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From the College of Natural Sciences
New Online Master’s Degree in Data Science is a First for The University of Texas at Austin

New Online Master’s Degree in Data Science is a First for The University of Texas at Austin

In response to high demand for professionals with scientific and technical training to understand and work with massive amounts of data, The University of Texas at Austin is set to launch a new online master's degree program in data science. Pending final approval by UT System and the Texas Higher Education Coordinating Board, the new program will ...
For Each Day’s Delay in Social Distancing, a COVID-19 Outbreak Lasts Days Longer

For Each Day’s Delay in Social Distancing, a COVID-19 Outbreak Lasts Days Longer

A new analysis of COVID-19 outbreaks in 58 cities has found that places that took longer to begin implementing social distancing measures spent more time with the virus rapidly spreading than others that acted more quickly

Updated: Model Forecasts When States, Cities Likely to See Peak in COVID-19 Deaths

Updated: Model Forecasts When States, Cities Likely to See Peak in COVID-19 Deaths

A computer model from the UT COVID-19 Modeling Consortium forecasts daily deaths from COVID-19 as of May 5, 2020. The likelihood that an area has passed its peak in daily deaths is indicated by colors ranging from burnt orange (very low) to dark purple (very high). Credit: University of Texas at Austin.

A University of Texas at Austin model that projects COVID-19 deaths for all 50 U.S. states and dozens of metro areas using geolocation data from cellphones to determine the impact of social distancing within each place finds, in many communities, deaths have likely not yet peaked. The model, originally launched with state data, was updated on April 24 to be the first publicly available model to show projections of deaths also by metro area.

Pandemic Model Shows Importance of Social Distancing in 22 Texas Cities

Pandemic Model Shows Importance of Social Distancing in 22 Texas Cities

Researchers have examined how COVID-19 would impact 22 metro areas in Texas under scenarios where levels of social distancing differ.

A new pandemic model of COVID-19 shows the positive role social distancing can play in preventing the spread of the illness in areas across the state. The report by researchers in The University of Texas at Austin's College of Natural Sciences projects significantly higher numbers of cases of infection, hospitalizations, intensive care unit admissions and deaths in 22 Texas communities under scenarios in which social distancing measures are moderate.

A New Texas COVID-19 Pandemic Toolkit Shows the Importance of Social Distancing

A New Texas COVID-19 Pandemic Toolkit Shows the Importance of Social Distancing

UPDATE: Revised model projections were released on April 6. Read the full report.

Since 2012 a pandemic-planning tool developed by researchers at The University of Texas at Austin has helped public health officials plan for the consequences of a deadly and virulent virus. Now the pandemic modeler who developed the toolkit is studying COVID-19 and has built a new model to project the spread of COVID-19 across the U.S. She has teamed up with Dell Medical School to assess the potential impact of the pandemic in the Austin-Round Rock area.

Coronavirus Spreads Quickly and Sometimes Before People Have Symptoms, Study Finds

Coronavirus Spreads Quickly and Sometimes Before People Have Symptoms, Study Finds

Infectious disease researchers at The University of Texas at Austin studying the novel coronavirus were able to identify how quickly the virus can spread, a factor that may help public health officials in their efforts at containment. They found that time between cases in a chain of transmission is less than a week and that more than 10% of patients are infected by somebody who has the virus but does not yet have symptoms.

Researchers Say Spread of Coronavirus Extends Far Beyond China’s Quarantine Zone

Researchers Say Spread of Coronavirus Extends Far Beyond China’s Quarantine Zone

Infectious disease researchers at The University of Texas at Austin and other institutions in Hong Kong, mainland China and France have concluded there is a high probability that the deadly Wuhan coronavirus spread beyond Wuhan and other quarantined cities before Chinese officials were able to put a quarantine in place. At least 128 cities in China outside of the quarantine zone, including cities with no reported cases to date, had a greater than even risk of exposure, according to a paper currently in press with Emerging Infectious Diseases, a journal of the U.S. Centers for Disease Control and Prevention.

UT Austin Launches Institute to Harness the Data Revolution

UT Austin Launches Institute to Harness the Data Revolution

Research from UT Austin professors and TRIPODS members Alex Dimakis and Eric Price shows that it is possible to learn a deep generative model that dreams images of human faces (right panel), trained by observing only occluded images (left panel). The middle panel shows a previous approach for solving this problem, that fails. [Figure from: AmbientGAN: Generative models from lossy measurements, by A. Bora, E. Price and A.G. Dimakis, ICLR 2018.]

Advances in machine learning are announced every day, but efforts to fundamentally rethink the core algorithms of AI are rare.

Statistician Abhra Sarkar Receives Mitchell Prize

Statistician Abhra Sarkar Receives Mitchell Prize

Abhra Sarkar was awarded the 2018 Mitchell Prize for his research in animal vocalization modelling. Photo credit: Vivian Abagiu.

Abhra Sarkar, assistant professor of statistics and data sciences at the University of Texas at Austin, was awarded the 2018 Mitchell Prize by the International Society for Bayesian Analysis in August for his research in animal vocalization modelling.

A Growth Mindset Intervention Can Change Students’ Grades if School Culture is Supportive

A Growth Mindset Intervention Can Change Students’ Grades if School Culture is Supportive

Boosting academic success does not have to derive from new teachers or curriculum; it can also come from changing students' attitudes about their abilities through a short online intervention, according to the latest findings from the National Study of Learning Mindsets published in Nature on Aug. 7. Faculty in the Department of Statistics and Data Sciences contributed to the research.

Corwin Zigler Uses Statistics to Link Air Pollution to Health Impacts

Corwin Zigler Uses Statistics to Link Air Pollution to Health Impacts

Corwin Zigler. Photo courtesy of UT Dell Medical School.

As a new academic year approaches, we aim to introduce you to some of the scientists and mathematicians in our community, especially faculty who joined our UT community recently. First up: Corwin Zigler, associate professor in UT Austin's Department of Statistics and Data Sciences and in the Dell Medical School's Department of Women's Health.

New Chair for Statistics and Data Sciences Envisions Era of Growth for Department

New Chair for Statistics and Data Sciences Envisions Era of Growth for Department

Kate Calder, currently a professor of statistics and co-director of the Mathematical Biosciences Institute at Ohio State University, will be the new chair of UT Austin's Department of Statistics and Data Sciences (SDS), beginning in the fall. Calder, who will be on campus this month for an in-depth public conversation about computational health April 30th, is an award-winning statistician.

Vital Statistics: The Potential of Math to Advance Medicine

Vital Statistics: The Potential of Math to Advance Medicine

Illustration: Jenna Luecke

From baseball to financial investing, from elections to oil drilling, analyzing data quickly to predict future outcomes is transforming industries and activities around the world.

Artificial Intelligence and Supercomputers to Help Alleviate Urban Traffic Problems

Artificial Intelligence and Supercomputers to Help Alleviate Urban Traffic Problems

A new tool uses artificial intelligence to recognize objects from City of Austin raw traffic camera footage and characterize how those objects move and interact. Image by Texas Advanced Computing Center/Center for Transportation Research

Look above the traffic light at a busy intersection in your city and you will probably see a camera. These devices may have been installed to monitor traffic conditions and provide visuals in the case of a collision. But can they do more? Can they help planners optimize traffic flow or identify sites that are most likely to have accidents? And can they do so without requiring individuals to slog through hours of footage?

Meet Oscar Madrid Padilla: First PhD Graduate from UT Austin’s Statistics Department

Meet Oscar Madrid Padilla: First PhD Graduate from UT Austin’s Statistics Department

Oscar Madrid Padilla. Photo credit: Vivian Abagiu.

Oscar Madrid Padilla will become the first person to receive a PhD by the University of Texas at Austin's Department of Statistics and Data Sciences (SDS) this May. The department was formed in August 2014 and replaced the Division of Statistics and Scientific Computation.