Associate Professor

Associate Professor, Department of Information Technology and Management (ITM)
Director, Center for Decision Making and Optimization (DMO)
Co-Director, PhD Program in the ITM Department
ITM Curriculum Coordinator for Applied Data Science and AI

Ph.D., Computer and Information Sciences, DePaul University, USA

Office:	IIT Galvin Tower #15E3-1, 10 West 35th Street, Chicago, IL 60616, USA
Telephone:	312.567.3575
Email:	yzheng66 [at] iit.edu
Snail Mail:	Dr. Yong Zheng IIT Galvin Tower #15E3-1 10 W 35th Street Chicago, IL, 60616-5314, USA
Social Media:
Résumé/Vitae:	Print

About

Dr. Yong Zheng is currently a tenured Associate Professor at Department of Information Technology and Management, College of Computing, Illinois Institute of Technology, Chicago, USA, and he also served as a Co-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, EAIT 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

• 2024 - Present, Associate Professor (tenured), Illinois Institute of Technology, USA
• 2018 – 2024, Assistant Professor, Illinois Institute of Technology, USA
• 2016 – 2018, Senior Lecturer, Illinois Institute of Technology, USA
• 2016 – 2017, Part-Time Lecturer, DePaul University, USA
• 2015 – 2015, Data Scientist at Pandora Media, Inc., USA

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

• • 2024, PI, Artificial Intelligence Journal (AIJ) Fund to support and promote AI Research at ACM IUI 2025
  • 2024, PI, ACM SIGAI Travel Fund for ACM IUI 2025
  • 2024, PI, NSF Grant (#2437064) to support participations in ACM IUI 2025
  • 2024, PI, NSF Grant (#2427819) to support participations in ACM RecSys 2024
  • 2024, PI, Seed Grant (GPU Computing Resources) by Argonne National Laboratory
  • 2023, NSF Merit Review Panelist in the review of NSF/CISE Grants
  • 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, 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
  • 2021, Excellence in Research Award by College of Computing at Illinois Institute of Technology
  • 2021, AWS Educate Credit
  • 2021, PI, ACM SIGCHI Development Fund for ACM UMAP 2021
  • 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)
  • 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

• Sponsors & Collaborators

  

Academic & Professional Services

University | Department Services

• ITM Tenure Track Faculty Search Committee (Chair), 2024 - 2025
• IIT Campus Committee on Promotion and Tenure (CAMCOPT), 2024 - 2025
• IIT Research Council, 2024 - Present
• ITM Chair Search Committee, 2024
• ITM Tenure Track Faculty Search Committee, 2023 - 2024
• Co-Director of the PhD Program in ITM Department, 2023 - Present
• ITM Grant Search Coordinator, 2023 - Present
• ITM Tenure Track Faculty Search Committee, 2022 - 2023
• 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

• General Chair, ACM HT, USA, Aug, 2025
• Sponsor Chair, ACM IUI, USA, Mar, 2025
• Student Support Co-Chair, ACM UMAP, Italy, July, 2024
• Sponsor Co-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, The 1st International Workshop on Decision Making and Optimization in Financial Technologies (DMO-FinTech) at PAKDD 2024
• Workshop Co-Chair, Optimizing Human Learning. 4th Workshop eliciting Adaptive Sequences for Learning (WASL 2024) at LAK 2024
• Workshop Chair, Hands-on Workshop on Academic Writing by Using Latex at ACM SIGITE 2023
• 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): 2024 (Short Paper Track)
• 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): 2024, 2023, 2022, 2021, 2020, 2019, 2018
• ACM Conference on Recommender Systems (RecSys): 2024, 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
• International Conference on Artificial Intelligence in Education (AIED): 2024
• 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
• 2024 - Present, Associate Editor at Education and Information Technologies (EAIT), Springer
• 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
• 2024 - 2025, Lead Guest Editor, Special issue on AI for Financial Services and Applications @ Discover Data, Springer
• 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 (EAIT), 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 Speaker, at the 4th Workshop eliciting Adaptive Sequences for Learning (WASL 2024) at LAK 2024, Mar, 2024
• 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

Journal Publications

• Yong Zheng. "Investigating Influential Factors in Group Learning: Personality Traits, COVID-19 Lockdowns and Back-to-School Policies", Discover Education, Vol. 3, 137, Springer, 2024
• 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
• 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, Vol. 20(1):21, Springer, 2023
• Yong Zheng, David (Xuejun) Wang. "Multi-Criteria Ranking: Next Generation of Multi-Criteria Recommendation Framework", IEEE Access, Vol. 10, p. 90715-90725, IEEE, 2022
• Yong Zheng. "DeepCARSKit: A Deep Learning Based Context-Aware Recommendation Library", Software Impacts, Vol. 13, 100292, Elsevier, 2022
• Yong Zheng. "Non-Dominated Differential Context Modeling for Context-Aware Recommendations", Applied Intelligence, Vol. 52 (9), p. 10008–10021, Springer, 2022
• Yong Zheng, David (Xuejun) Wang. "A Survey of Recommender Systems with Multi-Objective Optimization", Neurocomputing, Vol. 474, p. 141-153, Elsevier, 2022
• Yong Zheng. "Context-Aware Collaborative Filtering Using Context Similarity: An Empirical Comparison". Information, Vol. 13 (1): 42, MDPI, 2022
• 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
• 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
• 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
• Yong Zheng. "Preference Corrections: Capturing Student and Instructor Perceptions in Educational Recommendations", Smart Learning Environments, Vol. 6 (1):29, Springer, 2019
• 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 Publications

Others

Conference Tutorials

• Lemei Zhang, Peng Liu, Yashar Deldjoo, Yong Zheng and Jon Atle Gulla. "Understanding Language Modeling Paradigm Adaptations in Recommender Systems: Lessons Learned and Open Challenges", The 27th European Conference on Artificial Intelligence (ECAI), Oct, 2024 (Tutorial Website)
• 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)

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

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

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

• Open-Source Data Sets
  • ITM-Rec: An Open Data Set for Educational Recommender Systems
  • OpenTable: A Data Set for Multi-Criteria Recommender Systems
  • DePaulMovies: A Movie Rating Dataset for Context-Aware Recommendations
• Open-Source Libraries
  • MOPO-LSI: A Multi-Objective Portfolio Optimization Library for Sustainable Investments.
  • MCRecKit: An Open-Source Library for Multi-Criteria Recommendations.
  • 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. "Challenges in Educational Recommender Systems", Invited Keynote Speech at the 4th Workshop on Eliciting Adaptive Sequences for Learning (WASL) @ 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

Student Supervision

Students marked with * are the ones who had co-authored publications with Dr. Yong Zheng.

• PhD Students (Research Projects & Thesis)
• 2024 - Present, Xintong Yu
• 2016 - 2020, 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 (2017), Beatriz Blanco (2021), Project: Grey Sheep Users In RecSys
• Arturo Pavon Estrade (2018), Project: Personality-Aware Recommendations
• Juan Ruiz Toribio* (2019), Project: Transparency and Fairness
• Alejandro Susillo Ridao* (2020), Project: AI for Education
• Raquel Noblejas Sampedro (2018), Project: Mobile Security
• Jorge Torres (2019), Project: Group RecSys
• Gonzalo Florez Arias* (2022); Project: Recommender Systems based on Deep Learning
• Guillermo Canete (2023); Project: Generative Reviews
• Paula Labandeira Campos (2024); Project: Multi-Criteria Recommender Systems
• Ignacio Elvira Cruz (2025): Multi-Objective Financial Portfolio Optimization
• Ignacio Hidalgo Power (2025): Risk Premium Analysis in Financial Investments


• 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.

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