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Employment

Kavli IPMU, University of Tokyo2024–present
Project Assistant Professor (tenure-track) in Center for Data-Driven Discovery (CD3)

Education

Princeton University, Physics, PhD2019–2024
advisor: David N. Spergel
thesis: Getting ready for new Data: Approaches to some Challenges in Cosmology

Perimeter Institute, Theoretical Physics, MSc2018–2019
advisor: Kendrick M. Smith, co-advisor: J. Colin Hill
thesis: Capturing non-Gaussianity: Analytic model for the one-point probability distribution function of cosmological fields within the halo model

University of Oxford, Physics, BA First Class2015–2018
ranked top of the cohort ( ∼ 130 students) in years 2 and 3

Honors

Kusaka Memorial Prize in Physics (Princeton) $3000 2022
Member of the German Academic Scholarship Foundation €35k 2015–2019
Perimeter Scholars International Award (Perimeter) CA$45k 2018
Scott Prize for best performance in the 3rd year (Oxford) £400 2018
Winton Capital Prize for best performance in the 2nd year (Oxford) £250 2017
BP Scholarship (Oxford) £2000 2017
Rokos Award for summer research project (Oxford) £800 2016

Funding

JST PRESTO JPMJPR26287514, Human-AI Collaboration for Theoretical Physics ¥40M 2026-2029
FUTI Travel Award ¥350k 2026
JSPS KAKENHI 26K17136 (early-career), Reconstruction of the Local Universe with Machine Learning ¥3.5M 2026-2027
Royal Society International Collaboration Award Round 2 (Japan) 252140, with William Coulton, Transformative joint analyses of transformative datasets £225k 2026-2029
Google Research Ecosystem Grant for IPMU CD3 ¥11M 2025-2026
JSPS KAKENHI 24K22878 (research-activity startup), AI staring into the void ¥3M 2024-2025

Teaching

Astro-AI Asia Network summer school, Taipei organizer 2026
10th Vietnam School of Astrophysics, Quy Nhon Machine Learning 2026
Lecture for UTokyo GUC Scientific Programming 2026
Lectures for UTokyo class Cosmological Data Analysis 2026
Astro-AI Asia Network summer school, Seoul co-organizer 2025
Lecture for UTokyo GUC Scientific Programming 2025
Lecture & Tutorial for ILANCE students, IPMU Introduction to Machine Learning 2025
Astro-AI Asia Network summer school, Osaka Basic Deep Learning 2024

Advising

Alexis Tastet (Ecole Polytechnique Masters) visitor 2026
Miguel Ruiz Granda (UCantabria PhD) assisted visitor 2026-
Kristers Nagainis (Latvia/Leiden PhD) assisted visitor 2026-
Di He (UTokyo PhD) assisted 2025-
Lillie Szemraj (Princeton undergrad) assisted visitor 2025
Felicia Xiao (MIT undergrad) visitor 2025
Baptiste Barthe-Gold (Ecole Polytechnique Masters) visitor 2025
Jessica Cowell (Oxford DPhil → Manchester PD) assisted 2024-2025
Akira Tokiwa (UTokyo PhD → industry) assisted 2024-2025
Cooper Jacobus (UC Berkeley undergrad → Stanford PhD) visitor 2024
Bonny Wang (CMU Masters → UChicago PhD) visitor 2024-

Service

reviewer for ApJ, MNRAS, PRD, JCAP, NeurIPS ML4PS, ICML ML4Astro, ICML AI4Physics

Publications

Citations: 1597, h-index: 21 (INSPIRE-HEP, as of 2026-09-17)

1st author

  1. L. Thiele,
    Machine Learning Techniques for Astrophysics and Cosmology: Simulation-Based Inference,
    2026, arXiv:2605.10719 [astro-ph.CO], Invited chapter for the edited book "Machine Learning Techniques for Astrophysics and Cosmology" ( Eds. C. Bambi, V. Kashyap, S. Shashank, N. Yoshida, Springer Singapore, expected in 2026)
  2. L. Thiele,
    Bayesian Cosmic Void Finding with Graph Flows,
    2026, OJAp 9, arXiv:2602.14630 [astro-ph.CO], poster at ICML 2026 AI4Physics workshop
  3. L. Thiele, A.E. Bayer, N. Takeishi,
    Simulation-Efficient Cosmological Inference with Multi-Fidelity SBI,
    2025, arXiv:2507.00514 [astro-ph.CO], poster at ML4Astro workshop (colocated with ICML 2025)
  4. L. Thiele,
    De-baryonifying halos via optimal transport,
    2024, arXiv:2411.18399 [astro-ph.CO]
  5. L. Thiele, E. Massara, A. Pisani, C. Hahn, D.N. Spergel, S. Ho, B. Wandelt,
    Neutrino mass constraint from an Implicit Likelihood Analysis of BOSS voids,
    2024, ApJ 969, 89, arXiv:2307.07555 [astro-ph.CO]
  6. L. Thiele, G.A. Marques, J. Liu, M. Shirasaki,
    Cosmological constraints from HSC Y1 lensing convergence PDF,
    2023, PRD 108, 123526, arXiv:2304.05928 [astro-ph.CO]
  7. L. Thiele, M. Cranmer, W. Coulton, S. Ho, D.N. Spergel,
    Predicting the Thermal Sunyaev-Zel’dovich Field using Modular and Equivariant Set-Based Neural Networks,
    2022, MLST 3, 035002, arXiv:2203.00026 [astro-ph.CO], poster at the Fourth Workshop on Machine Learning and the Physical Sciences (NeurIPS 2021)
  8. L. Thiele, D. Wadekar, J.C. Hill, N. Battaglia, J. Chluba, F. Villaescusa-Navarro, L. Hernquist, M. Vogelsberger, D. Anglés-Alcázar, F. Marinacci,
    Percent-level constraints on baryonic feedback with spectral distortion measurements,
    2022, PRD 105, 083505, arXiv:2201.01663 [astro-ph.CO]
  9. L. Thiele, Y. Guan, J.C. Hill, A. Kosowsky, D.N. Spergel,
    Can small-scale baryon inhomogeneities resolve the Hubble tension? An investigation with ACT DR4,
    2021, PRD 104, 063535, arXiv:2105.03003 [astro-ph.CO]
  10. L. Thiele, J.C. Hill, K.M. Smith,
    Accurate Analytic Model for the Weak Lensing Convergence One-Point Probability Distribution Function and its Auto-Covariance,
    2020, PRD 102, 123545, arXiv:2009.06547 [astro-ph.CO]
  11. L. Thiele, F. Villaescusa-Navarro, D.N. Spergel, D. Nelson, A. Pillepich,
    Teaching neural networks to generate Fast Sunyaev Zel’dovich Maps,
    2020, ApJ 902, 129, arXiv:2007.07267 [astro-ph.CO]
  12. L. Thiele, C.A.J. Duncan, D. Alonso,
    Disentangling magnification in combined shear clustering analyses,
    2020, MNRAS 491, 1746, arXiv:1907.13205 [astro-ph.CO]
  13. L. Thiele, J.C. Hill, K.M. Smith,
    Accurate analytic model for the thermal Sunyaev-Zel’dovich one-point probability distribution function,
    2019, PRD 99, 103511, arXiv:1812.05584 [astro-ph.CO]

2nd & 3rd author

  1. B.Y. Wang, L. Thiele, M. Ho,
    Cluster Mass Inference from Galaxy Kinematics,
    2026, arXiv:2606.12938 [astro-ph.CO]
  2. A. Hell, L. Thiele,
    LLMs with in-context learning for Algorithmic Theoretical Physics,
    2026, arXiv:2605.08212 [cs.LG], poster at ICML 2026 AI4Physics workshop
  3. J. Armijo, L. Thiele, J. Liu,
    Replicating weak-lensing summary-statistic covariances with normalizing flows,
    2026, PRD 114, 023567, arXiv:2601.20669 [astro-ph.CO]
  4. B. Barthe-Gold, N.-M. Nguyen, L. Thiele,
    Reconstructing the local density field with combined convolutional and point cloud architecture,
    2025, arXiv:2510.08573 [astro-ph.CO], poster at ML4PS workshop NeurIPS 2025
  5. B.Y. Wang, L. Thiele,
    Set-based Implicit Likelihood Inference of Galaxy Cluster Mass,
    2025, arXiv:2507.20378 [cs.LG], spotlight talk at ML4Astro workshop (colocated with ICML 2025)
  6. J.A. Cowell, J. Armijo, L. Thiele, G.A. Marques, C.P. Novaes, D. Grandón, S. Cheng, M. Shirasaki, D. Alonso, J. Liu,
    First Constraints from Marked Angular Power Spectra with Subaru Hyper Suprime-Cam Survey First-Year Data,
    2025, MNRAS 546, 2, arXiv:2507.12315 [astro-ph.CO]
  7. C. Jacobus, L. Thiele, P. Harrington, J. Liu, Z. Lukic,
    Enhancing Cosmological Simulations with Efficient and Interpretable Machine Learning in the Gabor Wavelet Basis,
    2024, poster at Workshop on Machine Learning and the Physical Sciences (NeurIPS 2024)
  8. C.P. Novaes, L. Thiele, J. Armijo, S. Cheng, J.A. Cowell, G.A. Marques, E.G.M. Ferreira, M. Shirasaki, K. Osato, J. Liu,
    Cosmology from HSC Y1 Weak Lensing with Combined Higher-Order Statistics and Simulation-based Inference,
    2025, PRD 111, 8, arXiv:2409.01301 [astro-ph.CO]
  9. D. Grandón, G.A. Marques, L. Thiele, S. Cheng, M. Shirasaki, J. Liu,
    Impact of baryonic feedback on HSC Y1 weak lensing non-Gaussian statistics,
    2024, PRD 110, 103539, arXiv:2403.03807 [astro-ph.CO]
  10. A.M. Delgado, D. Anglés-Alcázar, L. Thiele, M. Ntampaka, S. Pandey, K. Lehman, R.S. Somerville, S. Genel, F. Villaescusa-Navarro,
    Predicting the impact of feedback on matter clustering with machine learning in CAMELS,
    2023, MNRAS 526, 4, arXiv:2301.02231 [astro-ph.GA]
  11. D. Wadekar, L. Thiele, J.C. Hill, S. Pandey, F. Villaescusa-Navarro, et al.,
    The SZ flux-mass (Y-M) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback,
    2022, MNRAS 522, 2, arXiv:2209.02075 [astro-ph.CO]
  12. B.K.K. Lee, W. Coulton, L. Thiele, S. Ho,
    An exploration of the properties of cluster profiles for the thermal and kinetic Sunyaev-Zel’dovich effects,
    2022, MNRAS 517, 420, arXiv:2205.01710 [astro-ph.CO]
  13. D. Wadekar, L. Thiele, F. Villaescusa-Navarro, J.C. Hill, D.N. Spergel, M. Cranmer, N. Battaglia, D. Anglés-Alcázar, L. Hernquist, S. Ho,
    Augmenting astrophysical scaling relations with machine learning: application to reducing the SZ flux-mass scatter,
    2022, PNAS 120(12), arXiv:2201.01305 [astro-ph.CO]
  14. F. Dinc, M. Medvidovic, L. Thiele,
    Effective Geometry Monte Carlo: A Fast and Reliable Simulation Framework for Molecular Communication,
    2019, IEEE Access 7, 28635
  15. F. Dinc, L. Thiele, B.C. Akdeniz,
    The effective geometry Monte Carlo algorithm: applications to molecular communication,
    2019, PLA 383, 2594, arXiv:1809.06438 [cs.ET]

Nth author

  1. N. Aghanim, B. Maffei, J. Aumont, A. Beelen, B. Borgo, et al. (incl. L. Thiele),
    FOSSIL: A future mission for CMB spectral distortion measurements,
    2026, arXiv:2609.17618 [astro-ph.CO]
  2. B. Cyr, N. Aghanim, E. Baker, E.S. Battistelli, R. Battye, et al. (incl. L. Thiele),
    Peering Beyond the Veil of Last Scattering: A View of the Universe with CMB Spectral Distortions,
    2026, arXiv:2609.16194 [astro-ph.CO]
  3. Y. Itow, J. Liu, H. Maesaka, V. Mikuni, N.-M. Nguyen, et al. (incl. L. Thiele),
    Future of Artificial Intelligence for Science in Japan 2024 Community Report,
    2026, arXiv:2608.27807 [hep-ph]
  4. J. Liu, V. Krishnaraj, K. Vovk, K. Aizawa, A.E. Bayer, et al. (incl. L. Thiele),
    AI’s Capability in Assisting Scientific Research in Physics, Astrophysics, and Cosmology II: Project Planning and Proposal Evaluation,
    2026, arXiv:2607.25881 [cs.CL]
  5. A. Hell, K. Vovk, V. Krishnaraj, J. Liu, K. Aizawa, et al. (incl. L. Thiele),
    AI’s Capability in Assisting Scientific Research in Physics, Astrophysics, and Cosmology I: Literature Review,
    2026, arXiv:2607.25672 [astro-ph.IM]
  6. G. Fabbian, F. Bianchini, A. Sabyr, J.C. Hill, C.C. Lovell, L. Thiele, D.N. Spergel,
    A new constraint on the y-distortion with FIRAS: implications for feedback models in galaxy formation and cosmic shear measurements,
    2025, arXiv:2512.03038 [astro-ph.CO]
  7. A. Tokiwa, A.E. Bayer, J. Armijo, J. Liu, R. Terasawa, L. Thiele, M. Alvarez, L. Blot, M. Takada,
    Impact of Simulation Box Size for Weak Lensing: Replication and Super-Sample Effects,
    2025, JCAP 07, 023 arXiv:2511.20423 [astro-ph.CO],
  8. E. Calabrese, J.C. Hill, H.T. Jense, A.L. Posta, I. Abril-Cabezas, et al. (incl. L. Thiele),
    The Atacama Cosmology Telescope: DR6 Constraints on Extended Cosmological Models,
    2025, JCAP 11, 063, arXiv:2503.14454 [astro-ph.CO]
  9. J. Armijo, G.A. Marques, C.P. Novaes, L. Thiele, J.A. Cowell, D. Grandón, M. Shirasaki, J. Liu,
    Cosmological constraints using Minkowski functionals from the first year data of the Hyper Suprime-Cam,
    2025, MNRAS 537, 4, arXiv:2410.00401 [astro-ph.CO]
  10. A. Kogut, E. Switzer, D. Fixsen, N. Aghanim, J. Chluba, et al. (incl. L. Thiele),
    The Primordial Inflation Explorer (PIXIE): Mission Design and Science Goals,
    2025, JCAP 004, 020, arXiv:2405.20403 [astro-ph.CO]
  11. S. Cheng, G.A. Marques, D. Grandón, L. Thiele, M. Shirasaki, B. Ménard, J. Liu,
    Cosmological constraints from weak lensing scattering transform using HSC Y1 data,
    2025, JCAP 01, 006, arXiv:2404.16085 [astro-ph.CO]
  12. G.A. Marques, J. Liu, M. Shirasaki, L. Thiele, D. Grandón, K.M. Huffenberger, S. Cheng, J. Harnois-Déraps, K. Osato, W.R. Coulton,
    Cosmology from weak lensing peaks and minima with Subaru Hyper Suprime-Cam survey first-year data,
    2023, MNRAS 528, 3, arXiv:2308.10866 [astro-ph.CO]
  13. F. Villaescusa-Navarro, S. Genel, D. Anglés-Alcázar, L.A. Perez, P. Villanueva-Domingo, et al. (incl. L. Thiele),
    The CAMELS project: public data release,
    2022, ApJS 265, 54, arXiv:2201.01300 [astro-ph.CO]
  14. B. Maffei, M.H. Abitbol, N. Aghanim, J. Aumont, E. Battistelli, et al. (incl. L. Thiele),
    BISOU: a balloon project to measure the CMB spectral distortions,
    2021, 16 th Marcel Grossmann Meeting, arXiv:2111.00246 [astro-ph.IM]
  15. F. Villaescusa-Navarro, S. Genel, D. Anglés-Alcázar, L. Thiele, R. Dave, et al.,
    The CAMELS Multifield Dataset: Learning the Universe’s Fundamental Parameters with Artificial Intelligence,
    2021, ApJS 259, 61, arXiv:2109.10915 [cs.LG]
  16. F. Villaescusa-Navarro, S. Genel, D. Anglés-Alcázar, D.N. Spergel, Y. Li, et al. (incl. L. Thiele),
    Robust marginalization of baryonic effects for cosmological inference at the field level,
    2021, arXiv:2109.10360 [astro-ph.CO]
  17. F. Villaescusa-Navarro, D. Anglés-Alcázar, S. Genel, D.N. Spergel, Y. Li, et al. (incl. L. Thiele),
    Multifield Cosmology with Artificial Intelligence,
    2021, arXiv:2109.09747 [astro-ph.CO]
  18. R. Cayuso, O.J.C. Dias, F. Gray, D. Kubizňák, A. Margalit, J.E. Santos, R.G. Souza, L. Thiele,
    Massive vector fields in Kerr–Newman and Kerr–Sen black hole spacetimes,
    2020, JHEP 159, arXiv:1912.08224 [hep-th]
  19. R. Cayuso, F. Gray, D. Kubizňák, A. Margalit, R.G. Souza, L. Thiele,
    Principal Tensor Strikes Again: Separability of Vector Equations with Torsion,
    2019, PLB 795, 650, arXiv:1906.10072 [hep-th]

Talks

Kavli Astrophysics Symposium, Cambridge 9/2026
Kavli Astrophysics Symposium, Cambridge invited 9/2026
New Frontiers in Cosmology, A Coruna 8/2026
Renoir Science, CPPM Marseille invited 5/2026
Sydney PPC Seminar, remote 4/2026
Fundamentals Seminar, IPMU 2/2026
AI4HEP East Asia, KEK Tsukuba invited 1/2026
AI4KMI, Nagoya invited 1/2026
3rd Shanghai Assembly 11/2025
28th IBIS, Naha invited 11/2025
NPML conference, Tokyo invited 10/2025
ML workshop @ McGill 9/2025
Mila, Montreal invited 9/2025
21st Rencontres du Vietnam invited 8/2025
AI for Fugaku seminar 7/2025
ML4Astro, UTokyo 5/2025
LeCosPA Meets IPMU, Taipei 4/2025
FOPM seminar, UTokyo 3/2025
Voids @ CPPM, Marseille invited 2/2025
KICC, Cambridge UK 2/2025
FAIRS-Japan workshop Nagoya invited 12/2024
11th KIAS workshop Gyeongju invited 10/2024
Cosmo’24 Kyoto 10/2024
LSS Quest Osaka 6/2024
MPA cosmology seminar 5/2024
Yale cosmology seminar invited 2/2024
AI4Phys @ IPMU 1/2024
CCA Cosmo x ML tristate meeting 10/2023
CMB constellation meeting KIPAC Stanford 10/2023
DESI lunch Berkeley Lab 10/2023
BCCP seminar UC Berkeley 10/2023
IPMU CD3 seminar 9/2023
Institute d’Astrophysique Spatiale Orsay 9/2023
Cosmo’23 Madrid 9/2023
Nagoya 4/2023
IPMU 3/2023
Princeton gravity group 2/2023
UCL Physics & Astronomy 9/2022
IAS astro coffee 3/2022
AAS 239 1/2022
Cosmology Talks 1/2022
Learn the Universe @ CCA 8/2021
CMB-S4 meeting 8/2021
MPA Garching 10/2020
German Astronomical Society 9/2020
Perimeter Institute 5/2020
Princeton/IAS cosmo lunch 5/2020
CCA Cosmo x ML 5/2020