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X-WR-CALDESC:Events for Department of Statistics
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DTSTART:20240310T070000
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260206T110000
DTEND;TZID=America/New_York:20260206T120000
DTSTAMP:20260422T040638
CREATED:20251215T135146Z
LAST-MODIFIED:20260127T160935Z
UID:29010-1770375600-1770379200@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Rotated Mean-Field Variational Inference and Iterative Gaussianization \nPresenter: Sifan Liu \nAbstract: Mean-field variational inference (MFVI) approximates a target distribution with a product distribution in the standard coordinate system\, offering a scalable approach to Bayesian inference but often severely underestimating uncertainty due to neglected dependence. We show that MFVI can be greatly improved when performed along carefully chosen principal component axes rather than the standard coordinates. The principal components are obtained from a cross-covariance matrix of the target’s score function and identify orthogonal directions that capture the dominant discrepancies between the target distribution and a Gaussian reference. \nPerforming MFVI in a rotated system defines a rotation followed by a coordinatewise transformation that moves the target closer to Gaussian. Iterating this procedure yields a sequence of transformations that progressively Gaussianize the target. The resulting algorithm provides a computationally efficient construction of normalizing flows\, requiring only MFVI sub-problems and avoiding large-scale optimization. In posterior sampling tasks\, we demonstrate that the proposed method greatly outperforms standard MFVI while achieving accuracy comparable to normalizing flows at a much lower computational cost. \n 
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-46/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260206
DTEND;VALUE=DATE:20260207
DTSTAMP:20260422T040638
CREATED:20260113T161431Z
LAST-MODIFIED:20260113T161431Z
UID:29211-1770336000-1770422399@statistics.sciences.ncsu.edu
SUMMARY:Triangle Sports Analytics Competition 2026: Submissions Due
DESCRIPTION:Competition Website
URL:https://statistics.sciences.ncsu.edu/event/triangle-sports-analytics-competition-2026-submissions-due/
CATEGORIES:Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260130T110000
DTEND;TZID=America/New_York:20260130T120000
DTSTAMP:20260422T040638
CREATED:20260121T141202Z
LAST-MODIFIED:20260121T204720Z
UID:29225-1769770800-1769774400@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Finding Anomalous Cliques in Inhomogeneous Networks using Egonets \nPresenter:  Srijan Sengupta \nAbstract: Cliques\, or fully connected subgraphs\, are among the most important and well-studied graph motifs in network science. We consider the problem of finding a statistically anomalous clique hidden in a large network. There are two parts to this problem: (1) detection\, i.e.\, determining whether an anomalous clique is present\, and (2) localization\, i.e.\, determining which vertices of the network constitute the detected clique. While this problem has been extensively studied under the homogeneous Erdos-Renyi model\, little progress has been made beyond this simple setting\, and no existing method can perform detection and localization in inhomogeneous networks within finite time. To address this gap\, we first show that in homogeneous networks\, the anomalousness of a clique depends solely on its size. This property does not carry over to inhomogeneous networks\, where the identity of the vertices forming the clique plays a critical role\, and a smaller clique can be more anomalous than a larger one. Building on this insight\, we propose a unified method for clique detection and localization based on a class of subgraphs called egonets. The proposed method generalizes to a wide variety of inhomogeneous network models and is naturally amenable to parallel computing. We establish the theoretical properties of the proposed method and demonstrate its empirical performance through simulation studies and application to two real world networks. \n 
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-51/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260126T170000
DTEND;TZID=America/New_York:20260126T183000
DTSTAMP:20260422T040638
CREATED:20260113T153332Z
LAST-MODIFIED:20260113T153332Z
UID:29210-1769446800-1769452200@statistics.sciences.ncsu.edu
SUMMARY:Professional Development Workshop
DESCRIPTION:Welcome back! We hope you’re off to a great start to the spring semester. Join us for the first Professional Development Workshop of the calendar year as we kick off the semester with a panel focused on careers in public service. \nCareers in State Government: Applying Statistics and Data Science \n📅 Date: Monday\, January 26\, 2026\n⏰ Time: 5:00 – 6:30 PM\n📍 Location: 5104 SAS Hall Commons \nIn this session\, students will hear from representatives from the North Carolina Office of the State Auditor (NC OSA) in a panel discussion on how statistics and data science are applied in state government. Panelists will also share information about the NC OSA Internship Program and pathways for students interested in government careers. \nWe hope you’ll join us for this informative and timely conversation as we begin the spring semester.
URL:https://statistics.sciences.ncsu.edu/event/professional-development-workshop-4/
LOCATION:5104 SAS Hall (Solomon Commons)\, NC\, United States
CATEGORIES:College of Sciences Calendar,Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260123T110000
DTEND;TZID=America/New_York:20260123T120000
DTSTAMP:20260422T040638
CREATED:20251215T135157Z
LAST-MODIFIED:20251215T144455Z
UID:29009-1769166000-1769169600@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 232A Withers Hall\, NC State Main Campus \nTitle: Multivariate spatial models for high-dimensional ecological data \nPresenter: Jeffrey W. Doser\, Ph.D. \nAbstract: The proliferation of big spatial data from autonomous monitoring systems\, national monitoring programs\, and citizen science platforms offers never-before-seen opportunities to address pressing natural resource management and conservation questions. Yet\, such massive spatial data present a variety of computational and statistical challenges that limit their use by practitioners. In this seminar\, I will discuss recent methodological and software advances that enable efficient modeling of multivariate spatial data where both the number of locations and number of outcomes at each location is large. Case studies motivated by ecological and forestry data will highlight the framework’s utility for informing natural resource management and conservation.
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-47/
LOCATION:Withers Hall 232A
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20260122T160000
DTEND;TZID=America/New_York:20260122T170000
DTSTAMP:20260422T040638
CREATED:20260113T161522Z
LAST-MODIFIED:20260113T161522Z
UID:29214-1769097600-1769101200@statistics.sciences.ncsu.edu
SUMMARY:Triangle Sports Analytics Competition 2026: Virtual Information Session
DESCRIPTION:Zoom Link\nCompetition Website
URL:https://statistics.sciences.ncsu.edu/event/triangle-sports-analytics-competition-2026-virtual-information-session/
CATEGORIES:Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260119
DTEND;VALUE=DATE:20260120
DTSTAMP:20260422T040638
CREATED:20251208T155443Z
LAST-MODIFIED:20251208T155443Z
UID:28967-1768780800-1768867199@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Holiday
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-holiday-12/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260112
DTEND;VALUE=DATE:20260113
DTSTAMP:20260422T040638
CREATED:20251208T155253Z
LAST-MODIFIED:20251208T155346Z
UID:28965-1768176000-1768262399@statistics.sciences.ncsu.edu
SUMMARY:Classes Resume - Spring 2026
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/classes-resume-spring-2026/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260101
DTEND;VALUE=DATE:20260102
DTSTAMP:20260422T040638
CREATED:20251208T154746Z
LAST-MODIFIED:20251208T155105Z
UID:28963-1767225600-1767311999@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-7/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251231
DTEND;VALUE=DATE:20260101
DTSTAMP:20260422T040638
CREATED:20251208T154658Z
LAST-MODIFIED:20251208T154658Z
UID:28960-1767139200-1767225599@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-6/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251230
DTEND;VALUE=DATE:20251231
DTSTAMP:20260422T040638
CREATED:20251208T154605Z
LAST-MODIFIED:20251208T154952Z
UID:28958-1767052800-1767139199@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-5/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251229
DTEND;VALUE=DATE:20251230
DTSTAMP:20260422T040638
CREATED:20251208T154501Z
LAST-MODIFIED:20251208T154501Z
UID:28956-1766966400-1767052799@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-4/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251226
DTEND;VALUE=DATE:20251227
DTSTAMP:20260422T040638
CREATED:20251208T154305Z
LAST-MODIFIED:20251208T154820Z
UID:28954-1766707200-1766793599@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-3/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251225
DTEND;VALUE=DATE:20251226
DTSTAMP:20260422T040638
CREATED:20251208T153935Z
LAST-MODIFIED:20251208T154342Z
UID:28952-1766620800-1766707199@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break-2/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251224
DTEND;VALUE=DATE:20251225
DTSTAMP:20260422T040638
CREATED:20251208T153727Z
LAST-MODIFIED:20251208T153827Z
UID:28948-1766534400-1766620799@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Winter Break
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-winter-break/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251213
DTEND;VALUE=DATE:20251214
DTSTAMP:20260422T040638
CREATED:20250203T180930Z
LAST-MODIFIED:20250203T180930Z
UID:27784-1765584000-1765670399@statistics.sciences.ncsu.edu
SUMMARY:University Graduation
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-graduation-3/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251212
DTEND;VALUE=DATE:20251213
DTSTAMP:20260422T040638
CREATED:20251208T161509Z
LAST-MODIFIED:20251208T161541Z
UID:29001-1765497600-1765583999@statistics.sciences.ncsu.edu
SUMMARY:Department Graduation
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/department-graduation/
CATEGORIES:Department,Faculty,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251210
DTEND;VALUE=DATE:20251211
DTSTAMP:20260422T040638
CREATED:20251208T161351Z
LAST-MODIFIED:20251208T161351Z
UID:28998-1765324800-1765411199@statistics.sciences.ncsu.edu
SUMMARY:Final Exams
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/final-exams-71/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251209
DTEND;VALUE=DATE:20251210
DTSTAMP:20260422T040638
CREATED:20251208T161304Z
LAST-MODIFIED:20251208T161304Z
UID:28996-1765238400-1765324799@statistics.sciences.ncsu.edu
SUMMARY:Final Exams
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/final-exams-70/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251208
DTEND;VALUE=DATE:20251209
DTSTAMP:20260422T040638
CREATED:20251208T161218Z
LAST-MODIFIED:20251208T161218Z
UID:28994-1765152000-1765238399@statistics.sciences.ncsu.edu
SUMMARY:Final Exams
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/final-exams-69/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251203
DTEND;VALUE=DATE:20251204
DTSTAMP:20260422T040638
CREATED:20250203T180606Z
LAST-MODIFIED:20250203T180606Z
UID:27779-1764720000-1764806399@statistics.sciences.ncsu.edu
SUMMARY:Reading Day
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/reading-day-13/
CATEGORIES:College of Sciences Calendar,Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251128
DTEND;VALUE=DATE:20251129
DTSTAMP:20260422T040638
CREATED:20250203T173035Z
LAST-MODIFIED:20250203T173035Z
UID:27740-1764288000-1764374399@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Holiday
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-holiday-41/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251127
DTEND;VALUE=DATE:20251128
DTSTAMP:20260422T040638
CREATED:20250203T172924Z
LAST-MODIFIED:20250203T172924Z
UID:27738-1764201600-1764287999@statistics.sciences.ncsu.edu
SUMMARY:University Closed - Holiday
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/university-closed-holiday-40/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20251126
DTEND;VALUE=DATE:20251127
DTSTAMP:20260422T040638
CREATED:20250203T180502Z
LAST-MODIFIED:20250203T180502Z
UID:27777-1764115200-1764201599@statistics.sciences.ncsu.edu
SUMMARY:No Classes - Holiday
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/no-classes-holiday-11/
CATEGORIES:Department,Faculty,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251117T170000
DTEND;TZID=America/New_York:20251117T183000
DTSTAMP:20260422T040638
CREATED:20251106T143441Z
LAST-MODIFIED:20251106T143441Z
UID:28903-1763398800-1763404200@statistics.sciences.ncsu.edu
SUMMARY:November Professional Development Workshop
DESCRIPTION:Professional Development Workshop – November Session\nExploring Graduate School in Statistics: Programs + Student Panel\n📅 Date: Monday\, November 17\, 2025⏰ Time: 5:00 – 6:30 PM📍 Location: SAS Hall 2229💻 Virtual Option: https://go.ncsu.edu/stat.pdw✅ Hybrid Event — Attend in person or join via Zoom \n\nJoin us for this month’s Professional Development Workshop\, co-sponsored by the Department of Statistics and the Statistics Club. This special session will feature two parts: \n1. Information Session: Statistics Graduate Programs\nHear from Dr. Stallrich and Dr. Jeng\, who will provide an overview of the graduate programs they oversee. They will share key details about program structure\, opportunities\, and what students can expect in their graduate studies. \n2. Grad Student Panel: The Transition from Undergrad to Graduate School\nFollowing the information session\, we’ll host a panel conversation with current graduate students who will discuss their experiences moving from undergraduate study into graduate programs.The Q&A will be moderated\, with time for open questions from attendees. \nThis is a great event for anyone considering graduate studies in Statistics or wanting to learn more about life as a graduate student. \nWe hope you’ll join us—either in person or online!
URL:https://statistics.sciences.ncsu.edu/event/november-professional-development-workshop/
LOCATION:2229 SAS Hall
CATEGORIES:College of Sciences Calendar,Department,Graduate,Undergraduate,University
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251114T120000
DTEND;TZID=America/New_York:20251114T160000
DTSTAMP:20260422T040638
CREATED:20251028T175031Z
LAST-MODIFIED:20251028T175537Z
UID:28887-1763121600-1763136000@statistics.sciences.ncsu.edu
SUMMARY:Professional Development Workshop
DESCRIPTION:Databricks + NCSU Student Exchange \n\nJoin us on Nov 14th at 12pm in SAS Hall 1216 for some pizza and an afternoon with Databricks. \nDatabricks will be in Raleigh providing an exchange of information and ideas on how the market is being driven by an increased usage of  Data and AI.  We invite students interested in building a career in data\, analytics\, machine learning\, AI or otherwise\, to join the forum: \n– to better understand the market growth \n– how to build a competitive curriculum for potential employment\, \n– what is available from the school \n– what is free and available to use. \nAdditionally\, we will discuss the “Art of the Possible” with Data and AI with how that is changing the world for us as data consumers and data providers.  We encourage students to actively engage in an interactive Q&A with the Databricks team for the best understanding possible. \n\n++++\n\n\n\n\nTime\nActivity \n\n\n12:00 – 1pm\nLunch and Networking\n\n\n  \n1 – 1:45 pm\n  \nDatabricks Overview & Data and AI Market Potential\n\n\n  \n2 – 2:30 pm\n  \nWhat makes a good Data and AI employee candidate?\n\n\n  \n2:30 – 3:15 pm\n  \nHow to structure a career with a Data and AI trajectory with live Q&A\n\n\n3:15 – 4pm\n  \n  \n  \nWhat is available now for the students \n  \n\nEnrolling in Free Edition\nWhat is available in the FSU catalog and how can that be extended via the UA and Databricks Catalog\nReviewing the Catalog
URL:https://statistics.sciences.ncsu.edu/event/professional-development-workshop-3/
LOCATION:1216 SAS Hall
CATEGORIES:College of Sciences Calendar,Department,Graduate,Undergraduate
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251114T100000
DTEND;TZID=America/New_York:20251114T120000
DTSTAMP:20260422T040638
CREATED:20251020T175034Z
LAST-MODIFIED:20251020T175034Z
UID:28870-1763114400-1763121600@statistics.sciences.ncsu.edu
SUMMARY:Statistics Student Poster Session
DESCRIPTION:
URL:https://statistics.sciences.ncsu.edu/event/statistics-student-poster-session/
LOCATION:5104 Commons
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251107T110000
DTEND;TZID=America/New_York:20251107T120000
DTSTAMP:20260422T040638
CREATED:20251020T174839Z
LAST-MODIFIED:20251031T142221Z
UID:28868-1762513200-1762516800@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 2203 SAS Hall\, NC State Main Campus \nTitle: Cracking the Code of the Unknown Virosphere: Detecting the Undetectable. \nPresenter:  Bonnie Hurwitz (BRC-NCSU) \nAbstract: Viruses are the most abundant biological entities on Earth and infect all major clades of life\, including bacteria\, archaea\, and eukaryotes. During infection\, viruses can influence host biology\, evolution\, and ecosystem dynamics; however\, 90% of viral DNA in natural communities is unknown\, limiting our understanding of host\, bacterial\, and viral interactions in diverse ecosystems. To explore these novel viral communities\, we are developing new tools and methods using machine learning and natural language processing to examine and interrelate viral and microbial communities with their environmental contexts in unprecedented depth and detail. Here\, I describe work in my lab to develop new capabilities in (i) viral sequence detection using composition-based pattern detection and machine learning\, and (ii) emerging biological stories in how we are using these tools to find novel viruses in the gut microbiome. These new approaches provide exciting avenues to find novel viruses and explore their interactions with diverse hosts and ecosystems without being limited to the known fraction of the viral population.
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-43/
LOCATION:2203 SAS Hall
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251031T110000
DTEND;TZID=America/New_York:20251031T120000
DTSTAMP:20260422T040638
CREATED:20251020T173731Z
LAST-MODIFIED:20251020T174546Z
UID:28864-1761908400-1761912000@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 2203 SAS Hall\, NC State Main Campus \nTitle: Synthetic Populations\, Personas and Agents \nPresenter: Georgiy Bobashev\, Ph.D. \nAbstract: Many experiments and estimate are not feasible or unethical to conduct with real people but possible in silico with synthetic individuals. I will present the construction\, and the use of geospatially explicit and statistically accurate person and household data\, which allow researchers to study community-and neighborhood-level effects\, design and test hypotheses that would not be possible without synthetic data. I will present the workflow for generating spatially explicit household- and individual-level synthetic populations for the United States representing 330 million individuals. Synthetic population could be used to probabilistically link multiple datasets for a specific purpose. There are statistical challenges with calibration and validation of these datasets. Agent-based models use these synthetic populations to study policy implications\, disease spread\, drug using behaviors\, etc. The use of synthetics individuals is now broadly expanding into health\, economic\, defense and other areas. With the developments of AI\, AI agents are taking over certain functions\, which creates new challenges in the development\, calibration and validation of these synthetic individuals.
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-42/
LOCATION:2203 SAS Hall
CATEGORIES:College of Sciences Calendar,Department,Seminars
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20251024T110000
DTEND;TZID=America/New_York:20251024T120000
DTSTAMP:20260422T040638
CREATED:20251013T174330Z
LAST-MODIFIED:20251013T174330Z
UID:28836-1761303600-1761307200@statistics.sciences.ncsu.edu
SUMMARY:Statistics Seminar
DESCRIPTION:Location: 2203 SAS Hall\, NC State Main Campus\n\nSpeaker: Dr. Vadim Zipunnikov\, Johns Hopkins Bloomberg School of Public Health\n\nTitle: Developing more sensitive endpoints by leveraging novel statistical methods for Digital\nHealth Technologies (DHTs) data\n\nAbstract: Digital Health Technologies (DHT) are now used to continuously track physical\nactivity and sleep in many clinical studies. This DHT data provides tremendous opportunities to\ndevelop novel more sensitive clinical trial endpoints. There is\, however\, a large gap between the\ncomplexity of DHT data and statistical methodology for fully leveraging the potential of DHT.\nThis talk will discuss recent developments of novel DHT-centric statistical methods that can\nprovide more sensitive endpoints by extracting and fusing together information from temporal\,\ndistributional\, and time-series aspects of DHT data.\n\nBio: Dr. Vadim Zipunnikov is an Associate Professor of Biostatistics at Johns Hopkins Bloomberg School of Public Health. He co-leads the Wearable and Implantable Technology (WIT) group at Johns Hopkins University and serves as the Biostatistics Director of the NIMH-funded Motor Activity Research Consortium for Health (mMARCH)\, overseeing collection and analysis of large-scale digital health data across several clinical sites globally. Dr. Zipunnikov’s research focuses on developing advanced statistical methods for analyzing multimodal digital health data (DHT) from wearables and smartphones\, including accelerometry\, heart rate\, glucose monitors\, and ecological momentary assessment (EMA). In his work\, Dr. Zipunnikov collaborates with the Food and Drug Administration on digital analytics for drug development\, having developed a two-year course for the FDA’s Office of Biostatistics to equip drug reviewers with essential skills in DHT analytics. His research has garnered press coverage in NIH Research Matters\, NIH Directors’ blog\, TIME\, Washington Post\, Wall Street Journal\, CNN\, and BBC Radio. He has mentored 14 PhD students and 4 postdoctoral fellows and has authored over 100 peer-reviewed publications on digital biomarkers of physical/motor activity\, sleep\, and circadian rhythmicity in neurological and mental health disorders\, including Alzheimer’s Disease\, Multiple Sclerosis\, and Bipolar Disorder. He is known for his collaborative approach\, mentoring emerging researchers\, developing novel DHT-centric methods\, and his smile.
URL:https://statistics.sciences.ncsu.edu/event/statistics-seminar-41/
LOCATION:2203 SAS Hall
CATEGORIES:College of Sciences Calendar,Department,Seminars
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