Nesar Ramachandra

Nesar Ramachandra

Computational Scientist, Argonne National Laboratory

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Pages

Posts

Blog Post number 4

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Blog Post number 3

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Blog Post number 2

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Blog Post number 1

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Published:

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portfolio

publications

Многопотоковый портрет космической паутины Н. Рамачандра и С. Шандарин (США)

Published in arXiv preprint arXiv:1412.7768, 2014

Google Scholar

Recommended citation: Nesar S Ramachandra and Sergei F Shandarin (2014). "Многопотоковый портрет космической паутины Н. Рамачандра и С. Шандарин (США)". arXiv preprint arXiv:1412.7768. https://scholar.google.com/scholar?cluster=18146240242250126125&hl=en&oi=scholarr

Tracing the cosmic web

Published in Monthly Notices of the Royal Astronomical Society, 2018

arXiv link

Recommended citation: Noam I. Libeskind, Rien van de Weygaert, Marius Cautun, Bridget Falck, Elmo Tempel, Tom Abel, Mehmet Alpaslan, Miguel A. Aragón-Calvo, Jaime E. Forero-Romero, Roberto Gonzalez, Stefan Gottlöber, Oliver Hahn, Wojciech A. Hellwing, Yehuda Hoffman, Bernard J. T. Jones, Francisco Kitaura, Alexander Knebe, Serena Manti, Mark Neyrinck, Sebastián E. Nuza, Nelson Padilla, Erwin Platen, Nesar Ramachandra , Aaron Robotham, Enn Saar, Sergei Shandarin, Matthias Steinmetz, Radu S. Stoica, Thierry Sousbie, Gustavo Yepes; Tracing the cosmic web, Monthly Notices of the Royal Astronomical Society , Volume 473, Issue 1, 1 January 2018, Pages 1195–1217 https://doi.org/10.1093/mnras/stx1976

Tracing the cosmic web

Published in Monthly Notices of the Royal Astronomical Society, 2018

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Recommended citation: Noam I Libeskind and Rien Van De Weygaert and Marius Cautun and Bridget Falck and Elmo Tempel and Tom Abel and Mehmet Alpaslan and Miguel A Aragón-Calvo and Jaime E Forero-Romero and Roberto Gonzalez and Stefan Gottlöber and Oliver Hahn and Wojciech A Hellwing and Yehuda Hoffman and Bernard JT Jones and Francisco Kitaura and Alexander Knebe and Serena Manti and Mark Neyrinck and Sebastián E Nuza and Nelson Padilla and Erwin Platen and Nesar Ramachandra and Aaron Robotham and Enn Saar and Sergei Shandarin and Matthias Steinmetz and Radu S Stoica and Thierry Sousbie and Gustavo Yepes (2018). "Tracing the cosmic web". Monthly Notices of the Royal Astronomical Society. https://academic.oup.com/mnras/article-abstract/473/1/1195/4062204

A modular deep learning pipeline for galaxy-scale strong gravitational lens detection and modeling

Published in arXiv preprint arXiv:1911.03867, 2019

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Recommended citation: Sandeep Madireddy and Nesar Ramachandra and Nan Li and James Butler and Prasanna Balaprakash and Salman Habib and Katrin Heitmann and LSST Dark Energy Science Collaboration (2019). "A modular deep learning pipeline for galaxy-scale strong gravitational lens detection and modeling". arXiv preprint arXiv:1911.03867. https://arxiv.org/abs/1911.03867

The SPTPoL extended cluster survey

Published in The Astrophysical Journal Supplement Series, 2020

Google Scholar

Recommended citation: LE Bleem and S Bocquet and B Stalder and Michael D Gladders and PAR Ade and SW Allen and AJ Anderson and James Annis and MLN Ashby and JE Austermann and S Avila and JS Avva and M Bayliss and JA Beall and K Bechtol and AN Bender and BA Benson and E Bertin and F Bianchini and C Blake and M Brodwin and D Brooks and E Buckley-Geer and DL Burke and JE Carlstrom and A Carnero Rosell and M Carrasco Kind and J Carretero and CL Chang and HC Chiang and R Citron and C Corbett Moran and M Costanzi and TM Crawford and LN da Costa and T de Haan and J De Vicente and S Desai and HT Diehl and JP Dietrich and MA Dobbs and TF Eifler and W Everett and B Flaugher and B Floyd and J Frieman and J Gallicchio and J García-Bellido and EM George and DW Gerdes and A Gilbert and D Gruen and RA Gruendl and J Gschwend and N Gupta and G Gutierrez and NW Halverson and N Harrington and JW Henning and C Heymans and GP Holder and DL Hollowood and WL Holzapfel and K Honscheid and JD Hrubes and N Huang and J Hubmayr and KD Irwin and DJ James and T Jeltema and S Joudaki and G Khullar and M Klein and L Knox and N Kuropatkin and AT Lee and D Li and C Lidman and A Lowitz and N MacCrann and G Mahler and MAG Maia and JL Marshall and M McDonald and JJ McMahon and P Melchior and F Menanteau and SS Meyer and R Miquel and LM Mocanu and JJ Mohr and J Montgomery and A Nadolski and T Natoli and JP Nibarger and G Noble and V Novosad and S Padin and A Palmese and D Parkinson and S Patil and F Paz-Chinchón and AA Plazas and C Pryke and NS Ramachandra and CL Reichardt and JD Remolina González and AK Romer and A Roodman and JE Ruhl and ES Rykoff and BR Saliwanchik and E Sanchez and A Saro and JT Sayre and KK Schaffer and T Schrabback and S Serrano and K Sharon and C Sievers and G Smecher and M Smith and M Soares-Santos and AA Stark and KT Story and E Suchyta and G Tarle and C Tucker and K Vanderlinde and T Veach and JD Vieira and G Wang and Jochen Weller and N Whitehorn and WLK Wu and V Yefremenko and Y Zhang (2020). "The SPTPoL extended cluster survey". The Astrophysical Journal Supplement Series. https://iopscience.iop.org/article/10.3847/1538-4365/ab6993/meta

VizieR Online Data Catalog: The SPTpol Extended Cluster Survey (Bleem+, 2020)

Published in VizieR Online Data Catalog, 2020

Google Scholar

Recommended citation: LE Bleem and S Bocquet and B Stalder and MD Gladders and PAR Ade and SW Allen and AJ Anderson and J Annis and MLN Ashby and JE Austermann and S Avila and JS Avva and M Bayliss and JA Beall and K Bechtol and AN Bender and BA Benson and E Bertin and F Bianchini and C Blake and M Brodwin and D Brooks and E Buckley-Geer and DL Burke and JE Carlstrom and A Carnero Rosell and M Carrasco Kind and J Carretero and CL Chang and HC Chiang and R Citron and C Corbett Moran and M Costanzi and TM Crawford and LN da Costa and T de Haan and S Desai and HT Diehl and JP Dietrich and MA Dobbs and TF Eifler and W Everett and B Flaugher and B Floyd and J Frieman and J Gallicchio and J Garcia-Bellido and EM George and DW Gerdes and A Gilbert and D Gruen and RA Gruendl and J Gschwend and N Gupta and G Gutierrez and NW Halverson and N Harrington and JW Henning and C Heymans and GP Holder and DL Hollowood and WL Holzapfel and K Honscheid and JD Hrubes and N Huang and J Hubmayr and KD Irwin and DJ James and T Jeltema and S Joudaki and G Khullar and M Klein and L Knox and AT Lee and D Li and C Lidman and A Lowitz and N Maccrann and G Mahler and MAG Maia and JL Marshall and M McDonald and JJ McMahon and P Melchior and F Menanteau and SS Meyer and R Miquel and LM Mocanu and JJ Mohr and J Montgomery and A Nadolski and T Natoli and JP Nibarger and G Noble and V Novosad and S Padin and A Palmese and D Parkinson and S Patil and F Paz-Chinchon and AA Plazas and C Pryke and NS Ramachandra and CL Reichardt and JD Remolina Gonzalez and AK Romer and A Roodman and JE Ruhl and ES Rykoff and BR Saliwanchik and E Sanchez and A Saro and JT Sayre and KK Schaffer and T Schrabback and S Serrano and K Sharon and C Sievers and G Smecher and M Smith and M Soares-Santos and AA Stark and KT Story and E Suchyta and G Tarle and C Tucker and K Vanderlinde and T Veach and JD Vieira and G Wang and J Weller and N Whitehorn and WLK Wu and V Yefremenko and Y Zhang (2020). "VizieR Online Data Catalog: The SPTpol Extended Cluster Survey (Bleem+, 2020)". VizieR Online Data Catalog. https://ui.adsabs.harvard.edu/abs/2020yCat..22470025B/abstract

A Modular Deep Learning Pipeline for Galaxy-Scale Strong Gravitational Lens Detection and Modeling

Published in Machine Learning and the Physical Sciences Workshop at the 33rd Conference on Neural Information Processing Systems (2019), 2020

arXiv link

Recommended citation: Sandeep Madireddy, Nan Li, Nesar Ramachandra , James Butler, Prasanna Balaprakash, Salman Habib, Katrin Heitmann; A Modular Deep Learning Pipeline for Galaxy-Scale Strong Gravitational Lens Detection and Modeling, Machine Learning and the Physical Sciences Workshop at the 33rd Conference on Neural Information Processing Systems (2019) https://arxiv.org/abs/1911.03867

Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks

Published in Monthly Notices of the Royal Astronomical Society, 2021

Google Scholar

Recommended citation: Kate Storey-Fisher and Marc Huertas-Company and Nesar Ramachandra and Francois Lanusse and Alexie Leauthaud and Yifei Luo and Song Huang and J Xavier Prochaska (2021). "Anomaly detection in Hyper Suprime-Cam galaxy images with generative adversarial networks". Monthly Notices of the Royal Astronomical Society. https://academic.oup.com/mnras/article-abstract/508/2/2946/6369368

Beyond the hubble sequence–exploring galaxy morphology with unsupervised machine learning

Published in Monthly Notices of the Royal Astronomical Society, 2021

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Recommended citation: Ting-Yun Cheng and Marc Huertas-Company and Christopher J Conselice and Alfonso Aragon-Salamanca and Brant E Robertson and Nesar Ramachandra (2021). "Beyond the hubble sequence–exploring galaxy morphology with unsupervised machine learning". Monthly Notices of the Royal Astronomical Society. https://academic.oup.com/mnras/article-abstract/503/3/4446/6168393

Peculiar velocity estimation from kinetic SZ effect using deep neural networks

Published in Monthly Notices of the Royal Astronomical Society, 2021

Google Scholar

Recommended citation: Yuyu Wang and Nesar Ramachandra and Edgar M Salazar-Canizales and Hume A Feldman and Richard Watkins and Klaus Dolag (2021). "Peculiar velocity estimation from kinetic SZ effect using deep neural networks". Monthly Notices of the Royal Astronomical Society. https://academic.oup.com/mnras/article-abstract/506/1/1427/6307032

Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z

Published in Monthly Notices of the Royal Astronomical Society, 2022

Google Scholar

Recommended citation: Nesar Ramachandra and Jonás Chaves-Montero and Alex Alarcon and Arindam Fadikar and Salman Habib and Katrin Heitmann (2022). "Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z". Monthly Notices of the Royal Astronomical Society. https://academic.oup.com/mnras/article-abstract/515/2/1927/6623680

Over 2.7 Million Carbon-Enhanced Metal-Poor stars from BP/RP Spectra in $ Gaia $ DR3

Published in arXiv e-prints, 2022

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Recommended citation: Madeline Lucey and Nariman Al Kharusi and Keith Hawkins and Yuan-Sen Ting and Nesar Ramachandra and Timothy C Beers and Young Sun Lee and Adrian M Price-Whelan and Jinmi Yoon (2022). "Over 2.7 Million Carbon-Enhanced Metal-Poor stars from BP/RP Spectra in $ Gaia $ DR3". arXiv e-prints. https://scholar.google.com/scholar?cluster=6329097045594348&hl=en&oi=scholarr

Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z

Published in Monthly Notices of the Royal Astronomical Society, 2022

arXiv link

Recommended citation: Nesar Ramachandra , Jonás Chaves-Montero, Alex Alarcon, Arindam Fadikar, Salman Habib, Katrin Heitmann; Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z , Monthly Notices of the Royal Astronomical Society, Volume 515, Issue 2, September 2022, Pages 1927–1941 https://doi.org/10.1093/mnras/stac1790

Interpretable Uncertainty Quantification in AI for HEP

Published in Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021, Submitted), 2022

arXiv link

Recommended citation: Thomas Y. Chen, Biprateep Dey, Aishik Ghosh, Michael Kagan, Brian Nord, Nesar Ramachandra ; Interpretable Uncertainty Quantification in AI for HEP, Submitted to the Proceedings of the US Community Study on the Future of Particle Physics (Snowmass 2021) https://doi.org/10.48550/arXiv.2208.03284

2023 AI Testbed Expeditions Report

Published in Preprint, 2023

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Recommended citation: Venkat Vishwanath and Murali Emani and Varuni Sastry and William Arnold and Rajeev Thakur and Valerie Taylor and Ian Foster and Salman Habib and Michael E Papka and Bryce Allen and Henry Chan and Rodrigo Ceccato de Freitas and Mathew J Cherukara and Miaoqi Chu and Jose M Monsalve Diaz and Neil Getty and Ross Harder and Kyle Hippe and Saugat Kandel and Antonino Miceli and Suresh Narayanan and Oleksandr Narykov and Alexander Partin and Nesar Ramachandra and Arvind Ramanathan and Esteban Rangel and Siddhisanket Raskar and Andrew Siegel and John Tramm and Thomas Uram and Azton Wells and Leighton Wilson and Fangfang Xia and Kazutomo Yoshii and Ruoxi Zhao and Tao Zhou (2023). "2023 AI Testbed Expeditions Report". Preprint. https://www.osti.gov/servlets/purl/2439992

Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field

Published in arXiv preprint arXiv:2303.16869, 2023

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Recommended citation: Lele Luan and Nesar Ramachandra and Sandipp Krishnan Ravi and Anindya Bhaduri and Piyush Pandita and Prasanna Balaprakash and Mihai Anitescu and Changjie Sun and Liping Wang (2023). "Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field". arXiv preprint arXiv:2303.16869. https://arxiv.org/abs/2303.16869

Carbon-enhanced metal-poor star candidates from BP/RP spectra in Gaia DR3

Published in Monthly Notices of the Royal Astronomical Society, 2023

Google Scholar

Recommended citation: Madeline Lucey and Nariman Al Kharusi and Keith Hawkins and Yuan-Sen Ting and Nesar Ramachandra and Adrian M Price-Whelan and Timothy C Beers and Young Sun Lee and Jinmi Yoon (2023). "Carbon-enhanced metal-poor star candidates from BP/RP spectra in Gaia DR3". Monthly Notices of the Royal Astronomical Society. https://academic.oup.com/mnras/article-abstract/523/3/4049/7191262

Constructing impactful machine learning research for astronomy: Best practices for researchers and reviewers

Published in arXiv preprint arXiv:2310.12528, 2023

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Recommended citation: Daniela Huppenkothen and Michelle Ntampaka and Matthew Ho and Morgan Fouesneau and Brian Nord and Joshua EG Peek and Mike Walmsley and John F Wu and Camille Avestruz and Tobias Buck and Massimo Brescia and Douglas P Finkbeiner and Andy D Goulding and Tomasz Kacprzak and Peter Melchior and Mario Pasquato and Nesar Ramachandra and Y-S Ting and Glenn van de Ven and Soledad Villar and VA Villar and Elad Zinger (2023). "Constructing impactful machine learning research for astronomy: Best practices for researchers and reviewers". arXiv preprint arXiv:2310.12528. https://arxiv.org/abs/2310.12528

Scalable Probabilistic Modeling and Machine Learning With Dimensionality Reduction for Expensive High-Dimensional Problems

Published in Preprint, 2023

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Recommended citation: Lele Luan and Nesar Ramachandra and Sandipp Krishnan Ravi and Anindya Bhaduri and Piyush Pandita and Prasanna Balaprakash and Mihai Anitescu and Changjie Sun and Liping Wang (2023). "Scalable Probabilistic Modeling and Machine Learning With Dimensionality Reduction for Expensive High-Dimensional Problems". Preprint. https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2023/87295/1170365

AstroMLab 3: Achieving GPT-4o Level Performance in Astronomy with a Specialized 8B-Parameter Large Language Model

Published in arXiv preprint arXiv:2411.09012, 2024

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Recommended citation: Tijmen de Haan and Yuan-Sen Ting and Tirthankar Ghosal and Tuan Dung Nguyen and Alberto Accomazzi and Azton Wells and Nesar Ramachandra and Rui Pan and Zechang Sun (2024). "AstroMLab 3: Achieving GPT-4o Level Performance in Astronomy with a Specialized 8B-Parameter Large Language Model". arXiv preprint arXiv:2411.09012. https://arxiv.org/abs/2411.09012

Benchmarking AI-evolved cosmological structure formation and expanding dimensions through parallelization frameworks

Published in APS April Meeting Abstracts, 2024

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Recommended citation: Xiaofeng Dong and Nesar Ramachandra and Azton Wells and Michael Buehlmann and Salman Habib and Katrin Heitmann (2024). "Benchmarking AI-evolved cosmological structure formation and expanding dimensions through parallelization frameworks". APS April Meeting Abstracts. https://ui.adsabs.harvard.edu/abs/2024APS..APRKK3006D/abstract

Efficient mapping between void shapes and stress fields using deep convolutional neural networks with sparse data

Published in Journal of Computing and Information Science in Engineering, 2024

Google Scholar

Recommended citation: Anindya Bhaduri and Nesar Ramachandra and Sandipp Krishnan Ravi and Lele Luan and Piyush Pandita and Prasanna Balaprakash and Mihai Anitescu and Changjie Sun and Liping Wang (2024). "Efficient mapping between void shapes and stress fields using deep convolutional neural networks with sparse data". Journal of Computing and Information Science in Engineering. https://asmedigitalcollection.asme.org/computingengineering/article/24/5/051008/1195153

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Published in Journal of Mechanical Design, 2025

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Recommended citation: Anirban Samaddar and Sandipp Krishnan Ravi and Nesar Ramachandra and Lele Luan and Sandeep Madireddy and Anindya Bhaduri and Piyush Pandita and Changjie Sun and Liping Wang (2025). "Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields". Journal of Mechanical Design. https://asmedigitalcollection.asme.org/mechanicaldesign/article/147/3/031701/1202979

EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants

Published in arXiv preprint arXiv:2502.20309, 2025

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Recommended citation: Franck Cappello and Sandeep Madireddy and Robert Underwood and Neil Getty and Nicholas Lee-Ping Chia and Nesar Ramachandra and Josh Nguyen and Murat Keceli and Tanwi Mallick and Zilinghan Li and Marieme Ngom and Chenhui Zhang and Angel Yanguas-Gil and Evan Antoniuk and Bhavya Kailkhura and Minyang Tian and Yufeng Du and Yuan-Sen Ting and Azton Wells and Bogdan Nicolae and Avinash Maurya and M Mustafa Rafique and Eliu Huerta and Bo Li and Ian Foster and Rick Stevens (2025). "EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants". arXiv preprint arXiv:2502.20309. https://arxiv.org/abs/2502.20309

talks

teaching

Graduate Teaching Assistant

Department of Physics and Astronomy, University of Kansas, 2014

  • Fall 2017 - PHSX 214 (General Physics II Honors)
  • Fall 2016 - PHSX 214 (General Physics II Honors)
  • Spring 2015 - PHSX 216 (General Physics I)
  • Fall 2014 - PHSX 114 (College Physics I)

Head Teaching Assistant

Department of Physics and Astronomy, University of Kansas, 2015

Coordinated Teaching Assistants in the Department. Managed performance analysis on labs and quizzes of nearly 4000 students in 12 courses.

  • Summer 2016
  • Spring​ ​2016
  • Fall​ ​2015​