Education

Ph.D. in Computer Science, Brigham Young University, 1998
M.S. in Computer Science, Brigham Young University, 1995
B.S. in Computer Science, Brigham Young University, 1992

Experience

Brigham Young University, Professor of Computer Science, 9/12 to present
Brigham Young University, Associate Professor of Computer Science, 9/07 to 8/12
Brigham Young University, Assistant Professor of Computer Science, 7/01 to 8/07
Penn State University, Graduate Faculty of Computer Science and Engineering, 3/00 to 7/01
Penn State University, Applied Research Laboratory, Research Associate, 9/99 to 7/01
fonix Corporation, Research Scientist, 7/98 to 9/99

Publications

Derrall Heath and Dan Ventura, “Semantic Style Creation”, Proceedings of the AAAI Workshop on Human-Machine Collaborative Learning, to appear, 2017

Rob Smith and Dan Ventura, “Novel Metrics for Evaluating Algorithms for Estimating Latent Signal from Repetitive Noisy Observations”, Proceedings of the 13th Annual Biotechnology and Bioinformatics Symposium, 2016

Dan Ventura, “Beyond Computational Intelligence to Computational Creativity in Games”, Proceedings of the IEEE Conference on Computational Intelligence and Games, pp. 427-435, 2016

Dan Ventura, “Mere Generation: Essential Barometer or Dated Concept?”, Proceedings of the Seventh International Conference on Computational Creativity, pp. 17-24, 2016

Derrall Heath and Dan Ventura, “Before a Computer Can Draw, It Must First Learn to See”, Proceedings of the Seventh International Conference on Computational Creativity, pp. 172-179, 2016

Derrall Heath and Dan Ventura, “Creating Images by Imagining Image Semantics using Vector Space Models”, Proceedings of the Association for the Advancement of Artificial Intelligence, pp. 1202-1208, 2016

Alok Desai, Dan Ventura and Dah-Jye Lee, “An Efficient Feature Descriptor Based on Synthetic Basis Functions and Uniqueness Matching Strategy”, Computer Vision and Image Understanding, 142: 37-49, 2016

Jared Lundell, Charles DuHadway and Dan Ventura, “Data-driven Kernels via Semi-Supervised Clustering on the Manifold”, Proceedings of the International Conference on Machine Learning and Applications, pp. 487-492, 2015

Paul M. Bodily, Stanley Fujimoto, Quinn Snell, Dan Ventura and Mark J. Clement, “ScaffoldScaffolder: Solving Contig Orientation via Bidirected to Directed Graph Reduction”, Bioinformatics, 32(1): 17-24, 2016

Daniel Johnson and Dan Ventura, “Musical Motif Discovery from Non-musical Inspiration Sources”, ACM Computers in Entertainment---Special Issue on Musical Metacreation, to appear, 2016

Dean M. Lebaron, Logan A. Mitchell and Dan Ventura, “Intelligent Content Generation via Abstraction, Evolution and Reinforcement”, Proceedings of the AIIDE Workshop on Experimental AI in Games, pp. 36-41, 2015

David Norton, Derrall Heath and Dan Ventura, “Accounting for Bias in the Evaluation of Creative Computational Systems: An Assessment of DARCI”, Proceedings of the International Conference on Computational Creativity, pp. 31-38, 2015

Simon Colton, Ian Gouldstone, Michael Cook, Dan Ventura and Jakob Halskov, “The Painting Fool Sees! New Projects with the Automated Painter”, Proceedings of the International Conference on Computational Creativity, pp. 189-196, 2015

Martin Mumford and Dan Ventura, “The Man Behind the Curtain: Overcoming Skepticism about Creative Computers”, Proceedings of the International Conference on Computational Creativity, pp. 1-7, 2015

Derrall Heath, Aaron Dennis and Dan Ventura, “Imagining Imagination: A Computational Framework Using Associative Memory Models and Vector Space Models”, Proceedings of the International Conference on Computational Creativity, pp. 244-251, 2015

Aaron Dennis and Dan Ventura, “Greedy Structure Search for Sum-Product Networks”, Proceedings of the International Joint Conference on Artificial Intelligence, pp. 932-938, 2015

Dan Ventura, “The Computational Creativity Complex”, in Computational Creativity Research: Towards Creative Machines, Tarek R. Besold, Marco Schorlemmer, Alan Smaill (eds.), Atlantis Press, pp. 65-92, 2015

Simon Colton, Alison Pease, Joseph Corneli, Michael Cook, Rose Hepworth and Dan Ventura, “On Studying and Handling Observer Issues in Computational Creativity Research and Practice”, in Computational Creativity Research: Towards Creative Machines, Tarek R. Besold, Marco Schorlemmer, Alan Smaill (eds.), Atlantis Press, pp. 3-36, 2015

Rob Smith, John T. Prince and Dan Ventura, “A Coherent Mathematical Characterization of Isotope Trace Extraction, Isotopic Envelope Extraction, and LC-MS Correspondence”, BMC Bioinformatics, 16(Suppl 7): S1, 2015 (an earlier version of the paper was presented at the 11th Annual Biotechnology and Bioinformatics Symposium 2014)

Alok Desai, Dah-Jye Lee and Dan Ventura, “Matching Affine Features with the SYBA Feature Descriptor”, Proceedings of the International Symposium on Visual Computing Part II, LNCS 8888, pp. 448-457, 2014

Spencer G. Fowers, Alok Desai, Dah-Jye Lee, Dan Ventura and James Archibald, “TreeBASIS Feature Descriptor and Its Hardware Implementation", International Journal of Reconfigurable Computing, vol. 2014, article ID 606210, 2014

Adam Drake and Dan Ventura, “Using Spectral Features to Improve Sentiment Analysis”, Proceedings of the International Conference on Machine Learning and Applications, pp. 153-158, 2014

Adam Drake and Dan Ventura, “Improving Spectral Learning by Using Multiple Representations”, Proceedings of the International Conference on Machine Learning and Applications, pp. 147-152, 2014

Spencer G. Fowers, Alok Desai, D.J. Lee, Dan Ventura and Doran K. Wilde, “An Efficient, Tree-Based Feature Descriptor and Matching Algorithm”, AIAA Journal of Aerospace Information Systems 11(9): 596-606, 2014

Dan Ventura, “Can a Computer be Lucky? And Other Ridiculous Questions Posed by Computational Creativity”, Proceedings of the Seventh Conference on Artificial General Intelligence, LNAI 8598, pp. 208-217, 2014

Simon Colton and Dan Ventura, “You Can't Know my Mind: A Festival of Computational Creativity”, Proceedings of the 5th International Conference on Computational Creativity, pp. 351-354, 2014

Daniel Johnson and Dan Ventura, “Musical Motif Discovery in Non-musical Media”, Proceedings of the 5th International Conference on Computational Creativity, pp. 91-99, 2014

Michael R. Smith, Ryan S. Hintze and Dan Ventura, “Nehovah: A Neologism Creator Nomen Ipsum”, Proceedings of the 5th International Conference on Computational Creativity, pp. 173-181, 2014

David Norton, Derrall Heath and Dan Ventura, “Autonomously Managing Competing Objectives to Improve the Creation and Curation of Artifacts”, Proceedings of the 5th International Conference on Computational Creativity, pp. 23-32, 2014

Robert Smith, Andrew D. Mathis, Dan Ventura and John T. Prince, “Proteomics, Lipidomics, Metabolomics: A Mass Spectrometry Tutorial from a Computer Scientist’s Point of View”, BMC Bioinformatics 15(Suppl 7): S9, 2014 (an earlier version of the paper was presented at the 10th Annual Biotechnology and Bioinformatics Symposium 2013)

Robert Smith, Dan Ventura and John T. Prince, “LC-MS Alignment in Theory and Practice: A Comprehensive Algorithmic Review”, Briefings in Bioinformatics, DOI: 10.1093/bib/bbt080, 2013

Adam Drake and Dan Ventura, “An Empirical Comparison of Spectral Learning Methods for Classification”, Proceedings of the International Conference on Machine Learning and Applications, pp. 9-14, 2013

Robert Smith and Dan Ventura, "A General Model for Continuous Noninvasive Pulmonary Artery Pressure Estimation", Computers in Biology and Medicine, 43(7): 904-13, 2013.

Derrall Heath, David Norton, Eric Ringger and Dan Ventura, "Semantic Models as a Combination of Free Association Norms and Corpus-based Approaches", IEEE International Conference on Semantic Computing, pp. 48-55, 2013.

Robert Smith, Tamil S. Anthonymuthu, Dan Ventura and John Prince, "Statistical Agglomeration: Peak Summarization for Direct Infusion Lipidomics", Bioinformatics, 29(19): 2445-2451, 2013.

Kristine Monteith, Bruce Brown, Dan Ventura and Tony Martinez, “Automatic Generation of Music for Inducing Physiological Response”, Proceedings of the 35th Annual Meeting of the Cognitive Science Society, pp. 3098-3103, 2013

Robert Smith, Dan Ventura and John Prince, "Controlling for Confounding Variables in MS-omics Protocol: Why Modularity Matters", Briefings in Bioinformatics, DOI: 10.1093/bib/bbt049, 2013.

Derrall Heath, David Norton and Dan Ventura, "Autonomously Communicating Conceptual Knowledge Through Visual Art", Proceedings of the 4th International Conference on Computational Creativity, pp. 97-104, 2013.

Robert Smith, Dan Ventura, John Prince, "Novel Algorithms and the Benefits of Comparative Validation", Bioinformatics, 29(12): 1583-1585, 2013.

Robert Smith, Ryan Williamson, Dan Ventura and John Prince, "Rubabel: Wrapping OpenBabel with Ruby", Journal of Chemoinformatics, 5(1): 35-44, 2013.

Spencer G. Fowers, D.J. Lee and Dan Ventura, "A Novel Feature Descriptor for Low-Resource Embedded Vision Sensors for Micro-UAV Applications", AIAA Journal of Aerospace Information Systems 10(8): 385-395, 2013.

David Norton, Derrall Heath and Dan Ventura, “Finding Creativity in an Artificial Artist”, Journal of Creative Behavior, 47(2): 106-124, 2013.

Derrall Heath and Dan Ventura, “Improving Multi-label Classification by Avoiding Implicit Negativity with Incomplete Data”, Computational Intelligence 30(3):535-561, 2014.

Spencer G. Fowers, D.J. Lee, Dan Ventura and James Archibald, “Nature-Inspired BASIS Feature Descriptor and Its Hardware Implementation”, IEEE Transactions on Circuits and System for Video Technology, 23(5): 756-768, 2013.

Aaron Dennis and Dan Ventura, “Learning the Architecture of Sum-Product Networks Using Clustering on Variables”, Neural Information Processing Systems, pp. 2042-2050, 2012.

Derrall Heath, David Norton and Dan Ventura, “Conveying Semantics through Visual Metaphor”, ACM Transactions on Intelligent Systems and Technology, 5(2):31:1--31:17, 2014.

Skyler Murray and Dan Ventura, “Algorithmically Flexible Style Composition Through Multi-Objective Fitness Functions”, 1st International Workshop on Musical Metacreation, pp. 55-62, 2012.

Kenneth Sundberg, Mark Clement, Quinn Snell, Dan Ventura, Michael Whiting and Keith Crandall, “Phylogenetic Search Through Partial Tree Mixing”, BMC Bioinformatics, 13(13): S8, 2012.

Spencer G Fowers, D.J. Lee, Dan Ventura and Doran K. Wilde, “A Novel, Efficient, Tree-Based Descriptor and Matching Algorithm”, Proceedings of the 21st International Conference on Pattern Recognition, pp. 2464-2467, 2012.

Kristine Monteith, Tony Martinez and Dan Ventura, “Automatic Generation of Melodic Accompaniments for Lyrics”, Proceedings of the Third International Conference on Computational Creativity, pp. 87-94, 2012.

Richard Morris, Scott Burton, Paul Bodily and Dan Ventura, “Soup Over Bean of Pure Joy: Culinary Ruminations of an Artificial Chef”, Proceedings of the Third International Conference on Computational Creativity, pp.119-125, 2012.

Robert Smith, Aaron Dennis and Dan Ventura, “Automatic Composition from Non-musical Inspiration Sources”, Proceedings of the Third International Conference on Computational Creativity, pp. 160-164, 2012.

Robert Van Dam, Irene Langkilde-Geary and Dan Ventura, “Adapting ADtrees for Improved Performance on Large Datasets with High Arity Features”, Knowledge and Information Systems, 35(3): 525-552, 2013.

Dan Ventura, “Rational Irrationality”, Game Theory for Security, Sustainability and Health, AAAI 2012 Spring Symposium Series, 2012.

Toh Koon Charlie Neo and Dan Ventura, “A Direct Boosting Algorithm for the K-Nearest Neighbor Classifier via Local Warping of the Distance Metric”, Pattern Recognition Letters, 33(1): 92-102, 2012.

Kenneth Sundberg, Mark Clement, Quinn Snell, Dan Ventura, Michael F. Whiting and Keith A. Crandall, “Partial Tree Mixing--a Novel Approach to Phylogenetic Search”, Biotechnology and Bioinformatics Symposium, 2011.

David Norton, Derrall Heath and Dan Ventura, “A Collaboration with DARCI”, ACM C&C Workshop on Semi-Automated Creativity, 2011.

David Norton, Derrall Heath and Dan Ventura, “An Artistic Dialogue with the Artificial”, Proceedings of the Eighth ACM Conference on Creativity and Cognition, pp. 31-40, 2011.

Mike Gashler, Dan Ventura and Tony Martinez, “Manifold Learning by Graduated Optimization”, IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics, 41(6): 1458-1470, 2011.

Kyle Dickerson and Dan Ventura, “Musical Query-by-Content using Self Organizing Maps”, Proceedings of the International Joint Conference on Neural Networks, pp. 705-710, 2011.

David Norton, Derrall Heath and Dan Ventura, “Autonomously Creating Quality Images”, Proceedings of the Second International Conference on Computational Creativity, pp. 10-15, 2011.

Kristine Monteith, Virginia Francisco, Tony Martinez, Pablo Gervás and Dan Ventura, “Automatic Generation of Emotionally-Targeted Soundtracks”, Proceedings of the Second International Conference on Computational Creativity, pp. 60-62, 2011.

Dan Ventura, “No Free Lunch in the Search for Creativity”, Proceedings of the Second International Conference on Computational Creativity, pp. 108-110, 2011.

Aaron Dennis, Andrew D. Michaels, Patti Arand and Dan Ventura, "Noninvasive Estimation of Pulmonary Artery Pressure Using Heart Sound Analysis”, Computers in Biology and Medicine, 40(9): 758-764, 2010.

David Norton and Dan Ventura, "Improving Liquid State Machines Through Iterative Refinement of the Reservoir”, Neurocomputing, 73(16-18): 2893-2904, 2010.

Jeffrey S. Whiting, Jonathan Dinerstein, Paris K. Egbert and Dan Ventura, "Cognitive and Behavioral Model Ensembles for Autonomous Virtual Characters”, Computational Intelligence, 26(2): 142-159, 2010.

Kristine Monteith, Tony Martinez and Dan Ventura, "Computational Modeling of Emotional Content in Music", Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 2356-2361, 2010.

David Norton, Derrall Heath and Dan Ventura, “Establishing Appreciation in a Creative System”, Proceedings of the First International Conference on Computational Creativity, pp. 26-35, 2010.

Kristine Monteith, Tony Martinez and Dan Ventura, "Automatic Generation of Music for Inducing Emotive Response", Proceedings of the First International Conference on Computational Creativity, pp. 140-149, 2010.

Dan Ventura, “A Sub-symbolic Model of the Cognitive Processes of Re-representation and Insight”, Proceedings of the ACM Conference on Creativity and Cognition, pp. 409-410, 2009 (a longer version of this first appeared in Creative Intelligent Systems: Papers from the AAAI Spring Symposium, 2008).

Adam Drake and Dan Ventura, "Search Techniques for Fourier-Based Learning", Proceedings of the International Joint Conference on Artificial Intelligence, pp. 1040-1045, 2009 (this first appeared in Search in Artificial Intelligence and Robotics: Papers from the AAAI Workshop, 2008).

Ilya Raykhel and Dan Ventura, "Real-time Automatic Price Prediction for eBay Online Trading", Proceedings of the Innovative Applications of Artificial Intelligence Conference, pp. 135-140, 2009.

Neil Toronto, Bryan Morse, Kevin Seppi and Dan Ventura, "Super-Resolution via Recapture and Bayesian Effect Modeling", Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2388-2395, 2009.

David Norton and Dan Ventura, "Improving the Separability of a Reservoir Facilitates Learning Transfer", Proceedings of the International Joint Conference on Neural Networks, pp.2288-2293, 2009 (this first appeared in Transfer Learning for Complex Tasks: Papers from the AAAI Workshop, 2008).

Kyle Dickerson and Dan Ventura, "Using Self-Organizing Maps to Implicitly Model Preference for a Musical Query-by-Content System", Proceedings of the International Joint Conference on Neural Networks, pp. 705-710, 2009.

Jonathan Dinerstein, Parris Egbert, Dan Ventura and Michael Goodrich, "Demonstration-based Behavior Programming for Embodied Virtual Agents", Computational Intelligence, 24(4): 235-256, 2008.

Dan Ventura, "A Reductio Ad Absurdum Experiment in Sufficiency for Evaluating (Computational) Creative Systems", Proceedings of the International Joint Workshop on Computational Creativity, pp. 11-19, 2008.

Heather Chan and Dan Ventura, “Automatic Composition of Themed Mood Pieces”, Proceedings of the International Joint Workshop on Computational Creativity, pp. 109-115, 2008.

Adam Drake, Eric Ringger and Dan Ventura, "Sentiment Regression: Using Real-Valued Scores to Summarize Overall Document Sentiment", Proceedings of the IEEE International Conference on Semantic Computing, pp. 152-157, 2008.

Robert D. Van Dam, Irene Geary and Dan Ventura, "Adapting ADtrees for High Arity Features", Proceedings of the Association for the Advancement of Artificial Intelligence, pp. 708-713, 2008.

Jonathan Dinerstein, Parris Egbert,Dan Ventura and Michael Goodrich, "Data-Driven Programming and Behavior for Autonomous Virtual Characters", Proceedings of the Association for the Advancement of Artificial Intelligence, pp. 1450-1451, 2008.

Dan Ventura, “Sub-symbolic Re-representation to Facilitate Learning Transfer”, Creative Intelligent Systems: Papers from the AAAI Spring Symposium, Technical Report SS-08-03, pp. 128-134, 2008.

Mike Gashler, Tony Martinez and Dan Ventura, "Iterative Non-linear Dimensionality Reduction with Manifold Sculpting", Neural Information Processing Systems 20, pp. 513-520, 2008.

Rob Van Dam and Dan Ventura, "ADtrees for Sequential Data and N-gram Counting", Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 492-497, 2007.

Sabra Dinerstein, Jonathan Dinerstein and Dan Ventura, "Robust Multi-Modal Biometric Fusion via SVM Ensemble", Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 1530-1535, 2007.

Jared Lundell and Dan Ventura, "A Data-dependent Distance Measure for Transductive Instance-based Learning", Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 2825-2830, 2007.

Neil Toronto, Bryan Morse, Dan Ventura, Kevin Seppi, "The Hough Transform's Implicit Bayesian Foundation", Proceedings of the IEEE International Conference on Image Processing, pp. 377-380, 2007.

Jake Merrell, Dan Ventura and Bryan Morse, "Clustering Music via the Temporal Similarity of Timbre", IJCAI Workshop on Artificial Intelligence and Music, pp. 153-164, 2007.

Nancy Fulda and Dan Ventura, "Predicting and Preventing Coordination Problems in Cooperative Q-learning Systems", Proceedings of the International Joint Conference on Artificial Intelligence, pp. 780-785, 2007.

Jonathan Dinerstein, Dan Ventura and Parris Egbert, "Learning Policies for Embodied Virtual Agents Through Demonstration", Proceedings of the International Joint Conference on Artificial Intelligence, pp. 1257-1262, 2007.

Kaivan Kamali, Dan Ventura, Amulya Garga and Soundar Kumara, "Geometric Task Decomposition in a Multi-agent Environment", Applied Artificial Intelligence, 20(5): 437-456, 2006.

Eric Goodman and Dan Ventura, "Spatiotemporal Pattern Recognition via Liquid State Machines", Proceedings of the International Joint Conference on Neural Networks, pp. 7579-7584, July 2006.

Neil Toronto and Dan Ventura, "Learning Quantum Operators from Quantum State Pairs", Proceedings of the IEEE Congress on Evolutionary Computation, pp. 9157-9162, July 2006.

David Norton and Dan Ventura, "Preparing More Effective Liquid State Machines Using Hebbian Learning", Proceedings of the International Joint Conference on Neural Networks, pp. 8359-8364, July 2006.

Nancy Fulda and Dan Ventura, "Learning a Rendezvous Task with Dynamic Joint Action Perception", Proceedings of the International Joint Conference on Neural Networks, pp. 627-632, July 2006.

Jonathan Dinerstein, Dan Ventura and Parris Egbert, "Fast and Robust Incremental Action Prediction for Interactive Agents", Computational Intelligence, 21(1): 90-110, 2005.

Adam Drake and Dan Ventura, "A Practical Generalization of Fourier-based Learning", Proceedings of the International Conference on Machine Learning, pp. 185-192, August 2005.

Neil Toronto, Dan Ventura and Bryan Morse, "Edge Inference for Image Interpolation", Proceedings of the International Joint Conference on Neural Networks, pp. 1782-1787, July 2005.

Eric Goodman and Dan Ventura, "Effectively Using Recurrently Connected Spiking Neural Networks", Proceedings of the International Joint Conference on Neural Networks, pp. 1542-1547, July 2005.

Adam Drake and Dan Ventura, "Comparing High-Order Binary Features", Proceedings of the Joint Conference on Information Sciences, pp. 428-431, July 2005.

Eric Goodman and Dan Ventura, "Time Invariance and Liquid State Machines", Proceedings of the Joint Conference on Information Sciences, pp. 420-423, July 2005.

Nancy Fulda and Dan Ventura, "Incremental Policy Learning: An Equilibrium Selection Algorithm for Reinforcement Learning Agents with Common Interests", Proceedings of the International Joint Conference on Neural Networks, pp. 1121-1126, July 2004.

Mark Richards and Dan Ventura, "Choosing a Starting Configuration for Particle Swarm Optimization", Proceedings of the International Joint Conference on Neural Networks, pp. 2309-2312, July 2004.

Stephen Whiting and Dan Ventura, "Learning Multiple Correct Classifications from Incomplete Data using Weakened Implicit Negatives", Proceedings of the International Joint Conference on Neural Networks, pp. 2953-2958, July 2004.

Bob Ricks and Dan Ventura, "Training a Quantum Neural Network", Neural Information Processing Systems 16, pp. 1019-1026, December 2003.

Nancy Fulda and Dan Ventura, "Target Sets: A Tool for Understanding and Predicting the Behavior of Interacting Q-learners", Proceedings of the International Joint Conference on Information Sciences, pp. 1549-1552, September 2003.

Mark Richards and Dan Ventura, "Dynamic Sociometry in Particle Swarm Optimization", Proceedings of the International Joint Conference on Information Sciences, pp. 1557-1560, September 2003.

Nancy Fulda and Dan Ventura, "Dynamic Joint Action Perception for Q-Learning Agents", Proceedings of the International Conference on Machine Learning and Applications, pp. 73-78, June 2003.

Nancy Fulda and Dan Ventura, "Concurrently Learning Neural Nets: Encouraging Optimal Behavior in Cooperative Reinforcement Learning Systems", Proceedings of the IEEE International Workshop on Soft Computing Techniques in Instrumentation, Measurement, and Related Applications, pp. 2-5, May 2003.

Dan Ventura, "Probabilistic Connections in Relaxation Networks", Proceedings of the International Joint Conference on Neural Networks, pp.934-938, May 2002.

Dan Ventura, "Pattern Classification Using a Quantum System", Proceedings of the Joint Conference on Information Sciences, pp.537-640, March 2002.

Dan Ventura, "A Quantum Analog to Basis Function Networks", Proceedings of the International Conference on Computing Anticipatory Systems, pp. 286-295, August 2001.

Dan Ventura, "On the Utility of Entanglement in Quantum Neural Computing", Proceedings of the International Joint Conference on Neural Networks, pp. 1565-1570, July 2001.

John Howell, John Yeazell and Dan Ventura, "Optically Simulating a Quantum Associative Memory", Physical Review A 62:42303, 2000.

Alexandr Ezhov, A. Nifanova, and Dan Ventura, "Quantum Associative Memory with Distributed Queries", Information Sciences 128(3-4):271-293, 2000.

Dan Ventura and Tony Martinez, "Quantum Associative Memory", Information Sciences 124(1-4):273-296, 2000.

Alexandr Ezhov and Dan Ventura, "Quantum Neural Networks", in Future Directions for Intelligent Systems and Information Science N. Kasabov (ed.), Physica-Verlag, pp. 213-235, 2000.

Dan Ventura, "Learning Quantum Operators", Proceedings of the Joint Conference on Information Sciences, pp. 750-752, March 2000.

Dan Ventura and Tony Martinez, "Initializing the Amplitude Distribution of a Quantum State", Foundations of Physics Letters 12(6):547-559, 1999.

Dan Ventura, "Quantum Computational Intelligence: Answers and Questions", IEEE Intelligent Systems 14(4):14-16, 1999.

Dan Ventura, "Implementing Competitive Learning in a Quantum System", Proceedings of the International Joint Conference on Neural Networks, paper 513 (CD-ROM), July 1999.

Dan Ventura, D. Randall Wilson, Tony Martinez and Brian Moncur, "A Neural Model of Centered Tri-gram Speech Recognition", Proceedings of the International Joint Conference on Neural Networks, paper 2188 (CD-ROM), July 1999.

D. Randall Wilson, Dan Ventura, Tony Martinez and Brian Moncur, "The Robustness of Relaxation Rates in Constraint Satisfaction Networks", Proceedings of the International Joint Conference on Neural Networks, paper 162 (CD-ROM), July 1999.

Dan Ventura and Tony Martinez, "A Quantum Associative Memory Based on Grover's Algorithm", Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 22-27, April 1999.

Dan Ventura, "Artificial Associative Memory using Quantum Processes", Proceedings of the Joint Conference on Information Sciences, vol. 2, pp. 218-221, October 1998.

Dan Ventura and Tony Martinez, "Quantum Associative Memory with Exponential Capacity", Proceedings of the International Joint Conference on Neural Networks, pp. 509-513, May 1998.

Dan Ventura and Tony Martinez, "Optimal Control Using a Neural/Evolutionary Hybrid System", Proceedings of the International Joint Conference on Neural Networks, pp. 1036-1041, May 1998.

Dan Ventura and Tony Martinez, "Using Evolutionary Computation to Facilitate Development of Neurocontrol", Proceedings of the International Workshop on Neural Networks and Neurocontrol, August 1997.

Dan Ventura and Tony Martinez, "An Artificial Neuron with Quantum Mechanical Properties", Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 482-485, April 1997.

Dan Ventura and Tony Martinez, "A General Evolutionary/Neural Hybrid Approach to Learning Optimization Problems", Proceedings of the World Congress on Neural Networks, pp. 1091-5, September 1996.

Dan Ventura and Tony Martinez, "Concerning a General Framework for the Development of Intelligent Systems", Proceedings of the International Conference on Artificial Intelligence, Expert Systems and Neural Networks, pp. 44-47, August 1996.

Dan Ventura and Tony Martinez, "Robust Optimization Using Training Set Evolution", Proceedings of the International Conference on Neural Networks, pp. 524-8, June 1996.

Dan Ventura, Tim Andersen and Tony Martinez, "Using Evolutionary Computation to Generate Training Set Data for Neural Networks", Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pp. 468-471, April 1995.

Dan Ventura and Tony Martinez, "An Empirical Comparison of Discretization Methods", Proceedings of the International Symposium on Computer and Information Sciences, pp. 443-450, November 1995.

Dan Ventura and Tony Martinez, "Using Multiple Statistical Prototypes to Classify Continuously Valued Data", Proceedings of the International Symposium on Neuroinformatics and Neurocomputers, pp. 238-45, September 1995.

Dan Ventura and Tony Martinez, "BRACE: A Paradigm For the Discretization of Continuously Valued Data", Proceedings of the Florida Artificial Intelligence Research Symposium, pp. 117-121, May 1994.


Other

Hannu Toivonen, Simon Colton, Michael Cook and Dan Ventura (editors), Proceedings of the Sixth International Conference on Computational Creativity, Park City, Utah, Brigham Young University Press, June 2015

You Can’t Know My Mind (with Simon Colton—a festival of computational creativity that included art, portraiture, poetry, music and cooking), Galerie Oberkampf, Paris, France, July 12-19, 2013

DARCI, “Peaceful on Black 4-3”, Utah County Art Gallery Fall Photography/Digital Art Show, October 3 – November 19 – Won 2nd Place in the Digital Art Category, with a $150 prize, Fall, 2011

David Norton, Derrall Heath and Dan Ventura, “Fitness Function: Turning the Loop Inside Out”, interactive art exhibit at The High Museum, Atlanta, Georgia (as part of the Eighth ACM Conference on Creativity and Cognition), November 2011

Dan Ventura, Pablo Gervás, D. Fox Harrell, Mary Lou Maher, Alison Pease and Geraint Wiggins, Proceedings of the Second International Conference on Computational Creativity, April 2011

Dan Ventura, Alison Pease, Rafael Pérez y Pérez, Graeme Ritchie and Tony Veale, Proceedings of the First International Conference on Computational Creativity, 2010

David Norton, Derrall Heath and Dan Ventura (with Joseph Ostraff and his VASTU 480R class), Fitness Function, interactive art exhibit at the Harris Fine Arts Center, Brigham Young University, March 19-31, 2010

Marcello Balduccini, Chitta Baral, Boyan Brodaric, Simon Colton, Peter Fox, David Gutelius, Knut Hinkelmann, Ian Horswill, Bernardo Huberman, Eva Hudlicka, Kristina Lerman, Christine Lisetti, Deborah McGuinness, Mary Lou Maher, Mark A. Musen, Mehran Sahami, Derek Sleeman, Barbara Thönssen, Juan Velasquez, and Dan Ventura, "Reports of the AAAI 2008 Spring Symposia", AI Magazine 29(3), pp. 107-115, 2008

Dan Ventura, Mary Lou Maher and Simon Colton (editors), Creative Intelligent Systems: Papers from the AAAI Spring Symposium, Technical Report SS-08-03, AAAI Press, 2008

Steve Bair, Uday Chakraborty, Shu-Heng Chen, Heng-Da Cheng, David K.Y. Chiu, Sanjoy Das, Grit Denker, Richard Duro, Manuel Grana Romay, Donald Hung, Etienne Kerre, Hong Va Leong, Chang-Tien Lu, Jie Lu, Liam Maguire, Chong Wah Ngo, M. Sarfraz, Chris Tseng, Shusaku Tsumoto, Dan Ventura, Paul P. Wang, Xin Yao, C.N. Zhang, Kaizhong Zhang (Editors), Proceedings of the Eighth Joint Conference on Information Sciences, July 2005

Ken Chen, Shu-Heng Chen, Heng-Da Cheng, David K.Y. Chin, Sanjoy Das, Richard Duro, Zhen Jiang, Nik Kasabov, Etienne Kerre, Hong Va Leong, Qing Li, Mi Lu, Manuel Grana Romay, Dan Ventura, Paul P. Wang, Jie Wu (Editors), Proceedings of the Seventh Joint Conference on Information Sciences, September 2003

Dan Ventura and Tony Martinez, "Kvantovaya Accotsiativnaya Pamyat'", Neirokomp'yutery: razrabotka i primenenie, N9-10, pp. 34-53, 2002 (Russian translation of "Quantum Associative Memory" in the journal Neurocomputers: development and applications)

H. John Caulfield, Shu-Heng Chen, Heng-Da Cheng, Richard Duro, Vasant Hanovar, Etienne E. Kerre, Mi Lu, Manuel Grana Romay, Timothy K. Shih, Dan Ventura, Paul Wang, Yuanyuan Yang (Editors), Proceedings of the Sixth Joint Conference on Information Sciences, March 2002

Dan Ventura, comments in "Discussion on Neurocomputers After Ten Years" (Eds. Frolov and Ezhov), Neural Network World, vol. 1 no. 2, pp. 103-174, 1999

Dan Ventura, Quantum and Evolutionary Approaches to Computational Learning, Ph.D. Dissertation, Computer Science Department, Brigham Young University, 1998

Dan Ventura, On Discretization as a Preprocessing Step for Supervised Learning Models, Master's Thesis, Computer Science Department, Brigham Young University, 1995


Seminars, Colloquia and Presentations

  • A Coherent Mathematical Characterization of Isotope Trace Extraction, Isotopic Envelope Extraction, and LC-MS Correspondence, 11th Annual Biotechnology and Bioinformatics Symposium, 2014 (with Rob Smith and John Prince)
  • Can Computational Creativity Produce a Commercially Successful Artificial Songwriter?, INFORMS Annual Meeting, 2014
  • Unprecedented Quantitative Evaluation of LC-MS Isotope Trace Feature Detection Using Ground Truth Data, poster at the 62nd Annual Conference of the American Society for Mass Spectrometry, Baltimore, MD, June 2014 (with Rob Smith, Ryan Money and John Prince)
  • Persistent Myths and Uncomfortable Truths: Taking MS-omics Data Processing from the Emperor's New Clothes to a Rigorous Science, poster at the 62nd Annual Conference of the American Society for Mass Spectrometry, Baltimore, MD, June 2014 (with Rob Smith and John Prince)
  • Sensitive Isotope Trace Feature Detection, poster at the 10th Annual Conference of the United States Human Proteome Organization, Seattle, WA April 2014. (with Rob Smith and John Prince)
  • A Critical Comparison of Several Ion Feature Extraction Methods, 10th Annual Biotechnology and Bioinformatics Symposium, 2013 (with Rob Smith, Christine Kendall, Ryan Money and John Prince)
  • [Art]ificial Intention, GECCO Evolutionary, Art, Design and Creativity Competition, finalist, 2013 (accompanying technical paper titled, “Semantic Models and Visuo-Linguistic Association as an Intentional Mechanism for Visual Art“) (with Derrall Heath and David Norton)
  • Label-free, ID-free, Parameter-free Peak Picking and Feature Selection for LC-MS Data, poster at the 61st Annual Conference of the American Society for Mass Spectrometry, Minneapolis, MN, June 2013 (with Rob Smith and John Prince)
  • On Characterizing Computational Creativity Tasks by Their Factorizability, University of Edinburgh, April 2013
  • Art[ificial]: Computational Creativity for Communicating Intention, University of Edinburgh, April 2013
  • From Artificial Intelligence to Computational Creativity, Queen Mary University London, March 2013
  • Art[ificial]: Computational Creativity for Communicating Intention, National University of Ireland, Maynooth, February 2013
  • Art[ificial]: Computational Creativity for Communicating Intention, Trinity College, Dublin, Ireland, February 2013
  • Why the Web Will Make Computational Creativity More Creative and Why it Won’t, The Creative Web: Computational Creativity as a Web Service, KAIST, Daejeon, South Korea, December 2012
  • Transferring Learning via Learned Transformations, NIPS Workshop on Transfer Learning by Learning Rich Generative Models, Whistler, British Columbia, December 2010 (with Chris Wilson)
  • Art[ificial]: Computational Creativity for Communicating Intention, invited talk for the 5th Mexican International Colloquium on Computational Creativity, Universidad Nacional Autónoma de México, November 2010
  • Roundtable Panelist on Computational Creativity and Interdisciplinary Work, Universidad Autónoma de Metropolitana, November 2010 (with Graeme Ritchie, Nick Montfort and Eduardo Peñaloza)
  • Using Self-Organizing Maps to Implicitly Model Preference for a Musical Query-by-Content System, AAAI Multidisciplinary Workshop on Advances in Preference Handling, July 2008 (with Kyle Dickerson)
  • Learning Agents: Cooperation, Plausibility, Prediction and Creativity, School of Computing, University of Utah, October 2007
  • Reservoir Shaping via Reinforcement Learning to Improve Liquid State Machines, NIPS Workshop on Echo State Networks and Liquid State Machines, Whistler, British Columbia, December 2006 (with David Norton)
  • Effecting Transfer via Learning Curve Analysis, NIPS Workshop on Inductive Transfer: 10 Years Later, Whistler, British Columbia, December 2005 (with Christophe Giraud-Carrier)
  • The Challenge of Computing using Quantum Computation, Department of Physics and Astronomy, Brigham Young University, colloquium, January 2004
  • Learning as Quantum Search, Quantum Neural Networks Workshop, Neural Information Processing Systems, Whistler, British Columbia, December 2002
  • Quantum Neural Computation, Mini-Symposium on Quantum Computing, College Station, Texas, May 2001
  • Experimental Validation of the Common Control Language, The Third Very Shallow Water/Surf Zone Mine Counter Measures Program Meeting, Panama City, Florida, February 2001
  • Why quantum computation is good for computational learning and computational learning is good for quantum computation, Department of Computer Science, Brigham Young University, February 2001
  • Quantum Computation and Computational Learning, Department of Physics and Astronomy, Brigham Young University, February 2001
  • Linear Optics for Quantum Neural Computing, Quantum Neural Computing Workshop, Neural Information Processing Systems, Breckenridge, Colorado, December 2000
  • Application of Quantum Computation to Computational Learning, DARPA Quantum Information Science and Technology Workshop, Greenbelt, Maryland, October 2000
  • Quantum Computation: Experiments in Linear Optics, Applied Research Laboratory, Penn State University, September 2000.
  • Field Programmable Scripts for Multiple UUV Missions, Second Very Shallow Water/Surf Zone Mine Counter Measures Program Meeting, Panama City, Florida, December 1999
  • Quantum Computation: Current and Future Perspectives, Fall meeting of the Applied Research Laboratory Advisory Board, Penn State University, November 1999
  • An Introduction to Quantum Computation, Applied Research Laboratory, Penn State University, October 1999
  • A Neural/Evolutionary Hybrid Learning System, Information Science and Technology Division, Applied Research Laboratory, Penn State University, July 1999
  • Quantum Computation: An Overview, Analogical Modeling of Language Group, Brigham Young University, July 1999
  • Quantum Computation: An Overview, Department of Computer Science, University of Massachusetts at Lowell, May 1999
  • Fourier Algorithms and Quantum Learning, Theoretical and Mathematical Physics Research Group, Brigham Young University, March 1998
  • A Genetic Algorithm - Neural Network Hybrid, Theoretical and Mathematical Physics Research Group, Brigham Young University, November 1998
  • Genetic Algorithms, Theoretical and Mathematical Physics Research Group, Brigham Young University, September 1996

Students

  • Kaivan Kamali, Masters of Computer Science and Engineering, May 2001 (with Soundar Kumara)
  • Rock Hymas, Bachelors of Science (CS) with Honors, April 2003
  • Mark Richards, Masters of Science (CS), April 2004
  • Nancy Owens, Masters of Science (CS), August 2004
  • Stephen Whiting, Masters of Science (CS), August 2004
  • Eric Goodman, Masters of Science (CS), April 2005
  • Jared Lundell, Bachelors of Science (CS), April 2006
  • Charles DuHadway, Bachelors of Science (CS), April 2006
  • Jeremy West, Bachelors of Science (CS), April 2007
  • Charlie Neo, Masters of Science (CS), December 2007
  • Heather Chan, Bachelors of Science (CS and Music Performance), April 2008
  • Rob Van Dam, Masters of Science (CS), April 2008
  • Ilya Raykhel, Masters of Science (CS), December 2008
  • Neil Toronto, Masters of Science (CS), April 2009
  • Kyle Dickerson, Masters of Science (CS), August 2009
  • Adam Drake, Doctor of Philosophy (CS), August 2010
  • Chris Wilson, Masters of Science (CS), August 2010
  • Chris Dalton, Bachelors of Science (CS), April 2011
  • Jeff Lund, Bachelors of Science (CS), April 2011
  • Craig Wilson, Bachelors of Science (EE), June 2012
  • Yemeng Zhu, Bachelors of Science (CS), June 2012
  • Skyler Murray, Masters of Science (CS), December 2012
  • Ryan Williamson, Undergraduate student
  • Rob Smith , Doctor of Philosophy (CS), June 2014
  • Daniel Johnson, Masters of Science (CS), August 2014
  • David Norton, Doctor of Philosophy (CS), December 2014
  • Derrall Heath , Doctor of Philosophy (CS), August 2016
  • Aaron Dennis, Doctor of Philosophy (CS), December 2016
  • Martin Mumford, MS student
  • Aaron Monson, BS student
  • Weixiang Ding, Bachelors of Science (CE), Sun Yat-Sen University, June 2015
  • Nathan Pocta, BS student, Clemson University
  • Paul Bodily, PhD student
  • Robert Pottorff, BS student
  • Ben Bay, BS student
  • Jacob O'Bryant, BS student
  • Drew Jex, BS student
  • Eric Sorensen, BS student
  • Michael Dubose, BS student
  • Ben Kingsley, BS student
  • Matthew Linford, BS student

Professional Activities

  • Secretary, Association for Computational Creativity, 2015-present
  • Senior Program Committee, Eighth International Conference on Computational Creativity, 2017
  • Reviewer, Artificial Intelligence and Statistics Conference, 2017
  • Reviewer, ACM CHI Conference on Human Factors in Computing Systems, 2017
  • Program Committee, 6th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), 2017
  • Program Committee, AISB Symposium on Computational Creativity, 2017
  • Program Committee, International Workshops on Computational Creativity, Concept Invention and General Intelligence (C3GI) 2016
  • Program Committee, 20th International Conference on Theory and Practice of Digital Libraries 2016
  • Program Committee, Computational Creativity & Games Workshop (CCGW) 2016
  • Panelist, National Science Foundation, 2016
  • Program Committee, AISB Symposium on Computational Creativity, 2016
  • Program Committee, 4th International Workshop on Musical Metacreation, 2016
  • Reviewer, Neural Information Processing Systems, 2016
  • Program Committee, PAAMS Workshop on Computational Models of Social Creativity, 2016
  • Senior Program Committee, Seventh International Conference on Computational Creativity, 2016
  • Program Committee, 5th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), 2016
  • Reviewer, Neural Information Processing Systems, 2015
  • Panelist, National Science Foundation, 2015
  • Program Committee, 21st International Symposium on Electronic Art, 2015
  • Program Committee, International Joint Conference on Artificial Intelligence, AI & The Arts Track , 2015
  • Local Chair, 6th International Conference on Computational Creativity, 2015
  • Program Committee, 6th International Conference on Computational Creativity, 2015
  • Program Committee, 4th International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), 2015
  • Program Committee, AISB Symposium on Computational Creativity, 2015
  • Program Committee, 3rd International Workshop on Musical Metacreation, 2014
  • Reviewer, Neural Information Processing Systems, 2014
  • General Chair, 5th International Conference on Computational Creativity, 2014
  • Program Committee, 3rd International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), 2014
  • Program Committee, AISB Symposium on Computational Creativity, 2014
  • Program Committee, NIPS Workshop on Constructive Machine Learning, 2013
  • Reviewer, Neural Information Processing Systems, 2013
  • Program Committee, 2nd International Workshop on Musical Metacreation, 2013
  • Program Committee, ACM Creativity and Cognition, 2013
  • Program Committee, 4th International Conference on Computational Creativity, 2013
  • Program Committee, 13th Ibero-American Conference on Artificial Intelligence (IBERAMIA), 2012
  • Program Committee, 1st International Workshop on Musical Metacreation, 2012
  • Program Committee, 1st International Conference on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), 2012
  • Senior Program Committee, Third International Conference on Computational Creativity, 2012
  • Program Committee, ACM Creativity and Cognition, 2011
  • Program Chair, Second International Conference on Computational Creativity, 2011
  • Panelist, National Science Foundation, 2010
  • Technical Program Committee, International Conference on Pattern Recognition, 2010
  • Program Chair, First International Conference on Computational Creativity, 2010
  • Program Committee, Australasian Workshop on Computational Creativity, 2009
  • Program Committee, ACM Creativity and Cognition, 2009
  • Technical Committee, International Joint Conference on Neural Networks, 2009
  • Panelist, Marsden Fund, 2008
  • Program Committee, International Joint Workshop on Computational Creativity, 2008
  • Technical Committee, International Joint Conference on Neural Networks, 2008
  • Technical Committee, IEEE Conference on Evolutionary Computation, 2008
  • Program Committee, IEEE Conference on Soft Computing in Industrial Applications, 2008
  • Chair, Creative Intelligent Systems, 2008 AAAI Spring Symposium Series (with Mary Lou Maher and Simon Colton)
  • Panelist (twice), National Science Foundation, 2007
  • Technical Committee, IEEE Conference on Evolutionary Computation, 2007
  • Technical Committee, International Joint Conference on Neural Networks, 2007
  • Program Committee, IEEE Three-Rivers Workshop on Soft Computing in Industrial Applications 2007
  • Area Editor, New Mathematics and Natural Computation, 2005-2006
  • Program Committee, International Symposium on Neural Networks, 2006
  • Program Committee, IEEE Mountain Workshop on Adaptive and Learning Systems 2006
  • Technical Committee, IEEE Conference on Evolutionary Computation, 2006
  • Technical Committee, International Joint Conference on Neural Networks, 2006
  • Program Committee, IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications, 2005
  • Program Co-Chair, International Conference on Computational Intelligence in conjunction with the Joint Conference on Information Sciences, 2005
  • Technical Committee, International Joint Conference on Neural Networks, 2005
  • Program Committee, International Conference on Neural Information Processing, 2004
  • Program Co-Chair, International Conference on Computational Intelligence in conjunction with the Joint Conference on Information Sciences, 2003
  • Participant, Faculty Development Series, Faculty Center, Brigham Young University, Fall 2001-Spring 2003
  • Program Chair, International Conference on Computational Intelligence in conjunction with the Joint Conference on Information Sciences, 2002
  • Certificate, The Penn State Course in College Teaching, Center for Excellence in Learning and Teaching, Penn State University, Fall 2000
  • Panelist, National Science Foundation, 2000, 2007, 2010
  • Member, Association for Intelligent Machinery
  • Guest Editor, Information Sciences Special Issue on Quantum and Neuro-quantum Information Processing, October 2000
  • Common Control Language Working Group Lead, Second Very Shallow Water/Surf Zone Mine Counter Measures Program Meeting, Panama City, Florida, December 1999
  • Organizer, Special sessions on Quantum Computation and Neuro-Quantum Information Processing, International Conference on Computational Intelligence and Neuroscience, February 2000
  • Organizing Committee, International Workshop on Quantum Neural Networks, Second Annual All-Russian Conference on Neuroinformatics, January 2000
  • Member, International Neural Network Society
  • Invited Speaker, International Conference on Computational Intelligence and Neuroscience special session on Neuro-Quantum Information Processing, October 1998
  • Program Committee, International Conference on Computational Intelligence and Neuroscience, October 1998
  • Program Committee, International Conference on Computational Intelligence and Neuroscience, March 2000

Committee Assignments

  • Faculty Expectations Review Committee Chair, Computer Science Department, Brigham Young University, 2016-
  • Associate Chair, Computer Science Department, Brigham Young University, 2014-
  • Faculty Search Committee Chair, Computer Science Department, Brigham Young University, 2014-
  • Member, Raises Committee, Computer Science Department, Brigham Young University, 2013-2014
  • Member, Promotion, Tenure and Leave Committee, Computer Science Department, Brigham Young University, 2013-2014
  • Member, PhD Recruiting Committee, Computer Science Department, Brigham Young University, 2013-2014
  • Graduate Coordinator, Computer Science Department, Brigham Young University, 2011-2012
  • Member, External Relations Committee, Computer Science Department, Brigham Young University, 2010-2011
  • Member, Undergraduate Committee, Computer Science Department, Brigham Young University, 2010-2011
  • Member, Computing Committee, Computer Science Department, Brigham Young University, 2009-2010
  • Chair, Graduate Admissions Committee, Computer Science Department, Brigham Young University, 2008-2010
  • Chair, Faculty Search Committee, Computer Science Department, Brigham Young University, 2007-2009
  • Member, Graduate Committee, Computer Science Department, Brigham Young University, 2006-2010
  • Chair, Colloquium Committee, Computer Science Department, Brigham Young University, 2005-2007
  • Member, CSR Search Committee, Computer Science Department, Brigham Young University, 2006
  • Member, Faculty Expectations Committee, Computer Science Department, Brigham Young University, 2004-2005
  • Member, Faculty Search Committee, Computer Science Department, Brigham Young University, 2003-2007
  • Chair, PhD Recruiting Committee, Computer Science Department, Brigham Young University, 2002-2005
  • Member, Graduate Committee, Computer Science Department, Brigham Young University, 2001-2003