The UIC PhD in Business Administration with an area of emphasis in Information and Decision Sciences (IDS) offers advanced training in business statistics, machine learning and data mining, operations research and operations management. Research cutting across these disciplines is highly encouraged. Students are prepared to contribute to basic theoretical, advanced computational and/or data-driven research with equal emphasis on rigor and impact on business. Research contributions typically have an impact on operations, marketing, finance and/or accounting business functions in industries such as energy, retail, healthcare and banking.
An PhD in Business Administration with an area of emphasis in IDS equips students with analytical and methodological skills in statistics, large-scale data analysis, predictive analytics, social network analysis, operations and supply chain management, optimization, etc. We take an inter-disciplinary approach to problem solving, and our graduates are trained to take this holistic view. Today’s business challenges call for advanced graduates in both academia and industry.
The PhD program requires at least 96 credit hours for students entering the program directly from the baccalaureate and 64 credit hours for those entering from a relevant masters degree.
A minimum of 32 hours of dissertation research is required. The course requirements fall into the three categories of foundational work, research specialization and business specialization
A. Foundational courses:
The student must demonstrate proficiency in basic quantitative methods by previous course work or by taking two courses in statistics, computing, or math, depending on student’s interests. Examples of foundational courses include:
B. Research specialization courses:
A six-course depth requirement is required. The specific courses depend on the student’s interests and should be chosen in consultation with the research advisor. However, it is expected that the student gather substantial knowledge in a specific area to execute research. Qualifying exams at the end of third semester will be based on these courses or a subset thereof (see examination requirements section for details).
Students interested in machine learning, data mining, operations research, and operations management may choose from the following courses, but are not limited to them:
Students interested in business statistics should choose the following three courses:
In addition, three of the following five courses must be taken:
C. Business specialization courses.
Students are required to take four business courses outside of their research specialization. Courses can be in topics such as operations management, accounting, marketing and finance. Three of these courses must belong to the same business area. In addition to broadening each student's business exposure, these courses are especially useful for PhD students seeking academic appointments upon graduation. Some of these course requirements may be waived based on a student’s prior graduate training (e.g., MS or MBA).
Students in machine learning, data mining, operations research and operations management are expected to execute two summer research papers in the first and second summers of the PhD. Each summer paper will be advised by one or more faculty members. The performance on the first summer paper will be taken into account as part of the qualifying examination. Subsequently, students embark on their dissertation research, which can include the summer research papers.
Research and Examination Requirements
Students must pass a qualifying exam, preliminary exam (dissertation proposal), and a dissertation defense.
For students interested in operations research, machine learning and operations management, the qualifying examination is given at the end of the third semester of study and is based on foundational and specialized courses related to the area of the student’s interest and the first summer research paper.
For students specifically interested in business statistics, the qualifying exam is given at the end of the first year and is based on on STAT 401-411 and ECON 534.
The Preliminary Examination consists of the dissertation proposal examination. The preliminary committee includes at least five faculty members, not all five being from the same department.
For a full list of program requirements, visit the UIC Catalog.
Xiaowei Gong- IBM DemandTec, Foster City, CA
Inna Khagleeva- State Street Bank (Boston) risk-model evaluation group
Wendy Yu- BMO Harris Bank, Chicago
Jing Cai- BlackRock, Hong Kong
Yu Chen- BNY ConvergEx, Iselin, NJ
Ziqian Huang- Catalina Marketing, Riverwoods, IL
Nordia Thomas- Univ of Wisconsin - LaCrosse
Cindy Kao- IBM DemandTec, Foster City, CA
Jian Su- KPMG market risk group, New York, NY
Jin Zhang- Discover Financial Services, Riverwoods, IL
John Sparks- UIC Department of IDS
Yuliya Yurova- Nova Southeastern Univ., Ft. Lauderdale, FL
Yanli Cui- John Deere (financial portfolio management division), Peoria, IL
Zhizin Kang- Univ of North Carolina - Pembroke
Airong Cai- IBM DemandTec, Foster City, CA
Chen Chen- PNC, LaSalle St., Chicago
Jun Liu- Georgia Southern Univ, Statesboro, GA