Dr. Small's main area of research in the field of Artificial Intelligence is Computational Linguistics. This stemmed from her research work at SUNY Albany where Dr. Small was the lead research scientist and third phase co-PI of the HITIQA project funded under the federal government's AQUAINT program. The AQUAINT program (2001-2008) was a federally funded highly competitive program whose goal was to develop Advanced Question Answering tools for Intelligence Analysts. She has made significant advances in the field of Question Answering, specifically analytical question answering (AQA). Dr. Small was previous CEO of Language Analytical Corporation (2007-2010), where she focused on CL work on various federal contracts as well as National Science Foundation, Small business Innovation Research grants. She has recently designed a new robotics program for the Department of Computer Science. Dr. Small's work has been funded by IARPA and the NSF. She has numerous book chapters, conference papers and journal articles.
Dr. Medsker's main areas of research are knowledge-based systems, neural network techniques for monitoring nuclear radiation, Independent Component Analysis for data mining, and online intelligent systems for capturing organizational data. He has published over 100 articles in refereed journals, numerous book chapters and four books. Dr. Medsker has had active grants and contracts continually for the past thirty years from a variety of organizations including NSF, Department of Energy, AT&T, Veridian Corporation, U.S. Department of Labor and the Administrative Office of the US Courts.
Dr. James Booker is an economist who has worked for over two decades on sustainable natural resource use. A faculty member at Siena College, he been a visiting professor and scholar at the University of Wyoming, Kalamazoo College, and the University of Colorado. Dr. Booker's published work covers severe, long term drought disasters, groundwater decline and management, and economic instability and natural resource price fluctuations. His funding sources include the U.S. Geological Survey and the U.S. Department of Agriculture. His most recent publications cover New York State linkages to critical energy and environmental resources (2011), and a review of advances in economic modeling of water resources (forthcoming, 2012).
Dr. Eccarius-Kelly specializes in comparative politics; in particular on questions related to civil society activism, political violence, and radicalization. Her regional areas of study include Latin America (indigenous communities) and the Middle East (Kurdish minorities). She has spent time in Turkey and Western Europe to interview members of militant Kurdish organizations, and in Mexico, Guatemala, El Salvador, Colombia, and Peru to carry out interviews with members of indigenous communities. Most recently, her research has focused on organizational transformations of guerrilla groups such as the PKK in Turkey and the FARC in Colombia, advancing the understanding of webbed political advocacy networks and linkages to criminal operations. Eccarius-Kelly is the author of The Militant Kurds (2011) and numerous book chapters as well as journal articles, and has been a recipient of private research foundations grants.
Dr. Lim's areas of interest in Artificial Intelligence are Computational Linguistics, Game Artificial Intelligence and Machine Learning for Bioinformatics. His current research in these areas includes processing open source data, development of intelligent backgammon systems, and protein folding using the Dill HP model. Dr. Lim also has interests in the area of Computer Science Education, in which he has several publications; he will also host CCSCNE-2013, a regional computer science education conference which annually hosts 300+ attendees, at Siena College.
Dr. Breimer is interested in combining Machine Learning and web-based system development to solve a variety of different problems. His past research includes the analysis of biological sequence data, the optimization of dynamic programming algorithms, and the delivery of context sensitive help using operating system event streams. Most recently, Dr. Breimer is interested in improving Implicit Association Tests (IAT) using a machine learning- and web-based cheater detection system.