Name | Region | Skills | Interests |
---|---|---|---|
Alana Romanella | Campus Champions | ||
Michael Blackmon | Campus Champions | ||
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 |
Name | Roles | Skills | Interests |
---|---|---|---|
Yongwook Song |
mentor |
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.
A personalized learning system that adapts to learners' interests, needs, prior knowledge, and available resources is possible with artificial intelligence (AI) that utilizes natural language processing in neural networks. These deep learning neural networks can run on high performance computers (HPC) or on quantum computers (QC). Both HPC and QC are emergent technologies. Understanding both systems well enough to select which is more effective for a deep learning AI program, and show that understanding through example, is the ultimate goal of this project. The entry to learning technologies such as HPC and QC is narrow at present because it relies on classical education methods and mentoring. The gap between the knowledge workers needed, which is in high demand, and those with the expertise to teach, which is being achieved at a much slower rate, is widening. Here, an AI cognitive agent, trained via deep learning neural networks, can help in emergent technology subjects by assisting the instructor-learner pair with adaptive wisdom. We are building the foundations for this AI cognitive agent in this project.
The role of the student facilitator will involve optimizing a deep learning neural network, comparing and contrasting with the newest technologies, such as a quantum computer (and/or a quantum computer simulator) and a high performance computer and showing the efficiency of the different computing approaches. The student facilitator will perform these tasks at the rate described in the proposal. Milestone work will be displayed and shared publicly via posting to the Jupyter Notebooks on Google Colab and linked to regular Github uploads.
Davidson College
Campus Champions
student-facilitator, research computing facilitator, ci systems engineer
Rutgers, the State University of New Jersey
ACCESS CSSN, Campus Champions, CAREERS, Northeast
mentor, researcher/educator, research computing facilitator, cssn, Consultant
Worcester Polytechnic Institute
Great Plains, Northeast, RMACC
administrator, ci systems engineer
University of Missouri-Kansas City
Campus Champions
researcher/educator, research computing facilitator
Rutgers University - New Brunswick
ACCESS CSSN, CAREERS
student-facilitator