| Department of Computer Science |
| 33 Colchester Ave. |
| University of Vermont |
| Burlington, VT 05405, USA |
Associate Professor of Computer Science with a secondary appointment in Mathematics and Statistics, University of Vermont, Burlington, VT 05405. Aug. 1996 – present.
Assistant Professor of Electrical Engineering, University of Vermont, Burlington, VT 05405. Aug. 1990 – Aug. 1996.
Research Fellow, Electrical Engineering Department, California Institute of Technology, Pasadena, California, 91125. Mar. 1987 – Mar. 1990.
Research Assistant, Physics Department, University of Texas, Austin, Texas, 78712. Jan. 1985 – Dec. 1986
Mathematics Instructor, Austin Community College, 1212 Rio Grande, Austin, Texas, 78701. Sept. 1980 – May 1984.
Teaching Assistant, Physics Department, University of Texas, Austin, Texas, 78712. Sept. 1978 – Dec. 1980.
Visiting Faculty, Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, July to August 2000.
Visiting Associate Professor of Electrical Engineering, The Technion, Haifa Israel, September 1998 to June 1999.
Visiting Scientist, Rome Laboratories, Rome, NY, June to August 1992.
Visiting Scientist, Rome Laboratories, Rome, NY, June to August 1991.
Visiting Scientist, IBM Burlington, Essex Junction, VT, July to August, 1990.
Ph.D. in Physics, The Univeristity of Texas at Austin. Dissertation Title: A Stability Analysis of a Nonlinear Optical Ring Cavity, December 1986.
A.B. in Physics, Revelle College, University of California at San Diego, June 1978.
Gary W. Johnson, Kenneth J. Bagstad, Robert R. Snapp, and Ferdinando Villa, “Service Path Attribute Networks (SPANs): A network flow approach to ecosystem service assessment”, International Journal of Agricultural and Environmental Information Systems (to appear).
Lingbo Yu, Robert R. Snapp, Theresa Ruiz, Michael Radermacher, “Probabilistic Principal Component Analysis with Expectation Maximization (PPCA-EM) Facilitates Volume Classification and Estimates the Missing Data”, Journal of Structural Biology, 171, 2010, pp. 18–30.
Helene M. Langevin , Kirsten N. Storch, Robert R. Snapp, Nicole A. Bouffard, Gary J. Badger, Douglas J. Taatjes, “Tissue stretch induces nuclear remodeling in connective tissue fibroblasts”, Histochemistry and Cell Biology, vol. 133 (4), 2010, pp. 405–415.
R. Costanza, B. Fisher, S. Ali, C. Beer, L. Bond, R. Boumans, N. L. Danigelis, J. Dickinson, C. Elliott, J. Farley, D. E. Gayer, L. MacDonald Glenn, T. Hudspeth, D. Mahoney, L. McCahill, B. McIntosh, B. Reed, S. A. T. Rizvi, D. M. Rizzo, T. Simpatico, and R. Snapp, “An integrative approach to quality of life measurement, research, and policy”, Surveys and Perspectives Integrating Environment and Society, 1 (1), 2008, pp. 11–15.
Robert Costanza, Brendan Fisher, Saleem Ali, Caroline Beer, Lynne Bond, Roelof Boumans, Nicholas L. Danigelis, Jennifer Dickinson, Carolyn Elliott, Joshua Farley, Diane Elliott Gayer, Linda MacDonald Glenn, Thomas Hudspeth, Dennis Mahoney, Laurence McCahill, Barbara McIntosh, Brian Reed, S. Abu Turab Rizvi, Donna M. Rizzo, Thomas Simpatico, and Robert Snapp, “Quality of Life: An Approach Integrating Opportunities, Human Needs, and Subjective Well-Being”, Ecological Economics, 61, 2007, pp. 267–276.
Zhen He, Byung S. Lee, and Robert R. Snapp, “Self-Tuning Cost Modeling of User-Defined Functions in an Object-Relational DBMS,” ACM Transactions on Database Systems, vol. 30, issue 3, 2005, pp. 812–853.
B. Lee, T. Critchlow, G. Abdulla, C. Baldwin, R. Kamimura, R. Musick, R. Snapp, and N. Tang, “The Framework for Approximate Queries on Simulation Data,” International Journal of Information Sciences, vol. 157, 2003, pp. 3–20.
Byung S. Lee, Robert R. Snapp, Ron Musick, and Terence Critchlow, “Metadata Models for Ad Hoc Queries on Terabyte-Scale Scientific Simulations”, Journal of the Brazilian Computer Society, vol. 8, no. 1, July 2002, pp. 9–22.
R. R. Snapp and S. S. Venkatesh, “Asymptotic series representations of the finite-sample risk of k nearest neighbor classifiers”, Annals of Statistics, vol. 26, no. 3, 1998, pp. 850–878.
Kenneth I. Golden, G. Kalman, Limin Miao, and Robert R. Snapp, “Retardation effects on collective excitations in correlated superlattices”, Physical Review B, 57 1998, pp. 9883–9893.
Kenneth I. Golden, G. Kalman, Limin Miao, and Robert R. Snapp, “Plasmon and shear modes in correlated superlattices”, Physical Review B, 55, 1997, pp. 16,349–16,358.
D. Psaltis, R. R. Snapp, and S. S. Venkatesh, “On the finite sample performance of the nearest neighbor classifier”, IEEE Transactions on Information Theory 40, 1994, pp. 820–837.
C. Ji, R. R. Snapp, D. Psaltis, “Generalizing smoothness constraints from discrete samples”, Neural Computation 2, 1990, pp. 188–197.
R. R. Snapp and W. C. Schieve, “Singular perturbation analysis of the mean-field limit of semiclassical optics”, Physical Review A, 41 1990, pp. 421–425.
H. J. Carmichael, R. R. Snapp, and W. C. Schieve, “Oscillatory instabilities leading to `optical turbulence’ in a bistable ring cavity”, Physical Review A 26, 1982, pp. 3408–3422.
R. R. Snapp, H. J. Carmichael, and W. C. Schieve, “The path to `turbulence:’ optical bistability and universality in the ring cavity.” Optics Communications, 40, 1981, pp. 68–72.
John T. Evans, Robert R. Snapp, Gagan Mirchandani, Richard M. Foote, “Using wavelets for fast Monte Carlo simulation of Ising systems with distribution matching”, Procedings of the 2011 IEEE/SP 17th Workshop on Statistical Signal Processing, 2011, pp. 313–316.
Gary W. Johnson, Kenneth J. Bagstad, Robert R. Snapp, Ferdinando Villa, “Service Path Attribution Networks (SPANs): Spatially Quantifying the Flow of Ecosystem Services from Landscapes to People”, Computational Science and Its Applications (ICCSA 2010), Lecture Notes in Computer Science, 6016, 2010, pp. 238–253.
Gagan Mirchandani, John T. Evans, Robert R. Snapp, Richard Foote, “Looking through wavelets to the Ising problem”, Procedings of the 2009 IEEE/SP 15th Workshop on Statistical Signal Processing, 2009, pp. 777–780.
Duane C. Compton and Robert R. Snapp, “Detecting trace components in liquid chromatography/mass spectrometry data sets with two-dimensional wavelets”, Proceedings of SPIE: Wavelet Applications in Industrial Processing V, Boston, August 2007.
Robert R. Snapp, “A PuzzlesFirst Approach to Computer Science”, Proceedings of the 11th annual SIGSCE conference on Innovation and Technology in Computer Science Education (ITiCSE06), 2006, p. 310; also appears in ACM SIGCSE Bulletin, vol. 38, issue 3, 2006, p. 310.
Robert R. Snapp, “Teaching Graph Algorithms in a Corn Maze”, Proceedings of the 11th annual SIGSCE conference on Innovation and Technology in Computer Science Education (ITiCSE06), 2006, p. 347; also appears in ACM SIGCSE Bulletin, vol. 38, issue 3, 2006, p. 347.
Xianhua Jiang, Robert R. Snapp, Yuichi Motai, and Xingquan Zhu, “Accelerated Kernel Feature Analysis”, Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), vol. 1, pp. 109–116.
Zhen He, Byung S. Lee, Robert R. Snapp, “Self-tuning UDF Cost Modeling Using the Memory Limited Quadtree”, Proceedings of the 9th International Conference on Extending Database Technology (EDBT), Heraklion, Crete, Greece, March 14–18, 2004. (This paper is also known as UVM, CS Technical Report CS–03–18.)
Robert R. Snapp, “Local Polynomial Metrics for k Nearest Neighbor Classifiers”, in Joab Winkler and Mahesan Niranjan, ed., Uncertainty in Geometric Computations, Kluwer, Boston, 2002, pp. 155–164.
Byung S. Lee, Robert R. Snapp, and Ron Musick, “Ad hoc query support for very large scientific data: the metadata approach”, Proceedings of the 16th Brazilian Symposium on Databases (SBBD), 2001.
G. Abdulla, C. Baldwin, T. Critchlow, R. Kammimura, I. Lozares, R. Musick, N. Tang, B. Lee, and R. Snapp, “Approximate ad hoc query engine for simulation data”, Proceedings of the First ACM and IEEE Joint Conference on Digital Libraries (JCDL), 2001, pp. 255–256.
Byung S. Lee, Robert R. Snapp, and Ron Musick, “Towards a query language on simulation mesh data: an object-oriented approach”, Proceedings of the International Conference on Database Systems and Advanced Applications (DASFAA), 2001.
Omri Guttman, Ron Meir, and Robert R. Snapp, “Nonlinear Fisher Discriminant using Mercer Kernels”, Proceedings of Neural Computation in Science and Technology, (NCST–99) Oct. 10–13, 1999.
Alessandro Palau and Robert R. Snapp, “The labeled cell classifier”, in Anil K. Jain, Svetha Venkatesh, and Brian C. Lovell, etc., Proceedings of the 14th International Conference on Pattern Recognition, IEEE Computer Society Press, 1998, pp. 823–827.
Robert R. Snapp and Tong Xu, “Estimating the Bayes Risk from Sample Data”, in D. S. Touretzky, M. C. Mozer, and M. E. Hasselmo, ed., Advances in Neural Information Processing Systems 8, MIT Press, 1996, pp. 232–238.
Robert R. Snapp, “Predicting the accuracy of Bayes classifiers”, in K. M. Hanson and R. N. Silver, ed., Maximum Entropy and Bayesian Methods, Sante Fe, New Mexico, U.S.A., 1995 Kluwer Academic Publishers, Dordrecht, Netherlands, 1996, pp. 295–302.
Robert R. Snapp and Santosh S. Venkatesh, “k Nearest Neighbors in Search of a Metric”, Proceedings of the 1995 IEEE International Symposium on Information Theory, Whistler, BC, Canada, 1995, p. 256.
Robert R. Snapp and Santosh S. Venkatesh, “Asymptotic Predictions of the finite-sample risk of the k-nearest-neighbor classifier”, in Proceedings of the 12th International Conference on Pattern Recognition, (Jerusalem, Israel), vol. 2, IEEE Computer Society Press: Los Alamitos, CA, 1994, pp. 1–7.
Robert R. Snapp and Santosh S. Venkatesh, “The Finite-Sample Risk of the k-Nearest-Neigbhbor Classifier under the Metric”, Proceedings of the 1994 IEEE-IMS Workshop on Information Theory and Statistics, Alexandria, VA, 1994, p. 98.
Demetri Psaltis, Robert R. Snapp and Santosh S. Venkatesh, “On the finite-sample performance of the nearest-neighbor classifier”, Proceedings of the 1993 IEEE International Symposium on Information Theory, San Antonio Texas, 1993, p. 354.
Santosh S. Venkatesh, Robert R. Snapp, and Demetri Psaltis, “Bellman Strikes Again: The rate of growth of sample complexity with dimension for the nearest neighbor classifier”, Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory (COLT), 1992, pp. 93–102.
John C. Englund, Robert F. Gragg, William C. Schieve, and Robert R. Snapp, `Fluctuations and instabilities in laser-like systems”, Peralta Fabi, ed., Proc. 1st Escuela Mexicana de Fisica Estadstica, Soc. Mex. Fisica, 1983.
Lingbo Yu, Robert Snapp, Michael Radermacher, “ Probabilistic Principal Component Analysis with Expectation Maximization (PPCA-EM) Facilitates Volume Classification and Estimates the Missing Data”, 66th Annual Meeting of the Microscopy Society of America, 2010.
Lingbo Yu, Robert Snapp, Michael Radermacher, “Multivariate Statistical Analysis of Volumes with Missing Data” 35th Annual Meeting of the Microscopical Society of Canada, 2008.
IPToolkit is a C++ library developed at Rome Laboratory in 1993.
nuclearSlice is a C++ program that computes a concavity index for images of cell nuclei in laser scanning confocal microscope images.
blobify is a clojure program that is currently being written to construct component trees of chromatin clusters in three-dimensional image stacks of cell nuclei.
Jonathan Parker, “Reinforcement Learning and Poker”, B.S. in Computer Science, University of Vermont, May 2008.
Samuel Brown, TBA, B.S. in Computer Science, University of Vermont, expected May 2012.
Ross Deming, “Neural Networks for Selective Edge Detection”, M.S. in Electrical Engineering, University of Vermont, October 1993.
Tong Xu, “Estimating the Infinite-Sample Risk for the k Nearest Neighbor Classifier”, M.S. in Electrical Engineering, University of Vermont, October 1995.
Xinguan Li, “Controlling Traffic Signals at Isolated Intersections using Q-Learning”, M.S. in Electrical Engineering, University of Vermont, October 1997.
Chaoyu Jin, “The Dependence of Approximation Error on the Sample Size for Feedforward Neural Networks”, M.S. in Electrical Engineering, University of Vermont, October 1997.
Gabriel Kontrovitz, “Real-Time Three-Dimensional Line-Art Rendering”, M.S. in Computer Science, University of Vermont, May 2000.
Dan Nardi, “Finding Every Occurrence of a Given Device in a VLSI Layout”, M.S. in Computer Science, University of Vermont, February 2004.
Duane Compton, “TWiGS: A New Algorithm for Denoising Liquid-Chromatogrphic-Mass-Spectrometric Data”, M.S. in Computer Science, University of Vermont, May 2008.
John T. Evans III, “A Wavelet-based Accelerated Monte Carlo Algorithm for Multiscale Simulation of the Ising Model”, M.S. in Electrical Engineering, University of Vermont, October 2010, (co-advisor with Richard Foote and Gagan Mirchandani).
Alessandro Palau, Implementing Nearest Neighbor Classifiers, Ph.D. in Electrical Engineering, University of Vermont, May 1997.
Gary W. Johnson, TBA, Ph.D. in Computer Science, University of Vermont, expected May 2012, (co-advisor with Ferdinando Villa).
Lingbo Yu, TBA, Ph.D. in Computer Science, University of Vermont, expected May 2012, (co-advisor with Michael Radermacher).