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.”
machine learning
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.
Mentors Wanted for High School Research in Statistics, Machine Learning
Olga Korosteleva seeks mentors to guide high school students through intensive, yearlong projects in statistics and machine learning.
XL-Files: If Statistics Must Die … Let It Go Out with All Its Styles
The survival of statistics as a profession—not just a scientific discipline—depends on embracing its many styles, from modeling to decision-making and consensus-building, especially as data science and AI reshape the landscape.
Empowering the Next Generation: How the Fall Technical Conference Bridges Academia and Industry
The conference brought together industry experts, academics, and students to explore real-world applications of statistics, data science, and quality, emphasizing collaboration, career development, and connecting academia with industry.
SDSS 2025 Explores Advances in AI, Statistics, Data Science
The 2025 Symposium on Data Science and Statistics in Salt Lake City brought together more than 350 data scientists, statisticians, and computer scientists to explore interdisciplinary advances in AI, statistics, and data science.