Carolina Grad Named Schwarzman Scholar
December 4, 2017
Carolina Grad Named Schwarzman Scholar
December 4, 2017
Congratulations to our 2015 MDS alum Min Yang on being selected for this prestigious program!
News Items
Dr. J.S. Marron to be Visiting Lecturer
October 3, 2017
Dr. J.S. Marron to be Visiting Lecturer
October 3, 2017
During the month of October Professor Steve Marron will be the Al-Kindi Distinguished Statistics Lecturer at King Abdullah University of Science and Technology in Saudi Arabia. KAUST is the premier science university in Saudi Arabia and attracts leading international faculty members.
Marron will speak about Object Oriented Data Analysis, which is an approach for tackling Complex Data; a less well advertised, but perhaps more challenging topic in the spirit of the familiar Big Data.
Faculty search – Assistant Professor
September 19, 2017
Faculty search – Assistant Professor
September 19, 2017
The Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill has an opening for a tenure-track position in statistics at the assistant professor level starting July 1, 2018. See the entire announcement below.
THE UNIVERSITY OF NORTH CAROLINA AT CHAPEL HILL
Department of Statistics and Operations Research
Assistant Professorship in Statistics
The Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill has an opening for a tenure-track position in statistics at the assistant professor level starting July 1, 2018.
Candidates are required to have a doctorate in a relevant field by the start date of the appointment. The Department is seeking candidates who have demonstrated interest in timely areas of application (e.g., social & computer networks, imaging, data mining, climatology, health-care analytics, genomics, business analytics, forensic science), have a strong theoretical training and the potential to maintain an excellent research program. The successful candidate will be comfortable with teaching courses in applied and theoretical statistics 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. We are particularly interested in candidates working at the interface of statistics and optimization.
We will begin considering candidates after November 15, 2017, 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 also 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 of recommendation must be submitted in electronic form only; click on https://unc.peopleadmin.com/postings/127832 to apply for this position. At the time of application candidates will be required to identify the names, titles and email addresses of professional references (4 required). Reference providers identified by the applicant will be contacted via email with instructions for uploading their letters of support.
Statistics Faculty Search Committee
Department of Statistics and Operations Research
University of North Carolina at Chapel Hill
The University of North Carolina at Chapel Hill is an equal opportunity employer that welcomes all to apply, including women, underrepresented minorities, protected veterans, and individuals with disabilities.
Dr. Yufeng Liu Named IMS Fellow
September 16, 2017
Dr. Yufeng Liu Named IMS Fellow
September 16, 2017
Yufeng Liu, Professor, University of North Carolina at Chapel Hill, has been named Fellow of the Institute of Mathematical Statistics (IMS). An induction ceremony took place July 31 at the Joint Statistics Meeting in Baltimore, Maryland.
Dr. Liu received the award for outstanding research in statistical learning, especially with respect to multiclass classification and thresholding, and for applications of statistical methods to genomics.
Each Fellow nominee is assessed by a committee of his/her peers for the award. In 2017, after reviewing 41 nominations, 20 were selected for Fellowship. Created in 1935, the Institute of Mathematical Statistics is a member organization which fosters the development and dissemination of the theory and applications of statistics and probability. The IMS has 3,500 active members throughout the world. Approximately 10% of the current IMS membership has earned the status of fellowship
Dr. Vladas Pipiras awarded competitive Senior Faculty Research and Scholarly Leave
August 22, 2017
Dr. Vladas Pipiras awarded competitive Senior Faculty Research and Scholarly Leave
August 22, 2017
Professor Vladas Pipiras received a competitive Senior Faculty Research and Scholarly Leave for Fall 2017 semester. The Senior Faculty Research and Scholarly Leaves are awarded annually by the University, with the competition open to most faculty across campus. Prof. Pipiras applied with the project on “Statistical methods for seakeeping problems arising in US Navy experiments,” and plans to spend the leave working with the US Navy researchers at the NSWC Carderock Division.
UNC Team Places 3rd, Earns Grant
May 8, 2017
UNC Team Places 3rd, Earns Grant
May 8, 2017
A team of five students recently competed in the Society of Actuaries 2017 Student Case Study Challenge, finishing third. The challenge provides an opportunity to apply actuarial skills to real-world problems through research, analysis, and the development of models. Finalists were invited to present their work to a panel of judges last week. The third place finish secured a $2,000 grant to UNC from the Society of Actuaries, as well as cash awards to the team. Members included MDS majors Trent Hollandsworth (team leader), Amy Nelson, Yirun Li and John Mullan, as well as Computer Science/Economics major Tyler Thrower.
Dr. Vladas Pipiras received NSF grant on “Statistical models, inference and computation for multidimensional time series data”
May 3, 2017
Dr. Vladas Pipiras received NSF grant on “Statistical models, inference and computation for multidimensional time series data”
May 3, 2017
Numerous data are nowadays collected over time and across multiple, often large number of sources, for example, the BOLD time signals across multiple brain regions arising from fMRI, the ocean wave height series across multiple spatial locations collected from buoys or satellites, or the multiple economic indicators (GPD, unemployment, and so on) gathered over time by the government agencies or private entities. Under the project, novel statistical modeling tools will be developed that can capture adequately both the temporal features of such data and also their dependencies across multiple sources. Available techniques often either neglect temporal dependencies for such high-dimensional data arising from multiple sources, or do not apply to the situations when the number of sources is large. With the fMRI data, for example, proper accounting for temporal dependence and large number of brain regions will lead to better distinction among various clinical categories (ADHD, autism or other). Understanding the temporal and spatial dependencies in wave height data will lead to better predictions of storm activity across the oceans. Further insight into economic activity is expected from the analysis of multiple economic indicators.
The project aims at developing an integrated approach to analyzing large multidimensional time series data, including their statistical models, estimation, computation (algorithms), and practice. The proposed research covers both short-range and long-range dependent multidimensional time series. For short-range dependent series, the focus is on sparse vector autoregressive and related models, dimension reduction, change point detection and some nonlinear models. The problems to be addressed concern regularization techniques, statistical significance, models exhibiting cyclical variations and other issues. Multidimensional long-range dependence is suggested as the important class complementing vector autoregressive and related short-range dependent series, thus gathering the two general classes of models employed in modern time series analysis. The goal is to develop a new methodology for multidimensional long-range dependent series with the so-called general phase, which controls the (a)symmetry properties of multidimensional time series, in both linear and nonlinear settings. The developed methods should be useful across a wide range of areas, including Neuroscience, Oceanography and Environmental Sciences, Geophysics, Economics and Finance, and others.
Mark He awarded competitive DoD Fellowship
April 26, 2017
Mark He awarded competitive DoD Fellowship
April 26, 2017
The department congratulates Ph. D. candidate Mark He, who has been awarded a National Defense Science and Engineering Graduate Fellowship by the Department of Defense (DoD). Mark was one of over 3,500 applicants for the estimated 150 fellowship opportunities, which are administered by the American Society for Engineering Education.
The NDSEG Fellowships are sponsored by the Air Force Office of Scientific Research, the Army Research Office, and the Office of Naval Research. (Mark will be sponsored by the ONR.) Through these fellowships, the DoD’s aim is to promote education and advanced training in science and engineering disciplines that are of military importance.
The award will cover full tuition and fees for up to four years in addition to providing a monthly stipend.
UNC team wins big at Duke Datathon
April 24, 2017
UNC team wins big at Duke Datathon
April 24, 2017
Ph.D. candidates Yunxiao Liu, Iain Carmichael, and John Palowitch, along with Yiming Hu, a Ph.D. candidate from Yale Biostatistics, took first place in the Duke Datathon on April 21st, 2017. The competition was sponsored by Citadel and Citadel Securities, in partnership with Correlation One. In recognition of their work, the team members received a $20,000 cash prize, were offered job interviews with Citadel, and became eligible to compete in the worldwide Citadel Datathon in November.
The Duke Datathon took place on the Duke campus, and began at 9AM. Teams were given a proprietary data set containing millions of U.S. job listings, along with many freely-available data sets containing demographic and economic statistics over the past decade. Having diverse research backgrounds, Yunxiao, Iain, John, and Yiming used a combination of time series and machine learning techniques to reveal macro and micro factors that affect the evolution of job growth.
The article “Bad semidefinite programs: They all look the same” by Professor Gabor Pataki is chosen as a featured article by SIAM Journal on Optimization
March 21, 2017
The article “Bad semidefinite programs: They all look the same” by Professor Gabor Pataki is chosen as a featured article by SIAM Journal on Optimization
March 21, 2017
The article by Gabor Pataki, “Bad semidefinite programs: they all look the same” has been chosen as a “Featured article” by SIAM Journal on Optimization: see at http://epubs.siam.org/journal/sjope8.
Semidefinite programs (SDPs) are one of the most important optimization problems today: they are applicable in engineering, economics, and many other fields and can be efficiently solved. At the same time, SDPs often exhibit certain pathological behaviors. This paper gives a very simple characterization of these pathological behaviors.
SIAM Journal on Optimization is one of the premier journals on optimization: it publishes more than 100 articles a year, and chooses one featured article approximately every 6 months.