About DMO

Decision making is a cognitive process that involves selecting a course of action or choice from among multiple alternatives. It's a fundamental aspect of human life and is present in various contexts, ranging from everyday situations to complex professional, personal, and strategic scenarios, such as resource allocations, risk management, strategic planning, cybersecurity, supply chain management, Web information systems (e.g., information retrieval and recommender systems), and so forth. Factors influencing decision making may include cognitive biases (mental shortcuts that can lead to errors in judgment), emotions, cultural and social influences, personal experiences, time constraints, and the availability of information.

Optimization, on the other hand, is a systematic process that aims to find the best possible solution based on specific criteria. It involves mathematical and computational techniques to minimize or maximize an objective function while adhering to a set of constraints. Optimization seeks to identify the globally optimal solution, which is the best solution achievable according to the defined criteria. Multiple optimization techniques have been proposed and applied in machine learning and AI, such as convex optimization, non-linear optimization, evolutionary algorithms, multi-objective optimization, game theroies, etc.

Welcome to the Center for Decision Making and Optimization (DMO) directed by Dr. Yong Zheng, where the future of informed decision-making meets the power of cutting-edge optimization techniques. In an increasingly complex and interconnected world, the ability to make informed choices and optimize outcomes is paramount. DMO is your gateway to a world of innovative research, advanced methodologies, and practical applications that empower individuals, organizations, and communities to navigate the complexities of decision-making with confidence and precision.

At DMO, we are dedicated to advancing the science and practice of decision-making and optimization across a wide range of disciplines and industries. Our multidisciplinary team of experts combines the latest advancements in mathematics, data science and AI, as well as domain-specific knowledge to tackle real-world challenges and create tangible solutions. Whether you're a business leader seeking to enhance operational efficiency, a researcher exploring new frontiers in optimization, or a policymaker aiming to make data-driven choices, DMO is your partner in unlocking the full potential of your decisions.

Research Interests

• General Areas: Data Science, Machine Learning, Artificial Intelligence
• Decision Making (DM): Multi-Criteria DM, Group DM, Multi-Objective DM, Human-Centric DM, Personalization, Recommender Systems, etc.
• Optimization: Linear/Non-Linear Optimization, Multi-Objective Optimization, Game Theories, etc.
• Application Areas: FinTech, Education, E-Commerce, Online Streaming, Social Media, etc.

Faculties

Industry Collaborators

• David Xuejun Wang, Morningstar, Inc., USA
• Emanuel Lacić, Infobip, Ltd., Croatia

Academic Collaborators

• National Taiwan University of Science and Technology, Taiwan
• Norwegian University of Science and Technology, Norway
• University of Salamanca, Spain
• University College Dublin, Ireland
• Stuart School of Business, Illinois Institute of Technology, USA

Student Supervision

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

• PhD Students (Research Projects & Thesis)
• 2025 - Present, Jian Zhang
• 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.

Contact

Contact:	Dr. Yong Zheng
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, USA

Industry Partners

Sponsors