Ashish Mahabal

According to our database, Ashish Mahabal authored at least 44 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Selfish Evolution: Making Discoveries in Extreme Label Noise with the Help of Overfitting Dynamics.

Nima Sedaghat, Tanawan Chatchadanoraset, Colin Orion Chandler, Ashish Mahabal, Maryam Eslami

CoRR, 2024

Light curve classification with DistClassiPy: A new distance-based classifier.

Siddharth Chaini, Ashish Mahabal, Ajit Kembhavi, Federica B. Bianco

Astron. Comput., 2024

2023

Biomonitoring and precision health in deep space supported by artificial intelligence.

Ryan T. Scott, Lauren M. Sanders, Erik L. Antonsen, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes

Nat. Mac. Intell., March, 2023

Biological research and self-driving labs in deep space supported by artificial intelligence.

Lauren M. Sanders, Ryan T. Scott, Jason H. Yang, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart J. Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes

Nat. Mac. Intell., March, 2023

2022

Applications of AI in Astronomy.

S. George Djorgovski, Ashish Mahabal, Matthew J. Graham, Kai Polsterer, Alberto Krone-Martins

CoRR, 2022

SNGuess: A method for the selection of young extragalactic transients.

N. Miranda, Johann-Christoph Freytag, Jakob Nordin, Rahul Biswas, Valery Brinnel, Christoffer Fremling, Marek Kowalski, Ashish Mahabal, Simeon Reusch, Jakob van Santen

CoRR, 2022

2021

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs.

Lauren M. Sanders, Jason H. Yang, Ryan T. Scott, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart J. Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes

CoRR, 2021

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health.

Ryan T. Scott, Erik L. Antonsen, Lauren M. Sanders, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes

CoRR, 2021

Tails: Chasing Comets with the Zwicky Transient Facility and Deep Learning.

Dmitry A. Duev, Bryce T. Bolin, Matthew J. Graham, Michael S. P. Kelley, Ashish Mahabal, Eric C. Bellm, Michael W. Coughlin, Richard Dekany, George Helou, Shrinivas R. Kulkarni, Frank J. Masci, Thomas A. Prince, Reed Riddle, Maayane T. Soumagnac, Stefan Johann van der Walt

CoRR, 2021

Nigraha: Machine-learning based pipeline to identify and evaluate planet candidates from TESS.

Sriram Rao, Ashish Mahabal, Niyanth Rao, Cauligi S. Raghavendra

CoRR, 2021

2020

Alert Classification for the ALeRCE Broker System: The Real-time Stamp Classifier.

Rodrigo Carrasco-Davis, Esteban Reyes, Camilo Valenzuela, Francisco Förster, Pablo A. Estévez, Giuliano Pignata, Franz E. Bauer, Ignacio Reyes, Paula Sánchez-Sáez, Guillermo Cabrera-Vives, Susana Eyheramendy, Márcio Catelán, Javier Arredondo, Ernesto Castillo-Navarrete, Diego Rodríguez-Mancini, Daniela Ruz-Mieres, Alberto Moya, Luis Sabatini-Gacitúa, Cristóbal Sepúlveda-Cobo, Ashish Mahabal, Javier Silva-Farfán, Ernesto Camacho-Iñiquez, Lluís Galbany

CoRR, 2020

2019

Enabling real-time multi-messenger astrophysics discoveries with deep learning.

Eliu A. Huerta, Gabrielle Allen, Igor Andreoni, Javier Mauricio Antelis, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Maya Fishbach, Francisco Förster, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Robert A. Gruendl, Anushri Gupta, Roland Haas, Sarah Habib, Elise Jennings, Margaret W. G. Johnson, Erik Katsavounidis, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Zsuzsa Márka, Kenton McHenry, Jonah Miller, Claudia Moreno, Mark S. Neubauer, Steve Oberlin, Alexander R. Olivas, Donald Petravick, Adam Rebei, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Leo Singer, Brigitta M. Sipocz, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

CoRR, 2019

Eliminating artefacts in Polarimetric Images using Deep Learning.

Dhruv Paranjpye, Ashish Mahabal, A. N. Ramaprakash, Gina Panopoulou, Kieran Cleary, Anthony Readhead, Dmitry Blinov, Kostas Tassis

CoRR, 2019

New methods to assess and improve LIGO detector duty cycle.

Ayon Biswas, Jess McIver, Ashish Mahabal

CoRR, 2019

Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era.

Gabrielle Allen, Igor Andreoni, Etienne Bachelet, G. Bruce Berriman, Federica B. Bianco, Rahul Biswas, Matias Carrasco Kind, Kyle Chard, Minsik Cho, Philip S. Cowperthwaite, Zachariah B. Etienne, Daniel George, Tom Gibbs, Matthew J. Graham, William Gropp, Anushri Gupta, Roland Haas, Eliu A. Huerta, Elise Jennings, Daniel S. Katz, Asad Khan, Volodymyr V. Kindratenko, William T. C. Kramer, Xin Liu, Ashish Mahabal, Kenton McHenry, J. M. Miller, Mark S. Neubauer, Steve Oberlin, Alexander Reinefeld, Shawn Rosofsky, Milton Ruiz, Aaron Saxton, Bernard F. Schutz, Alexander G. Schwing, Ed Seidel, Stuart L. Shapiro, Hongyu Shen, Yue Shen, Brigitta Miksztai-Réthey, Lunan Sun, John Towns, Antonios Tsokaros, Wei Wei, Jack Wells, Timothy J. Williams, Jinjun Xiong, Zhizhen Zhao

CoRR, 2019

View-Adaptive Weighted Deep Transfer Learning for Distributed Time-Series Classification.

Sreyasee Das Bhattacharjee, William J. Tolone, Ashish Mahabal, Mohammed Elshambakey, Isaac Cho, S. George Djorgovski

Proceedings of the 43rd IEEE Annual Computer Software and Applications Conference, 2019

Multi-View, Generative, Transfer Learning for Distributed Time Series Classification.

Sreyasee Das Bhattacharjee, William J. Tolone, Ashish Mahabal, Mohammed Elshambakey, Isaac Cho, Abdullah al-Raihan Nayeem, Junsong Yuan, S. George Djorgovski

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Bigger Buffer k-d Trees on Multi-Many-Core Systems.

Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, Tom Heskes

Proceedings of the High Performance Computing for Computational Science - VECPAR 2018, 2018

Context-Aware Deep Sequence Learning with Multi-View Factor Pooling for Time Series Classification.

Sreyasee Das Bhattacharjee, William J. Tolone, Mohammed Elshambakey, Isaac Cho, Ashish Mahabal, S. George Djorgovski

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Effective Image Differencing with ConvNets for Real-time Transient Hunting.

Nima Sedaghat, Ashish Mahabal

CoRR, 2017

Photometric redshift estimation: An active learning approach.

Ricardo Vilalta, Emille E. O. Ishida, Róbert Beck, R. Sutrisno, Rafael S. de Souza, Ashish Mahabal

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Deep-learnt classification of light curves.

Ashish Mahabal, Kshiteej Sheth, Fabian Gieseke, Akshay Pai, S. George Djorgovski, Andrew J. Drake, Matthew J. Graham

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Massively-parallel best subset selection for ordinary least-squares regression.

Fabian Gieseke, Kai Lars Polsterer, Ashish Mahabal, Christian Igel, Tom Heskes

Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

2016

Modeling lightcurves for improved classification of astronomical objects.

Julian Faraway, Ashish Mahabal, Jiayang Sun, Xiao-Feng Wang, Yi G. Wang, Lingsong Zhang

Stat. Anal. Data Min., 2016

Real-time data mining of massive data streams from synoptic sky surveys.

S. George Djorgovski, Matthew J. Graham, Ciro Donalek, Ashish Mahabal, Andrew J. Drake, Michael J. Turmon, Thomas J. Fuchs

Future Gener. Comput. Syst., 2016

From Sky to Earth: Data Science Methodology Transfer.

Ashish Mahabal, Daniel J. Crichton, S. George Djorgovski, Emily Law, John S. Hughes

Proceedings of the Astroinformatics 2016, Sorrento, Italy, October 19-25, 2016, 2016

Detection of quasars in the time domain.

Matthew J. Graham, S. George Djorgovski, Daniel J. Stern, Andrew J. Drake, Ashish Mahabal

Proceedings of the Astroinformatics 2016, Sorrento, Italy, October 19-25, 2016, 2016

2015

AstroStat - A VO tool for statistical analysis.

Ajit K. Kembhavi, Ashish Mahabal, T. Kale, S. Jagade, Ajay M. Vibhute, Prerak Garg, Kaustubh Vaghmare, S. Navelkar, T. Agrawal, Asis Kumar Chattopadhyay, Deoyani Nandrekar, Mohasin Shaikh

Astron. Comput., 2015

Star Classification Under Data Variability: An Emerging Challenge in Astroinformatics.

Ricardo Vilalta, Kinjal Dhar Gupta, Ashish Mahabal

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

From stars to patients: Lessons from space science and astrophysics for health care informatics.

S. George Djorgovski, Ashish Mahabal, Daniel J. Crichton, Basit Chaudhry

Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

2014

Ten Simple Rules for the Care and Feeding of Scientific Data.

Alyssa Goodman, Alberto Pepe, Alexander W. Blocker, Christine L. Borgman, Kyle Cranmer, Mercè Crosas, Rosanne Di Stefano, Yolanda Gil, Paul Groth, Margaret L. Hedstrom, David W. Hogg, Vinay L. Kashyap, Ashish Mahabal, Aneta Siemiginowska, Aleksandra B. Slavkovic

PLoS Comput. Biol., 2014

10 Simple Rules for the Care and Feeding of Scientific Data.

Alyssa Goodman, Alberto Pepe, Alexander W. Blocker, Christine L. Borgman, Kyle Cranmer, Mercè Crosas, Rosanne Di Stefano, Yolanda Gil, Paul Groth, Margaret L. Hedstrom, David W. Hogg, Vinay L. Kashyap, Ashish Mahabal, Aneta Siemiginowska, Aleksandra B. Slavkovic

CoRR, 2014

Automated Real-Time Classification and Decision Making in Massive Data Streams from Synoptic Sky Surveys.

S. George Djorgovski, Ashish Mahabal, Ciro Donalek, Matthew J. Graham, Andrew J. Drake, Michael J. Turmon, Thomas J. Fuchs

Proceedings of the 10th IEEE International Conference on e-Science, 2014

Immersive and collaborative data visualization using virtual reality platforms.

Ciro Donalek, S. George Djorgovski, Alex Cioc, Anwell Wang, Jerry Zhang, Elizabeth Lawler, Stacy Yeh, Ashish Mahabal, Matthew J. Graham, Andrew J. Drake, Scott Davidoff, Jeffrey S. Norris, Giuseppe Longo

Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013

Feature Selection Strategies for Classifying High Dimensional Astronomical Data Sets.

Ciro Donalek, Arun Kumar A., S. George Djorgovski, Ashish Mahabal, Matthew J. Graham, Thomas J. Fuchs, Michael J. Turmon, N. Sajeeth Philip, Michael Ting-Chang Yang, Giuseppe Longo

CoRR, 2013

Feature selection strategies for classifying high dimensional astronomical data sets.

Ciro Donalek, S. George Djorgovski, Ashish Mahabal, Matthew J. Graham, Andrew J. Drake, Arun Kumar A., N. Sajeeth Philip, Thomas J. Fuchs, Michael J. Turmon, Michael Ting-Chang Yang, Giuseppe Longo

Proceedings of the 2013 IEEE International Conference on Big Data (IEEE BigData 2013), 2013

2012

Data challenges of time domain astronomy.

Matthew J. Graham, S. George Djorgovski, Ashish Mahabal, Ciro Donalek, Andrew J. Drake, Giuseppe Longo

Distributed Parallel Databases, 2012

Flashes in a star stream: Automated classification of astronomical transient events.

S. George Djorgovski, Ashish Mahabal, Ciro Donalek, Matthew J. Graham, Andrew J. Drake, Baback Moghaddam, Mike Turmon

Proceedings of the 8th IEEE International Conference on E-Science, 2012

Data Understanding using Semi-Supervised Clustering.

Vasudha Bhatnagar, Rashmi Dobariyal, Priya Jain, Ashish Mahabal

Proceedings of the 2012 Conference on Intelligent Data Understanding, 2012

2011

The DAME/VO-Neural Infrastructure: an Integrated Data Mining System Support for the Science Community

Massimo Brescia, Anna Corazza, Stefano Cavuoti, Giovanni D'Angelo, Raffaele D'Abrusco, Ciro Donalek, S. George Djorgovski, Natalia Deniskina, Michelangelo Fiore, Mauro Garofalo, Omar Laurino, Giuseppe Longo, Ashish Mahabal, Francesco Manna, Alfonso Nocella, B. Skordovski

CoRR, 2011

Towards an Automated Classification of Transient Events in Synoptic Sky Surveys.

S. George Djorgovski, Ciro Donalek, Ashish Mahabal, Baback Moghaddam, Mike Turmon, Matthew J. Graham, Andrew J. Drake, Nihar Sharma, Yutong Chen

Proceedings of the 2011 Conference on Intelligent Data Understanding, 2011

2010

DAME: A Web Oriented Infrastructure for Scientific Data Mining & Exploration

Massimo Brescia, Giuseppe Longo, S. George Djorgovski, Stefano Cavuoti, Raffaele D'Abrusco, Ciro Donalek, Alessandro Di Guido, Michelangelo Fiore, Mauro Garofalo, Omar Laurino, Ashish Mahabal, Francesco Manna, Alfonso Nocella, Giovanni D'Angelo, Maurizio Paolillo

CoRR, 2010

Comparing SVM ensembles for imbalanced datasets.

Vasudha Bhatnagar, Manju Bhardwaj, Ashish Mahabal

Proceedings of the 10th International Conference on Intelligent Systems Design and Applications, 2010

2006

Some Pattern Recognition Challenges in Data-Intensive Astronomy.

S. George Djorgovski, Ciro Donalek, Ashish Mahabal, R. Williams, Andrew J. Drake, Matthew J. Graham, E. Glikman

Proceedings of the 18th International Conference on Pattern Recognition (ICPR 2006), 2006