Umaa Rebbapragada

4.7k total citations
29 papers, 524 citations indexed

About

Umaa Rebbapragada is a scholar working on Artificial Intelligence, Astronomy and Astrophysics and Ecology. According to data from OpenAlex, Umaa Rebbapragada has authored 29 papers receiving a total of 524 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Artificial Intelligence, 8 papers in Astronomy and Astrophysics and 4 papers in Ecology. Recurrent topics in Umaa Rebbapragada's work include Anomaly Detection Techniques and Applications (9 papers), Machine Learning and Data Classification (6 papers) and Machine Learning and Algorithms (5 papers). Umaa Rebbapragada is often cited by papers focused on Anomaly Detection Techniques and Applications (9 papers), Machine Learning and Data Classification (6 papers) and Machine Learning and Algorithms (5 papers). Umaa Rebbapragada collaborates with scholars based in United States, Australia and United Kingdom. Umaa Rebbapragada's co-authors include Dragomir Yankov, Eamonn Keogh, Carla E. Brodley, Pavlos Protopapas, Charles Alcock, Thomas Oommen, Frank J. Masci, M. M. Kasliwal, Kiri L. Wagstaff and Timothy C. Havens and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Remote Sensing and Machine Learning.

In The Last Decade

Umaa Rebbapragada

26 papers receiving 498 citations

Peers

Countries citing papers authored by Umaa Rebbapragada

Since Specialization

Citations

This map shows the geographic impact of Umaa Rebbapragada's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Umaa Rebbapragada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Umaa Rebbapragada more than expected).

Fields of papers citing papers by Umaa Rebbapragada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Umaa Rebbapragada. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Umaa Rebbapragada. The network helps show where Umaa Rebbapragada may publish in the future.

Co-authorship network of co-authors of Umaa Rebbapragada

This figure shows the co-authorship network connecting the top 25 collaborators of Umaa Rebbapragada. A scholar is included among the top collaborators of Umaa Rebbapragada based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Umaa Rebbapragada. Umaa Rebbapragada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Statistical Prediction of [CII] Observations by Constructing Probability Density Functions Using SOFIA, Herschel, and Spitzer Observations 2023 ·Journal of Astronomical Instrumentation ·Young Min Seo, Karen Willacy, Umaa Rebbapragada	0
2	Tracing Milky Way substructure with an RR Lyrae hierarchical clustering forest 2022 ·arXiv (Cornell University) ·(unknown), D. Woods, (unknown), (unknown), (unknown), (unknown), (unknown), Umaa Rebbapragada, A. Mahabal	3
3	COSMIC: Content-based Onboard Summarization to Monitor Infrequent Change 2020 ·Gary Doran, (unknown), M. Liukis, Lukas Mandrake, Umaa Rebbapragada, Kiri L. Wagstaff, (unknown), (unknown), (unknown), Paul Horton, (unknown), (unknown)	5
4	Real-bogus classification for the Zwicky Transient Facility using deep learning 2019 ·Monthly Notices of the Royal Astronomical Society ·Dmitry A. Duev, A. Mahabal, Frank J. Masci, M. J. Graham, B. Rusholme, R. Walters, (unknown), Sara Frederick, M. M. Kasliwal, Umaa Rebbapragada, Charlotte Ward	51
5	Scientist-Guided Autonomy for Self-Reliant Rovers 2017 ·International Joint Conference on Artificial Intelligence ·Gary Doran, Umaa Rebbapragada, Eugenie Song, Kiri L. Wagstaff, Daniel Gaines, Robert Anderson, A. R. Vasavada	1
6	Small Near-Earth Asteroids in the Palomar Transient Factory Survey: A Real-Time Streak-detection System 2017 ·Publications of the Astronomical Society of the Pacific ·(unknown), Thomas A. Prince, Russ R. Laher, Frank J. Masci, Brian Bue, Umaa Rebbapragada, Tom A. Barlow, J. Surace, G. Hélou, S. R. Kulkarni	19
7	Object-based classification of earthquake damage from high-resolution optical imagery using machine learning 2016 ·Journal of Applied Remote Sensing ·(unknown), Thomas Oommen, Umaa Rebbapragada, (unknown)	34
8	Time-domain Surveys and Data Shift: Case Study at the intermediate Palomar Transient Factory 2015 ·Umaa Rebbapragada, Brian Bue, P. R. Woźniak	1
9	Using Machine Learning to Enable Big Data Analysis within Human Review Time Budgets 2014 ·AGUFM ·Brian Bue, Umaa Rebbapragada, Kiri L. Wagstaff, David R. Thompson	0
10	Challenges and Opportunities in Applied Machine Learning 2012 ·AI Magazine ·Carla E. Brodley, Umaa Rebbapragada, Kevin Small, Byron Wallace	20
11	Active Label Correction 2012 ·Umaa Rebbapragada, Carla E. Brodley, Damien Sulla‐Menashe, M. A. Friedl	10
12	Integrating machine learning into a crowdsourced model for earthquake-induced damage assessment 2011 ·International Conference on Machine Learning ·Umaa Rebbapragada, Thomas Oommen	2
13	Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data 2011 ·International Conference on Machine Learning ·Umaa Rebbapragada, Kiri L. Wagstaff	2
14	Strategic targeting of outliers for expert review 2010 ·Carla E. Brodley, Umaa Rebbapragada	7
15	Onboard detection of natural sulfur on a glacier via a SVM and Hyperion data 2009 ·Lukas Mandrake, Kiri L. Wagstaff, (unknown), Umaa Rebbapragada, Daniel Tran, Rebecca Castaño, Steven Chien, R. T. Pappalardo	8
16	Improving onboard analysis of Hyperion images by filtering mislabeled training data examples 2009 ·Umaa Rebbapragada, Lukas Mandrake, Kiri L. Wagstaff, (unknown), Rebecca Castaño, Steve Chien, Carla E. Brodley	11
17	Finding anomalous periodic time series 2008 ·Machine Learning ·Umaa Rebbapragada, Pavlos Protopapas, Carla E. Brodley, Charles Alcock	95
18	Generating High-Quality Training Data for Automated Land-Cover Mapping 2008 ·Umaa Rebbapragada, (unknown), Carla E. Brodley, M. A. Friedl	6
19	Disk aware discord discovery: finding unusual time series in terabyte sized datasets 2008 ·Knowledge and Information Systems ·Dragomir Yankov, Eamonn Keogh, Umaa Rebbapragada	93
20	Disk Aware Discord Discovery: Finding Unusual Time Series in Terabyte Sized Datasets 2007 ·Dragomir Yankov, Eamonn Keogh, Umaa Rebbapragada	45

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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