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NIDA awards $1.57 million R01 grant to Dr. Ertefaie to study the effect of partial treatment compliance in constructing individualized treatment strategies

March 2020

This grant aims to develop methodologies to adjust for partial compliance in constructing individualized treatment strategies using sequential multiple assignment randomized trials data. Existing tools that estimate the treatment effects using intention-to-treat analyses ignore information on patients’ compliance. The work to be done fills this important gap by providing a set of analytical tools that consider the noncompliance in the setting of sequential clinical decision making. Drs. Brent Johnson (URMC), Michael Kosorok (UNC-Chapel Hill), James McKay (UPenn) and Andrew Wilson (NYU) are co-investigators on this grant.

NIAAA awards $0.42 million R21 grant to Dr. Ertefaie to develop individualized treatment strategies for controlling alcohol use

March 2020

The overarching aim of this work is to address the need for robust, rigorous and efficient methods for estimating optimal treatment strategies in high-dimensional settings. Current methods for constructing individualized treatment strategies rely on certain modeling assumptions, and thus, the results can be very sensitive to the postulated models. The R21 aims to relax these unrealistic assumptions by leveraging the state-of-the-art nonparametric regression methods. Novel techniques for identifying key treatment effect modifiers from a large list of candidate variables are also to be developed. This work helps to pave the way for future studies that advance personalized medicine. Drs. Rob Strawderman (URMC) and James McKay (UPenn) are co-investigators on this grant.​

The Del Monte Institute awards a $50,000 grant to Dr. Ertefaie to study the comparative effectiveness of treatment strategies in Parkinson’s Disease

March 2020

Among neurological disorders, the fastest growing is now Parkinson's disease (PD), surpassing Alzheimer's disease. Existing guidelines for symptomatic drug therapy for PD can best be described as "permissive". The relative lack of comparative evidence for different classes of drugs has created challenges in devising recommendations to follow any specific therapeutic strategy; indeed, there remains substantial heterogeneity in the choice of treatment strategies. The proposal aims to fill this important gap. A specific goal is to use the data collected as part of the Parkinson’s Progression Markers Initiative (PPMI) study to identify a sequence of treatment decisions (drug classes) to optimize an outcome of interest; and construct a set of best treatment strategies. We will focus on motor complications, anxiety and depression scores measured at 3 and 24 months of treatment initiation as important clinical outcomes. Dr. Charles Venuto (URMC) is a co-investigator on this grant.

Drs. Rice, Strawderman and Johnson honored with award for "Best paper in Biometrics for 2018!"

January 2020

John Rice, a former postdoctoral fellow now at the University of Colorado School of Public Health, along with his co-mentors Rob Strawderman and Brent Johnson, were recently notified by the Editors of Biometrics, a premiere statistical methodology journal, that their paper, Regularity of a Renewal Process Estimated from Binary Data, was selected by a committee of current and former journal editors as the "Best Paper in Biometrics by an International Biometric Society (IBS) member" for the year 2018. The authors have been asked to present this work in a showcase session at the upcoming IBC meeting in July that will be held in Seoul, South Korea. The motivating example for this paper involves determining the effect of an intervention on the regularity of HIV self-testing behavior among at-risk individuals when exact self-testing times are not recorded. Assuming that these unobserved testing times follow a renewal process, the article develops suitable methods for estimation and inference for the renewal distribution parameters when only the presence or absence of at least one event per subject in each of several observation windows is recorded. The concept of "regularity" is also quantified and subsequently estimated by the coefficient of variation (CV) of the interevent time distribution. The paper applies these new methods to the data from the motivating example, concluding that the use of text message reminders significantly improves the regularity of self-testing, but not its frequency. The paper closes with a discussion on interesting directions for further research. 

Roberta K. Courtman Revocable Trust awarded $50K to Drs. Zhang, Baran and Lin to study the brain connectomes of Supernormal older adults

January 2020

The objective of this project is to utilize the structural connectome to study the missing structural aspect in the “reserve vs. compensation” phenomenon to enrich the understanding of Supernormals’ cognitive superiority. Supernormals here refer to a group of old adults who have superior cognitive capacity with superior memory compared to their peers and even normal middle-aged adults. We suspect that, similar to their functional profile, Supernormals will have stronger structural reserve while relying on alternative structural compensation to resist amyloid-deposition and support cognitive function compared to typical agers. Ultimately, our long-term goal is to identify therapeutic targets that can resist AD pathophysiology or reduce AD pathophysiology’s adverse effect on cognition using knowledge gained from Supernormals.

NIMH awarded $0.75 million grant to Drs. Dunson and Zhang to study human brain structural connectivity

January 2020

NIMH has awarded $0.75 million grant to Drs. Dunson and Zhang to study human brain structural connectivity through the Collaborative Research in Computational Neuroscience (CRCNS) program. This project focuses on developing transformative methods for better characterizing and studying variability in human brain structural connection networks in relation to traits of the individual, including cognitive abilities and substance use. Diffusion magnetic resonance imaging (MRI) and structural MRI can be used to infer locations of millions of white matter fiber tracts acting as highways for neural activity and communication across the brain. The collection of interconnected fiber tracts is referred to as the brain connectome. Improvements in technology have enabled routine collection of high-resolution connectomes; however, there is a fundamental gap between state of the art in image acquisition and the tools available to reconstruct the connectome and study how connectomes vary across individuals in relation to individual characteristics. This project will enable substantial breakthroughs to close this gap by developing fundamentally new ways to process, represent, and analyze brain connectomes.

Statistician is among the Best Jobs for 2020

January 2020

U.S. News & World Report recently ranked Statistician as the #1 Best Business Job and #6 in the Top 100 Best Jobs across all categories. Statistician also ranked #6 among the Best STEM Jobs, partially due to its above-average salaries, low unemployment, and future job prospects. With a projected growth rate of 31% between 2018 and 2028, statistics is one of the fastest-growing fields in the United States!

The joint Greater Data Science Cooperative Institute (GDSC) by UofR and Cornell funded by NSF

October 2019

The National Science Foundation (NSF) has awarded a three-year grant to establish a Greater Data Science Cooperative Institute (GDSC) jointly by the University of Rochester and Cornell University that combines shared expertise from electrical engineering, mathematics, statistics, and theoretical computer science.

The UR-Cornell GDSC is based on two founding tenets: that enduring advances in data science require combining techniques and viewpoints across electrical engineering, mathematics, statistics, and theoretical computer science; and, that data-science research must be grounded in an application domain.  The following cross-disciplinary research directions are proposed: (i) Topological Data Analysis; (ii) Data Representation; (iii) Network & Graph Learning; (iv) Decisions, Control & Dynamic Learning; and, (v) Diverse & Complex Modalities. Additional cross-disciplinary research aims including the following are also integrated throughout these five research directions: combinatorial inference; multiple areas in machine and deep learning; and broadening machine learning with tools from signal processing, information & control theory.

The UR-Cornell GDSC specifically aims to consider applications in medicine and healthcare, an important application domain that represents a major strength of the UR,  and one for which advances in data science can have a direct, positive impact on society.

Dr. Tong Tong Wu (co-PI) from the Department of Biostatistics and Computational Biology will work with Dr. Mujdat Cetin (PI at UofR) from the Goergen Institute for Data Science and Dept. of Electrical and Computer Engineering, Dr. David Matteson (PI at Cornell) from the Dept. of Statistics and Data Science at Cornell, other co-PIs and faculty across both institutions to achieve the objectives of this new cooperative institute. Biostatistics faculty are anticipated to participate in foundational research efforts in several of the core areas, including data representation (e.g., through imaging and genomics); network and graph learning (e.g., through time-evolving networks); decisions, control and dynamic learning (e.g., through the study of dynamic treatment regimes); and diverse and complex modalities (e.g., through high-dimensional modeling without parametric structures).

Professor Sally W. Thurston named a Fellow of the American Statistical Association

April 2019

Sally Thurston profile pictureThe designation of ASA Fellow has been a significant honor for nearly 100 years where, under ASA bylaws, the Committee on Fellows can elect up to one-third of one percent of the total association membership as fellows each year. Selection for this honor is based on a nomination, letters of recommendation, and a positive vote of the Committee on Fellows. The honor is intended recognize statisticians with an established reputation that have made outstanding contributions to statistical science. Dr. Thurston is the 4th member of the current faculty to be honored as an ASA fellow, the others being Michael McDermott (2017), Robert Strawderman (2006), and David Oakes (1993).

NIH awards $3.8 million grant to reduce antibiotic overuse

February 2019

Professor Derick Peterson (Co-Investigator) and Ms. Andrea Baran (MS statistician) from the Department of Biostatistics and Computational Biology will continue their productive collaborations with Drs. Ann Falsey & Thomas Mariani (Co-PIs in Infectious Diseases and Pediatrics, respectfully) and Drs. Angela Branche and Edward Walsh (Co-Investigators in Infectious Diseases), supported by a new 5-year $3.8M NIH grant to reduce antibiotic overuse. The primary goal is to discriminate between bacterial and non-bacterial respiratory infection via high-dimensional gene expression profiling of blood. Such a diagnostic test would allow physicians to optimally manage patients with acute respiratory infections, which are a leading cause of antibiotic overuse and are linked to the rise of antibiotic resistant organisms. This grant builds upon prior research done as part of the NIH-funded Respiratory Pathogens Research Center (RPRC).

Prospective graduate students learn about our Master's and PhD programs

September 2018

The department’s Annual Open House for Prospective Graduate Students was held on September 29, 2018. This event provides students potentially interested in graduate study in biostatistics and statistics with an opportunity to learn about our programs, to meet with current students, faculty, and program alumni, and to gain some perspective on the many career opportunities this exciting field has to offer.

Students find summer opportunities across the United States

July 2018

Student standing outside the US FDAStudent standing in front of posterSummer is a popular time for students in the department to complete internships and travel to conferences. Internship sites this summer included AbbVie (biopharmaceuticals, Illinois), Ernst & Young (finance, New York), Travelers (insurance, Connecticut), Allergan (pharmaceuticals, California), and the U.S. Food and Drug Administration (federal agency, Maryland). Research was shared in presentations at the Society for Epidemiologic Research 51st Annual Meeting (Baltimore, MD), the Global Symposium of Innovation in Trauma Research Methods (Columbus, OH), and the Joint Statistical Meetings (Vancouver, Canada). We hope everyone has a fantastic summer!

$1 million grant awarded to Drs. Lamberti, Weisman, and Strawderman

May 2018

The Laura and John Arnold Foundation has awarded a $1 million grant to the University of Rochester Medical Center to evaluate Minnesota’s replication of the successful Rochester Forensic Assertive Community Treatment (R-FACT) program.

The R-FACT program was created 25 years ago by J. Steven Lamberti, M.D. and Robert L. Weisman, D.O., professors in the URMC Department of Psychiatry, to address high rates of arrest and incarceration of people with mental illness. Two years ago, officials in St. Paul and Minneapolis requested URMC’s expertise and began recreating the R-FACT model in their communities.

R-FACT has shown that strong collaboration between mental health and criminal justice professionals provides mentally ill individuals with more effective interventions, and ultimately reduces rates of criminal convictions, jail time, and hospitalizations by roughly 50 percent while doubling time in treatment compared to other programs.

The $1 million grant will allow Lamberti, Weisman, and Robert L. Strawderman, Sc.D., professor and chair of the URMC Department of Biostatistics and Computational Biology, to evaluate the effectiveness of R-FACT in the Midwestern cities.

Department recognized for supporting the Greater Rochester community

April 2018

During the annual fundraising campaign for the United Way of Greater Rochester, more than $1.4 million was donated to the charity by members of the University of Rochester. The Department of Biostatistics and Computational Biology was recognized for its generous support and high participation rate by winning a pizza party during a "25% participation in 25 days" drawing held towards the start of the campaign. Sheryl Hennekey, a department secretary who serves as one of the campaign coordinators, also received a Shining Star award for her efforts and enthusiasm. We are proud to support this strong tradition of giving back to the community and helping those in need.

Professor Matthew McCall selected as an associate editor for the journal BiostatisticsFront Cover of Biostatistics Journal

March 2018

Founded in 2000 by Scott L. Zeger and Peter J. Diggle, the objective of Biostatistics is to advance statistical science and its application to problems of human health and disease, with the ultimate goal of advancing the public's health. Biostatistics​ was the first journal to have a reproducibility policy and badge that could be earned for making a paper fully reproducible. Dr. McCall will join an editorial staff of approximately 40 associate editors and 2 co-editors.

Front Cover of Biometrics JournalProfessor Brent Johnson selected as an associate editor for the journal Biometrics

March 2018

Biometrics is the flagship journal of the International Biometric Society and is published quarterly both electronically and in print by Wiley. The first issue was published in 1947. Dr. Johnson will join an editorial staff of some 80 associate editors worldwide, 3 co-editors, and 1 executive editor.

Valeriia Sherina receives the William Jackson Hall Graduate Student Fellowship Award

January 2018

PhD candidate Valeriia Sherina was named as the 2017-2018 recipient of the William Jackson Hall Graduate Student Fellowship Award. This merit-based fellowship intends to recognize one or more Statistics doctoral students in their last semester or year of study whose academic record reflects the major cornerstones of Professor Hall’s distinguished career.

Students earn the Master of Arts in Statistics

December 2017

Students Ting Yin and Ruyue Zhang completed all degree requirements for the terminal Master of Arts in Statistics degree at the end of the Fall 2017 semester. The degree requires satisfactory completion of 32 credits and a final comprehensive written exam. We wish Ruyue and Ting the best as they begin their careers!

Department members enjoy a cruise along the Genesee River

October 2017

Department faculty, staff, and students spent the evening of October 9, 2017 on an authentic paddle boat viewing the beautiful fall foliage along the Lower Genesee Valley Gorge. The cruise offered a great opportunity to spend time with colleagues and celebrate the new semester. The event also featured a delicious feast of barbecue foods.

Professor Zhengwu Zhang joins the Department of Biostatistics and Computational BiologyZhengwu Zhang

October 2017

We are pleased to welcome Dr. Zhengwu Zhang to the department. Dr. Zhang completed his PhD at Florida State University in 2015 and was recently a Postdoctoral Fellow at Duke University and the Statistical and Applied Mathematical Science Institute (SAMSI). His appointment as Assistant Professor began on October 1, 2017.

Professor Michael P. McDermott named a Fellow of the American Statistical Association

August 2017

It is a distinction only conferred upon one-third of one percent of the ASA’s membership. Dr. Michael McDermott was recognized as a Fellow at an awards ceremony held during the Joint Statistical Meetings (JSM 2017) in Baltimore.

Students create The Rochester Data Science Society

April 2017

Shiyang Ma, a third-year doctoral student in the department, along with PhD students from the Health Services Research, Epidemiology, and Computer Science graduate programs have established The Rochester Data Science Society (RDSS). The mission of the RDSS is to enrich student understanding of how to use and manage data to solve complex problems while building bridges between students, alumni, industry, and Data Science Societies of neighboring universities. It is the first student organization at the University of Rochester for students interested in data science, statistics, computer science, engineering, health analytics, economics, and other related fields.

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