Dr. C. Lee Giles is a professor emeritus in the College of IST. Previously, he was the David Reese Professor at the College of IST.
He has been associated with Columbia University, the University of Maryland, University of Pennsylvania, Princeton University, and the University of Trento. His current research and research group interests are in intelligent information processing systems such as: Intelligent AI cyberinfrastructure and portals with a special interest in using large language models for computer and information science, chemistry, materials science, economics, medicine, biology and archaeology. Deep learning with grammars, automata, and rules. Novel web tools, search engines, scientometrics, web search and measurement.
Scholarly big data: large scale knowledge and information management and extraction, information retrieval, entity disambiguation and record linking, metadata extraction, text and data mining, machine learning, digital libraries and web databases, web services and social networks. Automated extraction, mining and integration of data and text and tools for Science of Science and Team Science and learning at scale. Novel applications and architectures of intelligent information systems and artificial intelligence for big data. Business and economic models for artificial intelligence, search and search engines.
His research is or has been supported by NSF, NASA, DARPA, Microsoft, FAST Search and Transfer, Ford, IBM, Internet Archive, Lockheed-Martin, Alcatel/Lucent, NEC, Raytheon, Smithsonian, US Department of Treasury, and Yahoo. He has consulted for or been on advisory boards of NEC, FAST Search and Transfer, PJM, KXEN, Databrary, US Department of Treasury, and the US Department of Defense. He and his collaborators, including current and former graduate students, have published over 500 journal and conference papers, book chapters, and edited books and proceedings. His work is very well cited, according to Google Scholar, and his is one of the top 200 h-indexes in Computer Science.
Recent work on Scholarly Big Data and access appeared in 2014 in PLOSOne and was in Nature, Science and other news. His 2006 coauthored paper in Science proposes a cyberinfrastructure for the historial sciences. His coauthored paper in 2004 in the Proceedings of the National Academy of Sciences created an automatic acknowledgement indexing methodology and showed that various funding agencies and individuals in computer and information science are much more acknowledged than others.
In 2002, he coauthored the paper "Winners Don't Take All" published in the Proceedings of the National Academy of Sciences on how the topic based web does not follow a power law distribution. In 1998, he coauthored a paper published in Science on the size and search engine coverage of the Web that was well cited in the popular press and in 1999 a well received follow-up paper in Nature. Several of his papers have won or been nominated for best paper awards and have been reprinted in edited collections.
His research has been highlighted in many places including the Society for Industrial and Applied Mathematics (SIAM) news, Wired Magazine, the Wall Street Journal, the Washington Post, the New York Times, Nature news and Science news. He has been involved in the creation and development of various novel search engines and digital libraries. He was one of the creators of the novel metasearch engines, Inquirus and Inquirus2. He was also one of the creators of the popular computer and information science search engine, CiteSeer, an autonomous citation indexing search engine and digital library that heavily uses machine learning and is now hosted at the College of Information Sciences and Technology at Penn State University. It has been replaced by the Next Generation CiteSeer, CiteSeerx.
He also created a niche search engine eBizSearch, a search engine for e-business documents, and, SMEALSearch, a search engine and digital library for academic business documents. He is very interested in cyberinfrastructure for science and the academy and was a codeveloper in the research and development of a portal and search tool for environmental chemistry, ChemxSeer. He prototyped a novel search engine for archaeology, ArchSeer, and also developed a new search engine for robots.txt, BotSeer, that indexed over 2 million robots.txt files. He also developed a search engine for collaboration networks, CollabSeer, and for citation recommendation, RefSeer. Recently, he codeveloped a search engine, PrivaSeer, for privacy policies.
He also proposed and published deep learning recurrent architectures, and tuned two BERT transformers for a privacy large language model, PrivBERT, and a language model for scientific paper summarization, SciBERTSUM. Dr. Giles plays an active professional role in scientific and technical and communities. He serves on many related conference program committees and has helped organize many related meetings and workshops. He has given many invited and keynote talks and seminars.
He has been or is an advisor and reviewer to USA and other government and university research programs. He has served on the editorial boards of IEEE Intelligent Systems, IEEE Transactions on Knowledge and Data Engineering, Machine Learning Journal, Computational Intelligence and Applications, IEEE Transactions on Neural Networks, Journal of Computational Intelligence in Finance, Journal of Parallel and Distributed Computing, Neural Networks, Neural Computation, and Academic Press. He is a Fellow of the ACM, a Fellow of the IEEE and a Fellow of the International Neural Network Society (INNS), and a member of AAAI. He received the INNS Dennis Gabor Award for outstanding achievements in neural engineering and the IEEE Computational Intelligence Society's Pioneer Award in Neural Networks.
His work on CiteSeer led to the National Federation of Advanced Information Services (NFAIS) Miles Conrad Award. He has twice received the IBM Distinguished Faculty Award. His previous positions include a Senior Research Scientist at NEC Research Institute (now NEC Labs), Princeton, NJ; a Program Manager at the Air Force Office of Scientific Research in Washington, D.C.; a research scientist at the Naval Research Laboratory, Washington, D.C.; and an Assistant Professor of Electrical and Computer Engineering at Clarkson University, Potsdam, N.Y.
During part of his graduate education he was a research engineer at Ford Motor Company's Scientific Research Laboratory. His graduate degrees are from the University of Michigan and the University of Arizona and his undergraduate degrees are from Rhodes College and the University of Tennessee. His academic genealogy includes two Nobel laureates and prominent mathematicians.
