Assistant Professor at Lehigh University
Allentown, Pennsylvania Area
- Current
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- Assistant Professor of Computer Science and Engineering at Lehigh University
- Creator at web-caching.com (Self-employed)
- Owner at Davison Computer Services (Sole Proprietorship)
- Past
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- Owner at Brian's Books (Sole Proprietorship)
- Research Assistant/Teaching Assistant at Rutgers University
- Software Developer at Principia Products
- Education
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- Rutgers, The State University of New Jersey-New Brunswick
- Rutgers, The State University of New Jersey-New Brunswick
- Bucknell University
- Recommended
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1 person has recommended Brian - Connections
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313
connections
- Industry
- Internet
- Websites
Brian Davison’s Summary
Dr. Brian Davison is an assistant professor of computer science and engineering and teaches courses on web search engines, web mining, networking, system administration, C and UNIX programming. He heads the Web Understanding, Modeling, and Evaluation (WUME) laboratory. Dr. Davison earned his B.S. in Computer Engineering from Bucknell University and has an M.S. and Ph.D. in Computer Science from Rutgers University. As a graduate student, he led development in the Rutgers DiscoWeb search engine project which was later spun out as an internet startup called Teoma (and was subsequently purchased by Ask Jeeves). He continues to do research in this area, focusing on the integration of text and link analysis applied to search and classification problems on the Web. Dr. Davison's interests additionally include information retrieval, data mining, network infrastructure for the WWW, and the analysis of trust and authority in information networks. He is a 2006 NSF Faculty Early CAREER award winner and one of twelve Microsoft Live Labs "Accelerating Search" award recipients. Dr. Davison's research has been supported by the National Science Foundation, the Defense Advanced Research Projects Agency, Microsoft Research, and Sun Microsystems.
Brian Davison’s Specialties:
WWW search engines, search engine spam, web link analysis, information retrieval, text and data mining, machine learning
