Skip to main content

DataFest 2023

March 8, 2023

ASA DataFest at Duke 2023

March 8, 2023

DataFest 2023

ASA DataFest at Duke 2023 is organized by the Department of Statistical Science at Duke University and will take place Friday March 24th through March 26th, 2023. The last day to register is March 10th.

DataFest is a data analysis competition where teams of up to five students attack a large, complex, and surprise data set over a weekend. Your job is to represent your school by finding and communicating insights into these data. The teams that impress the judges will win prizes as well as glory for their school. Everyone will have a wonderful experience, lots of food, and fun!

The event is open to all Undergraduate and Master’s students, regardless of level of programming experience. In previous years, students in introductory STAN courses have won awards and prizes. Additionally, in anticipation of the event weekend, Duke’s Center for Data and Visualization Sciences will host pre-event workshops. See the DataFest website for more details: https://www2.stat.duke.edu/datafest/workshops.html

Whether you form a team or wish to be assigned to a team, registration is open! You can sign up (and read more about DataFest) here: https://www2.stat.duke.edu/datafest/signup.html

SDSS position

January 10, 2023

Joint position with the School of Data Science and Society

January 10, 2023

Data Science Position

The School of Data Science and Society (SDSS) and the Statistics & Operations Research Department (STOR) are hiring a joint position. This joint hire will have its tenure home in the STOR Department but will hold a half-time appointment at SDSS and contribute to their teaching and research mission as well.

The new hire will be helping to build undergraduate and graduate programs with a strong quantitative core as well as many interdisciplinary options. As a part of this overarching initiative to deepen and expand research and teaching related to data science, applications are being invited at Assistant or Associate Professor rank with a starting date of July 01, 2023.

The STOR department is organized around four areas: theoretical and applied statistics; probability; stochastic modeling; and optimization. Faculty in the department conduct fundamental research in these areas and have many collaborations with other parts of UNC including health care, medicine, public health and environmental sciences.

The ideal candidate for this position would be someone with primary expertise in one of the STOR department’s core areas, at the intersection with data science including machine learning, and potential for developing significant collaborations with the SDSS. 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.

We will begin considering candidates after January 15, 2023, and will continue accepting applications until the position is filled. Questions should be directed to the Search Committee at stor-search-sdss@office.unc.edu.

Link to the job application https://unc.peopleadmin.com/postings/247369

RTG lectures by Resnick

January 4, 2023

Mini course by Sidney Resnick

January 4, 2023

RTG mini course

Sidney Resnick from Cornell visiting us from January 7th to January 28th. He will be giving a series of six lectures on the topic of:

Multivariate Power Laws and Preferential Attachment Modeling

This is part of the lecture series funded by the NSF RTG grant DMS 2134107.

Abstract: In one-dimension, heavy tails or power-laws are easily understood to represent Pareto like behavior where data plotted on a log-log scale looks roughly linear. The generalization to higher dimensions is not always obvious and the infinite variety of dependence possibilities can be daunting. Multivariate regular variation of measures is a clean, flexible and clear way forward. A variety of mathematical and statistical techniques guide a user.

Network modeling of social networks using preferential attachment presents other challenges. Models can be difficult to analyze and only occasionally do simulations from these models leave a comfortable impression that simulation matches reality. One glaring discrepancy is “reciprocity”, meaning the percentage of directed edges that link to nodes (network users) in both directions. (You like me and I like you. You reference my paper and I reference yours.) Real data exhibits higher reciprocity compared to what is given by simulations from traditional preferential attachment.

In- and out-degree sequence data for many social networks marginally exhibit the expected straight line power law behavior and preferential attachment models theoretically predict this both marginally and in the two-dimensional sense. We can add reciprocity to the model by assuming something like “when I connect to you, you flip a coin to decide if you want to connect with me.” This and its generalizations corrects the empirical under-prediction of reciprocity and introduces the feature that asymptotically the limit measure of regular variation concentrates on a line. This means large values of in- and out-degree tend to always be present simultaneously, a property called “asymptotic full dependence”. Without reciprocity, preferential attachment leads to in- and out-degree having a limit measure of regular variation that concentrates on the full positive quadrant meaning that a large value of either in- or out-degree can be associated with a variety of values in the other.

Schedule: The lectures will be held in Hanes 125 at the following dates and times:

  • TTh (Jan 10, 12): 4:15-5:30 pm
  • Tue (Jan 17): 4:45-6:00 pm
  • Th (Jan 19): 4:15-5:30 pm
  • TTh (Jan 24, 26): 4:15-5:30 pm

STOR students may earn credit by registering for STOR 893.

Pre-requisites: foundation in probability and statistics at the graduate level.

Bio: Sidney Resnick is the Lee Teng-Hui Professor in Engineering Emeritus at Cornell. Resnick joined the Cornell faculty in 1987 after nine years at Colorado State University, six years at Stanford University, and two years at the Technion, in Haifa, Israel. He received his Ph.D. from Purdue University in 1970. His interests center in applied probability and cross the boundary into statistics. Past foci include modeling queues, storage facilities, extremes, data and social networks, risk estimation and tail estimation. Resnick is a Fellow of the Institute of Mathematical Statistics, a founding associate editor of Annals of Applied Probability, and past associate editor of Journal of Applied Probability, Stochastic Processes and their Applications, Stochastic Models, Extremes, The Mathematical Scientist. He has authored or coauthored approximately 190 papers and four books.

RTG postdoc 2023

December 10, 2022

Postdoctoral position in NSF RTG

December 10, 2022

Postdoctoral position

The Department of Statistics and Operations Research invites applications for a three-year postdoctoral fellowship starting July 1, 2023. The position is funded by the Research training grant from the NSF, Networks: Foundations in Probability, Optimization, and Data Sciences.

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.

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

Interested candidates should submit application materials (CV, research statement, two or more letters of recommendations) by January 15, 2023 at https://unc.peopleadmin.com/postings/245920.

U.S. citizenship or permanent residency required.

Should you need any further information, please contact us via rtg_stor@unc.edu.

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.

Student Awards

December 5, 2022

2022-2023 Student Awards

December 5, 2022

Student Awards

The department would like to congratulate the following outstanding students.

Walter L. Deemer Excellence in Teaching Award

  • Ackerman, Andrew
  • Kar, Sumit

Excellence in Teaching Assistance and Instruction Award

  • Keefe, Thomas
  • Ozkan, Dilay
  • Andreou, Panagiotis

2022-2023 STOR Dissertation Award

  • Luo, Yiyun

Cambanis-Hoeffding-Nicholson Award
(for outstanding performance in first-year graduate courses and CWEs)

  • Kim, Minji
  • Lee, Seong Jin
  • Liu, Rui

Department Anniversary

November 26, 2022

STOR is turning 75 (ST) / 50 (OR)

November 26, 2022

STORFest

STOR Fest was the celebration of the department of Statistics and Operations Research turning 20 years! This coincides with the 75th anniversary of Statistics and 50th anniversary of Operations Research at Carolina.

Find more information and the anniversary activities at the STOR Fest website.

A Celebration in Memory of Ross Leadbetter

November 26, 2022

A Celebration in Memory of Ross Leadbetter

November 26, 2022

Honoring Leadbetter

The Department is organizing a meeting on Saturday, February 25, 2023.
See more information in the event website.

Speakers

Richard Davis (Columbia University)
Ivette Gomes (Universidade de Lisboa)
Tailen Hsing (University of Michigan)
Steve Marron (University of North Carolina at Chapel Hill)
Thomas Mikosch (University of Copenhagen)
Susan Murphy (Harvard University)
Vladas Pipiras (University of North Carolina at Chapel Hill)
Sid Resnick (Cornell University)
Holger Rootzen (Chalmers University of Technology)
Gennady Samorodnitsky (Cornell University)

RTG Women Luncheon

October 21, 2022

RTG Women Luncheon: Lisa M. LaVange

October 21, 2022

RTG Women Luncheon

Each semester the RTG program will host a luncheon for women trainees with a faculty role model, from within or outside UNC, to share and discuss unique challenges, experiences, and opportunities for women in STEM.

This semester the luncheon will be held on November 21st from 12:45pm to 2:00pm at Campus Y seminar rooms (207&208). We will have Lisa M. LaVange from Biostatistics as the faculty role model joining the lunch. She is a professor and chair of the Department of Biostatistics at UNC Chapel Hill. She also serves as the director of UNC’s Collaborative Studies Coordinating Center (2006-2011; 2018-present). Dr. LaVange has a broad background in the biostatistics field, including leadership roles in industry (RTI, Quintiles, Inspire Pharmaceuticals); academia (UNC/CSCC); and government (Center for Drug Evaluation and Research at the FDA). She was also the 2018 president of the American Statistical Association. At the CSCC, she has been the lead PI on the HCHS/SOL and SPIROMICS studies, and is currently the Coordinating Center PI for the Adolescent Medicine Trials Network for HIV/AIDS Intervention (ATN) and co-PI of the Precision Interventions for Severe and/or Exacerbation-Prone Asthma Network (PrecISE). She is co-instructor for BIOS 844: Leadership in Biostatistics, offered bi-yearly in the fall semester.

Doing Good With OM and OR

October 19, 2022

Doing Good With OM and OR

October 19, 2022

Doing good with OR

Nilay Argon is speaking on the Supply Chain Resource Cooperative (SCRC) academic conference on Friday, October 28, 2022, “Doing Good With OM and OR”.

Title: Disparities in Prioritization and Disposition Decisions in Emergency Departments

Abstract: Prior research has shown that health disparities exist in various forms in Emergency Departments (EDs), where certain patient populations have longer wait times, lower medical resource usage, and higher mortality rates. In this talk, I will discuss disparities in two ED decisions that have not received much attention before: prioritization for rooming after triage and disposition decision. Using data from a large academic ED, we identified patient age and race as characteristics that are associated with deviation from a first-come-first-served prioritization rule among patients with a similar triage acuity. We also found that ED disposition decisions, specifically whether or not a patient is admitted to the hospital after their ED stay, correlated with patient sex, race, and ethnicity. These findings suggest that there may be demographic disparities in ED rooming and disposition decisions after adjusting for clinical characteristics. Our results also support the hypothesis that there is an association between these disparities and ED crowding. I will conclude my talk with our ongoing work on solutions to diminish the effects of such disparities in EDs.