Machine Learning Day 2026
Event description
- Academic events
You are invited to Arizona State University’s West Valley campus for the seventh annual Machine Learning Day!
This event offers a unique platform for scholars and professionals from Arizona and beyond to connect and engage with machine learning, AI, and robotics. Researchers and practitioners will share valuable insights, aiming to address the pressing technical and social challenges of 21st-century Arizona. Machine Learning Day seeks to inspire fresh ideas and foster new collaborations in ML and AI research, advancing the future of these transformative fields.
8:50 a.m. – 9:00 a.m. – Welcome and Opening Remarks
Nina Fefferman, Director of the School of Mathematical and
Natural Sciences, Arizona State University.
9:00 a.m. – 10:00 a.m. – Morning Session 1
Rong Pan (ASU), Leveraging LLM for Ontology Extraction and Knowledge Graph Construction
Kevin Lin (University of Arizona), Data-based modeling of chaotic / stochastic dynamics with memory
Spring Berman (ASU), Designing Bio-Inspired Collective Behaviors for Robotic Swarms using Reinforcement Learning
10:05 a.m. – 10:20 a.m. Coffee/Poster Break
10:20 a.m. – 11:20 a.m. Keynote Address 1
Melanie Moses (UNM), Can we trust intelligence at scale?
11:20 a.m. – 12:20 p.m. – Morning Session 2
Heng Zhang (ASU), Large Language Models for Market Research: A Data-augmentation Approach
Alice Schwarze (Utah AI Policy Office), AI adoption and socio-economic impacts. A data-driven policy approach.
Selcuk Candan (ASU), The Power of 'Why?' in Decision Making in Complex, Dynamic Systems
12:20 p.m. – 12:30 p.m. – ASU Research Computing Presentation
12:30 p.m. – 1:30 p.m. – LUNCH
1:30 p.m. – 2:30 p.m. Keynote Address 2
Andrea Bertozzi (UCLA), GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability
2:30 p.m. – 2:45 p.m. Coffee/Poster Break
2:45 p.m. – 3:45 p.m. – Afternoon Session
Marco Janssen (ASU), AI and Experimental Social Science
Yuzhou Chen (UC Riverside), Topology-Guided Machine Learning for Spatio-Temporal Data and Beyond
Yang Ba (ASU), Measuring Dataset Diversity from a Geometric Perspective
3:45 p.m. – 4:00 p.m. – Coffee/Poster Break
4:00 p.m. – 5:00 p.m. – Industry Panel Session
John Almasan (TIAA)
Will Dupree (Aptima)
Xiaomin Li (Microsoft)
Sandeep Voona (ServiceNow)
Date
Friday, April 10, 2026
Time
8:40 am – 5:00 pm (MST)
Cost