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Mentors and Regional Facilitators
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
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Announcements

Title Date
Ookami Webinar 02/14/24

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Topics from Ask.CI

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CI Links

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

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

Jason Wells

Harvard University

Programs

ACCESS CSSN, Campus Champions

Roles

research computing facilitator, cssn

Placeholder headshot

Expertise

Katherine Nelson

Yale University

Programs

Campus Champions, CAREERS, ACCESS CSSN

Roles

mentor, administrator, Masquerade, ExportPeople, research computing facilitator, steering committee, regional admin

Picture of Kaylea Nelson

Expertise

Paul Rulis

University of Missouri-Kansas City

Programs

Campus Champions

Roles

researcher/educator, research computing facilitator

Paul Rulis

Expertise

People with Interest

Paul Rulis

University of Missouri-Kansas City

Programs

Campus Champions

Roles

researcher/educator, research computing facilitator

Paul Rulis

Interests

Morgan Newton

Santa Monica College

Programs

ACCESS CSSN

Roles

student-facilitator

Picture of Morgan Newton

Interests

Katherine Nelson

Yale University

Programs

Campus Champions, CAREERS, ACCESS CSSN

Roles

mentor, administrator, Masquerade, ExportPeople, research computing facilitator, steering committee, regional admin

Picture of Kaylea Nelson

Interests