2026 Candidate Profiles
President- Elect Nominee
Professor and Chair of the Department of Statistics and Professor of the Department of Biostatistics, Harvard University
Education
- BS in Applied Mathematics, Tsinghua University (1989)
- PhD in Biostatistics, University of Washington (1994)
Research Interests
- Integrative statistical, machine learning and generative AI methods
- Statistical genetics and genomics
- Analysis of massive Whole Genome Sequencing and biobank data
- Integrative analysis of different types of data
- Causal inference, causal mediation analysis and Mendelian Randomization
- Statistical methods for correlated and complex population and experimental data
- Nonparametric and semiparametric regression methods
- Measurement errors and missing data
- Random effects models and estimating equations
Previous Service to the Profession
- Previous IMS service:
- Chair, IMS AI committee, 2024-2025
- Member, IMS Fellow Selection Committee, 2019-2022
- IMS Council Member, 2018-2021
- Member, Joint Committee on Women in Mathematics, Institute of Mathematical Statistics and American Mathematical Society, 2008-2010
- Member, Program Committee, IMS-Pacific Rim Conference
- Editors and Associate Editors:
- Co-editor, Journal of the American Statistical Association Special AI Issue, 2024-
- Editor, Computational Biology Series, Taylor and Francis, 2012-2018
- Founding Co-Editor, Statistics in Biosciences (2009-2015)
- Coordinating Editor, Biometrics (2003-2005)
- Associate Editor, Journal of American Statistical Association, Applications and Case Studies, (1999-2002, 2013-2019)
- Associate Editor, Biometrika (2008-2011)
- Associate Editor, Biometrics (1997-2002)
- Associate Editor, Biostatistics (2000-2002)
- Other National and International Committee appointments:
- Committee Member, Study on Frontiers of Statistics in Science and Engineering: 2035 and Beyond, US National Academies of Sciences, Engineering and Medicine, 2025-2026.
- Committee Member, Study on International Talent Programs in the Changing Global Environment, US National Academies of Sciences, Engineering and Medicine, 2023-2024
- Chair, Organizing Committee of the International Prize in Statistics, ASA, 2022
- Member, Organizing Committee, ASA Chair Workshop, 2017 and 2018
- Founder, US Biostatistics Chair Group and annual meeting, 2016
- Chair, Statistical Genetics and Genomics Section, American Statistical Association, 2016
- Member, Noether Award Committee, American Statistical Association, 2014-2016
- Member, Regional Advisory Committee, ENAR. 2015-2017
- Member, Committee of Theoretical and Applied Statistics, US National Academy of Sciences, Engineering and Medicine, 2010-2015
- Chair, Committee of the Presidents of Statistical Societies (COPSS), 2010-2012
- Member, Board of Directors, National Institute of Statistical Sciences, 2010-2012
- Council member (2009-2014) and Editorial Representative, Executive Committee (2004-2007), International Biometric Society
- Member, Board of Directors, International Chinese Statistical Association, 2004-2006
- Chair and member, Spiegelman Award Selection Committee, American Public Health Association (APHA)(Member, 2003-2004, Chair, 2005)
- Member, Nomination Committee, ENAR, 2001-2003
- Scientific Advisory Committee Appointments:
- Member, Technical Advisory Group on COVID-19 Mortality Assessment, World Health Organization (WHO) and United Nation Department of Economic and Social Affairs (UN DESA), 2021-present
- Member, State of MA COVID-19 Task Force, 2020
- Member, Australia Research Council Centre of Excellence for Mathematical & Statistical Frontiers, 2015-2023
- Member, Advisory Committee, National Children Study, 2011-1015
- Member, Advisory Committee, National Institute of Statistical Science, 2009-2012
- National and International Conference Appointments:
- Program Committee, Joint Biostatistics Symposium, 2018
- Member, Program Committee, International Biometric Conference, 2012
- Member, Program Committee, 2006 IBC, Toronto
- Program Chair, 2000 ENAR Meetings, Chicago
Brief Statement
I am greatly honored to be nominated as President-Elect of the IMS, a society I greatly admire and care about. The IMS plays a vital role in advancing foundational theory, methodology, and applications in statistics and data science, while navigating the transformative opportunities and responsibilities posed by AI in research, education and practice. I would like to work with the IMS community to foster innovation and strengthen the impact of statistical science in the age of AI; support early-career researchers; advance education and research opportunities; and reinforce the IMS as a vibrant and inclusive global society through enhanced collaboration and communication.
Council Nominees
You may view the profile for each nominee by clicking on their name below.
Education
- PhD, Department of Statistics, University of California, Berkeley, 2008
Research Interests
- Probability on networks and random graphs, including structure and dynamics of random graph models and universality phenomena in critical regimes.
- Interacting stochastic processes on complex networks, such as epidemics, flows, and first/last passage percolation on sparse random graphs.
- Random trees, coalescent processes, and scaling limits, with emphasis on continuum limits and multiplicative coalescents.
- Statistical network analysis, including community detection, network tomography, and modeling of weighted and multilayer networks.
- Algorithmic aspects of stochastic models, including Markov chain Monte Carlo on network models and stochastic approximation methods for dynamic networks.
Previous Service to the Profession
- Associate editors for multiple journals including Statistical Science, Bernoulli and Annals of Applied Probability.
Brief Statement
I am honored to be nominated for the IMS Council. Throughout my career, I have benefited deeply from the IMS community: its journals, meetings, and the steady volunteer work that sustains our field, from thoughtful refereeing and editorial service to mentoring and advocacy for colleagues. I feel it is my turn to contribute in return. This is a turning point for our profession as new technologies reshape how quantitative work is produced and used, and I would welcome the chance to help IMS respond with rigor, openness, and care.
Professor of Statistics & Data Science at Cornell University, and Fellow at Cornell’s Center for Data Science for Enterprise and Society, Cornell University
Education
- 2011 — Ph.D., Princeton University, Operations Research & Financial Engineering
- 2007 — M.S., University of Belgrade, Department of Mathematics
Research Interests
- Theory-driven methods for causal inference and robust high-dimensional learning under realistic assumptions.
- Causal inference: ATE estimation under weak identification; dynamic/time-varying treatments; individualized policy learning with treatment heterogeneity.
- Robustness: Methods resilient to misspecification, sparsity violations, and distribution shift; minimax/adaptively robust estimators and theory-guided ML.
- Incomplete data & AI: Principled inference with missing/censored/semi-supervised data; foundations for reliable AI in high-stakes settings.
Previous Service to the Profession
- Editorial leadership
- Co–Editor-in-Chief, ACM/IMS Journal of Data Science (joint ACM–IMS journal), with Stratos Idreos and John Lafferty, 2022–2026
- Editorial service
- Associate Editor, JASA (Theory & Methods), 2019–present
- Associate Editor, Journal of Nonparametric Statistics, 2019–present
- Associate Editor, Scandinavian Journal of Statistics, 2019–present
- Associate Editor, JRSS-B, 2020–2021
- Conference and society leadership
- Program Chair (elected), ASA Section on Statistical Learning & Data Science (SLDS), 2021
- Program Co-Chair, Statistical Learning and Data Science Conference, 2020
- Program Chair, ASA SLDS at JSM (year not recalled)
- Multiple session organizer and speaker, IMS/SLDS/ASA/ISNPS and related meetings
- Institutional and committee service
- Committee member, development of the Data Science undergraduate minor, UC San Diego, 2017
- Founding faculty member (one of the first 15), Halıcıoğlu Data Science Institute (HDSI), UC San Diego, 2018
- Committee member, ISNPS; Chair, Student Paper Awards, 2026-
- Committee member, Student Paper Awards, ASA SLDS (JSM), 2020
- Treasurer, ASA Nonparametric Statistics Section, 2020
- NSF DMS Panelist (Statistics section) (2016, 2017, 2019)
- NSF DMS Career award Panelist (Statistics section) (2024, 2026)
Brief Statement
Thank you for considering my nomination to the IMS Council. I offer a perspective grounded in robust causal inference, double robustness, and high-dimensional statistics. If elected, I shall work to ensure that IMS remains the professional home for foundational probability and statistics, whilst engaging thoughtfully with rapidly evolving data science and artificial intelligence. My priorities include supporting members with guidance and fora on reliable inference in modern data science and AI, strengthening mentoring and visibility for early-career researchers, and fostering inclusive, globally connected programmes.
Professor of Statistics, Department of Mathematical Sciences, University of Copenhagen, Denmark
Education
- PhD, 2005, Biostatistics Department, University of Copenhagen
- MSc Statistics, 2000, Department of Mathematical Sciences, University of Copenhagen
- MSc Mathematics, 1999, Universidad Nacional de Educación a Distancia, Spain
Research Interests
- Statistical inference for stochastic processes
- Nonlinear dynamics
- Biostatistics
- Statistical ecology, in particular marine mammals in the Arctic
- Climate changes and tipping points
- Mathematical modeling of physiological systems
- Neuronal modelling
Previous Service to the Profession
- President of the Royal Danish Academy of Sciences and Letters (2024-2028)
- Vice-president, Presidium of the Royal Danish Academy of Sciences and Letters (2021-2024)
- Associate Editor Biometrika (2018-2024)
- Associate Editor Scandinavian Journal of Statistics (2010-2016)
- Associate Editor Mathematical Biosciences and Engineering (2007-2020)
- Chair of scientific committee for ECMTB-SMB conference in Nottingham (2016)
- Chair of ICMNS conference in Copenhagen (2019)
- Council member of the Bernoulli Society for Mathematical Statistics and Probability (2021-2025)
- Member of the European Math Society, Applied Math Committee (2018-2021)
- Member of the board of European Society of Mathematics and Theoretical Biology (2015-2020)
- Member Nasjonal bedømmelseskomite for opprykk til professor, Statistikk, Norge (2020-2023)
- Member ”faglig referencegruppe for varslingssystemet, COVID-19”, Sundhedsministeriet (2020-2022)
Brief Statement
I am honored to be nominated for the IMS council. I believe we are at a time when statistics are more important than ever due to the rapidly increasing volume and complexity of data. To make sound decisions and draw reliable conclusions, a full understanding of algorithms in data science and strong control over the properties of estimators are essential, which is why the IMS journals, conferences and our community are pivotal in this new era of data science. Moreover, interdisciplinary collaboration plays a crucial role, as statistical thinking and tools are most powerful when they are integrated across different fields and applied to complex, real-world problems. I hope to contribute to the continued development of our community, and to foster appropriate analysis and responsible use of data in other fields.
Education
- PhD in Mathematics, University of Buenos Aires, 2003
Research Interests
- Interacting Particle Systems
- Quasi-stationary Distributions
- Branching-selection Particle Systems
- Stochastic Models for Synchronization Phenomena
- Geometric and Topological Statistics
- Random Growth Processes
- Stochastic Differential Equations
- Reconstruction in Dynamical Systems
Previous Service to the Profession
- Associate Editor, Chaos, Solitons & Fractals
- Advisory Board, Bunge & Born Award (2018)
- Head, Undergraduate Data Science Program, University of Buenos Aires
- Review Panelist for Latin American Science Agencies (Argentina, Brazil, Chile, Colombia, Peru, Uruguay)
Brief Statement
I am honored by this nomination. The IMS’s mission thrives on both scientific rigor and a vibrant, global community. I bring the necessary perspective of a Latin American researcher and a practice that bridges probability with mathematical statistics and data science. On Council, I will be a steadfast advocate for the exceptional standards that define IMS publications and activities, ensuring this quality continues to unite and elevate our diverse membership worldwide and across disciplines.
Education
- B.S. Statistics, University of Science and Technology of China 2001
- M.S. Population Health Sciences, University of Wisconsin, Madison 2005
- Ph.D. Statistics, University of Wisconsin, Madison 2006
Research Interests
- Change point
- Diagnostic medicine
- Instrumental variable
- Network
- Personalized medicine
- Statistical learning
- Survival analysis
Previous Service to the Profession
- AE or Editorial Board Member for statistical journals: Annals of Applied Statistics, Annual Review of Statistics and Its Application, Biometrics (2010-2018), Biostatistics and Epidemiology, Lifetime Data Analysis, Statistical Methods in Medical Research
- Statistical Editor or Statistical Advisor for medical journals: Biomarkers, British Journal of Psychiatry, PLOS One, Research Methods in Medicine & Health Sciences
- International Biometric Society (IBS), Budget and Finance Committee: 2016-2019, 2020-2023
- International Chinese Statistical Association (ICSA), Board of Directors, 2024-2026
- Program Committee of IMS Asian Pacific Rim Meeting (APRM), 2024
- Program Committee of IMS International Conference of Statistics and Data Science (ICSDS), 2022-2024
- Co-chair of Organizing Committee for five Institute of Mathematical Sciences workshops in Singapore
Brief Statement
I am truly honored to be nominated for the IMS Council election. The IMS has played a vital role in my professional journey, and I deeply value its commitment to advancing probability and statistics as pillars of modern data science. I have collaborated extensively with statistical and medical researchers worldwide, which has strengthened my appreciation for a global and inclusive scientific community. If elected, I will actively contribute to IMS’s mission, promote international and interdisciplinary partnerships, expand engagement with developing regions, and support early-career researchers. It would be a privilege to serve the IMS during this transformative era for our field.
Eberly Family Chair Professor of Statistics, Department of Statistics, The Pennsylvania State University at University Park
Education
- Ph.D. in Statistics, 2000, University of North Carolina at Chapel Hill
- MS in Statistics, 1993, Institute of Applied Math, Chinese Academy of Sciences
- BS in Mathematics, 1990, Beijing Normal University
Research Interests
- Variable selection and feature screening for high-dimensional data
- Nonparametric and semiparametric regression modeling
- Statistical genetics and bioinformatics
- Statistical applications to engineering, meteorological research, neural science research & social behavioral science research
Previous Service to the Profession
- Service to the IMS
- Co-Editor of Annals of Statistics (2013-2015)
- Associate of Annals of Statistics (2007-2012)
- Associate Editor of Electronic Journal of Statistics: 2022-present
- Chair of scientific program committee for the 4th IMS China, July 1 – 4, 2013, Chengdu, China
- Co-chair of scientific program committee for the second IMS Asia Pacific Rim meeting in 2012, Tokyo, Japan
- Co-chair of scientific program committee for the first IMS Asia Pacific Rim meeting in 2009, Seoul, Korea
- IMS program chair for ENAR05, Austin, Texas
- Member of IMS Committee to Select Editors, 2020
- Member of publication committee, IMS (2013-2015)
- Member of committee on special lectures, IMS (2012 – 2014)
- Co-Chair for the Committee on Asia Pacific Rim Meeting of IMS (09/2007- 08/2012)
- Service to the Profession beyond the IMS
- Co-editor- elected and Co-editor of Journal of American Statistical Association (2026-2029)
- Co-editor of Statistical Learning and Data Science, 2025-present
- Associate Editor of Journal of American Statistical Association (2006-2026)
- Associate Editor of Journal of Multivariate Analysis: 2019-present
- Editorial board member of Science China Mathematics: 2018-present
- Associate Editor of Statistica Sinica: 2005—2012
- Chair of Scientific Program Committee of Statistical Foundations of Data Science and Their Application. May 8 – 10, 2023, Princeton University, USA.
- Associate Chair for Machine Learning and AI, Scientific Program Committee for the 2nd China
- Joint Statistical and Data Science Meetings (CJSM) July 12-14, 2024, Kunming, P.R. China.
- ASA Biometrics Section program chair for JSM 2007, August 2007, Salt Lake City, Utah
- Chair-elect, Chair and Past-Chair of ASA Nonparametric Statistics Section, 2019-2021.
- Chair of Publication Committee, The International Chinese Statistical Association, 2023, 2024, 2025
- Directors of International Chinese Statistical Association (ICSA) Board, 2007-2009
Brief Statement
I am deeply honored to be nominated for the IMS Council. Throughout my academic career, IMS has played an important role in supporting my professional growth. As an IMS Council member, I would be dedicated to advancing the mission of IMS, strengthening its leadership in the statistical communities, and shaping its influence on the development of AI, data science, and modern statistical learning, through conferences and publications, mentorship of junior researchers, and the training of graduate students.
Education
- University of California, Berkeley, Ph.D., Computer Science, May 2012
- Designated Emphasis in Communication, Computation, and Statistics
- University of California, Berkeley, M.A., Statistics, December 2011
- Princeton University, B.S.E., Computer Science, summa cum laude, June 2007
Research Interests
- Statistical machine learning
- Scalable algorithms
- Approximate inference
- Distribution compression
- High-dimensional statistics
- Probability
- Subseasonal forecasting
- Social good
Previous Service to the Profession
- Neural Information Processing Systems Foundation Board, 2024-
- Chair, ASA Section on Bayesian Statistical Science, 2025
- General Chair, Neural Information Processing Systems (NeurIPS), 2024
- COPSS Emerging Leader Award Committee, 2023-2024
- IMS Committee on Nominations, 2023-2024
- Ethics Review Chair, Neural Information Processing Systems (NeurIPS), 2023
- Census Scientific Advisory Committee, United States Census Bureau, 2021-2022
- Diversity and Inclusion Chair, Neural Information Processing Systems (NeurIPS), 2020, 2021
- Science Advisory Board, Institute for Pure & Applied Mathematics (IPAM), 2021
- Treasurer, International Society of Bayesian Analysis (ISBA) Section on Bayesian Computation (BayesComp), 2019-2020
- Scientific Committee, International Conference on Monte Carlo & Quasi-Monte Carlo Methods in Scientific Computing
- (MCQMC), 2025-2027
- Organizer, Workshop on Sampling Methods for Problems in Machine Learning and Data Sciences, Institute for Mathematical Sciences, 2025
- Organizer, Workshop on Sampling Methods for Problems Involving Differential Equations and Physical Sciences, Institute for Mathematical Sciences, 2025
- Organizer, Invited Session on Statistical Machine Learning, IMS Annual Meeting, 2022
- Organizer, Stein’s Method – The Golden Anniversary, Institute for Mathematical Sciences, 2022
- Organizer, Advances in Stein’s Method and Its Applications in Machine Learning and Optimization, BIRS, 2022
- Organizer, Workshop on Stein’s Method in Machine Learning and Statistics, ICML, 2019
- Organizer, Workshop on AI for Social Good, ICML, 2019
- Organizer, Session on Probabilistic Methods in Machine Learning, SPA, 2018
- Chair, Session on Convex Modeling for High-Dimensional Data Analysis, ASC-IMS, 2014
- Organizer, Workshop on Sparse Representation and Low-rank Approximation, NeurIPS, 2011
- Senior Area Chair / Senior Meta-Reviewer for International Conference on Machine Learning (ICML), 2022-
- Area Chair / Meta-Reviewer for ICML, 2019-2021
- Reviewer for ICML, 2013-2018
- Senior Area Chair for Neural Information Processing Systems (NeurIPS), 2021-2023, 2025-
- Area Chair for NeurIPS, 2017-2020
- Reviewer for NeurIPS, 2010-2016
- Editor for Environmental Data Science, 2021-2023
- Associate Editor for SIAM Mathematics of Data Science (SIMODS), 2023-2025
- Associate Editor for Annals of Statistics, 2019-2022, 2026-
- Proceedings of the National Academy of Sciences (PNAS) Statistical and Methodological Review Committee, 2024-2026
Brief Statement
I am honored that the IMS community is considering me for this position and excited to give back to a community that has already given me so much. I am a bridge builder and if elected will do my best to build and reinforce bridges between theory and application, between industry and academia, and between statistics and the world.
Education
- B.Stat., Statistics, Indian Statistical Institute, 1997
- M.Stat., Statistics, Indian Statistical Institute, 1999
- M.A., Statistics, University of California, Santa Barbara, 2000
- Ph.D., Statistics, Stanford University, 2005
Research Interests
- High-dimensional statistics
- Random matrix theory
- Random dynamical systems
- Neuroimaging
- Spatial statistics
Previous Service to the Profession
- Associate Editor of Journal of the American Statistical Association (2024- ), The Annals of Statistics (2013-2021), Bernoulli (2016-2018), Electronic Journal of Statistics (2016-2024), Journal of Statistical Planning and Inference (2012- 2023) , Series A (2012- ), Statistica Sinica (2009-2014); Guest editor of Computational Statistics and Data Analysis (2020-2021).
- Member: Committee on IMS New Researchers’ Conference (2011-2013)
- Conferences: Program/organizing committee member of at least eight symposia and workshops (including two BIRS workshops and one MATRIX workshop)
Brief Statement
It is a great honour to be nominated for election to the IMS Council. IMS has been playing an exemplary role in providing high-quality outlets for dissemination of statistical and mathematical research and creating open and equitable platforms for scholastic activities. If elected to the IMS council, I hope to be able to contribute by focusing especially on the following aspects: supporting young statisticians in building professional careers, improving participation of students and scholars from developing countries in IMS sponsored events, and increasing access to quality statistical education among a wider group of students, especially those from economically disadvantaged background.
Ge Li and Ning Zhao Professor of Statistics and Data Science, Department of Statistics and Data Science, The Wharton School, University of Pennsylvania
Education
- Ph.D. in Statistics, Stanford University, 2005
- M.S. in Computer Science, Stanford University, 2001
- B.S. in Mathematics, Stanford University, 2001
Research Interests
- Statistical foundations for single-cell and spatial genomics
- Data integration, denoising, and variance decomposition
- Statistical methods for studying cellular evolution, cancer, and aging
- High-dimensional inference and structured change-point detection
- Translational statistics at the interface of statistics, biology, and medicine
Previous Service to the Profession
- Chair, ASA Section on Statistical Genetics and Genomics (2023-2024)
- Editorial service including Annals of Applied Statistics (2015-2018), Briefings in Bioinformatics (2017-2021), and Genome Research (2020-2021)
- Extensive service on NIH and NSF study sections since 2011
- Taught and organized introductory overview lectures and workshops for ASA (2018, 2020, 2025).
Brief Statement
I am truly honored to be nominated for the IMS Council, and it will be my privilege to serve. I am committed to strengthening the role of statistics as a foundational discipline across the sciences, while ensuring that our core principles continue to shape emerging data-driven fields. Through my work bridging statistics with biology and medicine, I have seen both the growing opportunities for statistics to shape modern scientific discovery and the importance of statisticians to remain visible, engaged, and well represented. As an IMS Council member, I would work to broaden participation, amplify diverse voices, and help position statistics as an integrative and forward-looking discipline.
Kenan Distinguished Professor of Biostatistics, Statistics and Operational Research, Computer Science, Genetics, and Radiology, University of North Carolina at Chapel Hill
Education
- Ph.D, 2000, The Chinese University of Hong Kong
Research Interests
- Medical Imaging Analysis
- Functional Data Analysis
- Imaging Genetics
- Deep Learning
- Reinforcement Learning
- Big Data Integration
- Causal Inference
- e-commerce
Previous Service to the Profession
- Editor for Journal of American Statistical Association Application & Case Studies and Coordinating Editor, 2025-2027
- Associate Editor:
- 2009-2011, Biometrics
- 2007-2018, Statistics and its Interface
- 2011-2017, Neurosurgery
- 2011-, Statistica Sinica
- 2012-2018, Journal of American Statistical Association, A&CS
- 2013-2018, Annals of Statistics
- 2014-2018, Journal of American Statistical Association, T&M
- 2015-2020, Statistics in Biosciences
- 2015-2021, Computational Statistics and Data Analysis
- 2019-2023, Journal of Royal Statistical Society, Series B
- Statistical Consultant and Reviewer, New England Journal of Medicine-AI, 2024-
- Steering Committee Member, ASA Statistics up AI group, 2024-
- NIH and NSF panel reviewer, 2008-
- Student Award Committee, ICSA 2006 Applied Statistics Symposium
- International Chinese Statistical Association Board of Directors, 2012-2014
- ICSA Mentor-Mentee Program, 2024-
- Acting Chair 2012-2013 of Section on Statistics in Imaging in ASA
- ENAR Education advisory committee, 2011
- ENAR Student Award Committee, 2010-2013
- IMS Committee for the Hall Prize, 2023-2026
- Co-chair:
- Neuroimaging Data Analysis workshop at Banff, 2016
- Tsinghua-Sanya Mathematics and Statistics Workshop, 2016
- Information Processing in Medical Imaging (IPMI), 2017
- Workshop on Applications-Driven Geometric Functional Data Analysis, 2017
- Recent Advances in Statistical Analysis of Imaging Data, 2020
- Statistical Learning Methods for Modern AI, 2021
- Reinforcement Learning for Intelligent Transportation Systems Workshop, IJCAI, 2021
- KDD Workshop on Decision Intelligence and Analytics for Online Marketplaces, 2022-2023
- Reinforcement Learning Methods and Applications, 2022
- IMSI Workshop: Challenges in Neuroimaging Data Analysis, 2024
- NeuroConnect 2024: Advancing Brain Network Research Workshop, 2024
- MBZUAI Workshop on Statistics for the Future of AI, 2024
- Foundation Models and Their Biomedical Applications: Bridging the Gap, August 17-22, 2025
- One of four Program Leaders and Program Chair, SAMSI summer workshop on Neuroimaging Data Analysis (NDA), 2013
- Program Leader for SAMSI full-year program on Challenges in Computational Neuroscience (CCNS) with five workshops, one short course, and two regular courses, 2015-2016
Brief Statement
I am honored to be nominated for the IMS Council. If elected, I will work to strengthen IMS’s leadership in mathematical statistics and AI. With expertise in imaging genetics, medical imaging analysis, deep reinforcement learning, and big data integration, I have led efforts to combine diverse data sources in biomedical science, promoted statistics in e-commerce and organized panel discussions at ASA and JSM. There are many challenges ahead, from ensuring that statistical methods remain at the forefront of AI advancements to fostering cross-disciplinary engagement. I am committed to working with the Council to address these challenges and to position IMS as a leader in the evolving landscape of mathematical statistics, machine learning, and AI.