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Mentors and Regional Facilitators
Name Region Skills Interests
Adam Carlson Campus Champions
Carrie Brown CAREERS, ACCESS CSSN
Cody Stevens Campus Champions
Balamurugan Desinghu ACCESS CSSN, Campus Champions, CAREERS, Northeast
Derek Strong Campus Champions
Edwin Posada Campus Champions
Fernando Garzon ACCESS CSSN
Georgia Stuart TRECIS
Craig Gross Campus Champions
Ibrahim Sheikh CAREERS
Yu-Chieh Chi Campus Champions
Jacob Fosso Tande Campus Champions
Jordan Hayes Campus Champions
Jason Wells ACCESS CSSN, Campus Champions
Kali McLennan Campus Champions, Great Plains
shuai liu ACCESS CSSN
Michael Puerrer Campus Champions, Northeast
Maryam Taeb
Paul Rulis Campus Champions
Mike Renfro Campus Champions
Rob Harbert Northeast
Amy Roberts Campus Champions
Ruben Lara Campus Champions
Sean Anderson Campus Champions
Xiaoqin Huang ACCESS CSSN
Suhong Li CAREERS, ACCESS CSSN
Soham Pal Campus Champions, ACCESS CSSN
Sumit Saluja Campus Champions
Swabir Silayi Campus Champions
Tyler Burkett Kentucky
William Lai ACCESS CSSN
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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

William Lai

Cornell University

Programs

ACCESS CSSN

Roles

mentor, researcher/educator, research computing facilitator, research software engineer, ci systems engineer, Consultant

William KM Lai

Expertise

Jason Wells

Harvard University

Programs

ACCESS CSSN, Campus Champions

Roles

research computing facilitator, cssn

Placeholder headshot

Expertise

Balamurugan Desinghu

Rutgers, the State University of New Jersey

Programs

ACCESS CSSN, Campus Champions, CAREERS, Northeast

Roles

mentor, researcher/educator, research computing facilitator, cssn, Consultant

Bala Desinghu Photo

Expertise

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People with Interest

Joseph Antonucci

New Jersey Institute of Technology

Programs

CAREERS

Roles

student-facilitator

Interests

c
+25 more tags

William Lai

Cornell University

Programs

ACCESS CSSN

Roles

mentor, researcher/educator, research computing facilitator, research software engineer, ci systems engineer, Consultant

William KM Lai

Interests

Gretta Kellogg

Pennsylvania State University

Programs

ACCESS CSSN

Roles

cssn

Placeholder headshot

Interests

+26 more tags