Bin Yu, a UC Berkeley professor known for her work on interpretable machine learning and reproducible scientific methods, will present “Veridical Data Science Towards Trustworthy AI” on November 6 at Florida State University.
machine learning
Second NYC Chapter Workshop Recognizes AI, Statistics Intertwined
The ASA NYC Chapter’s Second AI Workshop, held July 26 in Tarrytown, New York, drew more than 100 participants for a full day of talks, demonstrations, mentoring, and a mini-hackathon showing that trustworthy AI depends on rigorous statistical foundations.
Your Work Has a Place at SDSS: Call for Abstracts
Practitioners, researchers, and educators are invited to to submit abstracts by November 30 for SDSS 2027, to be held April 27–29 in Pittsburgh, Pennsylvania.
JOURNAL HIGHLIGHT: ‘Journal of Computational and Graphical Statistics’
The ”Journal of Computational and Graphical Statistics” presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. The latest issue contains research articles spanning statistical learning, Bayesian computation, networks, functional and spatial data, streaming data, clinical-trial design, and high-dimensional inference.
From Model Accuracy to Data Reliability: A Practical Framework for ML Teams
Praveen Gupta Sanka discusses the Data Reliability Score, a framework developed with Vidya Sagar Minukuri. She says, “The idea is simple: As machine learning teams use quantitative metrics to decide whether a model is ready for deployment, they should also use quantitative metrics to decide whether the data is reliable enough to support that decision.”
Last Call to Register for SDSS 2026 in Milwaukee
The conference brings together data scientists, statisticians, and computer scientists for short courses, keynotes, and networking opportunities centered on the evolving role of AI.
‘Practical Significance,’ Take II, Volume 1: A Conversation with the Editors of ‘ASA Discoveries’
“ASA Discoveries” is the American Statistical Association’s new open-access journal designed to publish innovative work that doesn’t fit traditional journal molds.
Call for Papers: Statistics for Astronomical Imaging Data
The ASA journal Statistics and Data Science in Imaging is planning a special issue on statistics for astronomical imaging data.
SLDS Conference Planned for NYC in November
The ASA’s Section on Statistical Learning and Data Science Conference will be held November 1–3 in New York City, bringing together academia, industry, and government to explore advances in statistical learning, AI, and inference.
Duka and Zhang Honored with Ellis Ott Scholarships
Zoga Duka and Zihan Zhang received 2025 scholarships for their research in machine learning, analytics, and high-dimensional data modeling.