Curriculum Vitae
CV
Education, research experience, honors, and publications.
Education
- Ph.D in Physics, University of São Paulo, 2019/2024
- M.S. degree in Physics, University Federal of São Carlos, 2016/2018
- B.S. degree in Physics, University of São Paulo, 2012/2015
Research experience
- 2025 - present: Postdoctoral Scholar
- UC Berkeley
- Supervisor: PhD Uros Seljak
- 2025 - present: Researcher Affiliate
- Berkeley Lab
- Supervisor: PhD Uros Seljak
- 2024 - 2024: Visiting Scholar Consultant
- Simons Foundation
- Supervisor: PhD Francisco Villaescusa-Navarro
- 2019 - 2024: Doctor degree in Physics
- University of São Paulo
- Supervisor: PhD Luis Raul Weber Abramo
- 2022 - 2023: Guest researcher/Research Intern Abroad/Predoc at CCA
- Simons Foundation/Flatiron Institute/CMB Analysis and Simulation group
- Supervisor: PhD Francisco Villaescusa-Navarro
- 2016 - 2018: Master degree in Physics
- University Federal of São Carlos
- Supervisor: PhD Raphael Santarelli
- 2017: Participation of event organizing committee
- University Federal of São Carlos
- XIII Semana de Física (XIII SeFís)
- 2014 - 2015: Undergrad Research
- University of São Paulo
- Project title: Introduction to particle physics with emphasis on quantum fluctuations
- Supervisor: Professor Attilio Cucchieri
- 2012: Undergrad Research
- University of São Paulo
- Project title: Synthesis and characterization of BaTi0.9Zr0.1O3 powders
- Supervisor: Professor Antonio Carlos Hernandes
- 2009 - 2011: Highschool Research
- University of São Paulo
- Project title: Study of superconductivity and development of a superconductor material
- Supervisor: Professor Antonio Carlos Hernandes
Honors and Awards
- Honorable Mention – 2025 ICTP-SAIFR PhD Prize in Classical Gravity and Applications – SBF, 2025
- Honorable Mention – José Leite Lopes Prize for Best Doctoral Thesis 2025 – SBF, 2025
- SBF Award for Best PhD Thesis in the Area of Particle and Fields Physics – SBF, 2025
- Outstanding PhD thesis – Postgraduate Award, IF, USP, 2025
- Honorable mention for an outstanding scientific article - Postgraduate Award, IF, USP, 2024
- First best poster award in Master’s degree - XIII Physics Week (XIII SeFís), 2017
- Certificate of merit - Best student of the 3rd year of high school, 2011
- Certificate of merit - Best student of the 8th grade elementary school II, 2008
- Silver medal - X Brazilian Astronomy and Astronautics Olympiad (X OBA), 2007
- Honorable mention - II Brazilian Olympiad of Mathematics of Public schools (II OBMEP), 2006
- Silver medal - VIII Brazilian Astronomy and Astronautics Olympiad (VIII OBA), 2005
Publications
- Unraveling Hawking radiation
Santi, Natali Soler Matubaro de, & Santarelli, Raphael. 2019. https://doi.org/10.1590/1806-9126-rbef-2018-0312
- Mass Evolution of Schwarzschild Black Holes
de Santi, N.S.M., Santarelli, R., 2019. https://doi.org/10.1007/s13538-019-00708-y
- A machine learning suite to halo-galaxy connection
de Santi, N. S. M. and et al., 2023
- Mimicking the halo-galaxy connection using machine learning
Natalí S. M. de Santi, et al. 2022, https://doi.org/10.1093/mnras/stac1469
- Improving cosmological covariance matrices with machine learning
de Santi, N. S. M. and Abramo, L. R. 2022, DOI:10.1088/1475-7516/2022/09/013
- Primeiros passos na obtenção de parâmetros cosmológicos utilizando matrizes de covariância cosmológicas sem ruído
de Santi, N. S. M. and Abramo, L. R. 2022, DOI: 10.5151/astrocientistas2021-11
- Robust field-level likelihood-free inference with galaxies
Natalí S. M. de Santi et al 2023 ApJ 952 69
- High-fidelity reproduction of central galaxy joint distributions with Neural Networks
Natália V N Rodrigues, Natalí S M de Santi, et al., 2023, https://doi.org/10.1093/mnras/stad1186
- A Hierarchy of Normalizing Flows for Modelling the Galaxy-Halo Relationship
Lovell, C. C., Hassan, S., Anglés-Alcázar, D., et al. 2023, arXiv:2307.06967. doi:10.48550/arXiv.2307.06967
- Obtaining cosmological covariance matrices with machine learning
de Santi, N. S. M. and Abramo, L. R. 2023
- A universal equation to predict Ωm from halo and galaxy catalogues
Shao, H., de Santi, N. S. M., Villaescusa-Navarro, F., et al. 2023, ApJ, 956, 2, 149. doi:10.3847/1538-4357/acee6f
- The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites
Ni, Y., Genel, S., Anglés-Alcázar, D., et al. 2023, ApJ, 959, 2, 136. doi:10.3847/1538-4357/ad022a
- Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects
de Santi, N. S. M., Villaescusa-Navarro, F., Raul Abramo, L., et al. 2025, JCAP. doi:10.1088/1475-7516/2025/01/082
- Exploring the halo-galaxy connection with probabilistic approaches
Rodrigues, N. V. N., de Santi, N. S. M., Abramo, R., et al. 2025, AAP. doi:10.1051/0004-6361/202453284
- Galaxy Phase-Space and Field-Level Cosmology: The Strength of Semi-Analytic Models
Natalí S. M. de Santi, Francisco Villaescusa-Navarro, Pablo Araya-Araya, et al. 2026, ApJ. doi:10.3847/1538-4357/ae84b4
- Predicting galaxy bias using machine learning
Riveros-Jara, C., Montero-Dorta, A. D., Rodrigues, N. V. N., et al. 2026, AAP, doi:10.1051/0004-6361/202659262
- Cosmology with one galaxy: An analytic formula relating Ωm with galaxy properties
Liao, K., Villaescusa-Navarro, F., Teyssier, R., et al. 2026, ApJ. doi:10.3847/1538-4357/ae64e3
Talks
- Development of a magnetic levitation system — September 30, 2011
Poster presentation at XIX Congresso de Iniciação Científica da UFSCar (XIX CIC), Federal University of São Carlos, São Carlos, SP, Brazil
- Synthesis and characterization of BaTi0.9Zr0.1O3 powders — October 23, 2012
Poster presentation at 20 Simpósio Internacional de Iniciação Científica (XX SIICUSP), University of São Paulo, São Paulo, SP, Brazil
- Numerical studies on the classical and quantum harmonic oscillator — October 01, 2014
Poster presentation at IV Semana Integrada do Instituto de Física de São Carlos (SIFSC 4), University of São Paulo, São Carlos, SP, Brazil
- Regularization techniques in the Casimir effect — October 01, 2015
Poster presentation at V Semana Integrada do Instituto de Física de São Carlos (SIFSC 5), University of São Paulo, São Carlos, SP, Brazil
- Observer dependence in the particle concept and the Unruh Effect — August 25, 2017
Poster presentation at XIII Semana de Física (XIII SeFís), Federal University of São Carlos, São Carlos, SP, Brazil
- Improving covariance matrices using machine learning — December 17, 2020
Oral poster presentation at Latin American Workshop on Observational Cosmology, International Centre for Theoretical Physics (ICTP) & South American Institute for Fundamental Research (SAIFR), São Paulo, SP, Brazil
- Improving Covariance Matrices using Machine Learning — December 17, 2020
Meeting - Poster presentation at Latin American Workshop on Observational Cosmology, Virtual meeting
- First steps in the obtation of the cosmological parameters using denoised cosmological covariance matrices — February 10, 2021
Oral communication at Astrocientistas I: Encontro Brasileiro de Meninas e Mulheres da Astrofísica, Gravitação e Cosmologia, Virtual meeting
- Using machine learning to mimic the halo-galaxy connection — March 03, 2022
Talk at Group Meeting: Prof. Francesco Shankar, University of Southampton, Southampton, UK
- A machine learning suite to mimic the halo-galaxy connection — June 01, 2022
International Conference - Poster presentation at International Conference on Machine Learning for Astrophysics - ML4Astro, Virtual participation - Catania, Italy
- Improving cosmological covariance matrices using machine learning — June 10, 2022
Talk at Journal Club: Astronomical Observatory of Trieste, I.N.A.F., Trieste, Italy
- Improving cosmological covariance matrices with machine learning — September 16, 2022
Talk at AI in Astronomy, IAG, USP, São Paulo, SP, Brazil
- Obtaining cosmological covariance matrices with machine learning — September 26, 2022
Oral presentation at XLV Reunião Anual da Sociedade Astronômica Brasileira, Virtual participation
- Graph neural networks for robust parameter inference in cosmology: the first steps before real data — October 04, 2022
Oral presentation at XLVI Reunião Anual da Sociedade Astronômica Brasileira, Planetário Rio, Rio de Janeiro, RJ, Brazil
- Inferring cosmological parameters using galaxies — December 01, 2022
Oral presentation at CAMELS Workshop, Simons Foundation, New York, NY, US
- Halo-galaxy connection and machine learning: an aerial view — December 06, 2022
Oral presentation at II mini-Workshop on the halo-galaxy connection for the South American community, Universidad Técnica Federico Santa María, Santiago, Chile
- Obtaining cosmological information through machine learning — January 27, 2023
Talk at Gothamfest 2023, Simons Foundation, New York, NY, US
- Constraining Ωm using galaxies — February 17, 2023
Talk at Galaxy Formation Group Meeting, Flatiron Institute, New York, NY, US
- Can we use galaxies to constrain 𝛀m? — March 14, 2023
Talk at Journal club: Berkeley Cosmology Group, UC Berkeley, Berkeley, CA, US
- Constraining Ωm with phase-space information of galaxies — March 21, 2023
Oral presentation at KITP Conference: Galaxy Formation and Evolution in the Data Science Era, UC Santa Barbara, Santa Barbara, CA, US
- Using graph neural networks to constrain Ωm - A robust model — April 03, 2023
Talk at Cosmology Lunch Talks, Institute of Advanced Studies (IAS), Princeton, NJ, US
- Simulation-based inference: constraining Ωm with galaxies phase-space information — April 14, 2023
Talkn at Tri-state Cosmology X Data Science Meeting, Flatiron Institute, New York, NY, US
- Doing Cosmology with galaxies — April 18, 2023
Talk at Pizza Lunch Talks, Columbia University, New York, NY, US
- Implicit likelihood inference: a robust model to constrain 𝛀m — April 19, 2023
Talk at Group Seminars - Prof. Bhuvnesh Jain, UPenn, Philadelphia, PA, US
- A robust model to constrain 𝛀m with implicit likelihood free-inference — May 01, 2023
Talk at Open Group Seminars - Prof. Cora Dvorkin, Harvard University, Cambridge, MA, US
- Implicit likelihood inference using graph neural networks: a robust model to constrain 𝛀m — May 16, 2023
Talk at Data-Science X Astro seminar, Yale University
- Field-level likelihood-free inference with galaxies: a robust model — May 22, 2023
Talk at Cosmology Seminar KIPAC, Stanford University, Santa Clara County, CA, US
- Unraveling Cosmology from field-level likelihood-free inference - A robust model — May 31, 2023
Talk at Renoir Science Seminar, Recherche Energie NOIRe (RENOIR), Marseille, France
- Cosmology from galaxy phase-space information and a bit of halo-galaxy connection — May 31, 2023
Talk at Grav Seminars, Gravitational Geometry and Dynamics research group, Aveiro, Portugal - Online
- Field-level simulation-based inference: using GNNs to get a robust model — June 02, 2023
Talk at CITA cosmology discussion, University of Toronto, Toronto, Canada
- Cosmology from field-level likelihood-free inference: The first steps towards real data — June 23, 2023
Oral presentation at Pre-doc symposium , Flatiron Institute, New York, NY, US
- How to use Machine Learning (to try) to understand the Universe — October 13, 2023
Oral presentation at III mini-Workshop on the halo-galaxy connection for the South American community, Universidad de Atacama, Copiapó, Chile
- Before real data: pressing graph neural networks to do field-level simulation-based inference with galaxies — November 01, 2023
Oral communication at ML-IAF/CCA-2023: Debating the potential of machine learning in astronomical surveys, CCA, New York, NY, US & IAP, Paris, France
- The Influence of Systematics on Galaxy Catalogs - looking for a robust model to do field-level likelihood-free inference — December 06, 2023
Talk at Seminários do CBPF/COTEC, CBPF, Rio de Janeiro, Brazil
- A proper probabilistic approach for halo-galaxy connection and likelihood-free parameter inference — January 26, 2024
Oral presentation at AI driven discovery in Physics and Astrophysics - CD3, UTokyo, UTokyo, Japan
- Measuring the impact of systematics on the predictions of 𝛀m on simulated galaxy catalogs using graph neural networks — February 27, 2024
Talk at Yale Astronomy Data Science Seminar, Yale University, New Haven, CT, US
- Measuring the impact of systematics on the predictions of 𝛀m on simulated galaxy catalogs using graph neural networks — March 04, 2024
Talk at ML Session of DoA, Tsinghua University, Beijing, China
- Graph neural networks for Cosmology — May 01, 2024
Talk at First Learning on Graphs (LOG) conference in South America, ICMC
- Cosmology with graph neural networks — August 16, 2024
Talk at SP Research Group meetings in Astro & Cosmo, Principia Institute
- The use of machine learning and artificial intelligence in astrophysics, cosmology, and gravitation researches — April 01, 2025
Talk at As astrocientistas: III Encontro Brasileiro de Meninas e Mulheres da Astrofísica, Gravitação e Cosmologia, Astrocientistas
- How to use graph neural networks to understand the Universe? — June 19, 2025
Talk at AstroGainz group meeting, Chile
- Learning Cosmology with Graph Neural Networks — October 07, 2025
Talk at BCCP Seminars, UC Berkeley, Berkeley, US
- The Universe from the perspective of machine learning and data science — November 03, 2025
Talk at Public talks, UPEI, Cairo, Egypt
Teaching and other activities
- Tutor Experience
- Private teacher
- Introdução à Relatividade
- Teaching Assistant of Basic Physics III
- Teaching Assistant of Classical Electrodynamics I
- Tutorial on Halo-galaxy connection
- Pytorch and GNNs tutorial
- Machine Learning for Cosmology and Cosmological Simulations
Skills
- Computer Languages
- Bash
- C
- Cython
- Fortran
- LateX
- Python
- Slurm
- Machine Learning
- Anomaly Detection (AD)
- Computer Vision (CV)
- Convolutional Neural Networks (CNN)
- Decision Trees (DT)
- Generative Artificial Intelligence (GenAI)
- Graph Neural Networks (GNN)
- Logistic Regression (LR)
- Moment Neural Networks (MNN)
- Natural Language Processing (NLP)
- Neural Networks (NN)
- Normalizing Flows (NF)
- Random Forest (RF)
- Recommendation Systems (RS)
- Regression Data Augmentation (SMOGN)
- Symbolic Regression (SR)
- Support Vector Machines (SVM)
- Stacked Models (SM)
- Tools
- Emacs
- Git (github)
- Jupyter Notebooks
- Linux
- Mathematica
- Docker
- APIs
- AWS
- Languages
- Native speaker in Portuguese
- Proeficient in English
- Beginner in Spanish
Refereeing
- New Astronomy (New Astron.) - 2024
- Monthly Notices of the Royal Astronomical Society (MNRAS) - 2022/2023/2025
- The Astrophysical Journal (ApJ) - 2023
- Journal of Cosmology and Astroparticle Physics (JCAP) - 2025
Research Supervision
- Veer Mehta. Undergrad research. UC Berkeley. Inference of halo properties from galaxy simulation data using machine learning.
- Tirthankar De. Undergrad research. Indian Institute of Technology Roorkee. Statistical and machine learning approaches for cosmological parameter inference.
Member of thesis and dissertation examination committees
- Jara, C. B. R.; MONTERO-DORTA, ANTONIO D; Amigo, P.; de Santi, N. S. M.; RODRIGUES, NATÁLIA V N. Member of undergraduate thesis of Catalina Belén Riveros Jara. The halo-galaxy connection through the lens of a machine: predicting galaxy clustering. 2025. Undergraduate thesis in Astrophysics - Universidad Tecnica Federico Santa Maria - Chile.