Name | Region | Skills | Interests |
---|---|---|---|
Alana Romanella | Campus Champions | ||
Michael Blackmon | Campus Champions, ACCESS CSSN | ||
Kevin Brandt | Campus Champions, Great Plains | ||
Balamurugan Desinghu | ACCESS CSSN, Campus Champions, CAREERS, Northeast | ||
Daniel Sierra-Sosa | Campus Champions | ||
Fernando Garzon | ACCESS CSSN | ||
Ibrahim Sheikh | CAREERS | ||
Jeffrey Weekley | Campus Champions | ||
Od Odbadrakh | |||
Lonnie Crosby | Campus Champions | ||
shuai liu | ACCESS CSSN | ||
Michael Puerrer | Campus Champions, Northeast | ||
Maryam Taeb | |||
Nect Admin | Great Plains, Northeast, RMACC | ||
Jeffrey J. Nuc… | CAREERS | ||
Renos Zabounidis | Campus Champions | ||
Grant Scott | Great Plains | ||
Xiaoqin Huang | ACCESS CSSN | ||
Shaohao Chen | Northeast | ||
Simon Delattre | |||
William Lai | ACCESS CSSN | ||
Yongwook Song | Kentucky |
Title | Date |
---|---|
NSF requests research and education use cases for NAIRR | 02/22/24 |
NVIDIA GenAI/LLM Virtual Workshop Series for Higher Ed | 02/17/24 |
Open Call: Minisymposia for PASC24 | 10/05/23 |
Title | Date |
---|---|
Cyberinfrastructure-Enabled Machine Learning Summer Institute | 6/25/24 |
HPC and Data Science Summer Institute | 8/05/24 |
Title | Category | Tags | Skill Level |
---|---|---|---|
ACCESS HPC Workshop Series | Learning | deep-learning, machine-learning, neural-networks, big-data, tensorflow, gpu, training, openmpi, c, c++, fortran, openmp, programming, mpi, spark | Beginner, Intermediate |
AI/ML TechLab - Accelerating AI/ML Workflows on a Composable Cyberinfrastructure | Docs | ACES, documentation, TAMU, ai, visualization, deep-learning, machine-learning, neural-networks, login, authentication, composable-systems, gpu, nvidia, slurm, bash, modules, vim, anaconda, conda, programming, python, scikit-learn | Intermediate |
Attention, Transformers, and LLMs: a hands-on introduction in Pytorch | Learning | ai, deep-learning, machine-learning, neural-networks, pytorch | Intermediate |
The research focus is to apply the pre-training techniques of Large Language Models to the encoding process of the Code Search Project, to improve the existing model and develop a new code searching model. The assistant shall explore a transformer or equivalent model (such as GPT-3.5) with fine-tuning, which can help achieve state-of-the-art performance for NLP tasks. The research also aims to test and evaluate various state-of-the-art models to find the most promising ones.
University of Rhode Island
Campus Champions, Northeast
research computing facilitator
University of California, San Diego
ACCESS CSSN
mentor, research software engineer
University of California, San Diego
ACCESS CSSN
mentor, research software engineer