Artificial Intelligence Expert | UCR News

Databases, data mining, artificial intelligence. His technology for detecting farm pests based on flapping frequency has been featured in The New York Times, National His Geographic, Fast His Company, and more. https://www.cs.ucr.edu/~eamonn eamonn.keogh@ucr.edu

Evangelos Papalexakis Assistant Professor, Computer Science & Engineering Research in data mining, machine learning, and data science. His work developing algorithms that can detect fake news articles has been featured in Digital Trends, Yahoo, and he helped explain his algorithm for social media news filtering in The Guardian. https://www.cs.ucr.edu/~epapalex/evangelos.papalexakis@ucr.edu

Amit Roy Chowdhury Professor and Professor of Electrical and Computer Engineering. He specializes in computer vision, image processing, statistical pattern recognition and signal processing. His research group is involved in research projects related to camera networks, human behavior modeling, facial recognition, and biomedical image analysis. We discussed facial recognition algorithms on CNET. https://vcg.engr.ucr.edu; amitrc@ece.ucr.edu

christian shelton Professor of Computer Science and Engineering. He specializes in statistical machine learning. Machine learning is the study of algorithms that take past experience (data) and use it to improve future performance on different tasks in different ways. His primary focus is on the development and analysis of algorithms that infer, predict, or quantify events and processes that evolve over time. https://www.engr.ucr.edu/people/christianshelton.html cshelton@cs.ucr.edu

Vasilis Tsotras Professor, Computer Science & Engineering Database management, access methods, evolving databases, temporal databases, spatiotemporal databases, spatiotemporal knowledge management, spatiotemporal change management, sensor data, querying complex objects, evolving system design, multiversion schemas Evolution, physical trajectory query artifacts, data distribution, FPGA-based publish/subscribe systems, querying spatiotemporal patterns using accelerators, semantic spatiotemporal queries, scalable data management (ASTERIX), big active data management. http://www.cs.ucr.edu/~tsotras vassilis.tsotras@ucr.edu

Ren Xiaolei Associate Professor of Electrical and Computer Engineering. Associate Professor Xiaolei Ren of the University of California, Riverside is a leading international expert on these rising environmental costs. Since last year, he has published papers in scientific journals quantifying for the first time the water, carbon, and pollution emissions of his AI. Additionally, Wren and his team at UCR's Bones Institute of Technology are making breakthroughs in how water consumption from large data processing centers disproportionately impacts water-scarce regions. We conducted research. For example, several high-tech companies plan to build large data centers in Arizona, a desert state that relies on dwindling amounts of water from the Colorado River. Ren and his team further outlined how data processing could be distributed across different locations around the world so that the corresponding environmental impact is more equitably distributed. They are currently developing algorithms to fairly distribute the energy burden of AI and the corresponding environmental costs across different regions. Wren and his team's research has had an international impact, including the United Nations Educational, Scientific and Cultural Organization (UNESCO), the World Health Organization, the Organization for Economic Co-operation and Development, the World Economic Forum, the Government of Canada, the Government of the Netherlands, Innovate UK, and the Stanford Human Center. A.I. Ren's work has appeared in The Associated Press, Wall Street Journal, Nature, Bloomberg, CNBC, CBS, Fortune, The Hill, CBC (Canada), Financial Times (UK), Guardian (UK), and Telegraph (UK). It's being featured. , The Times (UK) and over 1,000 other news outlets and websites. He is the ideal expert source for reporting on big technology's energy demands and environmental impacts. Contact: shaolei.ren@ucr.edu