Professor, Computer Science and Engineering
Automated reasoning, artificial intelligence, machine learning, database systems, expert systems, computational biology, and data mining. Professor Elkan has expanded his early interest in fuzzy logic to writing learning, search, and reasoning algorithms. He was an early pioneer in Web applications of artificial intelligence, notably in the area of information retrieval (e.g. how search engines process very general or very specific queries to yield the best matches possible). Elkan has developed algorithms for reasoning about database queries and updates, and methods of formalizing commonsense knowledge about causation. He also co-authored a powerful Web engine for comparing proteins and DNA--allowing biologists to detect shared features and evolutionary relationships among the flood of protein and DNA sequence data produced by the Human Genome Project. Elkan is currently co-directing the Knowledge and Data Engineering (KDE) effort within Cal-(IT)2--a broad effort in database and data mining research to support applications involving massive data sets (initially from medical imaging and environmental sensor networks). He has also taken his work in AI and applied it to stock-market trading strategies. Elkan can also talk on how scientists and engineers communicate their ideas to the media and the public, having authored the CSE department's "Notes on Giving a Research Talk."
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