Three outstanding UCLA scientists win Presidential Early Career Awards

Three exceptional young UCLA scientists were honored by President Obama Monday with Presidential Early Career Awards for Scientists and Engineers (PECASE) — the highest honor bestowed by the U.S. government on science and engineering professionals in the early stages of their research careers. They are among 96 scientists and engineers in the nation to receive 2012 PECASEs. In announcing the awards, Obama said, "Discoveries in science and technology not only strengthen our economy, they inspire us as a people. The impressive accomplishments of today’s awardees so early in their careers promise even greater advances in the years ahead." Eleven federal departments and agencies join together annually to nominate scientists and engineers whose early accomplishments show the greatest promise for assuring U.S. preeminence in science and engineering and advancing the nation’s goals. The recipients are invited to a ceremony in Washington, D.C., next week where John P. Holdren, advisor to the president for science and technology and director of the White House Office of Science and Technology, will present the awards. Cai is an associate professor of education and co-director of the Center for the Study of Evaluation/National Center for Research on Evaluation, Standards, and Student Testing at UCLA’s Graduate School of Education & Information Studies. He was honored for his early contributions to measurement and statistical analysis, particularly in the area of statistical computing, and for leadership in shaping statistical practice in education, psychology and health. He is also affiliated with the UCLA Department of Psychology. Cai, who is an educational statistician whose work encompasses psychometrics — the science of quantitative measurement in education, psychology and the social sciences — has done collaborative applied research on addictions. His work emphasizes the development of new statistical methods for social science research and the application of new and existing methods of research to scholarship in education, psychology and related fields. His research expertise includes measurement and statistical modeling and computing, with wide-ranging applications in educational, psychological and health-related fields. His research is supported by the U.S. Department of Education and National Institutes of Health. Vaughan is an assistant professor of computer science at the UCLA Henry Samueli School of Engineering and Applied Science whose research interests are in machine learning, algorithmic aspects of economics and social computing. Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and analysis of algorithms that allow computers to calculate recommended behaviors or predictions based on empirical data, such as collections of documents on the Web or sets of tagged images. It is applicable to problems as diverse as natural language processing, speech recognition, spam detection, search, computer vision, gene discovery, medical diagnosis and robotics. Vaughan, who holds the Symantec Term Chair in Computer Science, said the growing popularity of the Internet and social networking sites like Facebook has led to the availability of novel sources of data on preferences, behaviors and beliefs of massive populations of users. A major goal of Vaughan’s research is to bridge the gap between theory and practice by designing a new generation of machine learning models and algorithms to address and explain the issues commonly faced when attempting to aggregate local information across large online communities. She receives federal funding for her research from the National Science Foundation. Shprits is a research geophysicist with UCLA’s Department of Earth and Space Sciences and the Department of Atmospheric and Oceanic Sciences. His PECASE citation praises him for "early-career leadership and innovative research and modeling in the realm of the Earth’s Van Allen radiation belts." Shprits, who has been conducting research at UCLA since 2002, studies electron transport and acceleration and loss in the Earth’s Van Allen radiation belts and has developed large numerical codes to model the electrons in these belts. The Van Allen radiation belts are two donut-shaped regions surrounding the Earth that contain high-energy particles trapped by the planet’s magnetic field. These particles can be harmful for satellites and humans in space. His research will help satellites guard against hazards and also help with the design of future satellite missions. Shprits has shown that while ultra-low frequency (ULF) waves can transport and accelerate electrons inside the radiation belts, they cannot explain increases in the "MeV electron flux" observed by satellites during geomagnetic storms. Shprits has also been one of the first to apply data assimilation techniques — which are widely used in navigation, atmospheric and ocean sciences and other fields — to model the radiation belts. He has used data assimilation to confirm that wave-particle interactions are critical for understanding radiation belt dynamics. Shprits’ research provides results that will be tested by a NASA mission — known as RBSP — to be launched later this year and a joint mission between UCLA and Moscow State University, Lomonosov, to be launched in 2013. Shprits is the principal investigator of the Lomonosov radiation belt investigation. NASA funds Shprits’ research. UCLA is California’s largest university, with an enrollment of nearly 38,000 undergraduate and graduate students. The UCLA College of Letters and Science and the university’s 11 professional schools feature renowned faculty and offer 337 degree programs and majors. UCLA is a national and international leader in the breadth and quality of its academic, research, health care, cultural, continuing education and athletic programs. Six alumni and five faculty have been awarded the Nobel Prize.

This site uses cookies and analysis tools to improve the usability of the site. More information. |