Shirley Ho Explained

Shirley Ho
Fields:Astrophysics, Deep Learning, Cosmology
Alma Mater:University of California, Berkeley, Princeton University
Thesis Title:Baryons, Universe and Everything Else in Between
Doctoral Advisor:David Spergel
Known For:dark matter, dark energy, Machine Learning in Astrophysics
Workplaces:Flatiron Institute, New York University

Shirley Ho is an American astrophysicist and machine learning researcher, currently at the Center for Computational Astrophysics at the Flatiron Institute, and an affiliated faculty at the Center for Data Science at New York University.[1] [2]

Biography

Ho graduated with a B.A. in physics and a B.A. in computer science from the University of California at Berkeley. She pursued her Ph.D. at the Department of Astrophysical Sciences of Princeton University.[3] In 2008 she obtained her doctorate in Astrophysical Sciences. Subsequently, she worked in the Lawrence Berkeley National Laboratory between 2008 and 2012 in a postdoctoral position as a Chamberlain and a Seaborg Fellow.

Ho worked at Carnegie Mellon University, first as an assistant professor and then as an associate (with indefinite tenure) professor in physics. Ho was named Cooper-Siegel Development Chair Professor in 2015 at Carnegie Mellon University.[4] In 2016, she moved back to the Lawrence Berkeley National Laboratory as a Senior Scientist while being on leave from Carnegie Mellon University.

In 2018, Ho joined the Simons Foundation as leader of the Cosmology X Data Science group[5] at the Center for Computational Astrophysics (CCA) at the Flatiron Institute.[6]

Research

Ho researches cosmology, deep learning and its applications in astrophysics and data science.[7] In particular, she is interested in developing and deploying deep learning to better understand the Universe, and other astrophysical phenomena.[8]

She has contributed to several areas of astrophysics: cosmic microwave background,[9] cosmological models, dark energy, dark matter,[10] [11] spatial distribution of galaxies and quasars,[12] Baryon Acoustic Oscillations,[13] [14] and cosmological simulations.[15]

Regarding deep learning and its and applications to cosmology and astrophysics.[16] [17] [18], Ho has been involved in the development of accelerated astrophysical simulations.[19] She took part in the development and deployment of deep-learning-accelerated simulation-based inference framework for large spectroscopic surveys,[20] and further accelerated physical simulations ranging from fluid dynamics to planetary dynamics simulations.[21] [22] [23] Her current team at the Flatiron Institute and Princeton University combines symbolic regression and neural networks to recover physical laws directly from observations, demonstrating symbolic regression as an example of good inductive bias for interpretable machine learning for science.[24] [25] [26]

While she almost always failed to balance her research interests in machine learning and the universe, her passion for science management has allowed her to attribute much of her scientific success to the students and collaborators she has been fortunate enough to work with.[27] Indeed, her ability to intercept scientific funding through connections with private foundations such as the Simons Foundation and the Schmidt Futures Foundation[28] culminates into the Polymathic AI[29] [30] funding endeavor.[31] Her team benefits from large enough resources to train large-scale machine learning models not only for astrophysics but also for Earth climate simulation,[32] which is generally hard to achieve in a non-commercial setting.[33] Her affiliations with multiple institutions, each with its own press department, ensure that she receives substantial media coverage, often in the form of first-person interviews that give her a direct platform to share her perspectives.[34] [35]

Prizes

Ho has won several prizes for her contributions to cosmology and astrophysics, including:

Notes and References

  1. Web site: 2017-10-06. Shirley Ho. 2020-09-13. Simons Foundation. en-US.
  2. Web site: Homepage of Shirley Ho. 2020-09-13. users.flatironinstitute.org.
  3. Web site: University. Carnegie Mellon. Shirley Ho - Department of Physics - Carnegie Mellon University. 2020-09-13. www.cmu.edu. en.
  4. Web site: University. Carnegie Mellon. Physicist Shirley Ho Receives Cooper-Siegel Professorship - Mellon College of Science - Carnegie Mellon University. 2020-10-30. www.cmu.edu. en. dead. https://web.archive.org/web/20200803014122/https://www.cmu.edu/mcs/news-events/2015/0428-Cooper-Siegel-Shirley-Ho.html. 2020-08-03.
  5. Web site: Cosmology X Data Science.
  6. News: James Simons's Foundation Starts New Institute for Computing, Big Data. The New York Times. 22 November 2016. Chang. Kenneth.
  7. Web site: Home . 2021-02-16 . users.flatironinstitute.org.
  8. Web site: 2019-06-26 . First AI Simulation of the Universe Is Fast and Accurate — and Its Creators Don't Know How It Works . 2021-02-16 . Simons Foundation . en-US.
  9. Ho . Shirley . Hirata . Christopher . Padmanabhan . Nikhil . Seljak . Uros . Bahcall . Neta . 2008-08-01 . Correlation of CMB with large-scale structure. I. Integrated Sachs-Wolfe tomography and cosmological implications . Physical Review D . 78 . 4 . 043519 . 0801.0642 . 2008PhRvD..78d3519H . 10.1103/PhysRevD.78.043519 . 1550-7998 . 38383124.
  10. Vagnozzi . Sunny . Giusarma . Elena . Mena . Olga . Freese . Katherine . Gerbino . Martina . Ho . Shirley . Lattanzi . Massimiliano . 2017-12-01 . Unveiling $\ensuremath$ secrets with cosmological data: Neutrino masses and mass hierarchy . Physical Review D . 96 . 12 . 123503 . 1701.08172 . 10.1103/PhysRevD.96.123503 . 119521570 . free.
  11. 0903.2845 . astro-ph.CO . Shirley . Ho . Simon . Dedeo . Finding the Missing Baryons Using CMB as a Backlight . 2009-03-01 . Spergel . David.
  12. Ho . Shirley . Cuesta . Antonio . Seo . Hee-Jong . de Putter . Roland . Ross . Ashley J. . White . Martin . Padmanabhan . Nikhil . Saito . Shun . Schlegel . David J. . Schlafly . Eddie . Seljak . Uros . 2012-12-01 . Clustering of Sloan Digital Sky Survey III Photometric Luminous Galaxies: The Measurement, Systematics, and Cosmological Implications . The Astrophysical Journal . 761 . 1 . 14 . 1201.2137 . 2012ApJ...761...14H . 10.1088/0004-637X/761/1/14 . 15716313.
  13. Anderson . Lauren . Aubourg . Éric . Bailey . Stephen . Beutler . Florian . Bhardwaj . Vaishali . Blanton . Michael . Bolton . Adam S. . Brinkmann . J. . Brownstein . Joel R. . Burden . Angela . Chuang . Chia-Hsun . 2014-06-11 . The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: baryon acoustic oscillations in the Data Releases 10 and 11 Galaxy samples . Monthly Notices of the Royal Astronomical Society . en . 441 . 1 . 24–62 . 1312.4877 . 2014MNRAS.441...24A . 10.1093/mnras/stu523 . 0035-8711 . 5011077 . free.
  14. Vargas-Magaña . Mariana . Ho . Shirley . Cuesta . Antonio J. . O'Connell . Ross . Ross . Ashley J. . Eisenstein . Daniel J. . Percival . Will J. . Grieb . Jan Niklas . Sánchez . Ariel G. . Tinker . Jeremy L. . Tojeiro . Rita . 2018-06-11 . The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: theoretical systematics and Baryon Acoustic Oscillations in the galaxy correlation function . Monthly Notices of the Royal Astronomical Society . 477 . 1 . 1153–1188 . 1610.03506 . 2018MNRAS.477.1153V . 10.1093/mnras/sty571 . 0035-8711 . 54838269 . free.
  15. Web site: The first AI universe sim is fast and accurate and its creators don't know how it works . 2020-09-13 . ScienceDaily . en.
  16. Ravanbakhsh . Siamak . 2016 . Estimating Cosmological Parameters from the Dark Matter Distribution . Proceedings of the 33rd International Conference on Machine Learning . 48 . 2407–2416 . 1711.02033.
  17. He . Siyu . Li . Yin . Feng . Yu . Ho . Shirley . Ravanbakhsh . Siamak . Chen . Wei . Póczos . Barnabás . 2019-07-09 . Learning to predict the cosmological structure formation . Proceedings of the National Academy of Sciences . en . 116 . 28 . 13825–13832 . 1811.06533 . 2019PNAS..11613825H . 10.1073/pnas.1821458116 . 0027-8424 . 6628645 . 31235606 . free.
  18. Wadekar . Digvijay . Villaescusa-Navarro . Francisco . Ho . Shirley . Perreault-Levasseur . Laurence . 2021 . HInet: Generating Neutral Hydrogen from Dark Matter with Neural Networks . The Astrophysical Journal . 916 . 1 . 42 . 2007.10340 . 2021ApJ...916...42W . 10.3847/1538-4357/ac033a . 220665447 . free.
  19. He . Siyu . 2019 . Learning to predict the cosmological structure formation . Proceedings of the National Academy of Sciences . 116 . 28 . 13825–13832 . 1811.06533 . 2019PNAS..11613825H . 10.1073/pnas.1821458116 . 6628645 . 31235606 . free.
  20. 2211.00723 . astro-ph.CO . Chang-Hoon . Hahn . SIMBIG : A Forward Modeling Approach To Analyzing Galaxy Clustering . 2022.
  21. Tamayo . Daniel . Cranmer . Miles . Hadden . Samuel . Rein . Hanno . Battaglia . Peter . Obertas . Alysa . Armitage . Philip J. . Ho . Shirley . Spergel . David N. . Gilbertson . Christian . Hussain . Naireen . 2020-08-04 . Predicting the long-term stability of compact multiplanet systems . Proceedings of the National Academy of Sciences . en . 117 . 31 . 18194–18205 . 2007.06521 . 2020PNAS..11718194T . 10.1073/pnas.2001258117 . 0027-8424 . 7414196 . 32675234 . free.
  22. 2006.11287 . cs.LG . Miles . Cranmer . Alvaro . Sanchez-Gonzalez . Discovering Symbolic Models from Deep Learning with Inductive Biases . 2020-06-19 . Battaglia . Peter . Xu . Rui . Cranmer . Kyle . Spergel . David . Ho . Shirley.
  23. 1910.07813 . astro-ph.CO . Jacky H. T. . Yip . Xinyue . Zhang . From Dark Matter to Galaxies with Convolutional Neural Networks . 2019-10-17 . Wang . Yanfang . Zhang . Wei . Sun . Yueqiu . Contardo . Gabriella . Villaescusa-Navarro . Francisco . He . Siyu . Genel . Shy . Ho . Shirley.
  24. Cranmer . Miles . 2020 . Discovering Symbolic Models from Deep Learning with Inductive Biases . NeurIPS 2020 . 2006.11287.
  25. Lemos . Pablo . Jeffrey . Niall . Cranmer . Miles . Ho . Shirley . Battaglia . Peter . 2022-02-04 . Rediscovering orbital mechanics with machine learning . Machine Learning: Science and Technology . 4 . 4 . 045002 . 2202.02306 . 2023MLS&T...4d5002L . 10.1088/2632-2153/acfa63 . 246607780.
  26. 2006.11287 . cs.LG . Miles . Cranmer . Alvaro . Sanchez-Gonzalez . Discovering Symbolic Models from Deep Learning with Inductive Biases . 2020-11-17 . Battaglia . Peter . Xu . Rui . Cranmer . Kyle . Spergel . David . Ho . Shirley.
  27. Web site: Artificial Intelligence . 2024-09-05 . Shirley Ho . en.
  28. Web site: Polymathic . 2024-09-07 . polymathic-ai.org.
  29. Web site: From Field to Fork: A Polymathic AI Journey to a More Sustainable Salsa . 2024-09-07 . www.linkedin.com . en.
  30. Web site: Polymathic AI . 2024-09-07 . www.envisioning.io . en.
  31. Web site: Breaking Boundaries with Polymathic AI: A Game-Changer for Researchers .
  32. Web site: 2023-10-16 . Scientists working on Polymathic AI, a new tool that will help make scientific discoveries . 2024-09-07 . The Indian Express . en.
  33. Web site: Stutz . David . 2024-03-27 . Thoughts on Academia and Industry in Machine Learning Research • David Stutz . 2024-09-07 . David Stutz . en-US.
  34. Web site: Science . NYU Center for Data . 2024-09-11 . Meet the Research Scientist: Shirley Ho . 2024-11-06 . Medium . en.
  35. Web site: Thomas . Sumner (Simons Foundation) . The first AI universe sim is fast and accurate—and its creators don't know how it works . Phys.org.
  36. Web site: Vu. Linda. 2018-05-14. Planck Collaboration Wins 2018 Gruber Cosmology Prize. 2024-09-06. Lawrence Berkeley National Laboratory. en.
  37. Web site: OYRA Award (MACRONIX PRIZE) OCPA. 2020-09-13. en-US. 4 July 2019. https://web.archive.org/web/20190704013158/http://ocpaweb.org/home/oyra-award-macronix-prize/. dead.
  38. Web site: SDSS Researcher Awarded for Outstanding Research. Sloan Digital Sky Survey. 2014-11-05. 2024-09-06. en-US.
  39. Web site: University. Carnegie Mellon. January 2015. Shirley Ho Wins Carnegie Science Award - Department of Physics - Carnegie Mellon University. 2020-09-13. www.cmu.edu. en.
  40. Web site: 2023-07-26 . Shirley Ho Named a Finalist for the 2023 Blavatnik National Awards for Young Scientists . 2023-08-23 . Simons Foundation . en-US.

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