PhD Dissertation
Journals

B. Matthews, S. Das, K. Bhaduri, K. Das, R. Martin, N. Oza. Discovering Anomalous Aviation Safety Events using Scalable Data Mining Algorithms. Journal of Aerospace Information Systems. Volume 10 Number 10, pp. 467475. October 2013. [pdf]

K. Das, A. N. Srivastava. Sparse InverseKernel Gaussian Process Regression. Statistical Analysis and Data Mining Journal. Volume 6 Issue 3, pp. 205220. June 2013. [pdf]

K. Das, K. Bhaduri, P. Votava. Distributed Anomaly Detection using 1class SVM for Vertically Partitioned Data. Statistical Analysis and Data Mining Journal. Volume 4 Issue 4, pp. 393406 August 2011. [pdf]

K. Bhaduri, K. Das, K. Borne, C. Giannella, T. Mahule, H. Kargupta. Scalable, Asynchronous, Distributed EigenMonitoring of Astronomy Data Streams. Statistical Analysis and Data Mining Journal. Volume 4, Issue 3, pp. 336352, June 2011. [pdf]

K. Das, K. Bhaduri, H. Kargupta. Multiobjective Optimization Based Privacy Preserving Distributed Data Mining in Peertopeer Networks. PeertoPeer Networking and Applications. Volume 4, Issue 2, pp. 192209. 2011. [pdf]

K. Das, K. Bhaduri, H. Kargupta. A Local Asynchronous Distributed Privacy Preserving Feature Selection Algorithm for Large PeertoPeer Networks. Knowledge and Information Systems Journal. Volume 24, Issue 3, pp. 341367. September 2010. [pdf]
 K. Das, K. Bhaduri, K. Liu, H. Kargupta. Distributed Identification of Topl Inner Product Elements and its Application in a PeertoPeer Network. IEEE Transactions on Knowledge and Data Engineering. Volume 20, Issue 4, pp. 475488, April 2008. [pdf]
 K. Liu, K. Bhaduri, K. Das, P. Nguyen, H. Kargupta. Clientside Web Mining fo Community Formation in PeertoPeer Environments. SIGKDD Explorations. Volume 8, Issue 2, pp. 1120. December 2006. [pdf]
Conferences and Workshops
 A. Asanjan, K. Das, A. Li, V. Chirayath, J. TorresPerez, S. Sorooshian. Learning Instrument Invariant Characteristics for Generating Highresolution Global Coral Reef Maps. ACM SIGKDD (KDD) 2020, Accepted. 2020. [pdf].
 A. Kodali, M. Szubert, K. Das, S. Ganguly, J. Bongard. Understanding climatevegetation interactions in global rainforests through a GPtree analysis. Parallel Problem Solving in Nature (PPSN) 2018, pp 525536. 2018. [pdf].
 A. Basak, K. Das, O. Mengshoel. CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences. arXiv preprint arXiv:1802.05421. 2018.
 K. Das, I. Avrekh, B. Matthews, M. Sharma, N. Oza. ASKtheExpert: Active learning based knowledge discovery using the expert. ECMLPKDD 2017, pp. 395399, Skopje, Macedonia. [pdf].
 M. Sharma, K. Das, M. Bilgic, B. Matthews, D. Nielsen, N. Oza. Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation. ECMLPKDD 2016, pp. 209225, Riva del Garda, Italy. [pdf].
 M. Szubert, A. Kodali, S. Ganguly, K. Das, J. Bongard. Semantic Forward Propagation for Symbolic Regression, PPSN 2016, pp. 364374, Dublin, Ireland. [pdf].
 M. Szubert, A. Kodali, S. Ganguly, K.Das, J. Bongard. Reducing Antagonism between Behavioral Diversity and Fitness in Semantic Genetic Programming, GECCO 2016, pp. 797804, Denver, CO. [pdf].
 A. Kodali, M. Szubert, S. Ganguly, J. Bongard, K. Das. Regression based modeling of vegetation and climate variables for the Amazon rainforests, AGU Fall Meeting, 2015. San Francisco, CA. Poster presentation. [pdf].
 K. Das. Evaluation of Big Data Containers for Popular Storage, Retrieval, and Computation Primitives in Earth Science Analysis, AGU Fall Meeting, 2015. San Francisco, CA. Poster presentation. [pdf].
 K. Das, K. Bhaduri, B. Matthews, and N. Oza. Large scale support vector regression for aviation safety. IEEE BigData 2015, pp. 9991006, Santa Clara, CA. [pdf].
 C. Basu, C. Koehler, K. Das, and A. Dey. PerCCS: PersonCount from Carbon dioxide using Sparse Nonnegative Matrix Factorization. UbiComp 2015, pp. 987998, Osaka, Japan. [pdf].
 K. Das, S. Agrawal, G. Atluri, S. Liess, M. Steinbach, and V. Kumar. Analyzing Global Climate System Using Graph Based Anomaly Detection, Stochastic Modeling and Complex System Approaches to Nonlinear Geophysical Systems Session I, AGU Fall Meeting, 2014. San Francisco, CA. (Oral presentation) [pdf]
 N. C. Oza, V. Kumar, R. R. Nemani, S. Boriah, K. Das, A. Khandelwal, B. Matthews, A. Michaelis, V. Mithal, G. Nayak, P. Votava. Integrating Parallel and Distributed Data Mining Algorithms into the NASA Earth Exchange (NEX). AGU Fall Meeting, 2014. San Francisco, CA. Poster. 2014. [pdf]
 S. Kumar, K. Das. Localizing anomalous changes in timeevolving graphs, Proceedings of ACM SIGMOD 2014, pp. 13471358. Snowbird, Utah. [pdf]
 K. Das, K. Bhaduri, N. Oza. ParitoSVR: Parallel Iterated Optimizer for Support Vector Regression in the Primal. Workshop on Optimization Methods for Anomaly Detection, pp. 13. 2014. Philadelphia, PA. [pdf]
 M. Stolpe, K. Bhaduri, K. Das, K. Morik. Anomaly Detection in Large Datasets by Vertically Distributed Core Vector Machines. Proceedings of ECMLPKDD, Part III, LNAI 8190, pp. 321336. 2013. Prague, Czech Republic. [pdf]
 K. Bhaduri, K. Das, B. Matthews. Detecting Abnormal Machine Characteristics in Cloud Infrastructures. Proceedings of the 2011 IEEE 11th International Conference on Data Mining Workshops, Vancouver, Canada. pp. 137144, 2011. [pdf]
 K. Das, A. N. Srivastava. Sparse Inverse Gaussian Process Regression with Application to Climate Network Discovery. NASA Conference on Intelligent Data Understanding, Mountain View, CA. pp 233 247. 2011. [pdf]
 K. Bhaduri, K. Das, C. Giannella. Distributed Monitoring of the R2 Statistic for Linear Regression. 11th SIAM International Conference on Data Mining, Phoenix, AZ. pp. 438449. 2011. [pdf]
 K. Das, A. Srivastava. BlockGP: Scalable Gaussian Process Regression for Multimodal Data. 10th IEEE International Conference on Data Mining, Sydney, Australia. pp. 791796. 2010. [pdf]
 K. Bhaduri, K. Das, P. Votava. Distributed Anomaly Detection using Satellite Data From Multiple Modalities. NASA Conference on Intelligent Data Understanding, Mountain View, CA. pp. 109123. 2010. [pdf]
 K. Das, K. Bhaduri, H. Kargupta. A Distributed Asynchronous Local Algorithm using Multiparty Optimization based Privacy Preservation. IEEE International Conference on PeertoPeer Computing, Seattle. pp. 212221. 2009. [pdf] (Invited for fast track submission to Springer Journal on PeertoPeer Networking and Applications (PPNA), as one of the outstanding papers of P2P'09 )
 K. Das, K. Bhaduri, S. Arora, W. Griffin, K. Borne, C. Giannella, H. Kargupta. Scalable Distributed Change Detection from Astronomy Data Streams using Local, Asynchronous Eigen Monitoring Algorithms. In The Ninth SIAM International Conference on Data Mining (SDM). pp 247  258. 2009. [pdf]
 K. Borne, H. Kargupta, K. Das, W. Griffin, C. Giannella. Scalable Scientific Data Mining in Distributed, PeertoPeer Environments. American Geophysical Union (AGU) Fall Meeting, 2008, San Francisco. [pdf]
 K. Das, W. Griffin, H. Kargupta, C. Giannella, Kirk Borne. Scalable MultiSource Astronomy Data Mining in Distributed, PeertoPeer Environments. Astronomical Data Analysis Software & Systems (ADASS), 2008, Montreal, Canada. [pdf]
 K. Bhaduri, K. Das, H. Kargupta. PeertoPeer Data Mining. Autonomous Intelligent Systems: Agents and Data Mining. V. Gorodetsky, C. Zhang, V. Skormin, L. Cao (Editors), LNAI 4476, Springer. pp. 110. 2007. [pdf]
 R. Dutton, P. Hu, K. Das, T. Gilbert, Y. Xiao. Can Temperature Probe Removal Be a Reliable Indicator for Case Finishing? American Society of Anesthesiologist (ASA) Annual Meeting. San Francisco. 2007. [pdf]
 K. Das, K. Liu and H. Kargupta. A Game Theoretic Perspective Toward Practical Privacy Preserving Data Mining. In National Science Foundation Symposium on Next Generation of Data Mining and CyberEnabled Discovery for Innovation. Baltimore, Maryland. 2007. [jpg]
 K. Liu, K Bhaduri, K. Das, P. Nguyen, H. Kargupta. Clientside Web Mining for Community Formation in PeertoPeer Environments. SIGKDD workshop on web usage and analysis (WebKDD). Philadelphia, Pennsylvania, USA. 2006. [pdf] (Selected as the most interesting paper from the WebKDD workshop)
 K. Das, P. Hu, Y. Xiao, M. Wasei. Reducing Uncertainty in Operating Room Management. In OR of the Future retreat. Columbia, Maryland. 2006. [pdf]
Book Chapters
 M. Stolpe, K. Bhaduri, K. Das. Distributed Support Vector Machines: An Overview. A chapter in Solving Large Scale Learning Tasks. Challenges and Algorithms. Springer Publishing House. 2016
 K. Das, K. Bhaduri, Parallel and Distributed Data Mining for Astronomy Applications. In Data Mining and Machine Learning for Astronomical Applications. Edited by K. Ali, A. Srivastava, J. Scargle and M. Way, CRC Press, 2010.
 K. Liu, K. Das, T. Grandison, H. Kargupta, PrivacyPreserving Data Analysis on Graphs and Social Networks. In Next Generation Data Mining. Edited by H. Kargupta, J. Han, P. Yu, R. Motwani, and Vipin Kumar, CRC Press, 2008. [pdf]
 K. Bhaduri, K. Das, K. SivaKumar, H. Kargupta. Algorithms for Distributed Data Stream Mining. A chapter in Data Streams: Models and Algorithms, Edited by C. Aggarwal, Springer. pp. 309332. 2006.
I did my M.S. thesis in Bioinformatic Visualization. Here is a copy of my thesis.