Outreach and Engagement
The Department of Statistics is an active community that engages students and lifetime learners at UConn and beyond.
We contribute to the field of statistics by hosting events and participating in professional organizations. We also share our know-how with UConn researchers in other fields – and enhance the University’s research profile in the process.
Current Initiatives
Education and Training
We offer general education and research courses that serve students in virtually all majors at UConn. Members of the Department also participate in UConn programs that benefit Connecticut students and educators.
- Our UConn Pre-College Summer course on data science exposes incoming first-year students to the essential components and computing skills needed for data science.
- We train UConn Early College Experience instructors, holding certification workshops for participating high school teachers each summer.
Consulting
We provide services to researchers and employees at UConn to help them better understand statistical concepts and apply them to their work. For example, our faculty and graduate students contribute to:
- Statistical Consulting Services, which advises researchers from other disciplines about the collection and analysis of data.
- EnergyStats, a collaboration with UConn's Utility Operations & Energy Management. Using statistical modeling and visualization of UConn's energy consumption data (either real-time high-frequency or monthly), EnergyStats can detect anomalous consumption behavior and to predict future usage.
Community Engagement
We maintain relationships with professional organizations and area companies and institutions. These connections open doors for our students and help us contribute to our field. Examples include:
- We are an active member of the American Statistical Association (ASA) Connecticut chapter and a founding member of the New England Statistical Society’s annual symposium.
- We host the Pfizer Colloquium each year in partnership with the ASA and Pfizer Inc.
Events
The Department of Statistics regularly sponsors and hosts conferences, colloquia, lectures, and seminar series where scholars of all levels can learn and collaborate. Many of these events are local, affordable, and accessible, allowing students to participate and in some cases present their own research. Examples include:
Recent Events
Statistics Colloquium: Graph-informed disease modeling from neuroimaging to EHR data, by Yize Zhao (Yale University)
Title: Graph-informed disease modeling from neuroimaging to EHR data Speaker:Yize Zhao, Associate Professor, Yale University. Time: Wednesday, November 18, 15:00 PM, Austin 313. Link: https://teams.microsoft.com/meet/2262859116495162?p=kNRyhsdYOkh9DB3pbp Abstract: Neurodegenerative and complex chronic diseases emerge from interactions that span biological networks and populations. I will introduce two Bayesian frameworks that quantify these interactions, from within-brain propagation to across-disease […]
[Read More]Statistics Colloquium: Bayesian Causal Inference with Uncertain Physical Process Interference, by Corwin Zigler (Brown University)
Title: Bayesian Causal Inference with Uncertain Physical Process Interference Speaker: Corwin Zigler, Professor at Brown University. Time: Friday, November 6, 10:00 AM, Austin 326. Link: https://teams.microsoft.com/meet/210569911634778?p=Jo739SHWl5ZtUQBKJX Abstract: Causal inference with spatial environmental data is often challenging due to the presence of interference: outcomes for observational units depend on some combination of local and non-local treatment. […]
[Read More]Interdepartmental Colloquium: From Wearable Data to Health Insights: Understanding Human Physiology Through Distributions, by Sujit K Ghosh(North Carolina State University)
Title: From Wearable Data to Health Insights: Understanding Human Physiology Through Distributions Speaker: Sujit K Ghosh,Professor of Statistics, North Carolina State University. Time: Friday, October 30, 11:00 a.m. – 12:00 p.m, Austin 340. Research Article: https://www.tandfonline.com/doi/full/10.1080/01621459.2025.2460232 Link: https://teams.microsoft.com/meet/210928975502383?p=leIjKWWrUALlnhshdo Abstract: Wearable devices provide unprecedented opportunities to understand how human physiology and behavior evolve in everyday life. […]
[Read More]Statistics Colloquium: Spectral Methods for signal recovery in multi-modal problems, by Subhabrata Sen(Harvard University)
Title: Spectral Methods for signal recovery in multi-modal problems Speaker: Subhabrata Sen, Associate Professor in the Department of Statistics at Harvard University. Time: Wednesday, October 28, 3:30pm, Austin 313. Link: https://teams.microsoft.com/meet/2881511424868238?p=Thv81ZoLZSNxUA9P90 Abstract: Motivated by multi-modal estimation, we will study a multi-view spiked random matrix model in which several noisy matrix observations contain correlated spikes. We […]
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