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Assistant Professor

[Picture of Dr. Yong Zheng 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:
Snail Mail: Dr. Yong Zheng
Perlstein Hall RM 221
10 W 33rd Street
Chicago, IL, 60616-3792, USA
Social Media:
Résumé/Vitae: Print

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, 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

Latest News

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)
CSP 572 (Data Science Practicum)
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

Academic & Professional Services

University | Department Services

  • IIT Research Council, 2024 - Present
  • ITM Chair Search Committee, 2024
  • Director of the PhD Program in ITM Department, 2023 - Present
  • ITM Grant Search Coordinator, 2023 - Present
  • ITM Tenure Track Faculty Search Committee, 2023 - 2024
  • 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

Track | Workshop Organizations

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): 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

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

The list of full publications can be found via Google Scholar (), DBLP (), ResearchGate ().

Book Chapters

Editorial Publications

Journal Publications

Conference Tutorials

Refereed Conference Publications

Others

  • Newsletter
  • Technical Reports
  • 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
    • DePaulMovies: A Movie Rating Dataset for Context-Aware Recommendations
  • 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. "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

Sponsored Projects

Year
Sponsors
Role
Project Summary
2023 - 2024
Argonne National Laboratory
PI
Project Title: Sustainable AI Models
Pending to be updated....



2022 - 2024
Morningstar, Inc.
PI
Project 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 2023
2022 - 2024
Google Cloud,
Amazon Web Services
PI
Project 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 - 2021
Digby's Detective & Security Agency, Inc.
PI
Project 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.
2018
Calamos Investments
Partner
Calamos 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)
    • 2024 - Present, TBA
    • 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, 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
    • Paula Labandeira Campos; Project: Multi-Criteria Recommender Systems

  • 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.