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scikit-learn

Mentors and Regional Facilitators
Name Region Skills Interests
Michael Blackmon Campus Champions
Benjamin Meyers Campus Champions
Cody Stevens Campus Champions
Balamurugan Desinghu ACCESS CSSN, Campus Champions, CAREERS, Northeast
Elie Alhajjar ACCESS CSSN
Craig Gross Campus Champions
Iman Rahbari Campus Champions, ACCESS CSSN
Yu-Chieh Chi Campus Champions
Jordan Hayes Campus Champions
Jason Wells ACCESS CSSN, Campus Champions
Kenneth Bundy CAREERS
shuai liu ACCESS CSSN
Michael Puerrer Campus Champions, Northeast
Maryam Taeb
Simon Delattre
Soham Pal Campus Champions, ACCESS CSSN
Swabir Silayi Campus Champions
Users
Name Roles Skills Interests
Anish Gaikwad
student facilitator
Ahamed Arafaat…
student facilitator
Balamurugan Desinghu
mentor
researcher/educator
rcf
Denis Kornev
researcher/educator
Hao Zheng
student facilitator
Hening Cui
student facilitator
Paritosh Kaushik
student facilitator
Kenneth Bundy
mentor
Madhukara Keku…
student facilitator
Parth Shah
student facilitator
Parameshwaran …
student facilitator
Stanley Nwoji
researcher/educator
Som Bishoyi
student facilitator
Seth Rosen
student facilitator
Sydney Shearer
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

Anish Gaikwad

New Jersey Institute of Technology

Programs

CAREERS

Roles

student-facilitator

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Expertise

Denis Kornev

Harrisburg University of Science and Technology

Programs

CAREERS

Roles

researcher/educator

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Expertise

Som Bishoyi

University of Massachusetts Dartmouth

Programs

CAREERS

Roles

student-facilitator

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Expertise

People with Interest

Fernando Garzon

University of California, San Diego

Programs

ACCESS CSSN

Roles

mentor, research software engineer

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Interests

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Benjamin Meyers

Rochester Institute of Technology

Programs

Campus Champions

Roles

research computing facilitator

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Interests

Joseph Antonucci

New Jersey Institute of Technology

Programs

CAREERS

Roles

student-facilitator

Interests

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