Dr. Douglas S. Blank
Bryn Mawr College
Department of Computer Science

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.

Dr. Christopher Brooks
University of San Francisco
Department of Computer Science

Christopher Brooks is an Associate Professor in the Computer Science department at the University of San Francisco. He is the director of Community Connections, a service-learning project within the CS program. His interests are in the union of the sets of Artificial Intelligence and Distributed Systems: multiagent systems, peer-to-peer systems, machine learning, intelligently dealing with Web data, and electronic commerce. He is also very interested in using technology to address problems related to social justice.

Dr. Philip Chan
Florida Institute of Technology
Department of Computer Science

Philip Chan is an associate professor of computer science at Florida Institute of Technology. He received his PhD in Computer Science from Columbia University. His research interests include machine learning, data mining, and their applications to distributed computing, computer security, and biomedical computing. He has published extensively and received support from DARPA in the area of machine learning and intrusion detection. Dr. Chan introduced to the curriculum courses in machine learning and has worked with undergraduate students on research projects in machine learning. He has served as a program committee member for the major data mining conferences: KDD, ICDM, and SDM, and is on the editorial board of Journal of Database Management. He co-edited the book "Advances in Parallel and Distributed Knowledge Discovery," AAAI/MIT Press, 2000.

Dr. Diane J. Cook
Washington State University
School of Electrical Engineering and Computer Science

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.

Dr. Susan Eileen Fox
Macalester College
Department of Mathematics and Computer Science

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.

Dr. Lawrence B. Holder
Washington State University
School of Engineering and Computer Science

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.

Dr. Timothy T. Huang
Middlebury College
Department of Computer Science

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.

Dr. Susan B. Imberman
College of Staten Island
Department of Computer Science

Susan Imberman is an Associate 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.

Dr. István Jónyer
Oklahoma State University
Department of Computer Science

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.

Dr. Simon D. Levy
Washington and Lee University
Department of Computer Science

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.

Dr. Robert McCartney
University of Connecticut
Department of Computer Science and Engineering

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.

Dr. Ralph Morelli
Trinity College
Department of Computer Science

Ralph Morelli is Professor of Computer Science at Trinity College in Hartford, where he has taught since 1985. His research interests are in Artificial Intelligence (expert systems, genetic and heuristic algorithms), Historical Cryptography, and Computer Science Education. He is author of a textbook on Java Programming, co-author of a monograph on Expert Systems, and co-editor of a book on Artificial Intelligence and Cognitive Science. He served as former membership chairman and board member of the Northeast branch of the Consortium for Computing Sciences in Colleges (CCSC-NE). He is currently PI of the Humanitarian FOSS (Free and Open Source Software) Project, an NSF-funded CPATH grant aimed at helping to revitalize undergraduate computing education by getting students engaged in building open source software that serves the community.

Dr. Jorge L. Ortiz
University of Puerto Rico
Department of Electrical and Computer Engineering

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.

Dr. Vasile Rus
University of Memphis
Department of Computer Science/Institute of Intelligent Systems

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.

Dr. Raja Sooriamurthi
Carnegie Mellon University
Information Systems Program

Raja Sooriamurthi is an Associate Teaching Professor at the Information Systems Program of Carnegie Mellon University. His research interests are in the areas of case-based reasoning, distributed reasoning, machine learning and CS/IS pedagogy. His research explored a novel model of case-based reasoning termed multi-case-base reasoning. Before joining Carnegie Mellon he was with the Information Systems department of the Kelley School of Business, Indiana University. Prior to Kelley, Raja also taught at the computer science department of the University of West Florida. At the Kelley School he 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 currently serves as the President of Alpha Iota Delta, the international honor society in the decision sciences and information systems. Raja also served as the Learning Lisp editor for the Association of Lisp Users (1997-2002).

Dr. Geoff Sutcliffe
University of Miami
Department of Computer Science

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.

Dr. Ellen L. Walker
Hiram College
Department of Computer Science

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.

Dr. Scott A. Wallace
Washington State University Vancouver
School of Engineering and Computer Science

Dr. Scott Wallace is an Assistant Professor of Computer Science at Washington State University Vancouver, the newest campus in the WSU system. His research centers on reliable agent systems and seeks to design new tools and methodologies for developing complex agents. His work in this area received a nomination for the best paper award at AAMAS-05. Dr. Wallace's research and innovation also extends to the area of computer science education. In addition to teaching Design and Analysis of Algorithms and Introduction to Artificial Intelligence, in 2005 Dr. Wallace introduced the first Computer Game Design course within the WSU system. He is a principle investigator in the NSF funded Java Instructional Gaming Project and the primary developer of the JIG game engine. The goal of this effort is to bring game-related projects into traditional computer science courses by providing a strong software infrastructure and a rich set of curricular resources to educators.

Dr. G. Michael Youngblood
University of North Carolina at Charlotte
Department of Computer Science

Dr. G. Michael Youngblood is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Charlotte (UNCC). He is the Co-Director of the Playground Lab, Director of the Game Intelligence Group, and runs the Undergraduate Game Design & Development Program. Dr. Youngblood's research interests include interactive artificial intelligence, game knowledge and information structures, and machine and human learning in games. He is a member of the 2007 DARPA Computer Science Study Group, and conducts research aimed at improving simulation characters and their development for use in mission rehearsal. Dr. Youngblood received his Honors B.S., M.S., and Ph.D. degrees in Computer Science and Engineering from The University of Texas at Arlington (UTA) in 1999, 2002, and 2005 respectively. He is a member of AAAI and ACM, and works with many conferences and publications related to game AI. Work on automated generation of advanced navigation meshes with his doctoral student Hunter Hale was voted the most influential research in game AI of 2008.