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Daniel Berleant

Daniel Berleant, Ph.D. is a Professor in the Department of Information Science, College of Engineering and Information Technology, University of Arkansas at Little Rock. He also serves in the University of Arkansas at Little Rock/University of Arkansas for Medical Sciences Joint Bioinformatics Program. A former Interim Department Chair, he has previously been at Iowa State University (Dept. of Electrical and Computer Engineering, with ancillary appointments in the Lawrence Baker Center for Bioinformatics and Biological Statistics, the Human-Computer Interaction Program, and the Information Infrastructure Institute) and the University of Arkansas, Fayetteville (Dept. of Computer Science and Computer Engineering, adjunct in Electrical Engineering).
 
Daniel earned his Ph.D. from the University of Texas at Austin in 1991. His BS is from MIT. He has worked in industry as a software engineer and taught courses to students ranging from the freshman to the advanced graduate levels. He and his students’ research has been funded through the National Science Foundation, National Institutes of Health, the Corporation for National and Community Service, and other agencies; and through industry including Procter and Gamble, Electricité de France, Invitrogen, and others. Research areas have included artificial intelligence, inference under severe uncertainty, web science, energy, text mining, and bioinformatics.
 
He has graduated five Ph.D. students and over 30 master’s degree students, and taught a wide variety of courses from the freshman to the advanced graduate levels. He is an author of over 90 scholarly papers, and led the development of four significant software projects. One article, Robert’s Rules of Order for e-mail meetings (with B. Liu), is on the IEEE Computer Society’s “Top Takes on Computing Technology” list because, according to Computer Society, it has “appeared in the Top Ten Articles listings, which are identified by actual & visitor’s views.”
 
Daniel’s book The Human Race to the Future: What Could Happen — and What to Do is published right here at the Lifeboat Foundation. This book describes a broad range of scientifically well-founded possible futures, and is aimed at readers like you.