NIDCR awards $3.5 million R01 grant to Drs. Xiao, Gill, and Wu to Predict Severe Childhood Tooth Decay in Early Infancy
Although largely preventable, Early Childhood Caries (ECC)—severe tooth decay among young children—affects one third of socioeconomically disadvantaged and racial/ethnic minority preschool children in the U.S. While ECC is an infectious disease initiated by cariogenic pathogens, it is now understood to be a multifactorial and ecology-based disease, with the interplay between host, environment, and oral microbiota affecting the onset and severity of ECC. The Oral Microbiome in Early Infancy (OMEI) study will address the urgent need to understand biological factors related to pediatric dental caries among the low-income and racial/ethnic minority groups and develop caries prediction models adjusting multilevel factors.
The OMEI will be the first study to our knowledge to comprehensively evaluate the longitudinal development of early life oral microbiome and their relation to dental caries among low-income minority infants. The study results will build a foundation for developing early life salivary diagnostic tools to predict ECC and further prevent ECC by shaping an infant's oral microbiome and other related multilevel factors. Dr. Michael Sohn will contribute his expertise in metagenomics sequencing to this study. Learn more about this study.
Student competition winners announced at UP-STAT 2022 conference
UP-STAT 2022, the 10th joint conference of the Upstate New York chapters of the American Statistical Association, brings together statistical, computational, and data scientists, as well as other professionals from related fields from upstate NY and its neighboring regions. As part of the conference, student paper, poster, and data analytics competitions are held with winners receiving award certificates and prizes.
A team of 2nd year PhD students (Jonathan Klus, Samantha Manning, and Luke McHan) won top honors at the UP-STAT 2022 Data Analytics Competition for their work entitled “Marginal Gains.” The competition’s theme was “Statistical Science at the Service of Social Justice” and contestants were challenged to investigate disparities in educational discipline and their relationships with jailing rates in the United States. Using data gathered from government and non-government sources, the student team developed a model to explain the association between these two areas of interest at the state and county level across the United States.
Samuel Weisenthal, a 4th year PhD student, received a 2nd place cash prize in the UP-STAT 2022 Student Poster Competition. His work, “Relative Sparsity,” involves a method developed to estimate a treatment strategy that improves patient outcomes, yet only differs from the standard of care in a way that is easy to explain. Working with his advisors, Professor Sally Thurston and Professor Ashkan Ertefaie, the research may help facilitate the adoption of data-driven decision aids into routine medical practice.
The 2022 hybrid conference was held May 2-4 in Buffalo, NY. Department faculty and PhD program alumni serving on UP-STAT conference organizing committees include Tanzy Love, Gregory Wilding (PhD `03), Lili Tian (PhD `01), Katherine Grzesik (PhD `17), and Mike McDermott.
Jeremiah Jones receives Distinguished Student Paper Award from ENAR
Jeremiah Jones received the Distinguished Student Paper Award from ENAR for his paper called "Causal Mediation Analysis: Selection with Asymptotically Valid Inference." The paper focuses on helping researchers understand how treatments effect outcomes by selecting the important pathways through which treatments operate. They also propose a tool for valid inference after selection of the pathways and provide proof for the characteristics of the methods.
Up to twenty Distinguished Student Paper Awards are given each year to assist students in presenting contributed papers at the ENAR Spring Meeting. Each winner receives a certificate, reimbursement for travel expenses up to $650, tuition waiver for one ENAR short course of choice, and an invitation to the Monday evening ENAR President's reception.
Rochester alumna to join Shanghai Jiao Tong University School of Medicine
Congratulations to Dr. Shiyang Ma who will join the Clinical Research Institute at Shanghai Jiao Tong University School of Medicine as an Assistant Professor in October 2022. She entered the University of Rochester as a Master of Arts in Statistics student in Fall 2014, transferred to the PhD Statistics program in Fall 2015, and graduated in Fall 2019 under the supervision of Professor Michael P. McDermott and Professor David Oakes. Since leaving Rochester, Dr. Ma has been a postdoctoral research scientist in the Department of Biostatistics at Columbia University, working with Professor Iuliana Ionita-Laza, and researching fine-mapping gene-based associations via knockoff analysis of UK Biobank data. Dr. Ma has published work in PNAS, Statistics in Medicine, Biometrical Journal, American Journal of Human Genetics, and elsewhere. We wish her all the best!
Dr. Norman-Haignere develops new methods on how the brain responds to sounds
Assistant Professor of Neuroscience and Biostatistics and Computational Biology Samuel Norman-Haignere, Ph.D., with the Del Monte Institute for Neuroscience at the University of Rochester has identified neurons in the brain that 'light up' to the sounds of singing, but do not respond to other types of music. Learn more about this research.
Dr. Iris Chen to talk with students about her post-graduate experiences
Dr. Iris Chen will share her experiences in industry at a myHub presentation called "Embrace and learn from your own career life adventure."
Since completing the University of Rochester Statistics PhD program in 2013, Dr. Chen has worked in a variety of settings ranging from small startups to one of the world's largest independent biotechnology companies. Students can learn more about her career journey and growth during the March 18th virtual event.
William Consagra excels in the JSM 2022 Student Paper Competition
PhD candidate William Consagra was recognized for his paper “Optimized Diffusion Imaging for Brain Structural Connectome Analysis” in the JSM 2022 Student Paper Competition Section on Statistics in Imaging. Papers were scored for statistical novelty, innovation and significance of contribution to the field of application, and professional quality.
Based on his work with Dr. Zhengwu Zhang and Dr. Arun Venkataraman, Mr. Consagra developed a new statistical framework that incorporates data from prior large-scale imaging studies in order to improve the efficiency of human brain structural connectome estimation. He will receive a cash prize and present his paper in a topic-contributed session at the Joint Statistical Meetings in Washington, D.C., in August 2022.
Drs. Land and McCall hone in on shared network of cancer genes
In a new study led by Hartmut "Hucky" Land, the Robert and Dorothy Markin Professor of Biomedical Genetics and deputy director of the Wilmot Cancer Institute, and Matthew McCall, an associate professor of Biostatistics and of Biomedical Genetics, the Wilmot Cancer Institute researchers used network modeling to hone in on a set of gene interactions that are critical to making cells malignant and are likely to be fertile ground for broad cancer therapies. Learn more about this research.
Professor Ashkan Ertefaie selected as an associate editor for the Harvard Data Science Review
Harvard Data Science Review is an open access journal published by MIT Press and hosted online by PubPub. The first issue was published in 2017. Harvard Data Science Review is a 2021 prose award winning publication for best new journal in science, technology and medicine. Dr. Ertefaie will join an editorial staff of approximately 75 associate editors.
Jeremiah Jones receives the William Jackson Hall Graduate Student Fellowship Award
PhD candidate Jeremiah Jones was named as the 2021-2022 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.
Jeremiah's research focuses on developing methods for causal inference that combine machine learning and interpretable statistical modeling. His research has found application in mediation analysis, which seeks to estimate and infer the magnitude of treatment effect flowing through different causal pathways. His research has also been applied to estimating dynamic treatment regimes, which assign patients to a predicted optimal treatment as evidence accumulates over time.
NINDS awards $3.14 million grant to Drs. Ertefaie, McDermott, and Venuto to advance personalized medicine in Parkinson’s disease using harmonized multi-site clinical data.
Parkinson’s disease (PD) manifests as a heterogeneous clinical syndrome and the variability in the clinical phenotype highlights the need to tailor the type and/or the dosage of treatment to the specific and changing needs of individuals. However, the relative lack of comparative evidence for different classes of drugs and the timing of their initiation has created challenges in devising recommendations to follow any specific therapeutic strategy. This two-phase study, funded by NINDS, will attempt to fill this important gap. The first phase (R61) focuses on creating a harmonized and curated data set by integrating data from six clinical trials and an observational study. In the second phase (R33), the harmonized data set will be leveraged to develop high quality individualized treatment strategies for PD with respect to several clinical outcomes. A robust marginal structural model will be developed that has better convergence properties than existing methods and leverages a non-parametric regression approach to mitigate the chance of misspecification of the nuisance parameters while providing valid inference (p-values and confidence intervals) for the parameters of interest.
NIGMS awards $1.97 million R01 grant to Dr. McCall to develop statistical methods for microRNA-sequencing experiments
This grant aims to improve the analysis of microRNA-sequencing data by developing statistical methods that directly address the challenges unique to measuring expression levels of microRNAs. MicroRNAs are essential regulators of gene expression, alterations in which have been shown to disrupt entire cellular pathways, substantially contributing to a variety of human diseases such as heart disease and cancer. Despite their importance, our understanding of the role of microRNAs is hampered by a lack of statistical methods designed specifically to analyze microRNA-sequencing data. By developing such methods, this project will help us identify how changes in microRNA abundance contribute to many human disease processes. This grant provides additional funding for a long-term collaboration between Dr. McCall (URMC) and Dr. Halushka (JHMI).
Alexis Zavez selected for William Jackson Hall Graduate Student Fellowship
PhD candidate Alexis Zavez was named as the 2019-2020 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.
Ms. Zavez's research is on developing flexible Bayesian latent variable models that can be utilized by researchers to better understand relationships among multiple observed exposures in the context of a particular outcome. The primary application for her work is inflammatory marker data measured in the Seychelles Child Development Study. Specifically, she is investigating the association between several prenatal inflammatory markers and child birth weight.
Biostatistics and Computational Biology Promotions
The Department of Biostatistics and Computational Biology would like to congratulate the following Faculty on their recent promotions: Changyong Feng, to Full Professor; Xing Qiu, to Full Professor; and Andrea Baran, to Senior Associate.
NIEHS awards another five years of T32 training grant funding
The Department of Biostatistics and Computational Biology’s T32 training grant “Training in Environmental Health Biostatistics” (T32ES007271) was awarded an additional five years of NIEHS funding starting in July 2020, following 25 years of prior NIEHS support. Dr. Sally W. Thurston has been the PI of this highly successful training program for the past five years, following many years of leadership by Dr. David Oakes. Other statistics trainers from the Department of Biostatistics and Computational Biology include Drs. Brent Johnson, Tanzy Love, Matthew McCall, Michael McDermott, and Robert Strawderman, and Environmental Health trainers Drs. Emily Barrett, Deborah Cory-Slechta, David Rich, and Edwin van Wijngaarden. The funding supports one postdoctoral fellow and three Statistics PhD students.
NIDA awards $1.57 million R01 grant to Dr. Ertefaie to study the effect of partial treatment compliance in constructing individualized treatment strategies
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
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
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!"
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
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
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
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
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).
Inaugural Michael P. McDermott Experimental Therapeutics Lecture held
The inaugural Michael P. McDermott Experimental Therapeutics Lecture was held on July 18, 2019. The lecture, titled “The Dark Past and Destiny of Clinical Trials”, was given by Dr. Clay Johnston, Dean of the Dell Medical School and Vice President for Medical Affairs at the University of Texas at Austin. The lecture, to be held annually, was named in honor of Dr. McDermott for his long-standing dedication to the mentoring and education of fellows in the Experimental Therapeutics in Neurological Disease training program in the Department of Neurology. The inaugural lecture was held as part of an event to celebrate the 30th anniversary of the training program, in which Dr. McDermott has been involved since its inception.
Professor Sally W. Thurston named a Fellow of the American Statistical Association
The 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 to 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
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).
William Jackson Hall Graduate Student Fellowship Awarded to Hao Sun
PhD candidate Hao Sun was named as the 2018-2019 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.
Prospective graduate students learn about our Master's and PhD programs
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
Summer 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
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
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 Biostatistics
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.
Professor Brent Johnson selected as an associate editor for the journal Biometrics
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
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
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
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 Michael P. McDermott named a Fellow of the American Statistical Association
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
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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