Information and Decision Sciences (IDS) programs and research emphasize the critical role of information systems, operations management, and data analytics in businesses and organizations. With a faculty comprised of world-class researchers and experienced industry professionals, we are committed to educating the next generation of leaders in the cutting-edge technologies and solutions that increasingly define success in the global market.
Our program curriculum evolves to encompass ongoing technological change and its effects on business. It emphasizes experiential learning and includes real world projects that integrate foundational knowledge at the business-technology interface. Projects with industry partners are a required component for both our undergraduate and graduate programs. These projects are supported by industry sponsors and faculty who are actively engaged with the Chicago-area business community. Our programs produce well-rounded analysts, consultants, and managers who are ready to meet the growing demand for these skills in the marketplace.
Research is an integral part of what we do. Our faculty is engaged in fundamental research at the forefront of some of the most important questions faced by modern businesses and socio-economic systems. IDS faculty are active in research in three main areas: 1. Information Management and Systems, 2. Business Analytics - Machine Learning, Statistics and Optimization, and 3. Supply Chain and Operations Management.
Negar Soheili Azad
Mary Beth Watson-Manheim
J Christopher Westland
Our faculty is active in three broadly defined research areas:
Each week, IDS faculty from across the nation bring their latest research to faculty, staff, and students. Seminars are held on Fridays in 2450 University Hall from 1:45 - 3:30 p.m. unless otherwise noted.
Nagesh Gavirneni, Cornell University.
"Government-to-Government (G2G) Contracts for India's Pulses Procurement: Ad-Hoc Bargaining, Long-Term Contracting, and Supplier Diversification"
Hao Lin, University of Notre Dame.
"Freemium Pricing in Digital Games with Virtual Currency"
Diego Klabjan, Northwestern University.
"Algorithms and Convergence Analysis for Stochastic Large-scale Machine Learning Algorithms with Distributed Features and Observations"
William Cooper, University of Minnesota.
"Optimal Pricing in Multinomial Logit Choice Models with Network Effects"
Xin Chen, UIUC.
"Stochastic Optimization with Decisions Truncated by Random Variables and Its applications in Operations"
Young Tan, University of Washington.
Andreas Waechter, Northwestern University.