Affiliate faculty are faculty who have indicated interest in providing feedback or in classroom testing some or all of the material being developed.  If you are interested in becoming an affiliate faculty, please contact Ingrid Russell at irussell@hartford.edu.  Faculty interested in adapting our material may consider applying  for an NSF CCLI Phase I funding.

 

Georgios C. Anagnostopoulos 
Assistant Professor, ECE Department, Florida Institute of Technology 
 

Dr. Anagnostopoulos is an Assistant Professor in the Electrical & Computer Engineering Department of Florida Institute of Technology in Melbourne, Florida. His research interests are statistical machine learning, neural networks and data mining.


Douglas Blank

Assistant Professor, Department of Computer Science and an adjunct faculty member of the Neural & Behavioral Sciences Program, Bryn Mawr College

 

Douglas Blank is an Associate Professor of Computer Science at Bryn Mawr College, an all-women's liberal arts college outside Philadelphia, PA. His research interests are in the areas of Developmental Robotics, Artificial Neural Networks, and Robotics Education. He has taught a variety of courses including Artificial Intelligence, Cognitive Science, Introduction to CS, Programming Languages, Emergence, Data Structures, Androids: Design and Practice, and college seminar courses for freshman, including "Robots Gone Berserk: A Look at Robots in Media." Professor Blank is currently co-director of the Institute for Personal Robots in Education (IPRE), a joint venture between Bryn Mawr College, the Georgia Institute of Technology, and Microsoft Research. The goals of the institute are to develop new hardware, software, and curricular materials for teaching introductory computer science courses with robots. Professor Blank is the creator of the award-winning "Python Robotics" system for exploring robotics in artificial intelligence courses. In addition, his work has been supported by previous grants from the National Science Foundation and the Mellon Foundation. Professor Blank has published several journal and conference papers on both developmental robotics and educational topics, and has won several Technical Excellence and Achievement Awards at the annual AAAI conference. He is a lifetime member of AAAI, and the ACM.

 

Esmail Bonakdarian
Assistant Professor, Department of Computer Science, Oberlin College
 

Dr. Bonakdarian is a Visiting Assistant Professor of Computer Science at Oberlin College. His research interests include Artificial Intelligence, particularly Evolutionary Computing, and the social impact of computing.


Patrick Brezillon

Researcher, CNRS, Laboratoire d'Informatique de Paris 6


Dr. Patrick Brezillon is a researcher at Laboratoire d'Informatique de Paris 6. Since 1997, he belongs to the SYSDEF team after merging with the Laboratoire d'Informatique de Paris 6. With its 400 members, the LIP6 is the biggest Lab. of Computer Science in Paris. The research of Dr. Brezillon focuses since 1992 on the study of Intelligent Assistant Systems, and particularly the aspects of explanation, context, and incremental knowledge acquisition. For several years, the emphasis of his studies is on the notion of context. Dr P. Brezillon is the initiator of the series of international and interdisciplinary conferences on modeling and using context, the next conference being CONTEXT-03, Stanford University, USA, June 2003.  He published papers in international conference and journals. He has been the chair of several workshops, co-organizer of two international conferences in AI area, member of several program committees, gave several invited talks and tutorials, and published more than 250 papers.


Mary Elaine Califf

Assistant Professor, School of Information Technology, Illinois State University

 

Dr. Califf is an Assistant Professor of Information Technology.  Her current research interests are in using machine learning for natural language processing.  She is particularly interested in machine learning methods that operate on complex and expressive representations.  She has participated in some research in inductive logic programming, but her recent focus has been on using ideas from ILP to develop a learning system that operates on a representation that is more specific to natural language problems.


James Caristi

Professor of Mathematics and Computer Science, Valparaiso University

Dr. Caristi teaches a wide variety of courses in both mathematics and computer science at Valparaiso University, and engages in research projects that involve both areas.  He is currently working on an expert system project with USDA.  Professor Caristi has worked with NASA in simulation and parallel processing, and with scientists at Montana State on various biological projects.  In 1990 he was awarded the Sears-Roebuck Foundation Teaching Excellence and Campus Leadership Award, and in 1999 he was awarded the Distinguished Teaching Award from the Indiana Section of the Mathematical Association of America.  He received the PhD degree in mathematics from the University of Iowa in 1975, and the BA degree from Florida State University in 1971.


Diane Cook

Huie-Rogers Chair Professor, School of Electrical Engineering and Computer Science, Washington State University

 

Dr. Cook is a Huie-Rogers Chair Professor in the School of Electrical Engineering and Computer Science at Washington State University.  Dr. Cook conducts research in artificial intelligence, machine learning, data mining, smart environments, robotics, and parallel algorithms.  She has published over 200 papers on these topics and has edited three books:  Mining Graph Data; Data Mining of Complex Data; and Smart Environments:  Technologies, Protocols, and Applications.  She serves as the editor-in-chief of the IEEE Transactions on Systems, Man, and Cybernetics, Part B:  Cybernetics, and has chaired numerous conferences on this topic.  Her work is supported in the amount of over ten million dollars by federal grants and contracts including an NSF CAREER award.  Dr. Cook is particularly interested in innovative approaches to teaching AI and machine learning.  She has developed five new courses in related areas, has served as the faculty advisor for the Society of Women Engineers, and sponsored a winning undergraduate team in the 1998 AAAI robot competition.


Andrea Danyluk

Associate Professor, Department of Computer Science, Williams College

 

Dr. Danyluk is an Associate Professor of Computer Science.  Her research interests are in the area of machine learning, specifically relating to issues involved in applied machine learning. Much of her work has focused on applications in telecommunications. Her work has been supported in part by NSF.  Danyluk has been involved in curricular issues at many levels, both at Williams College and in the larger CS community. Danyluk was a member of the Intelligent Systems Focus Group, contributing to the ACM / IEEE Task Force on Computing Curricula 2001. She was a member of the program committee for the FLAIRS Special Track on AI Education in 2004 and 2005. Together with Dr. Kim Bruce and Dr. Thomas Murtagh, she was awarded a NSF CCLI grant in 2000 to fully develop a new approach to teaching CS1 with Java, which has culminated in the forthcoming text Java: an Eventful Approach (Prentice Hall, 2005).


Paul De Palma

Associate Professor, Department of Computer Science, Gonzaga University

 

Dr. De Palma is an Associate Professor of Computer Science.  Before joining the Gonzaga faculty in 1990, he spent a decade in the computer industry.  He has degrees from St. Louis University, Temple University, where he was a University Fellow, and the University of California at Berkeley, where he was a Woodrow Wilson Fellow.  His research interests include the social impact of computing, natural language processing, and genetic algorithms.  He is currently at work on a book entitled Dim Sum for the Mind: Reflections on the Science and Industry of Computing.


Christo Dichev

Associate Professor, Department of Computer Science, Winston-Salem State University

 

Dr. DiChev is an Associate Professor of Computer Science.  His research interests include knowledge based systems, semantic web, web  mining and information extraction and web-based education.  Currently, he is a principal investigator on an NSF funded project titled “NSDL: Towards Reusable and Shareable Courseware: Topic Maps-based Digital Libraries”


Pierre M. Fiorini

Assistant Professor, Department of Computer Science, University of Southern Maine

 

Dr. Fiorini is an Assistant Professor of Computer Science.  He received the Ph.D. degree from the University of Connecticut in Computer Science & Engineering (1998), an M.S. in Computer Science & Engineering from the University of Connecticut (1995), and a B.S. in Computer Science from Trinity College (1989). His research interests include Queueing Theory, Computer Performance Modeling, Networking, Distributed Systems, Stochastic Processes, and Computational Intelligence. He is a member of the IEEE and ACM.


Susan Fox

Associate Professor, Department of Computer Science, Macalester College

Susan Fox is an Associate Professor in the Department of Mathematics and Computer Science at Macalester College. She serves as Computer Science Coordinator for the department. Her research interests are in Case-Based Reasoning, Machine Learning, Planning, and Robotics. She integrates undergraduate students into her research project, and supports independent and class projects within the department’s Robotics Lab. She teaches all levels of the computer science curriculum, and is dedicated to improving teaching and learning of undergraduates in the field, participating in computer science education and AI education activities. She has developed a suite of in and out-of-class assignments for AI that integrate interdisciplinary neuroscience students with computer science majors in the Artificial Intelligence class. She has been active in efforts to recruit and retain more women in computer science: co-PI for a Tensor Foundation grant to support women in Math and CS, co-PI on grant proposals for summer experiences for women undergraduates. She explored cross-disciplinary opportunities combining disciplines where women are currently underrepresented, to connect undergraduate women in fields with pre-teen girls. She has served on the program committees for several AI conferences, including FLAIRS.


Michael Georgiopoulos

Associate Professor, Department of Electrical and Computer Engineering, University of Central Florida

Dr. Michael Georgiopoulos is a Full Professor in the Electrical and Computer Engineering Department at the University of Central Florida and Co-Director of the Machine learning Lab.  He received his Ph.D. from the University of Connecticut.  His current research emphasis is in machine learning and neural network algorithms (with emphasis on ART neural networks), design of smart antennas using neural networks, and modeling of computer generated forces using neural network and symbolic techniques.  He serves as an associate editor of the IEEE Transactions of Neural Networks and Associate Editor of the Neural Networks Journal.  He has published 55 papers in journals and over 160 papers in conferences in the areas of neural networks, machine learning, and communications. He has principal or co-principal investigator on grants totaling more than $8.5M.


Susan Haller

Associate Professor, Department of Computer Science, University of Wisconsin- Parkside

 

Dr. Haller is an Associate Professor of Computer Science.  She received her Ph.D. in Computer Science from the State University of New York at Buffalo. Her  research areas are natural language processing, interactive discourse, and text planning.  She also is involved in research projects to attract and retain women in computer science and related technical areas of study.  She teaches courses in  programming languages, artificial intelligence, and operating systems.


Lawrence Holder
Professor, School of Electrical Engineering and Computer Science, Washington State University
 

Larry Holder is a Professor in the School of Electrical Engineering and Computer Science at Washington State University. He came to WSU in 2006 from the University of Texas at Arlington, where he taught computer science and engineering for 15 years. His research interests are in the areas of artificial intelligence, machine learning, data mining, graph theory and algorithms with applications to security and bioinformatics.  He has received more than $8 million in funding from federal agencies, including AFRL, DHS, NASA, NSF, and DARPA, and has over 100 publications in these research areas. Currently, Dr. Holder's research focuses on the development of algorithms for graph-based data mining with application to anomaly and fraud detection, counter-terrorism, biological networks, and other domains where the data can represented by a set of nodes and links.  He is also developing evaluation testbeds for AI systems using a realistic, real-time simulation of urban environments based on a modification of the popular Quake III computer game.  Dr. Holder has received numerous teaching and research awards and currently serves on the editorial board of the Journal of Intelligent Data Analysis. He received his B.S. (1986) degree in Computer Engineering and his M.S. (1988) and Ph.D. (1991) degrees in Computer Science all from the University of Illinois at Urban-Champaign.


Timothy Huang
Associate Professor, Department of Computer Science, Middlebury College

Timothy Huang is an Associate Professor of Computer Science at Middlebury College. His current research interests are in computer science education, machine learning, and strategic game playing. He is the recipient of a National Science Foundation CAREER Award, a Perkins Award for Excellence in Teaching, a Salzburg Seminar Presidential Fellowship, an International Joint Conference on Artificial Intelligence Distinguished Paper Award, and an International Conference on Pattern Recognition Best Industry-Related Paper Award Honorable Mention. Professor Huang earned his B.S. in mathematics with computer science from MIT and his Ph.D. in computer science from the University of California at Berkeley.


Susan B. Imberman
Assistant Professor, Department of Computer Science, College of Staten Island

Susan Imberman is an Assistant Professor of Computer Science at the College of Staten Island, City University of New York.  Her research interests span several areas within the domain of Artificial Intelligence.  Her most notable work deals with the use of data mining to analyze medical data.  Her papers dealing with surgical risk factors in accommodative esotropia (crossed eyes) have appeared in several highly ranked medical and computer journals.   She has also investigated the prediction of itemset emergence using incremental association rule algorithms in temporal data.  Dr. Imberman received the Computer Measurement Group's best journal article award in 2002 for her paper titled, “The KDD Process and Data Mining For Computer Performance Professionals."

Her second research area is in educational robotics.  Here she is involved in the use of low platform (inexpensive) intelligent robots to teach programming and Artificial Intelligence concepts.   Dr. Imberman has been able to incorporate robots into the computer science curriculum in new and innovative ways.  She has published many articles on her methods.  Students at the College of Staten Island are introduced to robots in their introductory programming courses.  In Dr. Imberman's Artificial Intelligence course, students build robots with the intelligence to learn.  Currently Dr. Imberman is involved in organizing students into an extra-curricular robotic soccer team. 


István Jónyer
Assistant Professor, Department of Computer Science, Oklahoma State University

István Jónyer is an Assistant Professor of Computer Science at Oklahoma State University. He received B.S., M.S., and Ph.D. degrees in Computer Science and Engineering from The University of Texas at Arlington in 1999, 2000, and 2003, respectively. His research interests are in machine learning, data mining, evolutionary algorithms and bioinformatics. His dissertation was concerned with context-free graph grammar induction based on the minimum description length principle. More recently, he applied his grammar acquisition techniques in bioinformatics, specifically on the problem of identifying transcription factor binding sites in bacterial genome in a project funded by the National Science Foundation and the Oklahoma State Regents for Higher Education. In his latest grant from the Federal Transit Administration he applies an array of data mining techniques to mine the national transit database. He teaches classes of artificial intelligence and various other topics on the undergraduate and graduate levels. He serves as a reviewer or program committee member for a number of journals and conferences. He is a co-organizer of the data mining special track at the 20th international FLAIRS conference in 2007.


Simon Levy
Assistant Professor, Department of Computer Science, Washington and Lee University

Simon Levy is an Assistant Professor of Computer Science at Washington and Lee University.  His research interests are in the areas of cognitive science and artificial intelligence, specifically: neural networks, applied genetic algorithms, distributed representations, and language evolution. He has published several conference papers in areas as diverse as parallel computing, neural networks, language evolution, and fractals, five of which have had undergraduate co-authors. He is a member of AAAI and ACM. His most recent honor was serving as a faculty mentor for the highly-competitive Google Summer of Code program.


Antonio M. Lopez, Jr.
Professor and the Conrad N. Hilton Endowed Chair in Computer Science
 

Dr. Lopez has been employed at Xavier University of Louisiana since July 1, 2000.  During the 2000 2001 academic year, he held the Chair in Artificial Intelligence at the United States Army War College, Carlisle, PA in the Center for Strategic Leadership, and he continued in dual status as Visiting Professor in Artificial Intelligence until July 2003.  At Xavier he has taught a variety of upper-level undergraduate computer engineering and computer science courses.  His research areas are: intelligent agents, knowledge-based systems, ontology development, and knowledge management.  He has been the faculty mentor for several undergraduate AI research projects. Dr. Lopez is also the Principal Investigator for a National Science Foundation funded, nationwide, longitudinal study of gender-based differences and ethnic and cultural models in the computing pipeline.


Max Louwerse

Assistant Professor, Department of Psychology/Institute for Intelligent Systems, University of Memphis

Dr. Max M. Louwerse is an Assistant Professor in the Department of Psychology and the Institute for Intelligent Systems at the University of Memphis. He received two M.A. degrees in language and literature (cum laude) from the University of Utrecht in The Netherlands and has a Ph.D. degree in Linguistics from the University of Edinburgh in Scotland. He studied and taught at the University of Florida, and was a postdoctoral fellow and visiting assistant professor in the Department of Psychology at the University of Memphis. He has published over 60 articles in a variety of journals and proceedings, edited an interdisciplinary volume on thematics and received awards for his teaching and research. His interests cover a wide range of topics in interdisciplinary research related to computational psycholinguistics, including cohesion and coherence relations in discourse comprehension and production, multimodal communication, mixed initiative dialog, narrative structure and various other aspects of discourse processing. He has been PI, Co-PI or senior researcher on 9 grants totaling almost $7 million funded by NSF, IES and ONR.


Robert McCartney

Associate Professor, Department of Computer Science and Engineering, University of Connecticut

Robert McCartney is an associate professor of Computer Science and Engineering at the University of Connecticut.  His research has been in Artificial Intelligence (case-based reasoning, planning, diagrammatic reasoning, robotics, evolutionary computation) and Computing Education (empirical studies of software design, concept acquisition, and student preconceptions).  He is currently the co-editor-in-chief of the ACM Journal on Educational Resources in Computing, and is on the editorial board of the journal Computer Science Education. At the University of Connecticut, he serves as Director of Accreditation for the School of Engineering, and Director of Undergraduate Programs in the Computer Science and Engineering department.


Lisa Meeden

Associate Professor, Computer Science Department, Swarthmore College

Dr. Lisa Meeden is an Associate Professor of Computer Science and Chair of the Cognitive Science Program at Swarthmore College.  Her research interests are in the areas of machine learning, artificial intelligence, robotics, and computer science education.  She has published extensively in these areas. Dr. Meeden has been a Co-PI on several NSF funded projects involving Robotics in the undergraduate curriculum.


Ralph Morelli

Associate Professor, Department of Computer Science, Trinity College

Ralph Morelli is Professor of Computer Science at Trinity College in Hartford, where he has taught since 1985.  His research interests are in the areas of Artificial Intelligence (mainly Expert Systems), Genetic Algorithms, Historical Cryptography, and Computer Science Education.  His most recent work has focused on applying machine learning and heuristic algorithms to the problem of analyzing historical ciphers.  He has published more than 20 journal and conference papers in these areas. He is the author of a textbook on Java Programming and co-author of a monograph on Expert Systems and co-editor of a book on Artificial Intelligence and Cognitive Science. He has been the recipient of two Research Opportunity Awards and an Instrumentation and Laboratory Improvement Award from the National Science Foundation, as well as a Pew Foundation award aimed at improving computer science education.  He is former membership chairman and board member of the Northeast branch of the Consortium for Computing Sciences in Colleges (CCSC-NE) and is a member of the ACM, IEEE-Computer Society, and the AAAI.


Dave Musicant

Assistant Professor, Department of Computer Science, Carleton College

 

Dr. Musicant is an Assistant Professor of Computer Science who specializes in data mining and machine learning.  His current work is on the EDAM project (Exploratory Data Analysis and Monitoring), which is an interdisciplinary project involving computer scientists, chemists, and atmospheric scientists.  A fundamental part of his published research has been based on Support Vector Machines, which are used in solving a variety of data mining and machine learning problems.  Dave teaches artificial intelligence, data mining, programming languages, database systems, data structures, and introductory computer science.


Maria Nisheva

Associate Professor, Department of Mathematics and Computer Science, Sofia University, Bulgaria

Dr. Nisheva is an Associate Professor of Computer Science at Sofia University. Her research interests include Artificial Intelligence, in particular Knowledge Based Systems and Functional Programming. She has published two text books and over 30 papers in the fields of Computer Algebra Systems, Knowledge Based Systems and Functional Programming.  She teaches the undergraduate AI course at Sofia University.


James L. Noyes

Professor, Department of Computer Science, Wittenberg University

 

Dr. Noyes is a Professor of Computer Science.  His AI research has primarily dealt with large-scale neural network learning and real-time expert systems.  His work has been funded by the AF Office of Scientific research.  He also authored a textbook entitled Artificial Intelligence with Common Lisp.


Jorge L. Ortiz

Professor, Department of Electrical & Computer Engineering, University of Puerto Rico Mayaguez Campus

 

Dr. Ortiz is a Professor of Electrical and Computer Engineering.  He has a BSEE and MSEE in Electrical Engineering from the University of Puerto Rico, and a Ph.D. in Electrical Engineering from the University of Houston, Texas in 1984.  He has served as Associate Dean of Engineering for Academic Affairs, and Associate Director of the Electrical & Computer Engineering Department at the University of Puerto Rico College of Engineering. He has participated in research activities in the Johnson Space Center in Houston, Texas; and the Naval Training System Center, Orlando, Florida.  He is a registered professional engineer, member of the IEEE, and the “Colegio de Ingenieros y Agrimensores de Puerto Rico.”  His present research interests are neural networks, morphological neural networks, natural language processing, and genetic algorithm applications.


Steven Ratering
Assistant Professor, Department of Computer Science, University of Wisconsin -- Eau Claire

Dr. Ratering is an Assistant Professor of Computer Science.  His primary areas of research are in robot navigation, neural networks, and undergraduate computer science education. Steve teaches artificial intelligence, theory of computation, discrete mathematics, and introductory programming courses in Java, C++, and Maple.


Anita Raja

Assistant Professor, Department of Software and Information Systems, University of North Carolina at Charlotte

 

Dr. Raja is as Assistant Professor of Computer Science.  She received a B.S. Honors in Computer Science with a minor in Mathematics summa cum laude from Temple University, Philadelphia in 1996, and a M.S. and Ph.D. in Computer Science from the University of Massachusetts Amherst in 1998 and 2003 respectively.  Her research interests are in the field of artificial intelligence including design and control of multi-agent systems, bounded-rationality, adaptive agent control, multi-agent learning, distributed information gathering and organizational design.


Robert Roos

Associate Professor, Department of Computer Science, Allegheny College

Dr. Roos is an Associate Professor of Computer Science. His interests include genetic programming, computational learning theory, theory of computation, and ways of fostering undergraduate research. He has been the advisor for several successful CRA CREW grants and has also directed a number of individual undergraduate research projects that have led to student publications at professional conferences. He is currently on sabbatical, studying robotics.


Vasile Rus

Assistant Professor, Department of Computer Science/Institute of Intelligent Systems, University of Memphis

Dr. Vasile Rus is currently an Assistant Professor of Computer Science at The University of Memphis where he holds a joint appointment position in the Department of Computer Science and Institute for Intelligent Systems. Dr. Rus has been recently named Systems Testing Research Fellow of the Fedex Institute of Technology. His research interests include artificial intelligence, intelligent systems, software engineering, text and data mining, natural language processing, knowledge representation based on natural language, and syntax-based semantics with applications to autotutoring, textual entailment, question answering and other applications where semantics is a must. Dr. Rus’ work has been supported by grants from National Science Foundation, Institute for Education Sciences, Office of Naval Research, Advanced Research and Development Agency, The University of Memphis, and Fedex Institute of Technology. Dr. Rus has been involved in the larger AI community as chair, Program Committee member, journal reviewer of various AI conferences and journals. He is also involved in conferences focusing on computer science education. In 2006 and 2007 Dr. Rus is the Workshop, Panel, and Tutorial Chair for the Conference of the Consortium for Computing Sciences - Mid-South. Dr. Rus has published few dozen peer reviewed papers on international conferences and journals related to AI and Natural Language Processing. He also has co-authored with an undergraduate student a conference and journal paper related to computer science education.


Kate Sanders

Associate Professor, Department of Computer Science, Rhode Island College

 

Dr. Sanders is an Associate Professor of Computer Science.  She received her Ph.D. from Brown University in computer science, with a dissertation on artificial intelligence and law.  Her research interests include artificial intelligence and computer-science education.  She has taught a wide variety of computer-science courses, including introduction to programming, software engineering, database, programming languages, artificial intelligence, machine learning, and natural language planning.


Ben Schafer
Assistant Professor, Department of Computer Science, University of Northern Iowa

Dr. Schafer is an Assistant Professor of Computer Science at the University of Northern Iowa.  His research interests include recommender technology, intelligent decision-support systems, electronic commerce, and agent assisted interfaces.  His most recent research has involved interface design for systems facilitating intelligent decision-support. He teaches artificial intelligence, intelligent systems, user interface design, and introductory computer science.


Raja Sooriamurthi

Clinical Assistant Professor, Kelley School of Business, Indiana University

Raja Sooriamurthi is a Clinical Assistant Professor of Information Systems at the Kelley School of Business of Indiana University.  His research interests are in the areas of case-based reasoning, distributed reasoning, machine learning and computer science pedagogy.  His current research  explores a novel model of case-based reasoning termed multi-case-base reasoning.  Prior to joining the Kelley School he was with the faculty of the University of West Florida.  At the Kelley School he has created a new course on programming and software development for Information Systems majors.  Both at the University of West Florida and at Indiana University his pedagogical  efforts have been recognized with several awards for excellence in teaching.  He serves on the program committees of the leading CBR conferences (ICCBR and ECCBR) as well as FLAIRS.  He was the co-chair of the special track on CBR at FLAIRS 2004 and 2005.  He also serves as the national vice-president of Alpha Iota Delta, the national honor society in the decision sciences.  He also served as the Learning Lisp editor for the Association of Lisp Users (1997-2002).


Geoff Sutcliffe

Associate Professor, Department of Computer Science, University of Miami

Geoff Sutcliffe is an Associate Professor, and Director of Undergraduate Studies, in the Department of Computer Science at the University of Miami. He received a BSc(Hons) and MSc from the University of Natal, and a PhD in Computer Science from the University of Western Australia. His research is in the area of Automated Reasoning, particularly in the evaluation and effective use of automated reasoning systems. His most prominent achievements are: the first ever development of a heterogeneous parallel deduction system, eventually leading to the development of the SSCPA automated reasoning system; the development and ongoing maintenance of the TPTP problem library, which is now the de facto standard for testing 1st order automated reasoning systems; the development and ongoing organization of the CADE ATP System Competition - the world championship for first order automated reasoning systems; and the specification of the TPTP communication standards for automated reasoning tools. The research has been supported by grants from the German Ministry for Research, the Australian Research Council, the European Union, and also by internal university grants from Edith Cowan University, James Cook University, and the University or Miami. The research has produced over 60 journal and conference papers. Additionally, he has been guest editor of six special journal issues on topics in automated reasoning. He has contributed to the automated reasoning and artificial intelligence communities as the conference chair of the 14th and 19th International Conferences on Automated Deduction (CADE), program co-chair of the 12th International Conference on Logic for Programming Artificial Intelligence and Reasoning (LPAR), program co-chair of the 19th and 20th International FLAIRS Conferences, co-founder and organizer of the "ES*" series of workshops on Empirically Successful Automated Reasoning, and as a regular program committee member and reviewer for automated reasoning and artificial intelligence journals and conferences. He is currently a CADE trustee and the vice-president of FLAIRS. As a faculty member he has supervised and examined several graduate theses, serves on the University and College curriculum committes at the University of Miami, and is the PI of a $467575 NSF grant providing scholarships for students taking Computer Science or Mathematics as a second major.


Guenter Tusch

Associate Professor, School of Computing and Information Systems, Grand Valley State University and Grand Rapids Medical Education and Research Center

 

Dr. Tusch is an Associate Professor of Computing and Information Systems.  His interests include the broad range of issues related to data mining and integrated decision-support systems and their effective implementation.  His current research focuses on classification and data mining in medical and bioinformatics applications.  Recently, he was principal investigator in a pilot clinical study together with a mayor hospital (Spectrum Health) to evaluate the impact of a clinical decision support tool.


Colleen van Lent
Assistant Professor, Computer Engineering and Computer Science, California 
State University Long Beach
 

Dr van Lent is an Assistant Professor of Computer Science.  Her research interests include Programming Languages and Artificial Intelligence with an emphasis in planning and using robots as pedagogical tools.


Ellen Walker

Professor, Department of Computer Science, Hiram College

 

Ellen Walker is a Professor of Computer Science at Hiram College, a small liberal arts college in Northeastern Ohio.  Her research interests include computer vision, fuzzy logic, artificial intelligence and computer science education. She is deeply interested in undergraduate teaching and mentoring as well as issues affecting women in computer science.  She has received funding from the National Science Foundation for both research and curriculum development, and published more than 35 articles in refereed conferences and journals.  In addition to teaching over 20 different undergraduate courses, she has advised over 50 undergraduate research projects. She has served as the Program Chair for the North American Fuzzy Information Processing Society conference, and for the Ohio Celebration of Women in Computing, and as the Publications Chair for SIGCSE.  She is a regular reviewer for several journals and conferences.  She is a Senior Member of ACM, a Senior Member of IEEE, and a member of AAAI, NAFIPS, the Consortium for Computing Science in Colleges (CCSC) and Sigma Xi.  She has served three terms on the Board of Directors at NAFIPS, and was selected as a Distinguished Professor for the Consortium of Associate Professors Project (CAPP) of CRA.  She has also been a Faculty Consultant for the Advanced Placement Exam in Computer Science.  Her honors include a Paul E. Martin Award from Hiram College and a Mentor Recognition Award from the University of California, San Diego.


Linda M. Wilkins

Associate Professor, Department of Computer Science, Providence College

 

Dr. Wilkins is an Associate Professor of Computer Science.  Her research interests are in artificial intelligence and in computer science education.  She has written and given several presentations on topics related to computer science education and has served on numerous panels in this area.


David Wilson

Assistant Professor, Department of Software and Information Systems, University of North Carolina at Charlotte

 

Dr. David C. Wilson is an Assistant Professor in the Department of Software and Information Systems at The University of North Carolina, Charlotte. Dr. Wilson’s research centers on the development of intelligent software systems to bridge the gaps between human information needs and the computational resources available to meet them. It involves the coordination of artificial intelligence and machine learning techniques with multimedia, database, internet, and communications systems to elicit, enhance, apply, and present relevant task-based knowledge. The research emphasizes the incorporation of spatial context to support reasoning, as well as a case-based reasoning approach, particularly for personalization and recommender systems applications.  Dr. Wilson has developed and taught new graduate and undergraduate courses in Knowledge Based Computation and Personalization and Recommender systems, as well as a variety of project-based software development and web related courses that touch on applications of machine learning techniques.  Dr. Wilson has served on program committees for a variety of AI related conferences, and he has organized conference workshops and tracks on case-based reasoning, computer game intelligence, and knowledge management.  He is currently the program chair for the 20th International FLAIRS conference, as well as workshop coordinator for the International Conference on Case Based Reasoning.