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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
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Posts
Blog Post number 4
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Blog Post number 3
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Blog Post number 1
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portfolio
Structures in the Dark matter Universe
Structures in the multi-stream view of the Universe 
Deep learning pipelines for Astrophysics
Strong lensing image under multiple layers in a Convolutional Neural Network 
publications
Multi-stream portrait of the cosmic web
Published in Monthly Notices of the Royal Astronomical Society, 2015
Recommended citation: Nesar S. Ramachandra , Sergei F. Shandarin; Multi-stream portrait of the cosmic web, Monthly Notices of the Royal Astronomical Society , Volume 452, Issue 2, 11 September 2015, Pages 1643–1653 https://doi.org/10.1093/mnras/stv1389
Topology and geometry of the dark matter web: a multistream view
Published in Monthly Notices of the Royal Astronomical Society, 2017
Recommended citation: Nesar S. Ramachandra, Sergei F. Shandarin; Topology and geometry of the dark matter web: a multistream view, Monthly Notices of the Royal Astronomical Society, Volume 467, Issue 2, 21 May 2017, Pages 1748–1762 https://doi.org/10.1093/mnras/stx183
Dark matter haloes: a multistream view
Published in Monthly Notices of the Royal Astronomical Society, 2017
Recommended citation: Nesar S. Ramachandra , Sergei F. Shandarin; Dark matter haloes: a multistream view, Monthly Notices of the Royal Astronomical Society, Volume 470, Issue 3, 21 September 2017, Pages 3359–3373 https://doi.org/10.1093/mnras/stx1474
Tracing the cosmic web
Published in Monthly Notices of the Royal Astronomical Society, 2018
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
Matter Power Spectrum Emulator for f(R) Modified Gravity Cosmologies
Published in Phys. Rev. D 103, 123525 (2020), 2020
Recommended citation: Nesar Ramachandra , Georgios Valogiannis, Mustapha Ishak, Katrin Heitmann (for the LSST Dark Energy Science Collaboration); Matter Power Spectrum Emulator for f(R) Modified Gravity Cosmologies, Phys. Rev. D 103, 123525 (2020) https://doi.org/10.1103/PhysRevD.103.123525
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
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
Probabilistic neural networks for fluid flow surrogate modeling and data recovery
Published in Phys. Rev. Fluids 5, 104401 (2020), 2020
Recommended citation: Romit Maulik, Kai Fukami, Nesar Ramachandra , Koji Fukagata, Kunihiko Taira; A Modular Deep Learning Pipeline for Galaxy-Scale Strong Gravitational Lens Detection and Modeling, Phys. Rev. Fluids 5, 104401 (2020) https://doi.org/10.1103/PhysRevFluids.5.104401
Peculiar Velocity Estimation from Kinetic SZ Effect using Deep Neural Networks
Published in Monthly Notices of the Royal Astronomical Society (2021), 2021
Recommended citation: Yuyu Wang, Nesar Ramachandra , Edgar M. Salazar-Canizales, Hume A. Feldman, Richard Watkins, Klaus Dolag; Peculiar Velocity Estimation from Kinetic SZ Effect using Deep Neural Networks, Monthly Notices of the Royal Astronomical Society (2021) https://doi.org/10.1093/mnras/stab1715
Physical Benchmarking for AI-Generated Cosmic Web
Published in Neural Information Processing Systems (NeurIPS) 2021 AI for Science Workshop (2021), 2021
Recommended citation: Xiaofeng Dong, Nesar Ramachandra , Salman Habib, Katrin Heitmann, Michael Buehlmann, Sandeep Madireddy; Physical Benchmarking for AI-Generated Cosmic Web, Neural Information Processing Systems (NeurIPS) 2021 AI for Science Workshop (2021) https://arxiv.org/abs/2112.05681
Machine learning synthetic spectra for probabilistic redshift estimation: SYTH-Z
Published in Monthly Notices of the Royal Astronomical Society, 2022
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
Differentiable Predictions for Large Scale Structure with SHAMNet
Published in The Open Journal of Astrophysics, 2022
Recommended citation: Andrew P. Hearin, Nesar Ramachandra , Matthew R. Becker, Joseph DeRose; Differentiable Predictions for Large Scale Structure with SHAMNet, The Open Journal of Astrophysics, Vol. 5, 2022 https://doi.org/10.21105/astro.2112.08423
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
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
talks
teaching
Undergraduate Teaching Assistant
Department of Physics, BITS-Pilani, 2011
- Fall 2011 - PHYC242 (Theory of Relativity)
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