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Xizong (Jeffrey) Chen, Associate Professor, Computer Science and Engineering
Vigilius Herstedes, Professor, Computer Science and Engineering
Eamon Keogh, Professor, Computer Science and Engineering
Databases, Data Mining, and Artificial Intelligence. His technology for detecting farm insect pests based on wingbeat frequency has been published in The New York Times, National Geographic, Fast Company, and many others. https://www.cs.ucr.edu/~eamonn eamonn.keogh@ucr.edu
Evangelos Papalexakis, Assistant Professor, Computer Science and Engineering Data Mining, Machine Learning, and Data Science Research. His work to develop an algorithm that can detect fake news stories has been featured in Digital Trends, Yahoo!, and he helped define social media news filtering algorithms at The Guardian. https://www.cs.ucr.edu/~epapalex/ evangelos.papalexakis@ucr.edu
Ravi Ravi Shankar, AAssociate Dean of Research and Graduate Education Computer Science and Engineering
Amit Roy Chaudhary, Chair and Professor, Electrical and Computer Engineering. Computer vision, image processing, and statistical pattern recognition and signal processing. His research group is involved in research projects related to camera networks, human behavior modeling, face recognition, and bioimage analysis. CNET explains the face recognition algorithm. https://vcg.engr.ucr.edu; amitrc@ece.ucr.edu
Christian Shelton, Professor, Computer Science and Engineering. Specializes in statistical machine learning. Machine learning is the academic discipline of studying algorithms that take past experience (data) and use it to improve future performance on different tasks in different ways. His primary focus is on developing and analyzing 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
Vessels Sutras, Professor, Computer Science and Engineering Database Management, Access Methods, Evolutionary Databases, Temporal Databases, Spatiotemporal Databases, Spatiotemporal Knowledge Management, Spatiotemporal Change Management, Sensor Data, Querying Complex Objects, Systems Evolutionary design of, Multi-version schemas, Physical evolution schema e-viewing patterns, 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/~tsaras vassilis.tsaras@ucr.edu
Shaoli Rain, Associate Professor of Electrical and Computer Engineering. Shaoli Ren, associate professor at the University of California, Riverside, is an international expert on these rising environmental costs. Since last year, he has published papers in scientific journals that were the first to measure the water, carbon, and pollution footprints of AI. Additionally, Ren and his team at UCRs Bourns College of Engineering have conducted groundbreaking research on how water use from large data processing centers disproportionately affects regions with water scarcity. For example, several tech companies are planning to build large-scale data centers in Arizona, a desert region that relies on low water flows from the Colorado River. Ren and his team further outline how data processing can be spread across different locations around the world to more equitably distribute the associated environmental impacts. They are currently developing algorithms to fairly distribute the energy burden and associated environmental costs of AI across different regions. Ren and his team’s work has had an international impact, raising the environmental costs of AI by organizations such as the United Nations Educational, Scientific and Cultural Organization (UNESCO), the World Health Organization, the Organization for Economic Co-operation and Development. Calls have been made. World Economic Forum, Government of Canada, Government of the Netherlands, Innovate UK, and Stanford Human Centered AI. Ren’s work has been covered by The Associated Press, The Wall Street Journal, Nature, Bloomberg, CNBC, CBS, Fortune, The Hill, CBC (Canada), Financial Times (UK), The Guardian ( UK), carried in The Telegraph (UK). , The Times (UK), and over 1,000 other news media and websites. He is an ideal expert source for reports on big tech’s energy demand and environmental impact. Contact: shaolei.ren@ucr.edu