems (CARS) @ ACM RecSys 2020, Sep, 2020
- Invited Speaker, at Information Retrieval Group Seminars, School of Computing Science, The University of Glasgow, UK, July 7, 2017
Journal Reviewer
- TOIS, ACM Transactions on Information Systems
- TORS, ACM Transactions on Recommender Systems
- TOIT, ACM Transactions on Internet Technology
- TWeb, ACM Transactions on the Web
- TMIS, ACM Transactions on Management Information Systems
- TIST, ACM Transactions on Intelligent Systems and Technology
- TiiS, ACM Transactions on Interactive Intelligent Systems (distinguished reviewer)
- TKDE, IEEE Transactions on Knowledge and Data Engineering
- TLT, IEEE Transactions on Learning Technologies
- TCSS, IEEE Transactions on Computational Social Systems
- TIFS, IEEE Transactions on Information Forensics & Security
- TETC, IEEE Transactions on Emerging Topics in Computing
- IEEE-IS, IEEE Intelligent Systems
- UMUAI, User Modeling and User-Adapted Interaction
- InfoSci, Information Sciences, Elsevier
- KBS, Knowledge-Based Systems
- NC, Neurocomputing, Elsevier
- IPM, Information Processing and Management
- ASOC, Applied Soft Computing
- AGNT, Autonomous Agents and Multi-Agent Systems
- WWWJ, World Wide Web: Internet and Web Information Systems
- ECRA, Electronic Commerce Research and Applications
- FGCS, Future Generation Computer Systems
- JASIST, Journal of the Association for Information Science and Technology
- SIMPAT, Simulation Modelling Practice and Theory
- IJITDM, International Journal of Information Technology & Decision Making
- Patterns@Cell.com
- PMC, Pervasive and Mobile Computing
- WIAS, Web Intelligence: An International Journal
- JIIS, Journal of Intelligent Information Systems
- JITT, Journal of Information Technology & Tourism
- SLE, Smart Learning Environments
- IJEntTM, International Journal of Entertainment Technology and Management
- IJSNM, International Journal of Social Network Mining
- JIIS, Journal of Internet and Information Systems
- IxD&A, Interaction Design and Architecture (s) Journal
- MDPI Journals: Applied Science, Information
Publications
Book Chapters
- Yong Zheng and Bamshad Mobasher. "Context-Aware Recommendations". In Book: Collaborative Recommendations: Algorithms, Practical Challenges and Applications (ISBN: 9789813275348), pp. 173-202, World Scientific Publishing, 2018
- Yong Zheng, Bamshad Mobasher, Robin Burke. "Emotions in Context-aware Recommender Systems". In Book: Emotions and Personality in Personalized Services: Models, Evaluation and Applications (ISBN: 3319314114), pp. 311-326, Springer, 2016
Editorial Publications
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Edited Conference/Workshop Proceedings
- 2022 - Present
- Yong Zheng, Shaghayegh Sahebi. "The International Workshop on Decision Making and Optimization in Education", Companion Proceedings of the 14th International Conference on Learning Analytics & Knowledge (LAK), March, 2024
- Ray Trygstad, Yong Zheng. "SIGITE '22: The 23rd ACM Conference on Information Technology Education", Proceedings of the 23rd ACM Conference on Information Technology Education (SIGITE), Chicago, IL, USA, September, 2022
- Casper Petersen, Cataldo Musto, David (Xuejun) Wang, Giovanni Semeraro, Simone Borg Bruun, Toine Bogers, Yong Zheng, Alexander Felfernig. "FinRec: The 3rd International Workshop on Personalization and Recommender Systems in Financial Services", Proceedings of the ACM Conference on Recommender Systems (RecSys), Seattle, USA, September, 2022
- Yong Zheng, Markus Zanker, Li Chen, Panagiotis Symeonidis. "Track Editorial: Track on Recommender Systems: Theory, User Interactions and Applications", at the 37th ACM SIGAPP Symposium on Applied Computing (ACM SAC), Brno, Czech Republic, 2022 [PDF]
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2017 - 2021
2017 - 2021
- Yong Zheng, Li Chen, Markus Zanker, Panagiotis Symeonidis. Track Editorial: Track on Recommender Systems: Theory, User Interactions and Applications", at the 36th ACM SIGAPP Symposium on Applied Computing (ACM SAC), South Korea, 2021 [PDF]
- Markus Zanker, Panagiotis Symeonidis, Yong Zheng. Track Editorial: Track on Recommender Systems: Theory, User Interactions and Applications", at the 35th ACM SIGAPP Symposium on Applied Computing (ACM SAC), Czech Republic, 2020 [PDF]
- Markus Zanker, Li Chen, Panagiotis Symeonidis, Yong Zheng. Track Editorial: "Track on Recommender Systems: Theory, User Interactions and Applications", at the 34th ACM SIGAPP Symposium on Applied Computing (ACM SAC), Limassol, Cyprus, April, 2019 [PDF]
- Shaghayegh (Sherry) Sahebi, Yong Zheng, Weike Pan, Ignacio Fernández. Workshop Editorial: "The 2nd Workshop on Intelligent Recommender Systems by Knowledge Transfer & Learning (RecSysKTL)", Proceedings of the 12th ACM Conference on Recommender Systems, Vancouver, Canada, Oct, 2018
- Nadia Najjar, Yong Zheng, Carlos E. Seminario. Track Editorial: "Special Track on Recommender Systems", at the 31st International Florida Artificial Intelligence Research Society Conference (FLAIRS 2018), Melbourne, Florida, USA, 2018
- Yong Zheng, Li Chen, Markus Zanker. Track Editorial: "Track on Recommender Systems: Theory, User Interactions and Applications", at the 33rd ACM SIGAPP Symposium on Applied Computing (SAC'2018), April 9-13 2018, Pau, France [PDF]
- Yong Zheng, Weike Pan, Shaghayegh (Sherry) Sahebi, Ignacio Fernández. Workshop Editorial: "The 1st Workshop on Intelligent Recommender Systems by Knowledge Transfer & Learning (RecSysKTL)", Proceedings of the 11th ACM Conference on Recommender Systems, Como, Italy, Aug 27-31, 2017
- Yong Zheng, Li Chen, Markus Zanker. Track Editorial: "Track on Recommender Systems: Theory and Applications", at the 32nd ACM SIGAPP Symposium on Applied Computing (SAC'2017), April 3-7, 2017, Marrakech, Morocco [PDF]
- 2022 - Present
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Edited Journal Special Issues
- Yong Zheng, et al. "Special Issue on Information Technology Education", Education and Information Technologies, Springer, 2023
- Yong Zheng, María N. Moreno-García. "Special Issue on Affective Computing and Recommender Systems", Applied Sciences, MDPI, 2022
- Yong Zheng, Li Chen, Markus Zanker, Panagiotis Symeonidis. "JIIS Preface for the Special Issue on Advances in Recommender Systems", Journal of Intelligent Information Systems, Springer, 2022
Journal Publications
- Yong Zheng, Kumar Neelotpal Shukla, Jasmine Xu, David (Xuejun) Wang, Michael O'Leary. "MOPO-LSI: An Open-Source Multi-Objective Portfolio Optimization Library for Sustainable Investments", Software Impacts, Vol. 16, 100499, Elsevier, 2023 (impact factor = 2.1)
- Yong Zheng, Shuaiqi Zheng. "Exploring Educational Impacts Among Pre, During and Post COVID-19 Lockdowns From Students with Different Personality Traits", International Journal of Educational Technology in Higher Education, Springer, 2023 (impact factor = 8.6)
- Yong Zheng, David (Xuejun) Wang. "Multi-Criteria Ranking: Next Generation of Multi-Criteria Recommendation Framework", IEEE Access, Vol. 10, p. 90715-90725, IEEE, 2022 (impact factor = 3.9)
- Yong Zheng. "DeepCARSKit: A Deep Learning Based Context-Aware Recommendation Library", Software Impacts, Vol. 13, 100292, Elsevier, 2022 (impact factor = 2.1)
- Yong Zheng. "Non-Dominated Differential Context Modeling for Context-Aware Recommendations", Applied Intelligence, Vol. 52 (9), p. 10008–10021, Springer, 2022 (impact factor = 5.3)
- Yong Zheng, David (Xuejun) Wang. "A Survey of Recommender Systems with Multi-Objective Optimization", Neurocomputing, Vol. 474, p. 141-153, Elsevier, 2022 (impact factor = 6.0)
- Yong Zheng. "Context-Aware Collaborative Filtering Using Context Similarity: An Empirical Comparison". Information, Vol. 13 (1): 42, MDPI, 2022 (impact factor = 3.1)
- Yong Zheng, Juan Ruiz Toribio. "The Role of Transparency in Multi-Stakeholder Educational Recommendations". User Modeling and User-Adapted Interaction, Vol. 31 (3):5, p. 513–540, Springer, 2021 (impact factor = 3.6)
- Yong Zheng, Archana Subramaniyan. "Personality-Aware Recommendations: An Empirical Study In Educations". International Journal of Grid and Utility Computing, Vol. 12 (5/6), p. 524-533, Inderscience Publishers, 2021
- Yong Zheng. "Penalty-Enhanced Utility-Based Multi-Criteria Recommendations". Information, Vol. 11 (12): 551, MDPI, 2020 (impact factor = 3.1)
- Diego Sánchez-Moreno, Yong Zheng, and María N. Moreno-García. "Time-Aware Music Recommender Systems: Modeling the Evolution of Implicit User Preferences and User Listening Habits in A Collaborative Filtering Approach". Applied Sciences, Vol. 10 (15): 5324, MDPI, 2020 (impact factor = 2.7)
- Yong Zheng. "Preference Corrections: Capturing Student and Instructor Perceptions in Educational Recommendations", Smart Learning Environments, Vol. 6 (1):29, Springer, 2019 (impact factor = 4.8)
- Yong Zheng. "Multi-Criteria Recommendations By Using Criteria Preferences as Contexts", Towards Integrated Web, Mobile, and IoT Technology, Lecture Notes in Business Information Processing (LNBIP), Vol. 347, Springer, 2019
Conference Tutorials
- Yong Zheng. "Tutorial: Educational Recommender Systems", The 24th International Conference on Artificial Intelligence in Education (AIED), Japan, July 2023 (Tutorial Website)
- Yong Zheng. "Educational Recommender Systems", The 14th IEEE Global Engineering Education Conference (EDUCON), Kuwait, May, 2023
- Yong Zheng, David (Xuejun) Wang. "Multi-Criteria Decision Making and Recommender Systems", The 28th ACM Conference on Intelligent User Interfaces (ACM IUI), Sydney, Australia, March, 2023
- Yong Zheng, David (Xuejun) Wang. "Multi-Objective Optimization and Recommendations", at the IEEE International Conference on Data Mining (ICDM), Dec, 2022 (Tutorial Website)
- Yong Zheng, David (Xuejun) Wang. "Multi-Objective Recommendations", Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Aug, 2021 (Tutorial Website)
- Yong Zheng, David (Xuejun) Wang. "Recommender Systems with Multi-Objective Optimization", ACM Conference on Recommender Systems (RecSys), 2021 (Accepted, but finally withdrawn due to that we cannot attend the conference in-person)
- Muthusamy Chelliah, Yong Zheng, Sudeshna Sarkar, Vishal Kakkar. "Recommendation for Multi-Stakeholders and through Neural Review Mining", Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM), Beijing, China, Nov, 2019 (Tutorial Website)
- Yong Zheng. "Multi-Stakeholder Recommendations: Case Studies, Methods and Challenges", Proceedings of the 13th ACM Conference on Recommender Systems (RecSys), Copenhagen, Denmark, September 19th, 2019 (Slide and Demo)
- Yong Zheng. "Context-awareness In Information Retrieval and Recommender Systems", Proceedings of the 15th IEEE/WIC/ACM International Conference on Web Intelligence (WI'16), Omaha, USA, Oct 2016 (Slide)
- Yong Zheng. "Context In Recommender Systems", Proceedings of the 31st ACM SIGAPP Symposium on Applied Computing (ACM SAC), Pisa, Italy, April 2016 (Slide)
Refereed Conference Publications
- 2022 - Present
- Yong Zheng. "ChatGPT for Teaching and Learning: An Experience from Data Science Education", The 24th ACM Conference on Information Technology Education (ACM SIGITE), USA, Oct, 2023 (Best Paper Nominee)
- Yong Zheng. "Academic Writing by Using Latex: A Hands-on Workshop", The 24th ACM Conference on Information Technology Education (ACM SIGITE), USA, Oct, 2023
- Yong Zheng, Kumar Neelotpal Shukla, Jasmine Xu, David (Xuejun) Wang, Michael O'Leary. "Multi-Objective Portfolio Optimization Towards Sustainable Investments", The 6th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (ACM COMPASS), Aug, 2023
- Yong Zheng, David (Xuejun) Wang. "Hybrid Multi-Criteria Preference Ranking by Subsorting". The 14th Multidisciplinary Workshop on Advances in Preference Handling (M-PREF) at IJCAI 2023, Aug, 2023
- Yong Zheng, David (Xuejun) Wang. "Multi-Criteria Ranking by Using Relaxed Pareto Ranking Methods", Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), June, 2023
- Yong Zheng, David (Xuejun) Wang. "A Comparative Study of Preference Ordering Methods for Multi-Criteria Ranking", Proceedings of the 10th IEEE Swiss Conference on Data Science, June, 2023
- Yong Zheng. "ITM-Rec: An Open Data Set for Educational Recommender Systems". Companion Proceedings of the 13th International Conference on Learning Analytics & Knowledge (LAK), Arlington, TX, USA, March 13-17, 2023
- Yong Zheng, Shuaiqi Zheng. "A Comparison of Students' Learning Behaviors and Performance Among Pre, During and Post COVID-19 Pandemic", Proceedings of the 23rd ACM Conference on Information Technology Education (ACM SIGITE), USA, 2022
- Yong Zheng, Gonzalo Florez Arias. "A Family of Neural Contextual Matrix Factorization Models for Context-Aware Recommendations", Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), Spain, July, 2022
- Yong Zheng. "DeepCARSKit: A Demo and User Guide", Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), Spain, July, 2022
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2016 - 2020
2016 - 2020
- Yong Zheng. "SIGITE and SIGCSE Symposiums: A Comparative Study", Proceedings of the 21st ACM Conference on Information Technology Education (ACM SIGITE), Omaha, USA, Oct 7 - 9, 2020
- Yong Zheng. "Multi-Stakeholder Personalized Learning with Preference Corrections", Proceeding of the 19th IEEE International Conference on Advanced Learning Technologies (IEEE ICALT), Maceió - Alagoas, Brazil, July 15-18, 2019 (Acceptance rate: 15.1%)
- Yong Zheng, Nastaran Ghane, Milad Sabouri. "Personalized Educational Learning with Multi-Stakeholder Optimizations", Adjunct Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), Cyprus, June, 2019
- Yong Zheng, Shephalika Shekhar, Alisha Anna Jose and Sunil Kumar Rai. "Integrating Context-Awareness and Multi-Criteria Decision Making in Educational Learning", Proceedings of the 34th ACM SIGAPP Symposium on Applied Computing (ACM SAC), Limassol, Cyprus, April, 2019 (Acceptance rate: 24%)
- Yong Zheng and Alisha Anna Jose. "Context-Aware Recommendations via Sequential Predictions", Proceedings of the 34th ACM SIGAPP Symposium on Applied Computing (ACM SAC), Limassol, Cyprus, April, 2019 (Acceptance rate: 24%)
- Yong Zheng. "Utility-Based Multi-Criteria Recommender Systems", Proceedings of the 34th ACM SIGAPP Symposium on Applied Computing (ACM SAC), Limassol, Cyprus, April, 2019 (Acceptance rate: 24%)
- Diego Sánchez-Moreno, Yong Zheng, and María N. Moreno-García. "Incorporating Time Dynamics and Implicit Feedbacks into Music Recommender Systems", Proceedings of the 17th IEEE/WIC/ACM International Conference on Web Intelligence (WI'18), Santiago, Chile, December, 2018 (Acceptance rate: 32%, short paper)
- Yong Zheng, Aviana Pu. "Utility-Based Multi-Stakeholder Recommendations By Multi-Objective Optimization", Proceedings of the 17th IEEE/WIC/ACM International Conference on Web Intelligence (WI'18), Santiago, Chile, December, 2018 (Acceptance rate: 30%, long paper)
- Yong Zheng. "Exploring User Roles In Group Recommendations: A Learning Approach", Adjunct Proceedings of the 26th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), Singapore, July, 2018
- Yong Zheng, Tanaya Dave, Neha Mishra and Harshit Kumar. "Fairness In Reciprocal Recommendations: A Speed-Dating Study", Adjunct Proceedings of the 26th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), Singapore, July, 2018
- Yong Zheng. "Identifying Dominators and Followers In Group Decision Making Based on The Personality Traits", Proceedings of HUMANIZE Workshop at ACM Conference on Intelligent User Interfaces, Tokyo, Japan, 2018
- Yong Zheng. "Personality-Aware Decision Making In Educational Learning", Proceedings of the 23rd ACM Conference on Intelligent User Interfaces (ACM IUI), Tokyo, Japan, March 7-11, 2018
- Yong Zheng. "Multi-Stakeholder Recommendation: Applications and Challenges", by The 1st Workshop on The Value-Aware and Multi-Stakeholder Recommendation held in conjunction with the 11th ACM Conference on Recommender Systems, Como, Italy, August 2017
- Yong Zheng. "Context Suggestion: Empirical Evaluations vs User Studies", Proceedings of the 16th IEEE/WIC/ACM International Conference on Web Intelligence (WI'17), Leipzig, Germany, August 2017
- Yong Zheng. "Indirect Context Suggestion", Proceedings of the 25th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), Bratislava, Slovakia, July 2017
- Yong Zheng. "Criteria Chains: A Novel Multi-Criteria Recommendation Approach", The 22nd ACM Conference on Intelligent User Interfaces (ACM IUI), Limassol, Cyprus, March 13-16, 2017 (Acceptance rate: 17%)
- Yong Zheng. "Context-Awareness In Recommender Systems", PhD Dissertation, DePaul University, USA, 2016
- Yong Zheng. "Adapt to Emotional Reactions In Context-aware Personalization", Proceedings of the 4th Workshop on Emotions and Personality in Personalized Systems (EMPIRE) held in conjunction with the 10th ACM Conference on Recommender Systems (ACM RecSys), Boston, USA, Sep 15-19, 2016
- Yong Zheng, Bamshad Mobasher, Robin Burke. "User-Oriented Context Suggestion", Proceedings of the 24th ACM Conference on User Modeling, Adaptation and Personalization (ACM UMAP), pp. 249-258, Halifax, Canada, July 2016 (Long paper Acceptance rate: 23.9%)
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2011 - 2015
2011 - 2015
- Yong Zheng. "Improve General Contextual SLIM Recommendation Algorithms By Factorizing Contexts", Proceedings of the 30th ACM Symposium on Applied Computing (ACM SAC), pp. 937-938, Salamanca, Spain, April 2015 (Finalist in ACM Student Research Competition)
- Yong Zheng, Bamshad Mobasher, Robin Burke. "Correlation-Based Context-aware Matrix Factorization", Proceedings of School of Computing Research Symposium (SOCRS), DePaul University, Chicago, USA, May 2015 (Best Paper Award)
- Yong Zheng. "Context Suggestion: Solutions and Challenges", Proceedings of the 15th IEEE International Conference on Data Mining (IEEE ICDM) Workshops, pp. 1602-1603, Atlantic City, NJ, USA, Nov 2015
- Yong Zheng, Bamshad Mobasher, Robin Burke. "CARSKit: A Java-Based Context-aware Recommendation Engine", Proceedings of the 15th IEEE International Conference on Data Mining (IEEE ICDM) Workshops, pp. 1668-1671, Atlantic City, NJ, USA, Nov 2015
- Yong Zheng, Bamshad Mobasher, Robin Burke. "Similarity-Based Context-aware Recommendation", Proceedings of the 16th International Conference on Web Information System Engineering (WISE), pp. 431-447, Miami, FL, USA, Nov 2015 (Acceptance rate: 28.5%)
- Yong Zheng, Bamshad Mobasher, Robin Burke. "Integrating Context Similarity with Sparse Linear Recommendation Model", Proceedings of the 23rd Conference on User Modeling, Adaptation and Personalization (UMAP), pp. 370-376, Dublin, Ireland, June 2015 (Overall Acceptance rate: 28.5%)
- Yong Zheng. "A Revisit to The Identification of Contexts in Recommender Systems", Proceedings of the 20th ACM Conference on Intelligent User Interfaces (ACM IUI) Companion, pp. 133-136, Atlanta, GA, USA, March 2015
- Yong Zheng, Bamshad Mobasher, Robin Burke. "Deviation-Based Contextual SLIM Recommenders", Proceedings of the 23rd ACM Conference on Information and Knowledge Management (ACM CIKM), pp. 271-280, Shanghai, China, Nov 2014 (Acceptance rate: 20.8%)
- Yong Zheng. "Deviation-Based and Similarity-Based Contextual SLIM Recommendation Algorithms", Proceedings of the 8th ACM Conference on Recommender Systems (ACM RecSys), pp. 437-440, Silicon Valley, Foster City, CA, USA, Oct 2014
- Yong Zheng, Bamshad Mobasher, Robin Burke. "CSLIM: A Contextual SLIM Recommendation Algorithm", Proceedings of the 8th ACM Conference on Recommender Systems (ACM RecSys), pp. 301-304, Silicon Valley, Foster City, CA, USA, Oct 2014 (Acceptance rate: 24%)
- Yong Zheng, Robin Burke, Bamshad Mobasher. "Splitting Approaches for Context-Aware Recommendation: An Empirical Study", Proceedings of the 29th ACM Symposium on Applied Computing (ACM SAC), pp. 274-279, Gyeongju, South Korea, March 2014 (Acceptance rate: 23%)
- Yong Zheng, Bamshad Mobasher, Robin Burke. "Context Recommendation Using Multi-label Classification", Proceedings of the 13th IEEE/WIC/ACM Conference on Web Intelligence (IEEE/WIC/ACM WI), pp. 288-295, Warsaw, Poland, Aug 2014
- Yong Zheng, Robin Burke, Bamshad Mobasher. "The Role of Emotions in Context-aware Recommendation", Proceedings of the 3rd Workshop on Human Decision Making in Recommender Systems held in conjunction with the 7th ACM Conference on Recommender Systems (ACM RecSys), pp. 21-28, Hong Kong, China, Oct 2013
- Yong Zheng, Robin Burke, Bamshad Mobasher. "Recommendation with Differential Context Weighting". Proceedings of the 21st International Conference on User Modeling, Adaptation and Personalization (UMAP), pp. 152-164, Rome, Italy, June 2013 (Overall Acceptance rate: 30%)
- Yong Zheng, Robin Burke, Bamshad Mobasher. "Optimal Feature Selection for Context-Aware Recommendation using Differential Relaxation". Proceedings of the 4th Workshop on Context-Aware Recommender Systems held in conjunction with the 6th ACM Conference on Recommender Systems (ACM RecSys), Dublin, Ireland, Sep 2012
- Yong Zheng, Robin Burke, Bamshad Mobasher. "Differential Context Relaxation for Context-aware Travel Recommendation". The 13th International Conference on Electronic Commerce and Web Technologies (EC-WEB), pp. 88-99, Vienna, Austria, Sep 2012 (Acceptance rate: 33%)
- Negar Hariri, Bamshad Mobasher, Robin Burke, Yong Zheng. "Context-Aware Recommendation Based On Review Mining", Proceedings of the 9th Workshop on Intelligent Techniques for Web Personalization & Recommender Systems held in conjunction with the 22nd International Joint Conference on Artificial Intelligence (IJCAI), pp. 30-36, Barcelona, Spain, July 2011
Others
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Newsletter
- Yong Zheng, Hanna Hauptmann, Guibing Guo. "ACM Conference on Recommender Systems September 18--22, 2023 at Singapore".
ACM SIGWEB Newsletter. 2023, Summer, Article 2 (Summer 2023), pp. 1-4, ACM
- Yong Zheng, Hanna Hauptmann, Guibing Guo. "ACM Conference on Recommender Systems September 18--22, 2023 at Singapore".
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Technical Reports
- Yong Zheng, Kumar Neelotpal Shukla, Jasmine Xu, David (Xuejun) Wang, Michael O'Leary. "MOPO-LSI: A User Guide", CoRR abs/2307.01719. July, 2023
- Yong Zheng, David (Xuejun) Wang. "Multi-Objective Recommendations: A Tutorial". CoRR abs/2108.06367. Aug, 2021
- Yong Zheng. "A User's Guide to CARSKit". CoRR abs/1511.03780. Nov, 2015
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Translations
- Chapter 11: Recommender Systems in Industry: A Netflix Case Study, In Book: edited by Francesco Ricci, et al., Recommender Systems Handbook Second Edition (推荐系统手册第二版, ISBN: 9787111600756), China Machine Press, 2018; Amazon.com, JD.COM
- Several book chapters In Book: edited by Hanhua Lu, et al., Framework and Application of Shared Information and Data (共享信息与数据框架及其应用; ISBN: 7115245118), Posts & Telecom Press, Beijing, China, December, 2010; JD.COM
Open-Source Products
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Open-Source Data Sets
- ITM-Rec: An Open Data Set for Educational Recommender Systems
- DePaulMovies: A Movie Rating Dataset for Context-Aware Recommendations
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Open-Source Libraries
- MOPO-LSI: A Multi-Objective Portfolio Optimization Library for Sustainable Investments.
- DeepCARSKit: A Deep Learning Based Context-Aware Recommendation Library.
- CARSKit: A Java-Based Open-Source Library for Context-Aware Recommendations.
Invited Talks
- Invited Keynote Speech
- Yong Zheng, Yizhu Gao. "Personalized Learning: Adaptive Learning and Educational Recommendation Technologies", Invited Keynote Speech at the 4th Workshop on Eliciting Adaptive Sequences for Learning @ LAK 2024, Mar, 2024
- Yong Zheng. "Multi-Objective Optimization and News Recommendations", Invited Keynote Speech at the International Workshop on News Recommendation and Analytics (INRA) @ ACM SIGIR 2022, Spain, July 2022
- Yong Zheng. "Recommender Systems Using Multi-Objective Optimization: An Overview", Invited talk at the 1st International Electronic Conference on Information (IECI 2021), December, 2021
- Yong Zheng. "Extending Contexts to Multi-Entity Recommender Systems", Invited Keynote Speech at CARS workshop @ ACM RecSys 2020, Sep, 2020
- Other Invited Talks or Panelist
- Invited Consultant and Panelist, at the Workshop on Recommender Systems in Education held by AI.EDU Research Lab at the FernUniversität in Hagen, Germany on Nov 3, 2023
- Yong Zheng. "Multi-Criteria Ranking for Recommender Systems", Selected Speech at INFORMS Business Analytics Conference, Aurora, CO, USA, April 16-18, 2023
- Shlomo Engelson Argamon, Yong Zheng. "Demystifying Data Science for Business Intelligence: Understanding Its Landscape and Deploying It Effectively", Invited talk at AT&T, Inc. September, 2021
- Yong Zheng. "Multi-Stakeholder Recommendations", Invited talk at Morningstar, Inc., Dec, 2019
- Yong Zheng. "Context-Aware Recommendations", Invited talk at Information Retrieval Group Seminars, School of Computing Science, The University of Glasgow, UK, July 7, 2017
- Industry visit and talks "Context-Aware Recommendations" at NPAW (Nice People At Work), Barcelona, Catalunya, Spain, March 31, 2017
- Yong Zheng. "Classification: Supervised Learning". Invited Talk at College of Computing, Illinois Institute of Technology, Chicago, USA, April, 2016
- Yong Zheng. "Context-aware Recommendation: A Quick View". Invited Talk at graduate student class CSC 480 – Artificial Intelligence, DePaul University, Chicago, USA, Feb 23, 2016
- Yong Zheng. "When Contexts Meet Recommendations". Invited Talk at Leonard N. Stern School of Business, New York University, New York, USA, Feb, 2016
- Yong Zheng. "Matrix Factorization in Recommender Systems". Invited Talk at graduate student class CSC 529 – Advanced Data Mining, DePaul University, Chicago, USA, Mar 4, 2015
- Yong Zheng. "Context-aware Splitting Approaches: split users or split items?". Research Colloquium, School of Computing, DePaul University, Chicago, USA, Sep 27, 2013
- Yong Zheng. "Assist your decision-making in various situations: Differential Context Relaxation for Context-aware Recommendations". Research Colloquium, School of Computing, DePaul University, Chicago, USA, Oct 5, 2012
Sponsored Projects
YearSponsorsRoleProject Summary2023 - 2024Argonne National LaboratoryPIProject Title: Sustainable AI Models
Pending to be updated....
2022 - 2024Morningstar, Inc.PIProject Title: Multi-Objective Financial Portfolio Optimization
Summary: The process of financial portfolio optimization involves choosing the most suitable mix of assets to meet a particular investment goal. Conventional portfolio optimization primarily focuses on maximizing returns and minimizing risks while overlooking the importance of social responsibility or sustainability in financial investments. This project aims to build multi-objective financial portfolio optimization for the investment of mutual funds, where Environmental, Social and Governance (ESG) factors ara additionally taken into consideration. The project is expected to deliver an open-source library for multi-objective financial portfolio optimization, along with strategies for explanations in order to enhance transparency.
Outcomes: the MOPO-LSI library, publications in Software Impacts, ACM COMPASS 20232022 - 2024Google Cloud,
Amazon Web ServicesPIProject Title: Recommender Systems Based on Deep Learning
Summary: Recommender systems (RecSys) have been developed to alleviate overloaded information and assist users' decison making by delivering a list of recommended items tailored to user preferences. This project aims to build and evaluate effective recommendation models based on the deep learning technologies, particularly for context-aware RecSys, multi-criteria RecSys, multi-objective RecSys.
Outcomes: the DeepCARSKit library, publications in ACM UMAP 2022 and 2023, Software Impacts, IEEE Access, etc.2020 - 2021Digby's Detective & Security Agency, Inc.PIProject Title: Predictive Staffing Model for Transit Security
Summary: The Chicago Transit Authority (CTA) functions as the entity responsible for overseeing public transportation within Chicago. It is in charge of a majority of the city's bus lines, metro systems, and train services. Digby's security provides services related to reporting crimes or other occurrences. They engage in the monitoring of 151 CTA metro stations and rail yards, strategically deploying their personnel to these areas and documenting any incidents that transpire. The primary objective of this endeavor is to assist Digby's in forecasting the likelihood and locations of potential incidents. This, in turn, allows them to allocate their personnel appropriately, ensuring they are present in the correct place at the right time.
Outcomes: the project establishes a connection between IIT and Digby's, leading to the successful acquisition of multiple internship positions for our students from 2020 to 2022.2018Calamos InvestmentsPartnerCalamos Investments is a diversified global investment firm offering innovative investment strategies including alternative, equity, sustainable, multi-asset, fixed income and convertible strategies. Through the partnership with Calamos Investments, we were able to send several graduate students as interns in the company in 2018. Some students finally acquired full-time positions at this company after their graduation.Student Supervision
Students marked with * are the ones who had co-authored publications with Dr. Yong Zheng.
- PhD Students (Research Projects & Thesis)
- Diego Sanchez-Moreno* (Part-time PhD Student at University of Salamanca, Spain)
Dissertation: Improving collaborative filtering music recommender systems: a focus on user characterization from behavioral and contextual factors - Graduate Students in the Joint Program with Universities in Spain (Research Projects & Thesis)
- Maria Delgado Franco, Beatriz Blanco, Project: Grey Sheep Users In RecSys
- Arturo Pavon Estrade, Project: Personality-Aware Recommendations
- Juan Ruiz Toribio*, Project: Transparency and Fairness
- Alejandro Susillo Ridao*, Project: AI for Education
- Raquel Noblejas Sampedro, Project: Mobile Security
- Jorge Torres, Project: Group RecSys
- Gonzalo Florez Arias*; Project: Recommender Systems based on Deep Learning
- Guillermo Canete; Project: Generative Reviews
- Other Graduate Students at ITM Department (Research Projects)
- Ruthvik Kilaru, Munawar Ali, Navaneeth Kamath; Project: AI for Education
- Arnold Liu*; Project: Data Science Running Efficiency Over Computing Machines/Clusters
- Shuaiqi Zheng*; Project: Impacts on Educational Learning by the COVID-19 Pandemic
- Mili Singh*, Mayur Agnani*; Project: Identification of Grey Sheep Users In Recommender Systems
- Tanaya Dave*, Neha Mishra*, Harshit Kumar*; Project: Reciprocal Recommendations
- Shephalika Shekhar*; Project: Multi-Criteria Recommender System
- Alisha Anna Jose*; Project: Context-Aware Recommender System
- Nastaran Ghane*, Milad Sabouri*; Project: Multi-Stakeholder Recommendations
- Sridhar Srinivasan*, Kim Taehun*; Project: Malware Detection and Usage Analysis In Mobile Apps
- Archana Subramaniyan*; Project: Personality-Aware Recommendations
- Vih Dogo*, Yash Agrawal*, Shubham Sudhir Madke*; Project: Crime Predictions over the Chicago Transit Authority Services,
a collaboration with Digby's Detective & Security Agency, Inc.