I conduct research in Data Science broadly interpreted. I aim to advance both statistical and computational tools for learning and inference problems using both model-based and data-driven methods. My research work spans the areas of Network Information Theory, Information-Theoretic Security, Statistical Signal Processing & Machine Learning, and Visual Information Processing & Analysis. Below are some representative publications in each area that capture the flavor and style of my research work which ranges from theoretical foundations through algorithm development/ analysis, and applications.

I develop solutions for both specific problems based on specific types of data as well as general statistical models and algorithms with efficiency guarantees that can be broadly used in many problems with different types of data.

Examples of the former include computer algorithms for automatically recognizing human gestures and actions as well as algorithms for authenticating human identity from signature-gestures, both based on visual data, e.g., video from cameras and depth video from a Kinect camera. A more detailed description of my research in Visual Information Processing & Analysis can be found here: VIP Laboratory.

An example of the latter is a new statistical model and algorithm that my research group developed for discovering hidden causes with mathematically provable performance guarantees, e.g., guarantees on computational, statistical, and communication efficiency. We have used this algorithm, with considerable success, on a publicly available dataset of NY Times articles to automatically discover shared hidden topics among the articles, and on the MovieLens dataset to learn and predict the movie preference behavior (movie ratings and relative rankings) of users. We have also successfully used a topic-discovery algorithm to automatically discover salient discussion topics in a corpus of 77 million tweets collected during the 2012 US presidential election.

A complete list of all my publications can be found under the Publications tab of this website.

Network Information Theory:

• N. Ma and P. Ishwar, “The Infinite-Message Limit of Two-Terminal Interactive Source Coding,” IEEE Transactions on Information Theory, vol. 59, no. 7, pp. 4071-4094, Jul. 2013.
• N. Ma, P. Ishwar, and P. Gupta,“Interactive Source Coding for Function Computation in Collocated Networks,” IEEE Transactions on Information Theory, vol. 58, pp. 4289-4305, Jul. 2012.
• N. Ma and P. Ishwar,“Some results on distributed source coding for interactive function computation,” IEEE Transactions on Information Theory, vol. 57, pp. 6180-6195, Sep. 2011.
• N. Ma and P. Ishwar,“On delayed sequential coding of correlated sources,” IEEE Transactions on Information Theory, vol. 57, pp. 3763-3782, Jun. 2011.
• P. Ishwar and S. S. Pradhan,“A relay-assisted distributed source coding problem,” in Proc. 3rd IEEE International Workshop on Information Theory and Applications (ITA), San Diego, CA, 27 Jan. – 1 Feb., 2008, pp. 136-141. [Invited paper]
• P. Ishwar, R. Puri, K. Ramchandran, and S. S. Pradhan,“On rate-constrained distributed estimation in unreliable sensor networks,” IEEE Journal on Selected Areas in Communications, Special issue on Self-Organizing Distributed Collaborative Sensor Networks, vol. 23, pp. 765-775, Apr. 2005.

Information-Theoretic Security:

• Y. O. Basciftci, Y. Wang, and P. Ishwar, “On Privacy-Utility Tradeoffs for Constrained Data Release Mechanisms,” in Proc. 11th IEEE International Workshop on Information Theory and Applications (ITA), San Diego, CA, 31 Jan. – 5 Feb., 2016. [Invited paper]
• Y. Wang, P. Ishwar, and S. Rane, “An Elementary Completeness Proof for Secure Two-Party Computation Primitives,” in Proc. IEEE International Information Theory Workshop (ITW), Tasmania, Australia, 2-5 Nov., 2014, pp. 521-525. [arXiv version]
  
• Y. Wang, S. Rane, and P. Ishwar, “On Unconditionally Secure Multiparty Computation for Realizing Correlated Equilibria in Games,” in Proc. IEEE Global Conference on Signal and Information Processing (GlobalSIP), Symposium on Cyber-Security and Privacy, Austin, TX, USA, 3-5 Dec., 2013,  pp. 241-244. [arXiv version]
  
• S. Rane, Y. Wang, S.C. Draper, and P. Ishwar, “Secure Biometrics: Concepts, Authentication Architectures and Challenges,” IEEE Signal Processing Magazine, Special Issue: Signal Processing for Cyber-security and Privacy, vol. 30, no. 5, pp. 51-64, Sep. 2013.
• Y. Wang, P. Ishwar, and S. Rane, “Information-Theoretically Secure Three-Party Computation with One Corrupted Party,” in Proc. IEEE International Symposium on Information Theory, Istanbul, Turkey, 7-12 Jul., 2013, pp. 3160-3164.
• Y. Wang, S. Rane, S. C. Draper, and P. Ishwar, “A Theoretical Analysis of Authentication, Privacy and Reusability Across Secure Biometric Systems,” IEEE Transactions on Information Forensics and Security, vol. 7, no. 6, pp. 1825-1840, Dec. 2012.
• Y. Wang and P. Ishwar,“On unconditionally secure multi-party sampling from scratch,” in Proc. IEEE International Symposium on Information Theory, Saint Petersburg, Russia, 31 Jul. – 5 Aug., 2011, pp. 1782-1786 [ISIT 2011 student paper award finalist].
• Y. Wang, S. Rane, W. Sun, and P. Ishwar,“On unconditionally secure computation with vanishing communication cost,” in Proc. 48th Annual Allerton Conference on Communication, Control, and Computing,Monticello, IL, 29 Sep. – 1 Oct., 2010, pp. 944-950.
• Y. Wang and P. Ishwar,“Bootstrapped oblivious transfer and secure two-party function computation,” in Proc. IEEE International Symposium on Information Theory (ISIT), Coex, Seoul, Korea, 28 Jun. – 3 Jul., 2009, pp. 1303-1307.
• S. Draper, P. Ishwar, D. Molnar, V. Prabhakaran, K. Ramchandran, D. Schonberg, and D. Wagner, “An evaluation of PMF-based tests for detection of least significant bit image steganography,” in Proc. 7th International Workshop on Information Hiding (IH), Barcelona, Spain, 6-8 Jun., 2005, pp. 327-341.
• M. Johnson, P. Ishwar, V. M. Prabhakaran, D. Schonberg, and K. Ramchandran, “On compressing encrypted data,” IEEE Transactions on Signal Processing, Special supplement on Secure Media, vol. 52, part 2, pp. 2992-3006, Oct. 2004.

Statistical Signal Processing & Machine Learning:

• W. Ding, P. Ishwar, and V. Saligrama, “Necessary and Sufficient Conditions and a Provably Efficient Algorithm for Separable Topic Discovery,” IEEE Journal on Special Topics in Signal Processing (JSTSP), Special Issue on Structured Matrices in Signal and Data Processing, submitted 2015 (under review). [arXiv version].
• L. Guo, C. Vargo, Z. Pan, W. Ding, and P. Ishwar, “Big Social Data Analytics in Journalism and Mass Communication: Comparing Dictionary-based Text Analysis and Unsupervised Topic Modeling,” Journalism and Mass Communication Quarterly, submitted 2015 (under review).
• L. Martin, A. Tuysuzoglu, W. C. Karl, and P. Ishwar, “Learning-Based Object Identification and Segmentation using Dual-Energy CT Images for Security,” IEEE Transactions on Image Processing, vol. 24, no. 11, pp. 4069-4081, Nov. 2015.
• W. Ding, P. Ishwar, and V. Saligrama, “A Topic Modeling Approach to Ranking,” in Proc. International Conference on Artificial Intelligence and Statistics (AIStats), San Diego, CA, 9-12 May, 2015.
• W. Ding, P. Ishwar, and V. Saligrama, “Most Large Topic Models are Approximately Separable,” in Proc. 10th IEEE International Workshop on Information Theory and Applications (ITA), San Diego, CA, 1-6 Feb., 2015, pp. 199-203. [Invited paper] [pdf]
• W. Ding, P. Ishwar, and V. Saligrama, “A Topic Modeling Approach to Rank Aggregation,” in Advances in Neural Information Processing Systems (NIPS), Workshop on Analysis of Rank Data: Confluence of Social Choice, Operations Research, and Machine Learning, Montreal, Canada, 13 Dec., 2014. [Student Best Paper Award] [arXiv version]
• W. Ding, P. Ishwar, V. Saligrama, and W. C. Karl, “Sensing-aware Kernel SVM,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, 4-9 May, 2014, pp. 2947-2951. [arXiv version]
• W. Ding, M. H. Rohban, P. Ishwar, and V. Saligrama, “Efficient distributed topic modeling with provable guarantees,” in Proc. International Conference on Artificial Intelligence and Statistics (AIStats), Reykjavik, Iceland, 22-25 Apr., 2014.
• W. Ding, P. Ishwar, and V. Saligrama, “Dynamic Topic Discovery through Sequential Projections,” in Proc. Forty-Seventh Annual Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, 3-6 Nov., 2013, pp. 1100-1104.
• M.H. Rohban, P. Ishwar, B. Orten, W.C. Karl, and V. Saligrama, “An Impossibility Result for High Dimensional Supervised Learning,” in Proc. IEEE International Information Theory Workshop (ITW), Seville, Spain, 9-13 Sep., 2013, pp. 1-5. [arXiv version]
• W. Ding, M. H. Rohban, P, Ishwar, and V. Saligrama,“Topic Discovery through Data-Dependent and Random Projections,” in Proc. IEEE International Conference on Machine Learning (ICML), Atlanta GA, USA, 16-21 Jun., 2013, JMLR W&CP 28 (3): 1202–1210. [Oral presentation] [arXiv version]
• Z. Sun, P. Ishwar, W. C. Karl, and V. Saligrama,“Sensing aware dimensionality reduction for nearest neighbor classification of high dimensional signals,” in Proc. IEEE International Statistical Signal Processing (SSP) Workshop, Ann Arbor, MI, 5-8 Aug., 2012, pp. 405-408. [Special session on “Challenges in High-Dimensional Learning and Inference: Fundamental Limits and Algorithms”.]
• A. Kumar, P. Ishwar, and K. Ramchandran,“High-resolution distributed sampling of bandlimited fields with low-precision sensors,” IEEE Transactions on Information Theory, vol. 57, pp. 476-492, Jan. 2011.
• A. Kumar, P. Ishwar, and K. Ramchandran, “Dithered A/D conversion of smooth non-bandlimited signals,” IEEE Transactions on Signal Processing, vol. 58, pp. 2654-2666, May 2010.
• E. Masry and P. Ishwar, “Field estimation from randomly located, binary noisy sensors,” IEEE Transactions on Information Theory, vol. 55, pp. 5197-5210, Nov. 2009.
• Y. Wang and P. Ishwar,“Distributed field estimation using randomly deployed, noisy, binary sensors,” IEEE Transactions on Signal Processing, vol. 57, pp. 1177-1189, Mar. 2009.
• P. Ishwar, V. M. Prabhakaran, and K. Ramchandran, “On joint classification and compression in a distributed source coding framework,” in Proc. IEEE Statistical Signal Processing (SSP) Workshop, St. Louis, MO, 28 Sep. – 1 Oct., 2003, pp. 34-37. [Invited paper in the special session on compression for sensor networks]
• P. Ishwar and P. Moulin, “On the existence and characterization of the maxent distribution under general moment inequality constraints,” IEEE Transactions on Information Theory, vol. 51, pp. 3322-3333, Sep. 2005.
• P. Ishwar and P. Moulin, “On the equivalence of set-theoretic and maxent MAP estimation,” IEEE Transactions on Signal Processing, vol. 51, pp. 698-713, Mar. 2003.
• P. Ishwar and P. Moulin,“Shift invariant restoration – an overcomplete maxent MAP framework,” in Proc. IEEE International Conference on Image Processing (ICIP), Vancouver, Canada, 10-13 Sep., 2000, vol. 3, pp. 270-272.
• P. Ishwar, K. Ratakonda, P. Moulin, and N. Ahuja, “Image denoising using multiple compaction domains,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Seattle, WA, 12-15 May, 1998, vol. 3, pp. 1889-1892. [Invited paper in special session on the role of sparsity in signal processing]

Visual Information Analysis & Processing:

• J. Dai, J. Wu, B. Saghafi, J. Konrad, and P. Ishwar, “Towards Privacy-Preserving Activity Recognition Using Extremely Low Temporal and Spatial Resolution Cameras,” in the  Sixth IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG) at CVPR’15, Boston, MA, 12 Jun., 2015, pp. 68-76. [Project website]
• N. Goyette, P-M. Jodoin, F. Porikli, J. Konrad, and P. Ishwar, “A Novel Video Dataset for Change Detection Benchmarking,” IEEE Transactions on Image Processing, vol. 23, no. 11, pp. 4663-4679, Nov. 2014. [Project website]
• J. Wu, P. Ishwar, and J. Konrad, “The Value of Posture, Build and Dynamics in Gesture-Based User Authentication,” in Proc. IEEE International Joint Conference on Biometrics (IJCB), Clearwater, FL, 29 Sep. – 2 Oct., 2014, pp. 1-8. [Project website 1], [Project website 2]
• J. Konrad, M. Wang, P. Ishwar, C. Wu, and D. Mukherjee, “Learning-based, automatic 2D-to-3D image and video conversion,” IEEE Transactions on Image Processing, Special Issue on 3D Video Representation, Compression and Rendering, vol. 22, no. 9, pp. 3485-3496, Sep. 2013. [Project website]
• K. Guo, P. Ishwar, and J. Konrad, “Action Recognition from Video using Feature Covariance Matrices,”IEEE Transactions on Image Processing, vol. 22, no. 6, pp. 2479-2494, Jun. 2013. [AVSS 2010 Best Paper Award], [Winner of Aerial View Activity Classification Challenge, ICPR 2010, Semantic Description of Human Activities Contest, SDHA contest web site], [Project website]
• J. Wu, J. Konrad, and P. Ishwar, “Dynamic Time Warping for Gesture-based user Identification and Authentication with Kinect,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, 26-31 May, 2013, pp. 2371-2375.
• M. Wang, P. Ishwar, J. Konrad, C. Gazen, and R. Saboo, “Coherent image selection using a fast approximation to the generalized traveling salesman problem,” in Proc. 20th ACM International Conference on Multimedia (MM), Nara, Japan, 29 Oct.-2 Nov, 2012, pp. 981-984.
• K. Lai, J. Konrad, and P. Ishwar, “GestureMouse: A Flexible Gesture-Based User Interface,” in the ChaLearn Gesture Challenge Demonstration Competitionat CVPR’12, Providence, RI, 16-21 Jun., 2012. [Project website]
• M. Wang, J. Konrad, P. Ishwar, Y-K. Jing, and H. Rowley, “Image saliency: from intrinsic to extrinsic context,” in Proc. IEEE International Conference on Computer Vision and Pattern Recognition (CVPR),Colorado Springs, CO, 21-23 Jun., 2011, pp. 417-424.
• Z. Li, P. Ishwar, and J. Konrad, “Video condensation by ribbon carving,”IEEE Transactions on Image Processing, vol. 18, pp. 2572-2583, Nov. 2009. [Project website]
• R. Puri, A. Majumdar, P. Ishwar, and K. Ramchandran, “Distributed Video Coding in Broadband Wireless Sensor Networks,”IEEE Signal Processing Magazine, Special Issue on Distributed Signal Processing in Sensor Networks, vol. 23, no. 4, pp. 94-106, Jul. 2006.
• P. Ishwar and P. Moulin,“On spatial adaptation of motion field smoothness in video coding,”IEEE Transactions on Circuits and Systems for Video Technology, vol. 10, pp. 980-989, Sep. 2000.