S
Santanu Das
Researcher at Ames Research Center
Publications - 37
Citations - 2101
Santanu Das is an academic researcher from Ames Research Center. The author has contributed to research in topics: Anomaly detection & Structural health monitoring. The author has an hindex of 17, co-authored 33 publications receiving 1963 citations. Previous affiliations of Santanu Das include Arizona State University & University of California, Santa Cruz.
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Journal ArticleDOI
Characteristics of planetary candidates observed by Kepler. II. Analysis of the first four months of data
William J. Borucki,David G. Koch,Gibor Basri,Natalie M. Batalha,Timothy M. Brown,Stephen T. Bryson,Douglas A. Caldwell,Jørgen Christensen-Dalsgaard,William D. Cochran,Edna DeVore,Edward W. Dunham,Thomas N. Gautier,John C. Geary,Ronald L. Gilliland,Alan Gould,Steve B. Howell,Jon M. Jenkins,David W. Latham,Jack J. Lissauer,Geoffrey W. Marcy,Jason F. Rowe,Dimitar Sasselov,Alan P. Boss,David Charbonneau,David R. Ciardi,Laurance R. Doyle,Andrea K. Dupree,Eric B. Ford,Jonathan J. Fortney,Matthew J. Holman,Sara Seager,Jason H. Steffen,Jill Tarter,William F. Welsh,Christopher C. R. Allen,Lars A. Buchhave,Jessie L. Christiansen,Bruce D. Clarke,Santanu Das,Jean-Michel Desert,Michael Endl,Daniel C. Fabrycky,Francois Fressin,Michael R. Haas,Elliott P. Horch,Andrew W. Howard,Howard Isaacson,Hans Kjeldsen,Jeffery J. Kolodziejczak,Craig Kulesa,Jie Li,Philip W. Lucas,P. Machalek,Donald W. McCarthy,Phillip J. MacQueen,Søren Meibom,Thibaut Miquel,Andrej Prsa,Samuel N. Quinn,Elisa V. Quintana,Darin Ragozzine,William Sherry,Avi Shporer,Peter Tenenbaum,Guillermo Torres,Joseph D. Twicken,Jeffrey Van Cleve,Lucianne M. Walkowicz,Fred C. Witteborn,Martin Still +69 more
TL;DR: In this article, the Kepler mission released data for 156,453 stars observed from the beginning of the science observations on 2009 May 2 through September 16, and there are 1235 planetary candidates with transit-like signatures detected in this period.
Proceedings ArticleDOI
Multiple kernel learning for heterogeneous anomaly detection: algorithm and aviation safety case study
TL;DR: This paper discusses a novel approach based on the theory of multiple kernel learning to detect potential safety anomalies in very large data bases of discrete and continuous data from world-wide operations of commercial fleets.
Journal ArticleDOI
Analysis of flight data using clustering techniques for detecting abnormal operations
TL;DR: The new method, enabled by data from the flight data recorder, applies clustering techniques to detect abnormal flights of unique data patterns and can support domain experts in detecting anomalies and associated risks from routine airline operations.
Journal ArticleDOI
Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms
TL;DR: The worldwide civilian aviation system is one of the most complex dynamical systems created and most modern commercial aircraft have onboard flight data recorders that record several hundred discrete events.
Journal ArticleDOI
Gaussian Process Time Series Model for Life Prognosis of Metallic Structures
TL;DR: Al 2024-T351 fatigue specimens have been modeled using a kernel-based multi-variate Gaussian Process approach and the collapse load condition is determined, which is a desirable feature for the online health monitoring and prognosis.