decision science phd online

Ph.D. Program

Decision Sciences

Duke's Fuqua School of Business

The Ph.D. program in Decision Sciences at Fuqua prepares students to pursue cutting-edge research under mentorship of our faculty. The training and research themes in our Ph.D. Program is comparable to that of top Ph.D. programs in operations research and management science with a strong methodological and rigorous component. The Decision Sciences Ph.D. program is primarily intended to prepare graduates for academic research careers, though positions in industry are also a possibility. Prospective Ph.D. students with strong mathematics background and a desire for theoretical research in areas of decision sciences and operations research are encouraged to apply.

The interdisciplinary nature of our program leads students  to take courses and interact with students and faculty from many other areas around Fuqua and Duke University. Our Ph.D. students take graduate-level courses in applied probability, computer science, decision sciences, economics, mathematics, operations research, and statistics as the foundation upon which to build a program of original research culminating in a dissertation. No previous course work in business administration is necessary or expected. In addition to Ph.D. courses offered by Decision Sciences faculty , our students are expected to take graduate courses at Fuqua School of Business, and at Duke computer science, economics, mathematics, and statistics departments. Programs of study and research are individually designed to fit each student’s interests and abilities.

Admissions:

Applications can only be submitted through Duke Graduate School . Full details about application procedures, academic regulations, deadlines, and the like can be found at the Duke Graduate School website. When completing the application, please select Department/degree: “Business Administration-Ph.D.” and Specialization “Decision Sciences.” (Late applications may be considered in exceptional circumstances; please contact Professor David Brown , the Ph.D. program coordinator for Decision Sciences).

Successful applicants will demonstrate a strong mathematical background and desire to pursue research compatible with our program. (Applicants primarily interested in descriptive, empirical or experimental research should consider applying to a different Ph.D. Program at Fuqua.)  All aspects of the application package are important: statement of purpose, transcripts and grades, standardized test scores (GRE is preferred to GMAT), recommendations from faculty, etc. Decision Sciences faculty make admission decisions, typically by mid-March. All admitted students are given a full tuition grant and a generous living stipend for five years, provided their progress is satisfactory.

Additional Information:

• Online Application
• Fuqua Ph.D. Program
• Decision Sciences Ph.D. Program Progress Guidelines

PhD Program

• Curriculum/Program Requirements
• Current Students
• Research and Awards

School of Engineering

Industrial and systems engineering, decision sciences and engineering systems, ph.d..

Graduate Program Director, Ph.D. Program: Jennifer Pazour ; Catalog 23-24 Link

The ISE doctoral program prepares students with the ability to create and apply new mathematical, computational, and statistical approaches to novel, cutting-edge applications of ISE. This fact allows our Ph.D. graduates to pursue successful careers within academia, industry, and government. Graduates of the ISE doctoral program receive a Ph.D. degree in Decision Sciences and Engineering Systems (DSES) - a name that can be attributed to the department's history in interdisciplinary approaches to solving critical, practically-motivated problems. In fact, the department itself was founded in 1987 under the DSES name and brought together faculty from mathematics, engineering, and management. The interdisciplinary nature of ISE research is a strong theme within the department and ISE faculty are examining problems in a broad set of application areas including disaster response, adaptive supply chains, homeland security, and team decision-making.

Our Ph.D. program offers both unique research and educational experiences for our students. The research pursued by our students fits into an important theme of RPI: "Why not change the world?" Our Ph.D. students are applying the intellectual strengths of ISE to critical challenges faced by the world over the next century, especially in the areas of disaster response and adaptive supply chains. We invite you to learn more about our research here . The educational experiences offered to our Ph.D. students, especially those interested in a career in academia, help to prepare them to educate 21st century students. These experiences include the potential to create "virtual office hours" that can be blended into the traditional classroom experiences for our undergraduate students.

The impact of these experiences have lead our recent alumni to great positions in academia and in industry. You can learn more about how our ISE Ph.D. program has prepared our recent alumni for their careers by looking at the profiles of recent PhD graduates . Doctoral Degree Requirements

• Plan of Study approved by PhD program director and Dean of the Graduate School
• Average GPA 3.5 or better
• Doctoral Qualifying Exam: A short version of Doctoral Candidacy Exam document, evaluated by two ISE faculty that are not the advisor.
• Doctoral Candidacy Exam (within one year after passing DQE)
• Doctoral Dissertation
• Oral defense

Average time to dissertation is around four years For details, please refer to Ph.D. Program in Decision Science and Engineering Systems .

Click here to view a recorded webinar from December 18, 2023 about the Ph.D. program and application process.

ISE PhD Award Descriptions

There are three awards for which current ISE PhD students are eligible to apply for and to receive as a student. The ISE Graduate Student Research Award recognizes scholarly contributions published in top-tier academic journals. The ISE PhD Outstanding Contributions to Education Award recognizes PhD students that have contributed significantly to undergraduate education during their time in the department. The Graduate Student Travel Award (partially) supports PhD students presenting their research at conferences.

ISE Graduate Student Research Award

The ISE Graduate Student Research Award will be given to any PhD student that has been lead author on an accepted publication, before the official receipt of their PhD, in a top-tier journal in industrial and systems engineering or related fields. The research conducted for this journal paper must have occurred while a PhD student at RPI and must be published in a top-tier academic journal. Evaluation criteria for the receipt of this award includes the quality of the research, the quality of the journal (particular emphasis will be given to articles published in the journals of professional societies including, but not limited to, INFORMS, IISE, IEEE, ACM, SIAM, and ASCE), and the contributions of the student to the research. There is a $500 cash prize associated with this award and a student is eligible to receive the award multiple times. In order to apply for this prize, you must submit a formal acceptance email to the PhD program director and have your faculty co-authors (if applicable) submit a letter of support describing the quality of the journal and your contributions to the research.

ISE PhD Student Outstanding Contributions to Education Award

The ISE PhD Outstanding Contributions to Education Award will be given to a PhD student that has made a contribution, in a significant fashion, to undergraduate education at RPI. Contributions are broadly defined and could include: (i) outstanding work as a teaching assistant for an undergraduate course, (ii) the creation of online learning modules and materials in order to supplement the learning experiences of our undergraduate students, or (iii) co-supervising undergraduate research projects with faculty in the department. There is a $500 cash prize associated with this award. In order to apply for this prize, you must submit at least one letter of support describing your contributions to education from a faculty member and a one-page reflective statement on your personal opinion on the impact of your contributions. This prize will be awarded once a year at the end of the spring semester.

ISE PhD Student Travel Award

The ISE PhD Student Travel Award is to provide partial support in order for our PhD students to present their research at conferences and learn about current advances in their chosen field. There will be up to 4 awards per fiscal year, each receiving $750 in support. Note that students can still apply for the Office of Graduate Education travel awards to cover additional costs. We encourage students to apply for these awards in August for any conference in the coming academic year as it is likely the funds will be spent quickly. In order to apply for this support, a student must submit the following items:

• The title and abstract of your planned presentation. This should follow the formatting requirements required by the chosen conference in terms of word count and structure.
• Current vita of the applicant and an unofficial transcript.
• A one-page description describing how participation at the conference will support their professional development. Discuss details in terms of target research communities, networking, session attendance and presentation skills.
• Lastly, students or their advisors should verify that funds are available to cover any costs incurred above the $750 travel award.

Review criteria for this award includes: (a) the quality of the research in the proposed abstract, (b) the academic achievement of the student, (c) the appropriateness of their plans for the conference with respect to their PhD studies and career goals, and (d) how close the student is in terms of completing their PhD and reaching the job market.

PhD Graduate Opportunities

Current PhD students, please visit this link for graduate opportunities:  CIEADH Related New PhD Opportunities .

Industrial and Systems Engineering Department

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Rensselaer Polytechnic Institute

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Staff Directory

PhD in Information & Decision Sciences

The PhD program in the department of Information and Decision Sciences is among the top-ranked programs in the country. The Carlson School of Management at the University of Minnesota is widely recognized as a pioneer in the study of management information systems.

Field-Leading Research

The  faculty bring diverse expertise to the department and publish their research in numerous field-leading journals. The department is also the home of the highly respected journal, MIS Quarterly. Faculty expertise spans various topics, including:

About the Program

Students here build on storied academic traditions. The University of Minnesota was the first school in the United States to establish a doctoral program in management information systems and continues to be one of the top five programs in the world.

The IDS faculty are leaders in their fields and their research is published in numerous top academic journals. The department is also the home of the highly respected journal, MIS Quarterly.

Carlson School of Management Information & Decision Sciences PhD requires 40 credits coursework, including IDSc seminars and supporting/methodology courses.

The students in the IDS PhD program come from a variety of backgrounds, including computer science, engineering, mathematics, statistics, and business. They are united by their shared interest in using information and technology to solve real-world business problems.

Management Information Systems Research Center

PhD students enjoy strong support from department faculty and regular interaction with distinguished speakers from around the world. Guest lecturers present at weekly seminars and other events hosted by the department and its related research center, the Management Information Systems Research Center.

Graduate Placement Success

Graduates of the PhD program in information and decision sciences have continued their teaching and research careers at Boston University, Indiana University, Penn State University, University of Wisconsin at Madison, University of Illinois at Urbana-Champaign, and other respected institutions.  

Alumni Perspectives

“The Carlson School has been an epicenter of academic research activity in management information systems for decades. Not only does it boast of distinguished scholars as its faculty but it has also shaped the careers of hundreds of IS scholars who now hold prestigious leadership positions in universities across the world. You get access to these people and their wonderful minds through an IDSc PhD here. The program offers excellent infrastructural support and access, diversity in the student pool, teaching resources and opportunities, and an affordable, cultured, safe, and friendly city to live in. Perhaps the greatest virtue of the IDSc program is a feeling of scholarly camaraderie across the faculty and PhD students, encouraging the free questioning of ideas and frequent intellectual debates.”

Assistant Professor in Operations and Information Management Wisconsin School of Business John and Anne Oros Term Professor

More about Yash Babar

Zachary Sheffler

“The PhD in Information and Decision Sciences gave me the tools and connections that I needed to develop as a researcher, while also affording me the freedom to define my own research agenda and interests. The diversity of expertise in the department gives students a variety of perspectives from which they can approach problems. This, combined with the high level of rigor, offers PhD students excellent preparation for jobs in academia.”

Assistant Professor in Operations & Information Management Isenberg School of Management at the University of Massachusetts Amherst

More about Zachary Sheffler

Get in touch

PhD Coordinator

Department Chair

Our Community

A Community of Scholars   The Information and Decision Sciences department also offers a highly successful Master of Science in Business Analytics (MSBA) program, an MIS undergraduate program ranked as one of the top-three programs in the United States, and various MBA courses. PhD students are exposed to these curricula via teaching opportunities that will help jump-start their own career in business education.

Collaboration with Industry The Twin Cities area is home to a dynamic business community that includes 17 Fortune 500 company headquarters as well as start-ups and entrepreneurs. The Carlson School is closely connected with the local industry, providing many opportunities for research collaboration with industry partners.

In a Vibrant, Modern Metro The Twin Cities of Minneapolis and St. Paul offer lakes, parks, bike trails, great dining, professional sports, world-class theaters and museums, and many other amenities. The Twin Cities are routinely ranked as one of the best places to live in the United States. The University's lively urban campus overlooks the Mississippi River, with convenient rail connections to both downtown districts and the airport.

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• Social and Decision Sciences

Dietrich College of Humanities and Social Sciences

Graduate program overview, the social and decision sciences doctoral program emphasizes multi-disciplinary approaches to complex problems..

One hallmark of the program is that it is research-centered. The small size of the program makes it possible for students to work closely with its internationally distinguished faculty on diverse projects and to engage in research at the outset. A second hallmark of the program is its flexibility.

Although there are core requirements for all students, the program is designed to make it easy to combine interests in several academic areas.

SDS offers seven areas of focus for its Ph.D. program:

• Behavioral Decision Research
• Cognitive Decision Science
• Behavioral Marketing and Decision Research (Joint with the Tepper School of Business)
• Behavioral Economics (Joint with the Tepper School of Business)
• Psychology and Behavioral Decision Research (Joint with the Department of Psychology)
• Medical Scientist Training Program MD-PhD (Joint with the University of Pittsburgh School of Medicine)

Students may also create an individually tailored program.

Each of the doctoral fields of study have the same general requirements and milestones. The first stage of requirements is known as precandidacy for the Ph.D.

To reach precandidacy, students must:

• Complete a minimum of twelve Ph.D. level courses, including four courses in methodology;
• Attend the first two semesters of the Social and Decision Sciences Ph.D. seminar, which is not counted as part of the above twelve courses;
• Complete a research paper by May of the second year (maximum 27 months);
• Qualifying exams due by January of the third year, but more typically by beginning of August of the second year (maximum 29 months);
• Dissertation proposal due by beginning of August of the fourth year (maximum 48 months).

Students achieve candidacy for the Ph.D. upon completion of the above requirements. The remaining Ph.D. requirements include writing and defending a doctoral dissertation within a recommended five years after entry into the program.

If you have general questions about the SDS Graduate programs, our application page includes several "frequently asked questions." You may also send your questions via email, to the appropriate contact found on the right.

Graduate Program Contacts

• John Miller , Chair of the Graduate Admissions Committee
• Gretchen Chapman , SDS Department Head
• Connie Angermeier , Coordinator of Student Programs: Ph.D. students' academic audits, SDS course scheduling, and all registration questions
• Jasia March , Administrative Coordinator: for all other Ph.D. questions
• For questions regarding our Ph.D. program and application process, contact us at [email protected]

Learn more about our Ph.D. Students

• Current SDS Ph.D Students
• Ph.D. Students on the Job Market
• Ph.D. Alumni

• Centers and Institutes
• School of Public Health
• Harvard University
• Beyond Harvard

Doctoral Program

The Harvard PhD Program in Health Policy , awarded by the Faculty of Arts and Sciences, is an interdisciplinary collaborative program among six Harvard University faculties. CHDS is home to the decision sciences concentration of the program. Read about the program’s decision science alumni.

Meet our students, learn about their research, activities, and interests.

Download concentration guide and explore main decision science  courses .

Selected resources are curated and posted to support our students.

PhD Program Applicant Information

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Behavioral Decision Making

The faculty span a broad range of areas, including behavioral economics, cognitive and social psychology, marketing, organizational behavior, behavioral finance, behavioral strategy and public policy. Opportunities exist to work with scholars from neighboring disciplines such as law, medicine and public health. The program emphasizes collaboration and requires students to work on projects with multiple faculty across subject areas, and provides flexibility for students regarding the job markets for which they prepare.

During the first two years of the program, students take coursework in basic methodology/statistics, as well as behavioral economics, choice architecture and judgment and decision-making. Students also take courses in an area of professional focus in preparation for the job market of their choice, such as marketing, organizational behavior, finance or strategy. Students will also attend the Behavioral Decision Making Speakers series, which brings in top decision scholars from around the world to discuss their research. Students are expected to present their research every year to the rest of the area and give feedback on other presentations at the weekly behavioral lab meetings. Through active intellectual interchange, students become adept at developing and evaluating behavioral research and become exposed to a wide array of methods, behavioral insights and research applications. Students are expected to maintain an active research program throughout the course of their graduate studies.

At the end of each of their first two years of study, students are required to submit a paper, either writing up a completed research project or providing a detailed proposal of a research project they are interested in conducting. Each of these two papers must be written in collaboration with a different area faculty member, ensuring that students are exposed to multiple perspectives, paradigms and approaches to research, and that each student has multiple mentors. At the end of their second year, students will take a qualifying exam, which will require them to demonstrate, through the criteria below, that they have mastered the essential skills for behavioral science research:

• Read a research paper by another scholar and provide a critical review of the strengths and weaknesses of that paper
• Design a study to test a novel hypothesis
• Analyze a novel data set and write up a results section

By the end of their fourth year, students must advance to candidacy for a Ph.D. by successfully proposing a dissertation project that details a plan of important, novel, independent research to a committee of faculty, and having that proposal formally approved. Finally, to receive a Ph.D. students must complete a dissertation according to university requirements.

Explore the Program

Monica Peña

Faculty Support Staff Email: [email protected] Phone: (310) 825-2507

Area Chair Email: [email protected]

Hengchen Dai

Ph.D. Liaison Email: [email protected]

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Harvard Ph.D. Program in Health Policy

• Decision Sciences

Concentration Chair:   Jane Kim

Students in the Decision Sciences concentration can expect to gain skills in quantitative techniques that are used for informing decision-making at the individual and population levels, including decision analysis, risk analysis, cost-benefit and cost-effectiveness analysis, disease and policy simulation modeling, and behavioral decision theory. Examples of the type of research they pursue includes evaluating the harm-benefits tradeoff of new medical technologies or pharmaceuticals, modeling the cost-effectiveness of public health policies, and the measurement of health preferences, including quality of life. After they graduate, these students most often work in academia, but also in industry or health care consulting. An important difference between this concentration and other tracks is that decision science research aims to quantify tradeoffs of harms versus benefits to directly inform a decision being made under conditions of uncertainty.

Decision Sciences Curriculum Guide

• Curriculum Overview
• Methods for Policy Research
• Political Analysis
• Core Course in Health Policy
• Policy Areas
• Joint Degrees

Decision Science

Laura L. Carstensen

Geoffrey Cohen

Justin Gardner

Michele Gelfand

Tobias Gerstenberg

James Gross

Brian Knutson

Hazel Markus

Jay McClelland

Anthony Norcia

Russell Poldrack

Ewart Thomas

Jeanne L. Tsai

Anthony Wagner

PhD Students

Sakaria Laisene Auelua-Toomey

Lynde Folsom

Leili Mortazavi

Andrew (Joo Hun) Nam

Eric Neumann

Jun Hwan (Joshua) Ryu

Shawn Schwartz

Tara Srirangarajan

Joshua Wilson

Postdoctoral Scholars

Elizabeth blevins.

Michael I. Demidenko

Lara Kirfel

Research staff.

Logan Bennett

Joshua William Buckholtz

Rachel Calcott

Golijeh Golarai

Tyler J Matteson

Julia Proshan

Jaime Ali Holguin Rios

Kylie Yorke

• Youth Program
• Wharton Online

Operations, Information and Decisions

Wharton’s program in operations, information and decisions emphasizes research on real management problems and maintains a balance between theory and implementation..

Wharton’s program in Operations, Information and Decisions emphasizes research on real management problems and maintains a balance between theory and implementation. The faculty trains scholars in decision making, information systems and operations management.

Our faculty leads in the development and application of an innovative blend of analytical and empirical approaches to important problems facing the private and public sectors, including the design, development, and evaluation of:

• behavioral approaches to individual and managerial decision making;
• information systems as a means of commerce and of decision making; and
• operations for the fulfillment of demand and broader economic and social needs.

Our PhD program provides a unique mix of behavioral, economic, statistical and analytical training to its students, and its strength is reflected in our students’ record of placement and achievement.

Three Areas of Specialization

Decision Making (DM)

What factors influence human judgment and decision-making? Why and when are people prone to judgement errors and biases? What kinds of interventions will help people make better decisions, or improve human welfare? Our interdisciplinary Decision-Making PhD program focuses on training students to conduct and publish academic research that helps to answer these important questions. Along the way, students receive rigorous quantitative/statistical training and acquire a deep understanding of the literature on judgment and decision-making, significant exposure to the fields of psychology, economics, organizational behavior, and marketing.

Information Systems (IS)

The Information Systems PhD Program covers a broad range of research interests, from the development of detailed analytical and information-technology-based methods for managing complex organizations to the broader economic evaluation of the impact of organizational and market-based use of information systems and information-based strategies.

Operations Management (OM)

The Operations Management PhD Program focuses on the processes that define an organization’s outputs, as well as the methods commonly used to analyze these processes. Students specializing in OM are interested in a wide range of functions, including operations strategy, product and process design, technology management, capacity planning, and supply chain management.  Their work similarly covers a wide range of organizations and industries, including education, health care, hospitality, manufacturing, distribution, and retailing.

Students must complete 16 course units (CU’s) of classes to graduate.  They may earn up to 4 CUs of credit for courses previously completed as a part of a master’s degree or PhD program, with the approval of the PhD Coordinator and the Wharton Doctoral Program Office.

For more information on courses and sample plan of study,  please visit the University Graduate Catalog .

Get the Details.

Visit the Operations, Information and Decisions website for details on program requirements and courses. Read faculty and student research and bios to see what you can do with an Operations, Information and Decisions PhD.

before you go

Help us keep in touch — it won’t take long, curriculum - decision sciences phd.

The Decision Sciences PhD curriculum requires a course of study that is designed to fit your research area. You’ll be expected to take all PhD courses offered in the Decision Sciences Academic Area as well as additional courses, identified for you specifically, that span decision theory, operations research, optimization and probability.

Course Requirements

Course schedule is designed based on each student’s academic background, needs, and interests. Students are required to take three PhD courses per semester during the Fall and Spring semesters in their first two years of PhD studies. The sequence of these courses will be tailored to each student’s personal program of study.

Students are expected to take all PhD courses offered in the Decision Sciences Academic Area as well as additional courses that span decision theory, operations research, optimization and probability. Academic Area courses currently include Bayesian Inference and Decision, Convex Optimization, Dynamic Programming and Optimal Control, and Stochastic Models. In addition, students are encouraged to choose electives that match their specific research interests from a wide range of courses offered by other academic areas at Fuqua, as well as at other departments of Duke University, such as the Departments of Computer Science, Economics, Mathematics, and Statistics. Faculty mentors will assist students in identifying appropriate courses.

First and second-year papers

Summer terms after the first and second year of PhD studies are devoted to writing original papers. For the first-year paper, which could be literature review or original research, the student should find a Decision Sciences faculty mentor by the end of the Spring semester of their first year. The paper is due by the end of the first year of the PhD studies, i.e., before the first day of the Fall semester of the student’s second year, and needs approval by the faculty mentor. The student needs to find a Decision Sciences faculty mentor for the second-year paper by the start of Spring semester of their second year. This original research paper is due by the end of the second year of the PhD studies, i.e., before the first day of the Fall semester of the student’s third year.

Qualifying exam

Students are required to present the first-year paper in the Decision Sciences seminar during the Fall semester of the second year. The Decision Sciences Ph.D. Program Progress Committee will examine the first-year paper, the student’s statement, grades, and feedback from the student’s first-year paper faculty mentor, and other faculty who have had the student in class and/or have had the student as a research or teaching assistant.

Research and teaching assistantships

A critical part of the program is forming professional relationships with faculty members and learning about the research and teaching processes. All students are expected to help faculty with research and teaching as needed. Assignments are made by the PhD program coordinator in consultation with DS faculty. (General program requirement is 10 hours per week for students in years two through five, and 4 hours per week during year one. Hours worked above these amounts generally qualify for hourly compensation at pre-specified rates established by Fuqua.)

Preliminary Examination

The preliminary examination in the Decision Sciences PhD program takes place during the Fall semester of the student’s third year. The student is required to present an original research paper, typically a revision and improvement of the second-year paper. The Preliminary Examination Committee will offer comments on the quality of the work as well as the potential of the presented research. In addition, the committee will review the student’s second-year course grades, paying particular attention to essential courses in operations and assess the student’s overall performance in the doctoral program, taking all of this information into account when determining whether the student passes the preliminary examination.

Dissertation Proposal

The student should form a dissertation committee no later than the Fall semester of their fourth year, with the proposal occurring in the Spring semester of the fourth year. Students have until the end of the summer of the fourth year to complete this requirement per graduate school requirements.

Dissertation Defense

The dissertation will be a natural outgrowth of student’s research throughout the PhD program. The dissertation defense (also known as the “final examination”) will be conducted by the end of the fifth year of the student’s PhD studies. At this final milestone, it is assessed whether the student has shown sufficient mastery of methodology and research to submit their dissertation and be granted a PhD from Duke University.

Sample Program Schedule

Asterisk indicates key milestone (qualifying, preliminary, and final exams

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PhD in Business Administration: Information and Decision Sciences (IDS) Emphasis

Chicago's Public Research University in the Heart of a World-Class Business City

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.

A 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.

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• Current Students Learn more about the program and see whether you would be a good fit here at UIC by reading about our current students’ backgrounds and research interests.
• Program Faculty Browse our full-time faculty. Contact information for adjunct faculty can be found on the university department roster.

Important Dates Heading link Copy link

The application deadline for this program is January 15.

Admission Heading link Copy link

Admission is competitive and applicants are considered on an individual basis. The college considers applications for full time degree seeking status for the Fall term only. The deadline to submit the application, fee and required materials is January 15. Please see the admissions section of our catalog for application requirements.

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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:

• Applied Statistical Methods (STAT 381-48)
• Statistical Models and Methods for Business Analytics (IDS 575)
• Data structures and algorithms (CS 401/CS 501/IDS 517)
• Real Analysis (MATH 414)

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:

• Deterministic Optimization, Stochastic Optimization, Machine Learning/Data-Mining, Stochastic Processes, Network Analysis, Advanced Predictive Models (IDS 576)
• Big Data Analytics (IDS 561)
• Advanced Data Management (IDS 521)
• IDS Seminar (IDS 595)

Students interested in business statistics should choose the following three courses:

• Introduction to Probability (STAT401)
• Statistical Theory (STAT 411)
• Econometrics (ECON, 534)

In addition, three of the following five courses must be taken:

• Econometrics II (ECON 535)
• Bus Research & Forecasting I (ID S582/ECON 537)
• Bus Research & Forecasting II (IDS 583/ECON 538)
• Research Methodology I (IDS 577)
• Research Methodology II (IDS 578)

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).

Research Requirements 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.

Qualifying Exam 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.

Preliminary Exam 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 .

Placements Heading link Copy link

2023 placements.

• Parshan Pakiman, Postdoc, University of Chicago
• Eren Ozbay, Discover Financial Services

2021 Placements

• Mehrnaz Amjadi, Senior Data Scientist, NVIDIA
• Danial Mohseni Taheri, Senior Data Scientist, Walmart Labs

2020 Placements

• Cheng Chen, University of Wisconsin at Milwaukee

2019 Placements

• Dachuan Chen, Nankai University

2014 Placements

• Xiaowei Gong, IBM DemandTec, Foster City, CA
• Inna Khagleeva, State Street Bank (Boston) Risk-Model Evaluation Group
• Wendy Yu, BMO Harris Bank, Chicago

2012 Placements

• Jing Cai, BlackRock, Hong Kong
• Yu Chen, BNY ConvergEx, Iselin, NJ

2011 Placements

• 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

2009 Placements

• John Sparks, UIC, Department of IDS
• Yuliya Yurova, Nova Southeastern University, Ft. Lauderdale, FL

2008 Placements

• Yanli Cui, John Deere (Financial Portfolio Management Division), Peoria, IL
• Zhizin Kang, University of North Carolina – Pembroke

2007 Placements

Airong Cai, IBM DemandTec, Foster City, CA

2006 Placements

• Chen Chen, PNC, LaSalle St., Chicago
• Jun Liu, Georgia Southern University, Statesboro, GA

Judgment and Decision Making Track

In this section.

• Degree Requirements
• What We Look For

The Judgment and Decision Making track in the PhD program in Public Policy provides a curriculum for doctoral students seeking rigorous interdisciplinary training in psychological science, behavioral economics, and decision science, with a focus on understanding and improving public policy.  A typical program of study includes emphasis on descriptive and normative approaches as well as on prescriptive interventions.

Graduates will be prepared for academic teaching and research positions in public policy schools, interdisciplinary programs (e.g., management, decision science), and traditional behavioral science departments (e.g., psychology), as well as for analytic positions in industry, think tanks, government, and international institutions.  

HKS has a strong core of faculty specializing in judgment and decision-making research as well as faculty specializing in applied policy domains where students may wish to focus.  Intrinsic to the program are teaching and research opportunities with leading scholars at HKS and elsewhere at Harvard. 

Simple intervention helps build emotional resilience during COVID-19

PPOL PhD student Ke Wang led a study to determine whether interventions to mitigate negative emotions and increase positive emotions could improve psychological resilience and help people respond better to adversity. Professor of Public Policy, Decision Science, and Management Jennifer Lerner , who is Wang’s advisor, was also an author in the study.

Master of Behavioral and Decision Sciences

Learn the theory, apply the tools, and make a difference

Penn’s Master of Behavioral and Decision Sciences (MBDS) is informed by contemporary theories and research methods of behavioral economics, decision sciences, network analysis, and public policy. Our program equips students with theoretical and practical tools to address a variety of real-life problems, putting you ahead of the curve in a growing field of study.

Our interdisciplinary degree prepares you to understand how individuals and groups make decisions, and how to effect those decisions. Housed in the School of Arts and Sciences, the MBDS program is rooted in the social sciences—the skills we teach help you make a positive, sustainable impact in your area of interest.

Penn's MBDS program is a STEM-designated program, coded as 30.1701.

Please note: GRE test scores are required for applicants who have less than five years of professional experience.

Impact decisions and behaviors in a variety of fields

Hear from Master of Behavioral and Decision Sciences Founding Director Cristina Bicchieri about how this unique theoretical and applied master’s degree provides the understanding and tools students need to enact behavioral change in individuals and in organizations.

If you are having trouble viewing this video, you can  watch it on YouTube .

Exclusive projects and industry engagement

The Master of Behavioral and Decision Sciences (MBDS) program at the University of Pennsylvania is a training ground for the next generation of applied behavioral scientists. Opportunities to engage with our industry affiliates—such as applied projects, skills-focused workshops, and industry-expert lectures and panels—open new perspectives and professional connections for our students.

Design Challenge »

Center for Social Norms and Behavioral Dynamics »

All industry opportunities »

Representing students in the 2023-2024 cohorts

Upcoming application deadlines

The application deadline for fall 2024 is February 1, 2024.

The priority admission deadline for fall 2025 is December 1, 2024. The regular deadline is February 1, 2025.

MBDS information session

Meet our program team and hear more about the MBDS curriculum, application process, faculty, and more.

Center for Social Norms and Behavioral Dynamics

Led by MBDS Founding Director Cristina Bicchieri, this research center aims to support positive behaviors on a global scale.

Ready to apply to MBDS?

Have a question about MBDS?

McNeil Building, Rm 438 3718 Locust Walk Philadelphia, PA 19104-3335

(215) 746-3618 [email protected]

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Decision Sciences

Depending on their backgrounds, students may also be required to take one of the doctoral statistics sequences within the Kelley School of Business. Students will also be required to take the basic economics sequence: economic modeling, game theory, and econometrics. Students without prior teaching experience in the U.S. will take one short course (X630) on teaching prior to teaching their first course.

Decision sciences doctoral students complete 18 credit hours of coursework within their major area. Because PhD students in this area are part of the Decision Sciences/Operations Management Doctoral Consortium , this coursework consists of both decision sciences and operations management courses. Specifically, students take the basic operations research sequence and the basic operations management sequence in their first two years. In addition to the basic courses, decision sciences majors generally also take topics courses. As with other business majors, students supplement the program with minor courses (9 credit hours), and methodology and analysis courses (9 credit hours).

Required Courses

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Economics and Decision Sciences

The economics and decision sciences specialization prepares students for high quality research on a wide array of both theoretical and empirical topics in economics. .

The Department of Economics and Decision Sciences at HEC Paris offers a Ph.D. in Economics program inclusive of a five-year fellowship . Our students are trained to the highest international standards to secure competitiveness in the international job market, spanning both academic and policy-making institutions.

The program

The first two years of the program expose students to cutting-edge courses in Economics as part of the Master in Economics , a collaborative postgraduate program jointly offered by HEC, ENSAE, and Ecole Polytechnique. This collaboration assembles the best researchers from the Economics departments of the three schools and HEC's department of Finance, providing students with unique and invaluable support in developing their research. In this vibrant and rich academic environment, students have significant flexibility and a broad range of options in assembling their study plans, allowing them to select courses that most effectively complement their initial background and desired research profile.

The subsequent three years are primarily focused on the completion of the thesis, promoting a rigorous and comprehensive approach to research. The high faculty-to-student ratio ensures that each student is actively involved in the life of the department, so that interactions happen continuously, far beyond the formal supervisor-student relationship. Integral to the training, the program encourages periods of visiting research at globally renowned institutions, enabling students to better understand the international academic community in which they will grow as researchers, particularly as they approach the job market towards the end of their studies. A variety of funding sources will ensure all the resources needed to a successful competition of any research in economics.

The department offers a rich array of research events that foster intellectual development and collaboration. One cornerstone is our weekly research seminar , where accomplished researchers from various universities share their latest findings, providing exposure to diverse perspectives and cutting-edge research. Furthermore, our faculty recurrently organizes international conferences, where PhD students are encouraged to attend and take active role; these include the “ D-TEA worskhop ”, “ Firms location and Economic Geography workshop ”, and “ Salento Macro Meetings ”, to cite only few of them. Another highlight is our annual Econ PhD workshop , a lively conference organized by our PhD students, where PhD students across prominent programs in Europe and US present and discuss their work. This workshop serves as a nexus for forging connections with future researchers and colleagues, nurturing interactions that often lead to collaborative research projects. Check out the amazing program of last year’s edition !

Research topics

PhD candidates will benefit from the outstanding research quality of the Economics and Decision Sciences faculty members. Faculty members regularly contribute to prestigious economics publications, including the American Economic Review, Econometrica, Journal of Political Economy, and the Review of Economic Studies, among others, on a wide array of both theoretical and empirical topics in Economics. The department hosts prestigious research grants from highly competitive contests like the national French ANR and the European Research Council.

The following non-exhaustive list provides some ideas of the type of research done in our department:

Within the realm of decision sciences , our department engages in both theoretical and experimental research, investigating individual and group decision-making, especially when confronted with uncertainty and the passing of time. Our projects encompass a wide spectrum of topics, ranging from fundamental aspects of decision theory to pressing issues such as decision-making in the context of climate change.

The department is also engaged at the forefront of theoretical exploration in various domains, including economic theory, game theory, and applied mathematics . Conducted work extends to dynamic games, social learning, strategic experimentation, information and mechanism design, as well as social and communication networks. This research extends to applied fields such as mechanism design and industrial organization.

Our department has a focus on entrepreneurship , investigating how to boost entrepreneurial talent, the influence of peers on career choices, and the challenges related to startup financing. In the sphere of innovation , our endeavors involve identifying innovative firms and studying green innovation through the construction of new data about patenting activities. We delve  competitive forces, R&D activities, and patent allocation, and study their implications for policy.

From a more macro perspective, our research projects focus on endogenous growth , incorporating firm heterogeneity, to shed light on the aggregate consequences of resource allocation inefficiencies. In the field of monetary economics , we explore various facets of monetary policy, including the role of household and firm expectations on inflation, consumers’ search, and the intricate interactions between fiscal and monetary policies.

In the field of urban economics , we actively investigate the ramifications of technological changes, such as automation and offshoring, in shaping cities and the relationships between firm structures and capabilities. Our department maintains a strong focus on studying the future of labor , harnessing innovative data and surveys. A central theme involves understanding the transformation of local labor markets in the face of technological progress.

Please, check out our faculty web page for much more detail about faculty work!

PhD Coordinator

Current students            Department website            Placement

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Home › All Programs › Science (BA/BS)

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Bachelor of Science or Arts in Science

Bachelor of science.

Online Bachelor's Program in the Nation

- U.S. News & World Report, 2024

Public Flagship University

Quick Facts

College of Science

Program details.

The College of Science is offering a Bachelor of Arts (BA) and a Bachelor of Science (BS) in Science.  

Both degrees meet you where you are in your education and career, allowing for a flexible program where you learn the basic knowledge of the foundations of various scientific disciplines that you can easily pair with a complementary degree. The BS in Science provides additional training in foundations in science and scientific thinking. These interdisciplinary degree programs emphasize biological and physical sciences you may utilize in intersectional fields such as education, policy, law, journalism, business, development, economics, and more. They will also provide a basic STEM background for medical and health services managers, medical assistants, natural sciences managers, and entry-level science technicians.   You may choose from a variety of emphases to tailor your science education to your specific interests. Gain a foundation in science that will prepare you as an adaptive problem solver and enable you to drive social, cultural, and economic change.

As a Science BA student, you must take calculus and four semesters of another language. You must also complete five upper-division electives with at least three courses in one area. As a BS in Science student, you must take calculus and two semesters of another language. You must also complete eight electives with at least four courses in one area.  

In addition to writing, math, language, and general education requirements, you will take core courses in statistics, introductory biology, introductory chemistry and physics, as well as in one of several areas of emphasis, including earth systems and sustainability, genetics and molecular biology, biochemistry, ecology, evolution and animal behavior, psychology, neuroscience, and cognitive science. 

●    The level of math required for the BA in Science program is MATH 113 ●    Math requirements for the BS in Science program include Math 122A, Math 122B, First-semester Calculus, or Math 125 Calculus ●    Students in both programs will take a capstone course: SCI 498

*Residents of some U.S. Territories may not be eligible. Please see our Eligibility & State Authorization page for more information.

In either the BA or BS, you will take four introductory science courses, at least one from each of biology, chemistry, and physics, a statistics course, and two additional courses that are prerequisites for taking upper-division electives in one or more emphases. 

BA in Science: You may choose between PHYS 102 & 181 or PHYS 141 . For the statistics requirement, you may take Math 263 or PSY 230.

BS in Science: For the statistics requirement, you may choose to take Math 263 or PSY 230.

The curriculum for this program includes:

MCB 181 R/L: Introductory Biology I with lab

Learn about the cell and its properties, basic genetics, the immune system, and recombinant DNA technology with illustrations from bacteria, plants, animals, and humans with a lab designed to complement what students learn in the lecture portion of the course.

ECOL 182 R/L: Introductory Biology 2 with lab

Study the origin, diversity, and evolution of life, focusing on the physiology of plants, animals, and organ systems. You will explore the processes of microevolution and macroevolution, animal behavior, and the ecology of populations and communities, emphasizing biotic interactions and biogeography. The lab complements what you learn in the lecture portion of the course.

CHEM 141 & 145: General Chemistry 1

This course uses the Quantitative Approach with a lab. You will learn about the central principles of modern chemistry using a quantitative atoms-first approach, and the lab is designed to complement what you learn in the lecture portion of the course.

PHYS 102 & 181: Introductory Physics 1 with lab

Learn about the motion of particles in one and two dimensions, forces, Newton's laws, energy, momentum, angular momentum, and conservation laws, gravitation, fluids: Archimedes and Bernoulli, mechanical waves, sound, temperature, heat, heat engines, and laws of thermodynamics in this introductory course without calculus, for liberal arts students and students emphasizing the biological sciences. The lab complements what you learn in the lecture portion of the course.

PHYS 141: Introductory Mechanics

This course introduces you to Newtonian mechanics, and you will learn about the statics and dynamics of point particles, rigid bodies, and fluids. Topics include vector algebra, projectile, and circular motion; Newton's Laws, conservation of energy, collisions, and conservation of momentum; rotational dynamics and conservation of angular momentum; statics, harmonic oscillators and pendulums; gravitation and Kepler's Laws, fluid statics and dynamics.

PHYS 142: Introductory Optics and Thermodynamics

This is a freshman-level course in the fundamental properties of light and heat and related applications such as optical instruments and heat engines. It introduces you to the propagation of light and heat. Topics include temperature scales and heat, laws of thermodynamics, basic kinetic theory of gases, heat engines, elementary wave theory and sound, light as an electromagnetic wave, geometrical optics, lenses and mirrors, physical optics, diffraction and interference, and optical instruments.

Math 263: Basic Statistics or Intro to Statistics and Biostatistics

Learn to characterize data in terms of distributions, measures of center and spread, scatterplots, nonlinear models and transformations, correlation, regression, design experiments using models from probability, discrete and continuous random variables, normal distributions, sampling distributions, the central limit theorem and apply statistical inference; confidence intervals and test of significance, t procedures, inference for count data, two-way tables and chi-square procedures, inference for regression, and analysis of variance.

PSY 230: Psychological Measurement and Statistics

Learn to apply statistics to data collected in experiments and evaluate scientific hypotheses to answer questions such as “Does sleep improve memory?” and “Does having friends improve mental health?” Learn how to apply the core statistical tools in science, such as t-tests, ANOVA, regression, and Chi-square tests in controlled scientific experiments.

Earning your Bachelor of Science in Bachelor of Science or Arts in Science will build core skills, including:

• Knowledge & understanding of scientific literature
• Basic laboratory skills
• Communication of scientific knowledge
• Scientific reasoning skills
• Written & oral skills
• Application of scientific reasoning
• Foundational knowledge in online group projects
• Communications
• Medical Services
• Health Services
• Natural Sciences

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Department of Industrial Engineering & Decision Analytics [Joint IEDA/ISOM seminar] - Online Resource Allocation with Non-Stationary Customers

A novel algorithm will be presented for online resource allocation under non-stationary customer arrivals and unknown demands. We assume multiple types of customers arrive in a nonstationary stochastic fashion, with unknown arrival rates in each period. It is also assumed that customers' click-through rates are unknown and can only be learned online. By leveraging results from the resourceful contextual bandit and online matching with adversarial arrivals, we develop an online scheme to allocate the resource to nonstationary customers. We prove that under mild conditions, our scheme achieves a “best-of-both-world” result: the scheme has a sublinear regret when the customer arrivals are near-stationary, and enjoys an optimal competitive ratio under general (non-stationary) customer arrival distributions. Finally, we conduct extensive numerical experiments to show our approach generates near-optimal revenues for all different customer scenarios.

This talk is based on a joint work with Mabel Chou and Xiaoyue Zhang at NUS IORA.

Hanzhang Qin is an Assistant Professor at the Department of Industrial Systems Engineering and Management at NUS. He is also an affiliated faculty member at the NUS Institute for Operations Research and Analytics and the NUS AI Institute. His research was recognized by several awards, including INFORMS TSL Intelligent Transportation Systems Best Paper Award and MIT MathWorks Prize for Outstanding CSE Doctoral Research. Before joining NUS, Hanzhang spent one year as a postdoctoral scientist in the Supply Chain Optimization Technologies Group of Amazon NYC. He earned his PhD in Computational Science and Engineering under supervision of Professor David Simchi-Levi, and his research interests span stochastic control, applied probability and statistical learning, with applications in supply chain analytics and transportation systems. He holds two master's, one in EECS and one in Transportation both from MIT. Prior to attending MIT, Hanzhang received two bachelor degrees in Industrial Engineering and Mathematics from Tsinghua University.