John W. Case was born in Clinton, Iowa, USA, and received the B.S. degree (with honors) in Physics from Iowa State University in Ames in 1964 and the M.S. and Ph.D. degrees in Mathematics in 1966 and 1969, respectively, from the University of Illinois in Champaign-Urbana where he was a National Science Foundation Graduate Fellow, 1966-1969.
Since 1989 he has been at the University of Delaware, Newark, where he is Professor of Computer
and Information Sciences and was Chair of the department 1989-1994. From September 2014 he will be Emeritus Professor there after his retirement. Previously he was in the Computer Science Departments of SUNY at Buffalo 1973-1989, where he was Associate Dean in the Faculty of Natural Sciences and Mathematics 1985, and at the University of Kansas 1969-1973.
He was Professor in the Information Security Institute, Queensland University of Technology, Brisbane, Australia, Fall 2009, as well as Visiting Professor in the School of Computer Science and Engineering at the University of New South Wales, Sydney, Australia, Fall 2001, Visiting Professor of Computer Science at The University of Rochester in NY 1987-1988, Visiting Associate Professor of Computer Science at Courant Institute, New York University and Visiting Fellow in Computer Science at Yale University 1980-1981.
He is best known for his work in computability-theoretic learning and inductive inference and for his theoretical work involving machine self-reference. He collaborates regularly with international
colleagues on three continents besides North America. He is interested in application of his theory work to cognitive science, understanding the reflective component of consciousness, philosophy of science, and applied machine learning. His research has also included the application of computability-theoretic techniques to the study of the structure, succinctness, and complexity of programs. He has been additionally interested in interconnection scheme, processor, and algorithm design for multi-dimensional lattice computers with application to the discretized, analogical representation of motion in space. He completed a project with a biologist colleague involving machine learning applied to bioinformatics.
He has graduated so far fourteen Ph.D. students with one more to finish soon. Of the fourteen finished, four are or were full professors at research universities, one of these former head of his school and director of an associated research institute, now a Deputy Vice Chancellor for Research and Commercialization. Two more of his former Ph.D. students are professors at teaching universities. One more is a tenured Assistant Professor in Rome, and another is a PostDoc in Germany. He has also supervised three bioinformatics postdocs. He has 28 grandstudents and greatgrandstudents known to him, for a total of at least 42 academic descendants thus far.
Selected Recent and Classic Publications
- On the Necessity of U-Shaped Learning (with L. Carlucci). Topics in Cognitive Science, invited for the Special Issue on Formal Learning Theory, 5 (2013), 56–88.
- Computability-Theoretic Learning Complexity (with T. K¨otzing). Philosophical Transactions
of the Royal Society A: Mathematical, Physical & Engineering Sciences (invited for the Turing Centenary themed issue with issue title, The foundations of computation, physics and mentality: the Turing legacy), 370 (2012), 3570–3596.
- Learning Secrets Interactively. Dynamic Modeling in Inductive Inference (with T. K¨otzing).
Information and Computation, 220 (2012), 60–73.
- Program Self-Reference in Constructive Scott Subdomains (with S. Moelius). Theory of Computing Systems (invited for the Special Issue for CiE'09), 51 (2012), 22–49.
- Algorithmic Scientific Inference: Within Our Computable Expected Reality. International
Journal of Unconventional Computing, 8 (2012), 192–206.
- Directions for Computability Theory Beyond Pure Mathematical. Invited book chapter in
Mathematical Problems from Applied Logic II. New Logics for the XXIst Century (edited
by D. Gabbay, S. Goncharov, and M. Zakharyaschev), International Mathematical Series,
Vol. 5, 53-98, Springer, 2007.
- The Power of Vacillation in Language Learning. SIAM Journal on Computing 28 (1999), 1941-1969.
- Incremental Concept Learning for Bounded Data Mining (with S. Jain, S. Lange, T.
Zeugmann) Information and Computation 152 (1999), 74-110.
- Subrecursive Programming Systems: Complexity and Succinctness (with J. Royer). Research
monograph in the series: Progress in Theoretical Computer Science, Birkh¨auser Boston, 1994.
- Infinitary Self-Reference in Learning Theory. Journal of Experimental & Theoretical Artificial Intelligence 6 (1994), 3-16.
- Comparison of Identification Criteria for Machine Inductive Inference (with C. Smith).
Theoretical Computer Science, 25 (1983), 193-220.
- Periodicity in Generations of Automata. Mathematical Systems Theory 8 (1974), 15-32.