ASA DataFest @ Duke is an annual data analysis competition organized locally by the Department of Statistical Science. Teams of up to five students will compete to provide insights from a large,… read more about Duke ASA DataFest »
Visualizations allow analysts to rapidly explore and make sense of their data. The ways we visualize data directly influence the conclusions we draw and decisions we make; however, our knowledge of… read more about Leveraging Visual Cognition in Data Visualization »
following the launch of GPT4-Agent, GPT4 has demonstrated its flexibility in utilizing tools like Advanced Data Analytics (ADA, previously known as code interpreter) and DALL- E3, although the… read more about InfiAgent: A Multi-Tool Agent for AI Operating Systems »
Ensemble decision tree methods such as XGBoost, RF, and BART have gained enormous popularity in data science for their superior performance in machine learning regression and classification tasks. In… read more about GS-BART: Graph split additive decision trees for classification and nonparametric regression of spatial and network data »
In this talk, I will discuss semi-parametric estimation when nuisance parameters cannot be estimated consistently, focusing in particular on the estimation of average treatment effects, conditional… read more about Debiasing in the inconsistency regime »
This presentation offers insights into the work environment at JMP Statistical Discovery LLC, a prominent statistical software company, with a specific focus on the Research and Development (R&D… read more about A Day in the Life: JMP R&D »
Recent interest has centered on uncertainty quantification for machine learning models. For the most part, this work has assumed independence of the observations. However, many of the most important… read more about Inference for machine learning under dependence »
Monte Carlo methods span a range of disciplines, drawing interest from statisticians, computer scientists, physicists, among others. In the Monte Carlo workflow, the upstream task involves designing… read more about The Many Facets of Monte Carlo Methods: From Sampling Algorithms to Unbiased Estimators »
Mixed effect modeling for longitudinal data is challenging when the observed data are random objects, which are complex data taking values in a general metric space without either global linear or… read more about CANCELLED:Geodesic Mixed Effects Models for Repeatedly Observed/Longitudinal Random Objects »
The exploratory and interactive nature of modern data analysis often introduces selection bias, posing challenges for traditional statistical inference methods. A common strategy to address this bias… read more about An Exact Sampler for Inference after Polyhedral Selection »
Optimization techniques, such as dual ascent, alternating direction method of multipliers, and majorization-minimization, are widely used in high-dimensional applications. The strengths of… read more about Bridged Posterior: Optimization, Profile Likelihood and a New Approach of Generalized Bayes »
The biochemical functions of proteins, such as catalyzing a chemical reaction or binding to a virus, are typically conferred by the geometry of only a handful of atoms. This arrangement of atoms,… read more about Probabilistic methods for designing functional protein structures »
Explore summer 2024 opportunities with Data+, Code+, CS+, Climate+, and Applied Ethics+, as well as the new Arts+, I&E+, and History+ programs! Students will be able to meet project leads and… read more about Plus Programs Information Fair »
The total electron content (TEC) maps can be used to estimate the signal delay of GPS due to the ionospheric electron content between a receiver and a satellite. This delay can result in a GPS… read more about Video Imputation and Prediction Methods with Applications in Space Weather »
In problems such as variable selection and graph estimation, models are characterized by Boolean logical structure such as presence or absence of a variable or an edge. Consequently, false positive… read more about Model selection over partially ordered sets »
Olivia Zimeng Fan is presenting her senior thesis research tomorrow, Wednesday, December 6th in Old Chemistry 123 at 10 am. Advisor: Dr. Amy Herring, Sara & Charles… read more about Assessing Power of Statistical Tests in Dopamine Neurodegeneration for Ordinal Categorical Data »
Young Jun is presenting his senior thesis research today in Perkins Seminar Room 4 at 1:30 -2:30 pm. This research explores the connection between blood glucose levels and cognitive function in… read more about Exploring the Relationship Between Blood Glucose Level and Cognitive Function Through Functional Data Analysis »
We study the problem of distribution-free dependence detection and modeling through the new framework of binary expansion statistics (BEStat). The binary expansion testing (BET) avoids the problem of… read more about BET and BELIEF »
Transportation of measure underlies many powerful tools for Bayesian inference, density estimation, and generative modeling. The central idea is to deterministically couple a probability measure of… read more about On low-dimensional structure in transport and inference »
Bayesian optimization (BayesOpt) optimizes time-consuming-to-evaluate objective functions arising in materials design, drug discovery, neural architecture design, and other applications. It combines… read more about Grey-Box Bayesian Optimization for Human-in-the-loop Optimization »
Do you have questions about our courses and programs? Zoom into our Undergraduate Coordinator's open advising session for advice and answers to your questions. read more about Open Advising for Pre-majors and Others »
In this presentation, we will introduce data science, AI, and biostatistics career opportunities in academic health care. The Duke BERD (Biostatistics, Epidemiology, and Research Design) Methods Core… read more about Career Opportunities in Academic Healthcare »
It is increasingly possible to develop treatments for psychiatric disorders by making targeted interventions on the brain. However, designing an appropriate protocol requires many choices. We… read more about Machine Learning to Infer and Control Brain State »
Do you have questions about our courses and programs? Zoom into our Undergraduate Coordinator's open advising session for advice and answers to your questions. read more about Open Advising for Pre-majors and Others »
The Duke Master in Interdisciplinary Data Science and Master in Statistical Science programs are once again teaming up to provide an in-person Career Fair! Over 300 students from various disciplines… read more about Career Fair (MIDS/MSS) »