Predrag V. Neskovic Adjunct Associate Professor of Brain and Neural Systems

I received my B.Sc. in theoretical physics from Belgrade University and a Ph.D. in physics from Brown University. I was a post-doc and then a faculty at the Institute for Brain and Neural Systems. I moved to Washington, DC in 2008 where I currently work in the Federal Government as a program manager covering the area of Mathematical Data Science.  

Brown Affiliations

Research Areas

scholarly work

P. Neskovic, I. Sherman, L. Wu, L. N Cooper. Learning faces with the BIAS model: On the importance of the sizes and locations of fixation regions, Neurocomputing 72(13-15): 2915-2922, 2009.

J. Wang, P. Neskovic, and L. N. Cooper. Selecting Data for Fast Support Vector Machine Training. Studies in Computational Intelligence, Vol. 35, pp. 61-84, 2007.

J. Wang, P. Neskovic, and L. N. Cooper. Improving Nearest Neighbor Rule with a Simple Adaptive Distance Measure. Pattern Recognition Letters, 28(2), pp. 207-213, 2007.

J. Wang, P. Neskovic and L. N. Cooper. Bayes Classification Based on Minimum Bounding Spheres. Neurocomputing, Vol. 70, pp. 801-808, 2007.

J. Wang and P. Neskovic and L. N. Cooper. A minimum Sphere Covering Approach to Pattern Classification. ICPR, pp. 433-436, 2006.

J. Wang and P. Neskovic and L. N. Cooper. Neighborhood Size Selection in the k-Nearest Neighbor Rule Using Statistical Confidence. Pattern Recognition, 39(3), pp. 417-423, 2006.

P. Neskovic, L. Wu and L. N. Cooper. Learning by Integrating Information Within and Across Fixations. Lecture Notes In Computer Science: Artificial Neural Networks - ICANN, Vol. 4132, pp. 488-497, 2006.

J. Wang and P. Neskovic and L. N. Cooper. A Probabilistic Model For Cursive Handwriting Recognition Using Spatial Context. ICASSP, 2005.

T. Steinherz, E. Rivlin, N. Intrator, and P. Neskovic. An Integration of Online and Pseudo-Online Information for Cursive Word Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI, 27(5), pp. 669-684, 2005.

P. Neskovic, D. Schuster and L. N Cooper. Biologically inspired recognition system for car detection from real-time video streams. Neural Information Processing: Research and Development, J. C. Rajapakse and L. Wang (eds.), Springer-Verlag, pp. 320-334, 2003.

P. Neskovic, P. C. Davis and L. N. Cooper. Interactive Parts Model: an Application to Recognition of On-line Cursive Script. Advances in Neural Information Processing Systems (NIPS), pp. 974-980. 2000.

research overview

My research interests are mainly in the fields of statistical pattern recognition, machine learning, and biologically inspired vision. 

funded research

"Using advanced mathematical techniques to analyze physiological responses to stimulation of specific acupoints." The Rhode Island Foundation, PI, 2007.

"Using physiological measurements and artificial neural networks to monitor and predict cognitive states." Research Seed Fund Award, Brown University, PI (with William Heindel), 2005-2006.

"Visual analysis of complex scenes: breaking camouflage and detecting occluded objects using Bayesian inference." Army Research Office (ARO), W911NF-04-1-0357, Co-PI (with Leon Cooper), 2004-2009.

"Reducing the cognitive workload while operating in complex sensory environments: constructing a recognition system that utilizes aspects of human perception and cognition." ARO, DAAD19-01-1-0754, Co-PI (with Leon Cooper), 2001-2004.