Name | Region | Skills | Interests |
---|---|---|---|
Aaron Jezghani | Campus Champions | ||
Anita Schwartz | Campus Champions | ||
Carrie Brown | Great Plains | ||
Cody Stevens | Campus Champions | ||
Gaurav Khanna | Campus Champions, CAREERS, Northeast | ||
Jason Wells | ACCESS CSSN, Campus Champions | ||
Keri Toksu | Northeast, Campus Champions | ||
Katherine Nelson | Campus Champions, CAREERS, ACCESS CSSN | ||
Andrew Monaghan | RMACC, Campus Champions | ||
Paul Rulis | Campus Champions | ||
Swabir Silayi | Campus Champions | ||
Scott Valcourt | Northeast, Campus Champions | ||
Tom Maiden | ACCESS CSSN | ||
Trey Breckenridge | Campus Champions |
Name | Roles | Skills | Interests |
---|---|---|---|
Gaurav Khanna |
mentor regional facilitator researcher/educator rcf steering committee |
||
Katherine Nelson |
mentor rcf steering committee |
||
Igor Nachevnik |
student facilitator |
Title | Date |
---|---|
Ookami Webinar | 02/14/24 |
Title | Category | Tags | Skill Level |
---|---|---|---|
Ask.CI Q&A Platform for Research Computing | Website | resources, programming-best-practices | Beginner, Intermediate, Advanced |
Header-only C++ JSON library | Learning | resources, c++ | Intermediate, Advanced |
Thrust resources | Learning | parallelization, gpu, resources | Intermediate, Advanced |
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.
University of Missouri-Kansas City
Campus Champions
researcher/educator, research computing facilitator
Georgia Institute of Technology
Campus Champions
research computing facilitator
Mississippi State University
Campus Champions
research computing facilitator
University of Utah
RMACC, Campus Champions
mentor, research computing facilitator
University of Missouri-Kansas City
Campus Champions
researcher/educator, research computing facilitator
University of California, Riverside
ACCESS CSSN
student-facilitator, cssn