Three faculty members from the College of Natural Sciences have received distinguished Faculty Early Career Development (CAREER) Awards totaling $1.6 million over 5 years from the National Science Foundation.
Carlos Baiz, assistant professor in the Department of Chemistry, Philipp Krähenbühl, assistant professor in the Department of Computer Science and Qiang Liu, assistant professor in the Department of Computer Science (starting fall 2019), were selected for the NSF's most prestigious award in support of early-career faculty.
The CAREER award, which comes with a federal grant for research and education activities for five years, recognizes junior faculty for their potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.
Baiz will use his award funding to study how biomolecules inside cells, such as the proteins and DNA that perform all the critical functions of life, interact with each other and with the water surrounding them. Earlier research may have oversimplified these interactions by studying biomolecules floating freely in a highly diluted solution of water. In reality, they exist crowded together like kids packed into a swimming pool on the first day of summer break. That crowding can have big implications for the biomolecules' shapes and the ways they bend, fold and twist. It can also affect the behavior of the water itself. Baiz hopes the research ultimately leads to a more fundamental understanding of how biomolecules perform their complex functions in their native environments.
Krähenbühl uses machine learning to enable computers to make sense of the visual world. With help from the CAREER award, he plans to develop methods for compressing videos that are more efficient and compact—as well as more robust in the face of missing or corrupt information—than existing compression methods. This can reduce the massive economic and environmental costs of modern digital infrastructure. He also plans to develop computer systems that are better at recognizing what's going on in videos or in the world around them, which could result, for example, in surveillance and assistive technologies for the elderly that are more responsive, or autonomous robots that can move through the world and interact with humans more safely.
Liu notes that artificial intelligence systems have improved dramatically in recent years, allowing computers to categorize images better than humans, beat the world champion at the board game Go and make intelligent recommendations for everything from movies to health care to education. At their core, these technologies rely on probabilistic models. But as these systems become more complex, it becomes more difficult to quickly and efficiently calculate the probabilities. With this award, Liu plans to develop a new framework for computing probabilities, called Stein Variational Gradient Descent, that might break through this bottleneck.
For more information, contact: Marc Airhart, College of Natural Sciences, 512-232-1066.