The 2020 HiPerGator Symposium focused on active research applications of Artificial Intelligence (AI) at the University of Florida. After the July 21 announcement of UF’s partnership with NVIDIA, the University is leveraging AI to spur teaching, research, and workforce development. The 2020 HiPerGator Symposium was open to everyone in the UF community:
Date: Tuesday, October 27, 2020
Time: 9:00 a.m. — 2:00 p.m.
Location: Virtual Event via Zoom
Registration (free): https://informatics.research.ufl.edu/hipergator-symposium-2020-registration/
The symposium featured postdoctoral associates and graduate students currently using HiPerGator for Machine Learning (ML) and AI technologies in a broad variety of disciplines. The program consisted of ten-minute lightning talk presentations and poster sessions.
Postdoctoral associates and graduate students currently using HiPerGator for ML and AI research submitted abstracts for poster presentations and lighting talks. Applicants chose to have their abstract considered for a lightning talk, poster presentation, or both.
Lightning talks were presented via Zoom to the whole audience. Researchers selected for posters uploaded a PDF of their poster and were scheduled to be on Zoom for discussion with participants at set times. Participants were able to view all of the posters and select which they wished to “visit” during the poster sessions.
The organizing committee evaluated all submissions and selected the poster session presenters and lightning talk speakers. The deadline for submissions was September 29, and presenters were notified on October 13.
Listed below are the posters presented at the Symposium:
- MultiML: a method to predict optimal sample size in Multi-Omics data analyses using Machine Learning
- Leandro Balzano-Nogueira, Sonia Tarazona, Ana Conesa
- Deep Learning Approach On IMU Based Irregular Surface Gait Alteration Recognition
- Song Li, Boyi Hu
- Refinement of Protein Structures Using Machine Learning
- Kavindri Ranasinghe, Hatice Gockan, Roman Zubatyuk, Nigel W. Moriarty, Pavel Afonine, Mark Waller, Malgorzata Biczysko, Olexandr Isayev, Adrian Roitberg
- AIM by ANI: The Development of an Atoms-in-Molecules Partition through Machine Learning
- Kate K. Davis, Adrian Roitberg, and Ramón A. Miranda-Quintana
- Interfacing AMBER and TorchANI, a deep learning model for molecular dynamics of biomolecules
- Ignacio Pickering, Adrian Roitberg
- Topological Data Analysis of Actin Networks
- Nikola Milicevic, Peter Bubenik, Parker Edwards, Kristen Skruber, Eric Vitriol
- A network analysis framework for complex virome data
- Ricardo I. Alcalá-Briseño, Jan Kreuze, Karen A. Garrett
- Are avocados toast? Decision support for laurel wilt disease management at a regional level
- B. Etherton, R. A. Choudhury, Y. Xing, J. Crane, D. Carrillo, E. Evans, J. Wasielewski, L. Stelinski, R. C. Ploetz, K. A Grogan, and K. A. Garrett