G. Burns and H. Chalupsky. "It's All Made Up" - Why we should stop building representations based on interpretive models and focus on experimental evidence instead. AAAI Discovery Informatics Workshop, 2014. [pdf]
H. Chalupsky and E. Hovy. RIPTIDE: Learning Violation Prediction Models from Boarding Activity Data. In Proceedings of the IEEE International Conference on Technologies for Homeland Security, 2013. [pdf]
H. Chalupsky, R. DeMarco, E. Hovy, P. Kantor, A. Matlin, P. Mitra, B. Ozbas, F. Roberts, J. Wojtowicz and M. Xi. Estimating violation risk for fisheries regulations. In P. Perny, M. Pirlot, and A. Tsoukias (eds), Proceedings of International Conference on Algorithmic Decision Theory III, Lecture Notes in Computer Science, LNAI 8176, Springer, 2013, 297-308.
H. Chalupsky. Story-Level Inference and Gap Filling to Improve Machine Reading. In Proceedings of the Twenty-Fifth International FLAIRS Conference. 2012. [pdf]
H. Chalupsky. Using KOJAK Link Discovery Tools to Solve the Cell Phone Calls Mini Challenge. Proceedings of the IEEE Symposium on Visual Analytics Science and Technology (IEEE VAST 2008). DVD only. [pdf] (this is a summary of our KOJAK submission to the VAST 2008 Cell Phone Calls Mini Challenge)
S. Lin and H. Chalupsky. Discovering and Explaining Abnormal Nodes in Semantic Graphs. IEEE Transactions on Knowledge and Data Engineering, 20(8): pages 1039-1052, 2008. [draft pre-print]
A. Valente, D. van Brackle, H. Chalupsky and G. Edwards. Implementing Logic Spreadsheets in LESS. Knowledge Engineering Review, 22(3): pages 237-253, 2007.
R. Mulkar, J.R. Hobbs, E. Hovy, H. Chalupsky, and C.Y. Lin. Learning by reading: Two experiments. In Proceedings of the IJCAI 2007 workshop on Knowledge and Reasoning for Answering Questions. 2007 [pdf]
J. Adibi, T. Barrett, S. Bhatt, H. Chalupsky, J. Chame and M. Hall. Processing-In-Memory Technology for Knowledge Discovery Algorithms. Proceedings of Second International Workshop on Data Management on New Hardware (DaMoN 2006). June, 2006 [pdf]
P. Maechling, H. Chalupsky, M. Dougherty, E. Deelman, Y. Gil, S. Gullapalli, V. Gupta, C. Kesselman, J. Kim, G. Mehta, B. Mendenhall, T. Russ, G. Singh, M. Spraragen, G. Staples, K. Vahi. Simplifying Construction of Complex Workflows for Non-Expert Users of the Southern California Earthquake Center Community Modeling Environment. SIGMOD Record, 34(3): pages 24-30, September 2005 [pdf]
J. Adibi and H. Chalupsky. Scalable Group Detection via a Mutual Information Model. In Proceedings of the First International Conference on Intelligence Analysis (IA-2005). [pdf]
J. Adibi, H. Chalupsky, E. Melz and A. Valente. The KOJAK Group Finder: Connecting the Dots via Integrated Knowledge-Based and Statistical Reasoning. In Proceedings of the Sixteenth Innovative Applications of Artificial Intelligence Conference (IAAI-04), 2004. [pdf] [postscript]
S. Lin and H. Chalupsky. Using Unsupervised Link Discovery Methods to Find Interesting Facts and Connections in a Bibliography Dataset. SIGKDD Explorations, 5(2): pages 173-178, December 2003. This entry made 2nd place in the Open Task of the 2003 KDD Cup. [pdf]
S. Lin and H. Chalupsky. Unsupervised Link Discovery in Multi-relational Data via Rarity Analysis. In Proceedings of the Third IEEE International Conference on Data Mining (ICDM '03). 2003. [pdf]
M. Pool, K. Murray, J. Fitzgerald, M. Mehrotra, R. Schrag, J. Blythe, J. Kim, H. Chalupsky, P. Miraglia, T. Russ and D. Schneider. Evaluating SME-Authored COA Critiquing Knowledge. In Proceedings of the Second International Conference on Knowledge Capture (K-CAP 2003). 2003
H. Chalupsky and T.A. Russ. WhyNot: Debugging Failed Queries in Large Knowledge Bases. In Proceedings of the Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI-02), pages 870-877, Menlo Park, 2002. AAAI Press. [pdf] [postscript]
H. Chalupsky, Y. Gil, C.A. Knoblock, K. Lerman, J. Oh, D.V. Pynadath, T.A. Russ, and M. Tambe. Electric Elves: Agent technology for supporting human organizations. In AI Magazine, 23(2): Summer 2002, pages 11-24, AAAI Press. (this is a slightly expanded version of the IAAI-01 paper). [pdf] [postscript]
H. Chalupsky, Y. Gil, C.A. Knoblock, K. Lerman, J. Oh, D.V. Pynadath, T.A. Russ, and M. Tambe. Electric Elves: Applying agent technology to support human organizations. In Proceedings of the Thirteenth Innovative Applications of Artificial Intelligence Conference (IAAI-01), pages 51-58, Menlo Park, 2001. AAAI Press. [pdf] [postscript]
D.V. Pynadath, M. Tambe, Y. Arens, H. Chalupsky, Y. Gil, C. Knoblock, H. Lee, K. Lerman, J. Oh, S. Ramachandran, P.S. Rosenbloom and T. Russ. Electric Elves: Immersing an agent organization in a human organization. In Proceedings of the AAAI Fall Symposium on Socially Intelligent Agents - The Human in the Loop, Menlo Park, CA, 2000. AAAI. [pdf] [postscript] H. Chalupsky. OntoMorph: a translation system for symbolic knowledge. In A.G. Cohn, F. Giunchiglia, and B. Selman, editors, Principles of Knowledge Representation and Reasoning: Proceedings of the Seventh International Conference (KR2000), San Francisco, CA, 2000. Morgan Kaufmann. [pdf] [postscript]
H. Chalupsky and R.M. MacGregor. STELLA - a Lisp-like language for symbolic programming with delivery in Common Lisp, C++ and Java. In Proceedings of the 1999 Lisp User Group Meeting, Berkeley, CA, 1999. Franz Inc. [pdf] [postscript]
H. Chalupsky, E. Hovy, and T. Russ. Progress on an automatic ontology alignment methodology. ANSI Ad Hoc Group on Ontology Standards; available at http://ksl-web.stanford.edu/onto-std/hovy/index.htm. 1997.
H. Chalupsky and S.C. Shapiro. Reasoning about incomplete agents. In Proceedings of the Fifth International Conference on User Modeling (UM-96), pages 169-177. User Modeling, Inc., 1996. [pdf] [postscript]
H. Chalupsky. SIMBA: Belief Ascription by Way of Simulative Reasoning. PhD thesis, Department of Computer Science, State University of New York at Buffalo, Buffalo, NY, 1996. [pdf] [postscript]
H. Chalupsky and S.C. Shapiro. SL: A subjective, intensional logic of belief. In Proceedings of the Sixteenth Annual Conference of the Cognitive Science Society, pages 165-170, Hillsdale, NJ, August 1994. Lawrence Erlbaum. [pdf] [postscript]
H. Chalupsky. Using hypothetical reasoning as a method for belief ascription. Journal of Experimental and Theoretical Artificial Intelligence (JETAI), 5(2&3):119-133, April-September 1993. [pdf] [postscript]
S.C. Shapiro, H. Chalupsky, Hsueh-Cheng Chou, and D.M. Mark. Intelligent user interfaces: Connecting ARC/INFO and SNACTor, a semantic network based system for planning actions. In Proceedings of the Twelfth Annual ESRI User Conference, V. 3, pages 151-165. Environmental Systems Research Institute, Redlands, California, 1992.
S.C. Shapiro, H. Chalupsky, and Hsueh-Cheng Chou. Connecting ARC/INFO and SNACTor. Technical Report 91-13, Department of Computer Science, SUNY at Buffalo, Buffalo, NY, July 1991. 22 pages. [pdf] [postscript]
H. Chalupsky. Caching and consistency: A solution in RLL-1. In E. Buchberger and J. Retti, editors, Proceedings of the Third Austrian Conference on Artificial Intelligence, volume 151 of Informatik Fachberichte, pages 114-124. Springer Verlag, 1987.
H. Chalupsky. Implementation of a kernel system for RLL-1, a representation language language. Master's thesis, Technical University of Vienna, Austria, 1985. in German.