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October 28, 2023

STANDS: Our revamped MS Program

October 28, 2023


The MS program in Statistics, Analytics and Data Science (STANDS) offers students a rigorous program of training in the areas of statistics, optimization, stochastic modeling, and probability. The program is designed to be flexible enough to accommodate students with different technical backgrounds and subject matter interests, and it allows students to pursue a variety of coursework in theory, methodology, computation, and applications.

The MS program in Statistics, Analytics and Data Science, formally an MS degree in Statistics and Operations Research, can function as a stand-alone, terminal, degree for individuals seeking jobs in the private or public sector. However, it also provides a valuable complement to a number of Ph.D. programs in the natural and social sciences, enhancing the credentials of students in these programs seeking academic or industry jobs. In the past, students have completed MS degrees in STOR concurrently with a Ph.D. in areas such as Economics, Sociology, Psychology, Mathematics, and Physics. Terminal Master’s students, who seek employment immediately after completion of the degree, have readily found jobs in industry and government.

Check the program website for more information.

Hiring 2023

October 10, 2023

Available Faculty Positions

October 10, 2023

Faculty Positions
Faculty Positions

The Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill has openings for three tenure-track positions at the assistant professor level in the areas of Data Science, Analytics and Probability starting July 1, 2024.

The department and university are committed to diversity, equity and inclusion, advancing the ideals espoused at We welcome applications from candidates who will add to the department’s diversity.

The University of North Carolina at Chapel Hill is an equal opportunity, affirmative action employer and welcomes all to apply without regard to age, color, disability, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, sexual orientation or veteran status.

We will begin considering candidates after November 3, 2023, and will continue accepting applications until the position is filled. The application package should include a cover letter, an up-to-date curriculum vitae, research and teaching statements, representative papers, and a graduate transcript. Applicants should arrange for four letters of recommendation. At least one of the letters should include an evaluation of the applicant’s teaching ability. Application materials and letters must be submitted in electronic form only.

Joint faculty position in Data Science (STOR/SDSS)

Candidates must possess a PhD in Statistics, Operations Research, or some closely related field by the start date of the appointment. Applicants are also expected to have a strong track record in research, teaching, and service commensurate with the level of the appointment. The successful candidate will be expected to direct an independent research program supported by extramural funding, to participate in data science activities and to teach at the undergraduate and graduate levels through the STOR department and SDSS. For further information on SDSS please visit

Faculty position in Analytics

Candidates are required to have a doctorate (or foreign equivalent) in statistics, operations research, industrial and systems engineering or a related field, with a focus on data-driven decision making, machine learning or other areas related to analytics. The Department is seeking candidates who have the potential to maintain a strong research program in analytics. A commitment to data-driven, application-oriented and interdisciplinary research will be a positive factor in the consideration of candidates. Duties of this position include teaching, research, and service. The successful candidates will be comfortable with teaching courses at both undergraduate and graduate levels in the department at the intersection of their expertise and the needs of the department.

Faculty position in Probability

Candidates are required to have a doctorate (or foreign equivalent) in Mathematics, Statistics or a related field with a focus in the area of probability theory by the start date of the appointment. The Department is seeking candidates who have strong training and an established research record in probability. Duties of this position include teaching, research, and service. The successful candidate will be comfortable with teaching courses in probability and related areas at the undergraduate and graduate levels, as well as introductory courses in the department. The potential for interaction with other groups in the department and the university will be a positive factor in the consideration of candidates.

Postdoctoral position in Networks

This position is a three-year postdoctoral fellowship starting July 1, 2024 funded by the Research training grant from the NSF, Networks: Foundations in Probability, Optimization, and Data Sciences. U.S. citizenship or permanent residency required.

The position comes with a two-course teaching load per year. The primary responsibility of the postdoctoral fellow will be to develop an independent and vigorous research program with guidance from RTG faculty members. In addition, the postdoctoral fellow will be actively involved in various activities of the RTG including mentoring of undergraduates in research and running of research seminars. Areas of interest include Probability, Optimization, Statistics, Machine Learning, Data Science.

Morgan Wood INFORMS award

October 1, 2023

Amazon SCOT – INFORMS scholarship

October 1, 2023

INFORMS scholarship

Ph.D. student Morgan Wood was recently selected as one of the winners of the Amazon SCOT – INFORMS scholarship for the 2023 INFORMS Annual meeting as well as a Bonder Scholar for the Doctoral Student Colloquium.

Workshop Funded by BIRS

September 22, 2023

Workshop at the Casa Matemática Oaxaca (CMO/BIRS)

September 22, 2023

BIRS/CMO workshop

A workshop on “Mathematical and Statistical Tools for High Dimensional Data on Compressive Networks” has been funded by the Banff International Research Station (BIRS) to run at the Casa Matemática Oaxaca (CMO) from May 26 to May 31 in 2024. The workshop will have up to 42 onsite and 300 virtual participants.

The proposal was led by the FRG Team (Prof. Jingfang Huang, Prof. Shahar Kovalsky, Prof. Yao Li, Prof. Jeremy Marzuola, Prof. Yichao Wu, Prof. Kai Zhang, and Prof. Ping-shou Zhong) and Prof. Linglong Kong from the University of Alberta and Prof. Jordan Rodu from the University of Virginia.

Information will be updated at the workshop website.

Newsletter 2023

September 15, 2023

STORies Newsletter – 2023

September 15, 2023


Dear friends,
Welcome to the 2023 annual issue of STORies. My message in the previous issues of STORies focused on department’s past academic year and immediate future. I will deviate slightly from that format in the current issue. As I am starting my 5th and last year as the chair, it is difficult not to look back at my whole 4+ year term from both department and personal perspectives.

The department has grown considerably. With 3 new positions about to open in this academic year, if they are filled, this would bring the total number of faculty hired to 13 during my term. I doubt strongly this was due to my “special” administrative skills. The department has experienced growth very much in response to the spike of interest in statistics, analytics, data science and related fields.

With increasing interest in our disciplines, the department worked to be outward looking and be part of the movement.

This included participating in data science initiatives (e.g., undergraduate major and minor) and activities (e.g., career fairs) on campus, often with its other units. This included raising our visibility, as with this newsletter or revamped STOR website, connecting with alumni and industry, as with the STOR Fest about to take place, and so on.

The department has been constantly thinking about improving its curricula across undergraduate and graduate programs. The PhD program was largely unified between statistics and operations research. There is more focus on the MS program, as it was given permission to charge differential tuition. Our undergraduate program has probably experienced and will experience a lot of changes, as we adapt to the changing landscape of our disciplines.

Every chair has not only their opportunities but also their challenges. The COVID peak period was challenging for everyone, to put it mildly. Zoom classes, uncertainty in planning, last minute adjustments, lack of in-person contacts and other emergencies made department’s operations difficult for several years. We all hope that this period is largely behind us. Navigating the university politics and personnel issues is part of any chair’s job that I discovered, for better or worse, to rely on the on-the-job training.

Vladas Pipiras

On a personal level, being the chair has been an invaluable experience and growth opportunity. It has been an honor to serve the department. Anything accomplished would have been impossible without the help and involvement of many graduate students, wonderful staff, dedicated faculty, and the college administration. The fact that the faculty, and by extension their graduate students, are world-class researchers make this department a special place, and any chair’s job much easier.

Do continue supporting the department in any way you can! Same holds for the new incoming chair yet to be elected who will be the one writing this message next year.

Vladas Pipiras
Department Chair

Read the entire newsletter

Welcome new faculty members 2023

August 1, 2023

Welcome new faculty members

August 1, 2023

New faculty

The Statistics and Operations Research Department would like to welcome our newest faculty members, Assistant Professors Daniel Kessler (jointly with SDSS), Patrick Lopatto and Ali Mohammad Nezhad!

Dr. Kessler

Dr. Kessler completed his PhD in 2023 at the Department of Statistics at the University of Michigan advised by Professor Liza Levina. He is currently an NSF Postdoctoral Fellow at the University of Washington where he works with Professor Daniela Witten. His research interests include the statistical analysis of networks, post-selective inference, high-dimensional statistics, applications involving human neuroimaging, computational and cognitive neuroscience, and high-performance computing. He looks forward to joining STOR in 2024 and will also hold a joint appointment in the School of Data Science and Society.

Dr. Kessler

Dr. Lopatto

Dr. Lopatto studies problems arising from causal inference, high-dimensional statistics, and random matrix theory. He also enjoys making statistics accessible and engaging for students. He received his PhD in mathematics from Harvard University in 2020. He was a postdoctoral member of the Institute for Advanced Study, and he is currently a postdoc at Brown University. Dr. Lopatto will join STOR in 2024.

 Dr. Lopatto

Dr. Mohammad Nezhad

Dr. Mohammad Nezhad was previously a Postdoctoral Research Associate at the Carnegie Mellon University, and a Golomb Visiting Assistant Professor in the Department of Mathematics at Purdue University, mentored by Professor Saugata Basu. He received his PhD in Industrial and Systems Engineering from Lehigh University in 2018 under the supervision of Professor Tamas Terlaky. His research lies at the intersection of continuous optimization, computational complexity, and real algebraic geometry. Dr. Mohammad Nezhad has recently developed interest in computational topology and its applications to optimization and machine learning.

Dr. Nezhad

2023 Graduation Ceremony

May 20, 2023

2023 Graduation Ceremony

May 20, 2023

2023 Graduation

Congratulations class of 2023!

The department held a graduation ceremony on Sunday May 8. The keynote speaker was Dr. Zeynep Tufekci (Craig Newmark Professor of Journalism, Columbia University & Director of the Craig Newmark Center for Journalism Ethics and Security).

This year’s cohort included 193 STAN majors, and the following graduate students:

Daiqi Gao
Wei Gu
Younghoon Kim
Deyi Liu
Wei Liu
Yiyun Luo
Dhruv Patel
Haodong Wang
Siqi Xiang

Xianwen He
Soohyun Kim
Ziang Li
Parvathi Meyyappan
Kyungjin Sohn
Eun-Ah Song
Isabel Wiesenthal

Alumni INFORMS award

April 28, 2023

2023 INFORMS Franz Edelman award

April 28, 2023


Our Ph.D. alumnus Minghui Liu (who graduated in 2015 and was advised by Gabor Pataki) was part of the winning team for the 2023 INFORMS Franz Edelman award for their work on “Optimizing Walmart’s Outbound Supply Chain from Strategy to Execution – A Grocery Case Study”.

Neurodegenerative disease discovery

April 28, 2023

Neurodegenerative disease discovery

April 28, 2023

Alzheimer's discovery

New research uncovers link between neurogenerative disease and subcortical shape changes in the brain

A recent research led by Prof. Zhengwu Zhang from the Department of Statistics and Operations Research (STOR) at UNC-Chapel Hill uncovered how neurodegenerative diseases like Alzheimer’s can accelerate atrophy in subcortical brain regions in individuals aged 60-75, compared to the normal aging process.

Through a series of brain scans, size changes were visible in the lateral ventricle, which contains and helps circulate cerebrospinal fluid, and the hippocampus, which supports limbic system processing of emotion, memory and behavior.

These findings were published recently as a discussion paper in the Journal of American Statistics Association (JASA), one of the most prestigious statistical journals which only publishes a few discussion papers each year. In the paper, the research team introduced a new method called longitudinal elastic shape analysis (LESA) for examining changes in specific brain regions over time. This comprehensive framework consists of five key components: subcortical surface extraction, elastic shape analysis, principal components analysis (PCA) of shapes, continuous shape trajectory fitting, and shape-trajectory-on-scalar regression.

The study was a joint effort between the College of Arts and Gillings School of Global Public at UNC Chapel Hill and the Florida State University. The co-authors of the study include Zhengwu Zhang, PhD, assistant professor in STOR at UNC; Yuexuan Wu, a doctoral student in the Department of Statistics at FSU; Di Xiong, a visiting doctoral student in biostatistics at UNC; Anuj Srivastava, PhD, a professor of statistics at FSU; and two biostatistics professors, Joseph G. Ibrahim, PhD and Hongtu Zhu, PhD.

The team applied this innovative framework to study brain MRI scans of 2,275 individuals, analyzing a total of 9,628 shape surfaces. They found that the atrophy of subcortical regions begins early in life, around the age of 30, and accelerates after 60 years old. Furthermore, findings show that Alzheimer’s disease further speeds up this shrinkage in comparison to normal aging for those between 60 to 70 years old.

The LESA framework enables researchers to accurately identify shape changes on the subcortical surfaces. They discovered that atrophy of the hippocampus associated with Alzheimer’s disease primarily occurs in the back of the organ, which is where crucial parts, known as subfields CA1, CA1, CA2 and CA4, are located. In addition, both Alzheimer’s disease and genetic risk factors, specifically the presence of two genetic alleles called ApoE4, contribute to more severe atrophy of subcortical regions, such as hippocampus and lateral ventricle, during the aging process.