UNIVERSITY

AI COLLABORATION SYMPOSIUM

Enabling faculty across the Dallas-Fort Worth Region to collaborate with colleagues to engage larger opportunities for research and applications in AI

On Friday, September 29, 2023 the Texas Research Alliance held the first Dallas-Fort Worth University AI Collaboration Symposium to enable area research university faculty to collaborate with colleagues to engage larger opportunities for research and applications in artificial intelligence.  Over 100 area professors and university leaders attended the program.

PRESENTATIONS FROM THE DAY

AGENDA

Coffee and pastries will be served

Paul Krueger, Dean, College of Engineering, University of North Texas
and
Victor Fishman, Executive Director, Texas Research Alliance

Introduction -  “Prabha” Balakrishnan Prabhakaran - Associate Vice President for Research Centers and Institutes, University of Texas at Dallas

Speaker: Hector Munoz-Avila, Program Director, IIS, NSF

- 10:00am to 10:30am - The University of North Texas: Song Fu, Computer Science and Engineering Department Chair
- 10:30am to 11:00am - The University of Texas at Arlington: Gautam Das, Associate Dean For Research, College of Engineering
- 11:00am to 11:15am - Break
- 11:15am to 11:45am - The University of Texas at Dallas, “Prabha” Balakrishnan Prabhakaran, Associate Vice President for Research Centers and Institutes
- 11:45am to 12:15pm - Suku Nair, Associate Provost and Chief Innovation Officer, Southern Methodist University: Director of Data Science and Computing

Lunch will be served before keynote address begins

Introductions - SMU

Keynote Speaker: Lukman Ramsey, Head AI Solutions, Public Sector and Education, Google

Lukman is global Head of AI Solutions for the Public Sector in Google Cloud, with a focus on smart analytics and AI based solutions for the education and government.  Formerly he was the ML/AI Solutions lead, working with customers across Google Cloud to enable business applications in AI and ML.  He speaks regularly at conferences around the world about Google’s AI technology and its applications in education, including ASU+GSV, the keynote at the World AI Summit, EDUCAUSE, the Disney Datathon, McKinsey Analytics Forum, and Google Cloud NEXT conferences.

Lukman joined Google in January of ‘17 after acting as CTO for a series of New York startups in education technology, AI and speech recognition. Most recently he was the founding CTO and Chief Product Officer for Acrobatiq, a spin-out of the Open Learning Initiative at CMU, providing machine learning analytics and courseware for both on-ground and online universities. Prior to that he was CTO of Neverware, a startup that builds virtual desktop servers for high schools.  Earlier in his career he built speech recognition applications and platforms for call centers. His first startup in 2007 was a voice-driven virtual assistant for small business.

Lukman did his PhD work in Computer Science at UC San Diego, doing computer vision research at JPL in the Machine Learning systems group. As an undergrad at MIT in Cognitive Science and Computer Science he worked on multi-layer neural networks before it was called "deep learning." His academic interests have always centered on the intersection of Cognitive Science and Computer Science.

 

Introduction -  Gautam Das, Associate Dean For Research, College of Engineering, The University of Texas at Arlington

This is an opportunity to discuss use-cases of interest to faculty and to identify potential partners across the region for continuing discussions. Faculty should begin to think about use-case areas that they would like their university to  lead for the region. 

A taxonomy of industry use-cases is provided to support discussion. This taxonomy is not exclusive and faculty should suggest changes as their experience dictates.

-  AI/ML in Education

-  Responsible AI

-  AI & ML in financial services: Includes technologies that embed AI & ML into existing financial services via advanced analytics, process automation, robo-advisors, and self-learning programs. Product categories include financial chatbots, intelligent banking, lending analytics, payment optimization, predictive underwriting, and robo-advisors

- AI in healthcare: Includes technologies that leverage AI & ML to improve medicine and the provision of care. Product categories include AI-based drug discovery, clinical decision support, genetic analytics, healthcare administration, and personal health.

- Consumer AI: Includes technologies that use AI & ML to enhance B2C business models. Product categories include AI in media & entertainment, AI & ML advertising technology, digital avatars and gaming, e-commerce recommendation engines, education technology, intelligent price optimization, and smart retail.

- Industrial AI & ML: Includes technologies that automate industrial processes and unlock industrial data to find new efficiencies. Product categories include crop maximization, energy grid automation, geospatial analysis, heavy industry automation, IoT predictive analytics, supply chain optimization, and telecommunications optimization.

- AI & ML in financial services: Includes technologies that embed AI & ML into existing financial services via advanced analytics, process automation, robo-advisors, and self-learning programs. Product categories include financial chatbots, intelligent banking, lending analytics, payment optimization, predictive underwriting, and robo-advisors.

- AI in healthcare: Includes technologies that leverage AI & ML to improve medicine and the provision of care. Product categories include AI-based drug discovery, clinical decision support, genetic analytics, healthcare administration, and personal health.

- Consumer AI: Includes technologies that use AI & ML to enhance B2C business models. Product categories include AI in media & entertainment, AI & ML advertising technology, digital avatars and gaming, e-commerce recommendation engines, education technology, intelligent price optimization, and smart retail. 

 

This is the opportunity for faculty who participated in each of the breakout sessions to share their thinking about the path forward for capturing opportunities in their use – case area and which of the universities would like to take leadership for the region in that use-case. TRA intends to support these regional use-case groups in formulating approaches to government and industry opportunities in their areas and working with the Dallas Regional Chamber to bring this use-case capability to industry.

TRA will use the information from the Symposium build industry and government funding opportunities for our faculty. TRA will work with the universities to establish  regional use-case coalitions that can take the lead for these use-case opportunities.

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