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All Data Sciences Group Publications

Journal Publications (DSG Primary)

  1. The Influence of System Stability and Dynamics on the Accuracy of Level-Crossing Prediction
    R. Martin, IEEE Transactions on Automatic Control, Vol. 61 No. 1, 264-269, January 2016. abstract | pdf
  2. Optimization of Perturbation Parameters for Simulated Free Shear Layer Flow
    R. Martin, International Journal of Flow Control, Vol. 6 No. 4, 135-145, December 2014. abstract | pdf
  3. Optimal level-crossing prediction for jump linear MIMO dynamical systems
    R. Martin, Automatica, Vol. 49 No. 8, 2440-2445, August 2013. abstract | pdf
  4. Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems
    I. A. Raptis, R. Martin, R. Mah, N. Oza, D. Mavris, S. Oh, K. Kim, Y. Lee, C. Sconyers, and G.J. Vachtsevanos, International Journal of Prognostics and Health Management, Vol. 4 No. 1, 59-74, February 2013. abstract | pdf
  5. Discovering Anomalous Aviation Safety Events UsingScalable Data Mining Algorithms
    B. Matthews, S. Das, K. Bhaduri, K. Das, R. Martin, and N. Oza, Journal of Aerospace Information Systems, Vol. 10 No. 10, 467-475, October 2013. abstract | pdf
  6. Extreme Value Analysis of Optimal Level-Crossing Prediction for Linear Gaussian Processes
    R. Martin, Journal of Time Series Analysis, Vol. 33 No. 4, 583-607, July 2012. abstract | pdf
  7. General Purpose Data-Driven System Monitoring for Space Operations
    D. Iverson, R. Martin, M. Schwabacher, L. Spirkovska, W. Taylor, R. Mackey, J. Patrick Castle, and V. Baskaran, Journal of Aerospace Computing, Information, and Communication, Vol. 9 No. 2, 26-44, October 2012. abstract | pdf
  8. Distributed Anomaly Detection using 1-class SVM for Vertically Partitioned Data
    K. Das, K. Bhaduri, and P. Votava, Statistical Analysis and Data Mining Journal, Vol. 4 No. 4, 393-406, August 2011. abstract | pdf
  9. Errata for “A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes”
    R. Martin, IEEE Transactions on Information Theory, Vol. 57 No. 11, 7658-7658, November 2011. abstract | pdf
  10. A Local Asynchronous Distributed Privacy Preserving Feature Selection Algorithm for Large Peer-to-Peer Networks
    K. Das, K. Bhaduri, and H. Kargupta, Knowledge and Information Systems, Vol. 24 No. 3, 341-367, September 2010. abstract | pdf
  11. Multi-objective optimization based privacy preserving distributed data mining in Peer-to-Peer networks
    K. Das, K. Bhaduri, and H. Kargupta, Peer-to-Peer Netw. Applications, Vol. 4 No. 2, 192-209, June 2010. abstract | pdf
  12. A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes
    R. A. Martin, IEEE Transactions on Information Theory, Vol. 56 No. 10, 5083-5096, October 2010. abstract | pdf
  13. Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring
    M. Schwabacher, N. Oza, and B. Matthews, Journal of Aerospace Computing, Information, and Communication, Vol. 6 No. 7, 464-482, July 2009. abstract | pdf
  14. Classification of Aeronautics System Health and Safety Documents
    N. Oza, J. Castle, and J. Stutz, The IEEE Systems, Man, and Cybernetics Society, Part C: Applications & Reviews, Vol. 39 No. 6, 670-680, November 2009. abstract | pdf
  15. Distributed Identification of Top-l Inner Product Elements and its Application in a Peer-to-Peer Network
    K. Das, K. Bhaduri, K. Liu, and H. Kargupta, IEEE Transactions on Knowledge and Data Engineering, Vol. 20 No. 4, 475-488, April 2008. abstract | pdf
  16. Key Real World Applications of Classifier Examples
    N. Oza and K. Tumer, Information Fusion: Special Issue on Applications of Ensemble Methods, Vol. 9 No. 1, 4-20, January 2008. abstract | pdf
  17. Advances in digraph model processing applied to automated monitoring and diagnosis
    D. Iverson and A. Patterson-Hine, Journal of Diagnosis, Reliability Engineering and System Safety, Vol. 49 No. 3, 325-334, January 1995. abstract | pdf

Journal Publications (DSG Co-Author)

  1. Vector Autoregressive Model-based Anomaly Detection in Aviation Systems
    I. Melnyk, B. Matthews, H. Valizadegan, A. Banerjee, and N. Oza, Journal of Aerospace Information Systems, Vol. 13 No. 4, 161-173, March 2016. abstract | pdf
  2. Sensor-Based Predictive Modeling for Smart Lighting in Grid-Integrated Buildings
    C. Basu, J. Caubel, K. Kim, E. Cheng, A. Dhinakar, A. Agogino, and R. Martin, IEEE Sensors Journal, special issue on Sensing Technologies for Intelligent Urban Infrastructures, Vol. 14 No. 12, 4216-4229, December 2014. abstract | pdf
  3. Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems
    C. Sconyers, Y. Lee, K. Kim, S. Oh, D. Mavris, G. Vachtsevanos, N. Oza, R. Mah, R. A. Martin, and I. A. Raptis, International Journal of Prognostics and Health Management, Vol. 4 No. 7, 15, February 2013. abstract | pdf
  4. Rotor health monitoring combining spin tests and data-driven anomaly detection methods
    A.Abdul-Aziz, M. R. Woike, N. C. Oza, B. L. Matthews, and J. D. Lekki, Structural Health Monitoring, Vol. 2 No. 1, 3-12, September 2011. abstract | pdf
  5. Space Shuttle Main Propulsion System Anomaly Detection: A Case Study
    B. Matthews, A. Srivastava, D. Iverson, B. Beilx, and B. Lane, IEEE Aerospace and Electronic Systems Magazine, Vol. 26 No. 9, 4-13, September 2011. abstract | pdf
  6. Scalable, Asynchronous, Distributed Eigen-Monitoring of Astronomy Data Streams
    K. Bhaduri, K. Das, K. Borne, C. Giannella, T. Mahule, and H. Kargupta, Statistical Analysis and Data Mining Journal, Vol. 4 No. 3, 336-352, August 2011. abstract | pdf
  7. Efficient Keyword-Based Search for Top-K Cells in Text Cube
    B. Ding, B. Zhao, C. X. Lin, J. Han, C. Zhai, A. N. Srivastava, and N. C. Oza, IEEE Transactions on Knowledge and Data Engineering, Vol. 23 No. 12, 1795 - 1810, February 2011. abstract | pdf
  8. Topic Modeling for OLAP on Multidimensional Text Databases: Topic Cube and its Applications
    D. Zhang, C. Zhai, J. Han, N. Oza, and A. Srivastava, Statistical Analysis and Data Mining, Special Issue on the Best Papers of SDM'09, Vol. 2 No. 5-6, 291-293, November 2009. abstract | pdf
  9. Peer-to-Peer Data Mining, Privacy Issues, and Games
    K. Bhaduri, K. Das, and H. Kargupta, Proceedings of Autonomous Intelligent Systems: Multi-Agents and Data Mining, LNAI, Vol. 4476 , 1-10, June 2007. abstract | pdf
  10. Client-side Web Mining for Community Formation in Peer-to-Peer Environments
    K. Liu, K. Bhaduri, K. Das, P. Nguyen, and H.Kargupta, ACM SIGKDD Explorations Newsletter, Vol. 8 No. 2, 11-20, August 2006. abstract | pdf
  11. Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing Spectra
    A. Srivastava, N. Oza, and J. Stroeve, IEEE Transactions on Geoscience and Remote Sensing, Vol. 43 No. 3, 590-600, March 2005. abstract | pdf
  12. Characterization of model-based reasoning strategies for use in IVHM architectures
    S. Poll, D. L. Iverson, and A. Patterson-Hine, Proceedings of the Volume 5107: System Diagnosis and Prognosis: Security and Condition Monitoring Issues III, August 2003. abstract | pdf
  13. Automated Telescope Monitoring and Diagnosis
    C. M. Monahan, F.A. Patterson-Hine, and D. L. Iverson, Proceedings of a symposium held as part of the 106th annual meeting of the Astronomical Society of the Pacific, Vol. 79 , 120-128, June 1994. abstract | pdf

Book Chapters (DSG Primary)

  1. Classification
    N. Oza, Advances in Machine Learning and Data Mining for Astronomy, 1-20, 2012. abstract | pdf
  2. Anomaly Detection in a Fleet of Systems
    N. Oza and S. Das, Machine Learning and Knowledge Discovery for Engineering Systems Health Management, 3-44, 2011. abstract | pdf
  3. Evaluation of Anomaly Detection Capability for Ground-Based Pre-Launch Shuttle Operations
    R. A. Martin, Aerospace Technologies Advancements, 142-164, 2010. abstract | pdf
  4. Ensemble Data Mining Methods
    N. Oza, Encyclopedia of Data Warehousing and Mining, Second Edition, 770-785, 2004. abstract | pdf

Conference Papers (DSG Primary)

  1. Anomaly detection in aviation data using extreme learning machines
    V. M. Janakiraman and D. Nielsen, International Joint Conference on Neural Networks, Vancouver, B.C., 1993-2000, July 2016. abstract | pdf
  2. Discovery of Precursors to Adverse Events using Time Series Data
    Vijay Manikandan Janakiraman, Bryan Matthews, and Nikunj Oza, 2016 SIAM International Conference on Data Mining, Miami, FL, 2016. abstract | pdf
  3. Comparative study of metroplex airspace and procedures using machine learning to discover flight track anomalies
    B. Matthews, D. Nielsen, J. Schade, K. Chan, and M. Kiniry, Proceedings of the Digital Avionics Systems Conference, Prauge, Czech Republic, 2G4-1 - 2G4-15, September 2015. abstract | pdf
  4. Optimization of Perturbation Parameters for Simulated Free Shear Layer Flow
    R. A. Martin and U. Kaul, Proceedings of the 7th AIAA Flow Control Conference, Atlanta, GA, June 2014. abstract | pdf
  5. Identifying Precursors to Anomalies Using Inverse Reinforcement Learning
    V. Janakiraman, S. Das, B. Matthews, and N. Oza, Workshop on Optimization Methods for Anomaly Detection, SDM 2014, Philadelphia, PA, 2014. abstract | pdf
  6. Automated Discovery of Flight Track Anomalies
    B. Matthews, D. Nielsen, J. Schade, K. Chan, and M. Kiniry, Proceedings of the IEEE/AIAA 33rd Digital Avionics Systems Conference, Colorado Springs, CO, 4B3-1 - 4B3-15, October 2014. abstract | pdf
  7. Energy Analysis of Multi-Function Devices in an Office Environment
    R. Martin and S. Poll, Proceedings of ASHRAE Winter Conference, New York, NY, January 2014. abstract | pdf
  8. Discovery of Abnormal Flight Patterns in Flight Track Data
    B. Matthews, A. Srivastava, J. Schade, D, Schleicher, K. Chan, R. Gutterud, and M. Kiniry, Proceedings of the 2013 Aviation Technology, Integration, and Operations Conference, Los Angeles, CA, August 2013. abstract | pdf
  9. SPARSE INVERSE GAUSSIAN PROCESS REGRESSION WITH APPLICATIONTO CLIMATE NETWORK DISCOVERY
    K. Das and A. Srivastava, Proceedings of the Conference on Intelligent Data Understanding, Mountain View, CA, October 2011. abstract | pdf
  10. General Purpose Data-Driven System Monitoring for Space Operations
    David L. Iverson, Rodney Martin, Mark Schwabacher, Lilly Spirkovska, William Taylor, Ryan Mackey, and J. Patrick Castle, 53rd Annual ISA POWID Symposium, Summerlin, NV, June 2010. abstract | pdf
  11. ADAPTIVE FAULT DETECTION ON LIQUID PROPULSION SYSTEMS WITH VIRTUAL SENSORS: ALGORITHMS AND ARCHITECTURES
    B. Matthews and A. Srivastava, Proceedings of the JANNAF Conference on Propulsion Systems, Colorado Springs, CO, May 2010. abstract | pdf
  12. Ares I-X Ground Diagnostic Prototype
    M. Schwabacher, R. Martin, R. Waterman, R. Oostdyk, J. Ossenfort, and B. Matthews, Proceedings of AIAA Infotech@Aerospace Conference, Atlanta, GA, April 2010. abstract | pdf
  13. Near Real-Time Optimal Prediction of Adverse Events in Aviation Data
    R. Martin and S. Das., Proceedings of AIAA Infotech@Aerospace Conference, Atlanta, GA, April 2010. abstract | pdf
  14. Block-GP: Scalable Gaussian Process Regression for Multimodal Data
    K. Das and A. Srivastava, International Conference on Data Mining, Sydney, Australia, 791-796, December 2010. abstract | pdf
  15. Data-Driven Anomaly Detection Performance for the Ares I-X Ground Diagnostic Prototype
    R. A. Martin, M. A. Schwabacher, and B. L. Matthews, In Proceedings of the International Conference on Prognostics and Health Management, Portland, OR, October 2010. abstract | pdf
  16. A Local Distributed Peer-to-Peer Algorithm Using Multi-Party Optimization Based Privacy Preservation for Data Mining Primitive Computation
    K. Das, K. Bhaduri, and H. Kargupta, Proceedings of the IEEE Peer to Peer Conference, Seattle, WA, 212-221, September 2009. abstract | pdf
  17. Comparative Analysis of Data-Driven Anomaly Detection Methods
    B. Matthews and A. Srivastava, Proceedings of the JANNAF Conference on Propulsion Systems, Orlando, FL, May 2008. abstract | pdf
  18. Scalable Distributed Change Detection from Astronomy Data Streams using Local, Asynchronous Eigen Monitoring Algorithms
    K. Das, K. Bhaduri, S. Arora, W. Griffin, K. D. Borne, C. Giannella, and H. Kargupta, Proceedings of the SIAM International Conference on Data Mining, Atlanta, GA, 245-256, April 2008. abstract | pdf
  19. Data Mining Applications for Space Mission Operations System Health Monitoring
    D. Iverson, SpaceOps 2008 Conference, Heidelberg, Germany, 2008. abstract | pdf
  20. An Investigation of State-Space Model Fidelity for SSME Data
    R. A. Martin, In Proceedings of the International Conference on Prognostics and Health Management, Denver, CO, October 2008. abstract | pdf
  21. Comparison of Unsupervised Anomaly Detection Methods
    R. Martin, M. Schwabacher, N. Oza, and A. Srivastava, Proceedings of the JANNAF Conference on Propulsion Systems, Denver, CO, May 2007. abstract | pdf
  22. Unsupervised Anomaly Detection and Diagnosis for Liquid Rocket Engine Propulsion
    R. A. Martin, In Proceedings of the IEEE Aerospace Conference, Big Sky, MT, March 2007. abstract | pdf
  23. INDUCTIVE SYSTEM HEALTH MONITORING WITH STATISTICAL METRICS
    D. Iverson, JANNAF 10th Modeling and Simulation Conference, Charleston, SC, June 2005. abstract | pdf
  24. Inductive System Health Monitoring
    D. Iverson, Proceedings of the Proceedings of the International Conference on Artificial Intelligence, Las Vegas, BV, June 2004. abstract | pdf
  25. Digraph reliability model processing advances and applications
    D. Iverson and A. Patterson-Hine, Proceedings of AIAA Computing in Aerospace Conference, San Diego, CA, 1189-1199, October 1993. abstract | pdf
  26. Automatic translation of digraph to fault-tree models
    D. Iverson, Proceedings of Annual Reliability and Maintainability Symposium, Las Vegas, NV, 354-362, January 1992. abstract | pdf
  27. A Diagnosis System Using Object-Oriented Fault Tree Models
    D. Iverson and A. Patterson-Hine, Proceedings of Fifth Conference on Artificial Intelligence for Space Applications, MSFC, Huntsville, AL, 341-349, May 1990. abstract | pdf
  28. Object-oriented fault tree models applied to system diagnosis
    D. Iverson and A. Patterson-Hine, Proceedings of the Applications of Artificial Intelligence VIII, Orlando, FL, United States, 1013-1023, April 1990. abstract | pdf

Conference Papers (DSG Co-Author)

  1. Scalable Causal Learning for Predicting Adverse Events in Smart Buildings
    Aniruddha Basak, Ole Mengshoel, Stefan Hosein, and Rodney Martin, International Workshop on Artificial Intelligence for Smart Grids and Smart Buildings, AAAI 2016, Phoenix, AZ, March 2016. abstract | pdf
  2. Identifying Contributing Factors of Occupant Thermal Discomfort in a Smart Building
    A. Basak, O. Mengshoel, S. Hosein, R. A. Martin, J. Jayakumaran, M. Gurrola Morga, and I. Aghav, In First International Workshop on Artificial Intelligence for Smart Grids and Smart Buildings 30th Annual Conference on Artificial Intelligence, February 2016. abstract | pdf
  3. Enhancing Flight Test Safety with Real-time Early Warning Techniques
    l. Barshi and D. Iverson, Proceedings of the 33rd International Test and Evaluation Symposium, Reston, VA, October 2016. abstract | pdf
  4. Demonstrating Autonomous Mission Operations Onboard the International Space Station
    Jeremy D Frank, David Iverson, Christopher Knight, Sriram Narasimhan, Keith Swanson, Michael S Scott, May Windrem, Kara M Pohlkamp, Jeffery M Mauldin, Kerry Mcguire, and Haifa Moses, Proceedings of 2015 AIAA Space Conference, Pasadena, CA, 2015. abstract | pdf
  5. Relative Comparison Kernel Learning with Auxiliary Kernels
    E. Heim, H. Valizadegan, and M. Hauskrecht, Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, Nancy, France, 563-578, September 2014. abstract | pdf
  6. Affordable and Personalized Lighting Using Inverse Modeling and Virtual Sensors
    C. Basu, B. Chen, J. Richards, A. Dhinakaran, A. Agogino, and R. A. Martin, In Proceedings of the Conference on Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, San Diego, CA, March 2014. abstract | pdf
  7. Exploration technologies for operations
    Ernest E. Smith, David J. Korsmeyer, Vern Hall, Jessica Marquez, David L. Iverson, Jay P. Trimble, Richard M. Keller, Jeremy Frank, John Chachere, and William J. Clancey, SpaceOps 2014 Conference, Pasadena, CA, 2014. abstract | pdf
  8. Neural Network Forecasting of Solar Power for NASA Ames Sustainability Base
    C. Poolla, A. Ishihara, S. Rosenberg, R. Martin, C. Basu, A. Fong, and S. Ray, IEEE Symposium Series on Computational Intelligence, December 2014. abstract | pdf
  9. A system for fault management and fault consequences analysis for NASA’s Deep Space Habitat
    Silvano P. Colombano, Liljana Spirkovska, Vijayakumar Baskaran, Gordon Aaseng, Robert S. Mccann, John Ossenfort, Irene Smith, David L. Iverson, and Mark Schwabacher, Proceedings of AIAA SPACE 2013 Conference & Exposition, San Diego, CA, September 2013. abstract | pdf
  10. Integrated Health Monitoring and Fault Adaptive Control for an Unmanned Hexrotor Helicopter
    J. Ge, B. LeFevre, M. Roemer, and R. A. Martin, In Proceedings of the SAE AeroTech Congress & Exhibition, Montréal, Canada, September 2013. abstract | pdf
  11. Simple Sensitivity Analysis for Orion GNC
    T. Pressburger (Invited), B. Hoelscher, R. A. Martin, and K. Sricharan, AIAA Guidance, Navigation, and Control (GNC) Conference, August 2013. abstract | pdf
  12. Embedding Temporal Constraints for Coordinated Execution in Habitat Automation
    P. Morris, M. Schwabacher, M. Dalal, and C. Fry, Proceedings of the International Workshop on Planning and Scheduling for Space, Moffett Field, CA, March 2013. abstract | pdf
  13. Supporting Personalizable Virtual Internet of Things
    J. Zhang, Z. Li, O. Sandoval, N. Xin, Y. Ren, R. A. Martin, B. Iannucci, M. Griss, S. Rosenberg, J. Cao, and A. Rowe, IEEE 10th International Conference on Autonomic & Trusted Computing, Vietri sul Mare, Italy, December 2013. abstract | pdf
  14. A Particle Filtering-based Framework for Real-time Fault Diagnosis of Autonomous Vehicles
    I. A. Raptis, C. Sconyers, R. A. Martin, R. Mah, N. Oza, D. Mavris, and G. J. Vachtsevanos, In Proceedings of the International Conference on Prognostics and Health Management, New Orleans, LA, October 2013. abstract | pdf
  15. Aircraft Anomaly Detection using Performance Models Trained on Fleet Data
    D. Gorinevsky, B. L. Matthews, and R. A. Martin, Proceedings of the Conference on Intelligent Data Understanding, Boulder, CO, October 2012. abstract | pdf
  16. Using Medieval Architecture as Inspiration for Display Design: Parameter Interrelationships and Organizational Structure
    Immanuel Barshi, Asaf Degani, David L. Iverson, and Peter J. Lu, Proceedings of the 56th Annual Meeting of the Human Factors and Ergonomics Society, Boston, MA, 1799-1803, October 2012. abstract | pdf
  17. Fleet Level Anomaly Detection of Aviation Safety Data
    S. Das, B. Matthews, and R. Lawrence., Proceedings of the Annual Conference of the Prognostics and Health Management Society, Montreal, Canada, September 2011. abstract | pdf
  18. Algorithms for Speeding up Distance-Based Outlier Detection
    K. Bhaduri, B. Matthews, and C. Giannella, Proceedings of the 17th ACM SIGKDD Conference on Knowledge, Discovery and Data Mining, San Diego, CA, August 2011. abstract | pdf
  19. Distributed Monitoring of the R2 Statistic for Linear Regression
    K. Bhaduri, K. Das, and C. Giannella, Proceedings of the SIAM International Conference on Data Mining, Phoenix, Arizona, April 2011. abstract | pdf
  20. Sparse Solutions for Single Class SVMs: A Bi-Criterion Approach
    S. Das and N. Oza, Proceedings of the SIAM International Conference on Data Mining, Phoenix, Arizona, April 2011. abstract | pdf
  21. Pseudo-Label Generation for Multi-Label Text Classification
    M.S. Ahmed, L. Khan, and N. Oza, Proceedings of the Conference on Intelligent Data Understanding, Mountain View, CA, October 2011. abstract | pdf
  22. Fast and Flexible Multivariate Time Series Subsequence Search
    K. Bhaduri, Q. Zhu, N. Oza, and A. Srivastava, Proceedings of the 16th ACM SIGKDD Conference on Knowledge, Discovery and Data Mining, Washington, D.C., July 2010. abstract | pdf
  23. Multiple Kernel Learning for Heterogeneous Anomaly Detection: Algorithm and Aviation Safety Case Study
    S. Das, B. Matthews, A. Srivastava, and N. Oza, Proceedings of the 16th ACM SIGKDD Conference on Knowledge, Discovery and Data Mining, Washington, D.C., July 2010. abstract | pdf
  24. Anomaly Detection for Next-Generation Space Launch Ground Operations
    Lilly Spirkovska, David L. Iverson, David R. Hall, William M. Taylor, Ann Patterson-Hine, Barbara L. Brown, Bob A. Ferrell, and Robert D. Waterman, SpaceOps 2010 Conference, Huntsville, AL, April 2010. abstract | pdf
  25. Propulsion Health Monitoring of a Turbine Engine Disk Using Spin Test Data
    A.Abdul-Aziz, M. Woike, N. Oza, B. Matthews, and G. Baaklini, Proceedings of the Smart Structures and Materials and Nondestructive Evaluation and Health Monitoring: 17th Annual International Symposium, San Diego, CA, March 2010. abstract | pdf
  26. Distributed Anomaly Detection Using Satellite Data From Multiple Modalities
    K. Bhaduri, K. Das, and P. Votava, Proceedings of the conference on Intelligent Data Understanding, Mountain View, CA, 109-123, October 2010. abstract | pdf
  27. Multi-label ASRS Dataset Classification Using Semi Supervised Subspace Clustering
    Mohammad Salim Ahmed, Latifur Khan, Nikunj C. Oza, and Mandava Rajeswari, Proceedings of the conference on Intelligent Data Understanding, Mountain View, CA, October 2010. abstract | pdf
  28. Detecting Anomalies in Multivariate Data Sets with Switching Sequences and Continuous Streams
    S. Das, B. Matthews, K. Bhaduri, N. Oza, and A. Srivastava, Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems, Vancouver, B.C., Canada, December 2009. abstract | pdf
  29. Discriminative Mixed-Membership Models
    H. Shan, A. Banerjee, and N. Oza, proceedings of the IEEE International Conference on Data Mining (ICDM), Miami Beach, FL, December 2009. abstract | pdf
  30. Theoretically Optimal Distributed Anomaly Detection
    A. Lazarevic, N. Srivastava, A. Tewari, J. Isom, N. Oza, and J. Srivastava, Proceedings of the IEEE International Conference on Data Mining (ICDM), Workshop on Mining Multiple Information Sources, MIami Beach, FL, December 2009. abstract | pdf
  31. ν-Anomica: A Fast Support Vector based Novelty Detection Technique
    S. Das, K. Bhaduri, N. Oza, and A. Srivastava, IEEE International Conference on Data Mining (ICDM), Miami Beach, FL, December 2009. abstract | pdf
  32. Learning to Improve Earth Observation Flight Planning
    R. Morris, N. Oza, L. Keely, E. Kurklu, and A. Strawa, Proceedings of the 20th Conference on Innovative Applications of Artificial Intelligence (IAAI-08), Chicago, IL, July 2008. abstract | pdf
  33. Algorithms for Spectral Decomposition with Applications
    A. Srivastava, B. Matthews, and S. Das, Proceedings of the JANNAF Conference on Propulsion Systems, Orlando, FL, May 2008. abstract | pdf
  34. Machine Learning for Earth Observation Flight Planning Optimization
    E. Kurklu, R.M. Morris, and N. Oza, AAAI Spring Symposium Series, Workshop on Semantic Scientific Knowledge Integration, Stanford, CA, March 2008. abstract | pdf
  35. Discovery of Recurring Anomalies in Text Reports
    Ashok Srivastava, R. Akella, V. Diev, S. P. Kumaresan, Dawn Mcintosh, E. D. Pontikakis, Z. Xu, and Y. Zhang, Proceedings of IEEE Aerospace Conference, Big Sky, MT, March 2006. abstract | pdf
  36. Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults
    L. Spirkovska, D. Iverson, S. Poll, and A. Pryor, Proceedings of AIAA Infotech@Aerospace Conference, Arlington, VA, September 2005. abstract | pdf
  37. Mining Distance-Based Outliers in Near Linear Time with Randomization and a Simple Pruning Rule
    S. Bay and M. Schwabacher, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, washington, d.c., August 2003. abstract | pdf
  38. An integrated approach to system design, reliability, and diagnosis
    A. Patterson-Hine and D. Iverson, Proceedings of the Digital Avionics Systems Conference, Virginia Beach, VA, 480 - 487, October 1990. abstract | pdf

DSG Technical Reports

  1. On Organization of Information: Approach and Early Work
    Asaf Degani, Charles Jorgensen, David Iverson, Michael Shafto, and Leonard Olson, NASA/TM-2009-215368, 2009. abstract | pdf
  2. Integrated System Health Management (ISHM) Technology Demonstration Project Final Report
    Ryan Mackey, David Iverson, Greg Pisanich, Mike Toberman, and Ken Hicks, NASA TM 2006-213482, 2006. abstract | pdf
  3. System Modeling and Diagnostics for Liquefying-Fuel Hybrid Rockets
    S. Poll, D. Iverson, J. Ou, D. Sanderfer, and A. Patterson-Hine, 2003. abstract | pdf
  4. Real-Time Surface Traffic Adviser
    Brian J. Glass, Liljana Spirkovska, William J. Mcdermott, Ronald J. Reisman, James Gibson, and David L. Iverson, NASA-Case-ARC-14268-2, 2001. abstract | pdf
  5. Multiple Fault Isolation in Redundant Systems
    M. Shakeri, Krishna R. Pattipati, V. Raghavan, Ann Patterson-Hine, and David L. Iverson, NASA/CR-97-205940, 1997. abstract | pdf
  6. Program Finds Minimal Cut Sets
    Iverson and D. L., NASA Tech Briefs (ISSN 0145-319X); 18; 6; P. 61, 1994. abstract | pdf

DSG Presentations

  1. Machine Learning for Space Research Problems
    H. Valizadegan, misc, Machine Learning Innovation Summit, San Francisco, CA, June 2017. abstract | pdf
  2. Enhancing Flight Test Safety with Real-time Early Warning Techniques
    l. Barshi and D. Iverson, misc, 33rd International Test and Evaluation Symposium, Reston, VA, October 2016. abstract | pdf
  3. Towards Automatic Classification of Exoplanet-Transit-Like Signals: A Case Study on Kepler Mission Data
    H. Valizadegan, R. A. Martin, S. D. McCauliff, J. M. Jenkins, J. Catanzarite, and N. C. Oza, misc, International Astronomical Union, Honolulu, HI, August 2015. abstract | pdf
  4. Optimal Prediction of Adverse Events in Aviation Data
    R. Martin and S. Das, misc, CIDU (Conference on Intelligent Data Understanding), Mountain View, CA, October 2010. abstract | pdf
  5. Recent Results on “Approximations to Optimal Alarm Systems for Anomaly Detection”
    R. Martin, misc, IEEE International Symposium on Information Theory, Toronto, Canada, July 2008. abstract | pdf
  6. Approximations to Optimal Alarm Systems for Anomaly Detection
    R. Martin, misc, CIDU (Conference on Intelligent Data Understanding), Mountain View, CA, June 2007. abstract | pdf
  7. Investigation of Optimal Alarm System Performance for Anomaly Detection
    R. Martin, misc, National Science Foundation Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation, Baltimore, MD, October 2007. abstract | pdf

Team

Group Lead
Nikunj Oza, Ph.D.

Group Members
Kamalika Das, Ph.D.
Dave Iverson
Vijay Janakiraman, Ph.D.
Rodney Martin, Ph.D.
Bryan Matthews
Nikunj Oza, Ph.D.
John Stutz
Hamed Valizadegan, Ph.D.
Veronica Phillips

Current Affiliates
Rama Nemani, Ph.D.

Past Affiliates
Ram Akella, Ph.D. - UCSC, UARC
Mike Berry, Ph.D
Kanishka Bhaduri, Ph.D.
Peter Brende - SIVD - UCSC, UARC
Suratna Budalakoti-RIACS
Aditi Chattopadhyay, Ph.D.
Santanu Das, Ph.D. - UARC
Robert Delgadillo-FCCD Internship
Vesselin Diev - UCSC, UARC
Gregory Dorais, Ph.D.
Elizabeth Foughty
Darren Galaviz - FCCD Internship
Paul Gazis, Ph.D.
Michelle Ho - SHARP Internship
Upender Kaul, Ph.D. - NASA
Rebekah Kochavi - QSS
Sakthi Preethi Kumaresan - UCSC, UARC
Alex Lotch - Boston University
Bill Macready, Ph.D. - UARC
Amy Mai - SGT
Marianne Mosher, Ph.D. - NASA
Manos Pontikakis - UCSC, UARC
Avik Sarkar - Open University, U.K.
Smadar Shiffman, Ph.D. - QSS
Ashok Srivastava, Ph.D. - NASA
David Thompson, Ph.D. - NASA
Len Trejo, Ph.D. - NASA
Eugene Turkov
Richard Watson
David Wolpert, Ph.D.
Bing Xu - UCSC, UARC
Brett Zane-Ulman - CSC
Yi Zhang, Ph.D. - UCSC, UARC

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