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proposal-development

Mentors and Regional Facilitators
Name Region Skills Interests
Ami Gaspar Campus Champions, Northeast
Alana Romanella Campus Champions
Kevin Brandt Campus Champions, Great Plains
Christopher Maher Campus Champions
Balamurugan Desinghu ACCESS CSSN, Campus Champions, CAREERS, Northeast
Diana Toups Dugas RMACC, SWEETER, Campus Champions
Elie Alhajjar ACCESS CSSN
Eden Furtak-Cole Campus Champions
Gaurav Khanna Campus Champions, CAREERS, Northeast
Henry Neeman Campus Champions
Ibrahim Sheikh CAREERS
James Deaton Campus Champions, Great Plains, ACCESS CSSN
Kirk Anne Campus Champions
Mohammadreza H… Campus Champions
Paul Rulis Campus Champions
Mike Renfro Campus Champions
Xiaoqin Huang ACCESS CSSN
Thomas Cheatham Campus Champions, RMACC
Users
Name Roles Skills Interests
Chitral Samala
student facilitator
Balamurugan Desinghu
mentor
researcher/educator
rcf
Gaurav Khanna
mentor
regional facilitator
researcher/educator
rcf
steering committee
Ibrahim Sheikh
student facilitator
mentor
regional facilitator
researcher/educator
rcf
Julia Huang
student facilitator
Niall Howlett
researcher/educator
Stanley Nwoji
researcher/educator
Som Bishoyi
student facilitator
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Engagements

High Performance Computing vs Quantum Computing for Neural Networks supporting Artificial Intelligence
Pace University

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.

Status: Complete

People with Expertise

Mohammadreza Hadizadeh

Central State University

Programs

Campus Champions

Roles

researcher/educator, research computing facilitator

Expertise

Diana Toups Dugas

New Mexico State University

Programs

RMACC, SWEETER, Campus Champions

Roles

mentor, researcher/educator, research computing facilitator

Expertise

Thomas Cheatham

University of Utah

Programs

Campus Champions, RMACC

Roles

mentor, research computing facilitator, domain champion

User

Expertise

People with Interest

Kirk Anne

Rochester Institute of Technology

Programs

Campus Champions

Roles

research computing facilitator

Placeholder headshot

Interests

Pramod Misra

Georgia Institute of Technology

Programs

ACCESS CSSN

Roles

cssn

Placeholder headshot

Interests

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Justin Oelgoetz

Austin Peay State University

Programs

Campus Champions

Roles

mentor, researcher/educator, research computing facilitator

Placeholder headshot

Interests