Research with AI & Big Data: creating Rigor and Reproducibility
Monday, August 17, 2026
9am-1pm
CU Boulder
JSCBB (BIOT) B115; Over flow JSCBB 230; parking information: https://www.colorado.edu/facility/jscbb/about
| 8:30 | breakfast and registration | |
| 9:00 | Intro (Robin Dowell) | Intro to AI and Big data Rigor and Reproducibility |
| 9:15 | Ryan Layer | Software Engineering for Scientists: The Norms Don't Change, Even When the Tools Do |
| 9:45 | Daniel Acuna | How willing are LLMs to commit scientific fraud? A study of 16 commercial and open models |
| 10:15 | coffee break | |
| 10:30 | Jes Persinger | A (Hopefully) Not-So-Cautionary Tale of Reproducibility: Where AI and Big Data Can Run Amok |
| 11:00 | coffee break | |
| 11:15 | Jed Brown | The epistemic function of verification and validation in computational science and engineering |
| 11:45 | Milton Pividori | Standards for reproducible AI research |
| 12:15 | Mary Allen | Lunch and learn; Guided vibe-coding activity with reflection |
This is an interdisciplinary gathering on ethics, accountability, and best practices in AI-driven research — bringing together graduate students, faculty, and lab members from across the university.
Talks, Workshops & Panel Discussion
Speakers include: Robin Dowell, Mary Allen, Jes Persinger, Ryan Layer and Daniel.Acuna, Jed Brown and Milton Pividori.
Workshop: Lunch and learn; Guided vibe-coding activity with reflection (Making your vibe code rigorous, reproducible and right , bring a computer to learn!)
Developed by the "Predoctoral Training Program in Biological Data Science (BDS)" 1T32GM144289.
This event is jointly funded by " "Predoctoral Training Program in Biological Data Science (BDS)", the Office of Research Integrity (Compliance), and "AI in Genetics by the Templeton Foundation".
If you have questions please contact Mary Allen (Mary.A.Allen@colorado.edu).
Zoom option: https://cuboulder.zoom.us/j/92592929762