Cultivating and Connecting the Ecosystem and Scaling Innovations
By: Michael Colaresi, PhD | Director, Hub for AI and Data Science Leadership
I know I'm not alone in finding AI dazzling, dizzying, and depressing—sometimes all at once. But sitting in front of my screen, just me against a billion-parameter model and a suite of surveillance tools with a profit motive, the work can feel lonely and the decisions daunting.
Students: Tony Hoang, Rachel Amanor, Ashlee Wood
A new problem that has arisen with AI is deciding what data to use when training new models. The more information and data that a model is trained on, and the more diverse that information is, the more accurate and reliable the model will be. When looking at the problem from this perspective only, it does not sound like much of a problem — use as much data as possible to train a model. But is anything ever that simple?
Students: Elda Solomon, Alisha Sharma
Our biggest installment yet of the Participatory Approaches to Data Community of Practice Brownbag Series was held last month in the University Center for Social and Urban Research. Dr. Tina Ndoh, Gabby Gray, and Mariska Goswami built upon the existing conversations within our community of practice by honing in on public health applications of participatory and community engaged work.
The DataSci+AI Forum brought together the University of Pittsburgh's work at the forefront of promoting responsible AI and data science practices. Building on Pitt Data Science Day in 2025, the 2026 edition drew a substantially larger audience and reflected broader engagement both within and beyond the University of Pittsburgh. We were interested in comparing the two years and it shows that the AI and Data Science Forum is increasing in scale and strengthening its ability to bring together a wider community around data science and artificial intelligence.
We are proud to announce and showcase the Best Poster Award winners at the 2026 Pitt Data Science and AI Forum Student Poster Session. The presenters of the following posters were awarded a cash and merchandise prize. Congratulations to our award winners and all who submitted posters for a great poster session!
On-Chain Decentralized Learning and Cost-Effective Inference for DeFi Attack Mitigation — Abdulrahman Alhaidari
By: Kendra Oliver, Ph.D., M.P.S.
Pitt’s new Hub for AI and Data Science Leadership (HAIL) will unite AI efforts across campus. Continue reading ...
Building on the success of the RDS@Pitt Student Scholars Program for undergraduate students, the Hub for AI and Data Science Leadership (HAIL) is launching a graduate-level opportunity in the 2026 spring and summer semesters.
