UTSA | Catalyst 2020
Catalyst 2020 | UTSA
The AI Consortium is an interdisciplinary collaboration that fosters
“The consortium is important as it is bringing world-renowned experts
innovative research in AI. The MATRIX brings students, practitioners
together from top institutions within San Antonio to share their
and researchers from multiple institutions under one umbrella,
backgrounds and experience to collaborate and help solve new and
utilizing their unique skillsets to address emerging research chal-
challenging problems using AI in a wide variety of fields,” Mentzer
lenges. Dr. Dhireesha Kudithipudi ’06 is the director of MATRIX. She
says. Other external partners include researchers from UT Health
is a professor of electrical and computer engineering and computer
San Antonio and Texas Biomedical Research Institute.
science, and the Robert F. McDermott Chair in Engineering. Her research expertise is in neurally inspired AI algorithms, AI accelerators,
“The MATRIX AI Consortium at UTSA has brought together researchers
energy-efficient machine learning and novel computing substrates.
from multiple colleges at UTSA and institutions in and around the San Antonio area to leverage these advances and collaboratively address
“The goal of the AI initiative at UTSA is to strategically collaborate
some of the most difficult multidisciplinary research challenges in
and engage with the private sector, academia, the Greater San
these areas,” adds Jadliwala. “Addressing these multidisciplinary
Antonio community and key international partners to advance the
research problems requires significant domain expertise in specific
state of the art with transdisciplinary solutions,” Kudithipudi says.
areas and fields, and the confluence of expertise currently available
“UTSA has been carving a niche in this space with strategic cluster
within MATRIX will definitely help with that challenge.”
hires over the past few years. The university and its partners already
The Promising Reality of Artificial Intelligence
UTSA’s AI Consortium harnesses the power of artificial intelligence to solve real-world problems Technological advances in computing capability, access to large datasets and innovative algorithms have increased the impact of artificial intelligence (AI) in our daily lives. Recent analyses predict that AI will add approximately $8 trillion in gross value to the U.S. economy by 2035. This technology will
have a strong presence in neuroscience, brain health, cybersecurity
The consortium facilitates training opportunities through seminars,
and applied domains. We are building a new sandbox for research
lab rotations and hackathons that foster innovative transdisciplinary
teaming that builds on these strengths.”
research. The consortium currently has funded research projects from both industry and federal agencies, including the National
MATRIX is composed of external research partners and internal UTSA
Science Foundation, National Institute of Health, Air Force Research
members specializing in computer science, electrical and computer
Laboratory and the Defense Advanced Research Projects Agency.
engineering, cybersecurity, biomedical engineering, neuroscience, geoscience, medicine, and psychology. Dr. Sushil Prasad, professor
“I think the consortium’s focus on employing AI and machine learn-
and chair of the Department of Computer Science and a core mem-
ing tools and techniques to address problems that impact human
ber in MATRIX, agrees that the consortium is uniquely positioned to
health and well-being is something very unique and noteworthy,”
address emerging problems in human-aware AI by leveraging the
says Jadliwala. “In light of the COVID-19 pandemic, and the contin-
broad expertise of its members in a collaborative framework. “Basic
uous threat to human well-being through similar threats, the need
AI algorithms and allied techniques have been around for some time
for such a data- and AI-centric focus on human health has assumed
but have become increasingly effective in solving societal problems
greater significance.” During the pandemic, the consortium published
with the advent of massively parallel computers and accelerators,”
the COVID-19 Resources & Recovery Site, a website that populated a
Prasad says. “Exploration of advanced AI algorithms, software and
recovery map with real-time data so the public could assist with locat-
hardware techniques and their interplay with big data and advanced
ing scarce resources during the pandemic.
cyberinfrastructure will continue. However, opportunities have opened up for deep societal questions to be explored, including
“Our COVID-19 tracking maps for Texas and San Antonio took advan-
how well AI systems can interact with people and how safe, secure
tage of the web-based Geographic Information System (Web GIS):
drive creative solutions for real-world problems in biomedicine, health care
and ethical these are. Such questions call for truly multidisciplinary,
ArcGIS Online, a spatial data science and visualization tool,” says Dr.
delivery, food insecurity, human trafficking, cybersecurity and transportation.
collaborative teams involving all stakeholders, and AI Consortium is
Hongjie Xie, professor and chair of the Department of Geological Sci-
The complexity of these global problems will require a highly prepared work-
creating such collaborations.”
ences. “These maps interactively display the number and progression of confirmed infections, fatalities and administered tests by county or
force capable of managing exponentially expanding volumes of data and
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utilizing machine learning. MATRIX, the UTSA AI Consortium for human well-
Christopher Mentzer, assistant director of research and development
zip code in real time. This data provides valuable information for fu-
being, is prepared to address these challenges.
at the Southwest Research Institute, co-leads the consortium’s Ma-
ture studies on which factors—including geographic, environmental,
chine Learning and Deployment group alongside assistant professor
demographic, social and economic—would have contributed to such
Dr. Murtuza Jadliwala of UTSA’s Department of Computer Science.
differences spatially and temporally.” 13
