Thomas G. de Jong

211, building C4

Faculty of Mathematics and Physics

Kanazawa, Japan

I am a mathematician. But I dabble a lot in the applied sciences. So far my application domains include AI, celestial mechanics, cell biology. My mathematical expertise mainly concerns dynamical systems and lately I am very drawn to data science and neural network problems. Currently, my main focus is reservoir computing. I am in the Notsu-lab at the Faculty of Mathematics and Physics in Kanazawa University. My research is funded by CREST.

For my research I mainly use Python. I have worked on a couple of mechanical and material science problems in collaboration with industry, and I am always on the look for new collaborations.

I am an organizer of the Kanazawa Analysis Seminar KAS, Differential Equations for Data science Seminar DEDS and Continuum Mechanics Focusing on Singularities CoMFoS. I am a member of the Reservoir Computing seminar group and a member of the Dutch Royal Mathematical Society (KWG)

I very strongly believe in a grass-roots approach to science. I am very supportive of open-source. I think that a delta-function perspective on research is outdated in the age of model-free methods.

Current projects:

Reservoir computing: Kohei Nakajima , Hirofumi Notsu
Biomath (replicating oscillators): Ayumi Ozawa , Matthew Smart , Hayden Nunley
Reservoir computing (lyapunov exponents for high-dimensional systems): Alef Sterk
Pedestrian flow and swarms: Alessandro Corbetta
Data science and Archeology: Krist Vaesen , Fulco Scherjon , Andrew Sorensen, Stan van Zon
Biomath (surface-bulk PDEs): Koondanibha Mitra , Antoine Diez

Collaborators not mentioned above: Henk Broer, Nozomi Akashi, Tomohiro Taniguchi, Georg Prokert, Joost Hulshof, Patrick van Meurs

Students I am supervising or have supervised: Elsa Bernholm (Karlstad University), Yuma Nakamura (Kanazawa University), Kharisma Putri (Kanazawa University), Yue Shu (Kanazawa University)

Teaching: I am teaching ODEs using the lovely book 微分方程式 by 長瀬道弘.

news

Apr 12, 2024	DEDS April 12th Ayumi Ozawa (Deeper understanding of synchronization and Oscillation quenching through the reduction of dynamics)
Apr 4, 2024	KAS April 4th Koondanibha Mitra (Analysis of coupled degenerate and singular systems in biofilm modelling)
Feb 29, 2024	DEDS March 15th Alef Sterk (Bifurcations in the Lorenz-96 model)
Feb 19, 2024	Differential Equations for Data Science 2024 (DEDS2024) is this year from February 19 (Mon) to February 21 (Wed)
Feb 5, 2024	I will be in Tokyo from Feb 5 to Feb 9 for the study group with mathematics. I will be working on data driven human body balance models

latest posts

Feb 12, 2024	Batch image conversion
Jan 10, 2024	Mixing MathJaX with CSS, HTML
Dec 29, 2023	1D asymptotic stability proof

selected publications

arXiv

Well-posedness results for general reaction-diffusion transport of oxygen in encapsulated cells

Yuma Nakamura, Kharisma S. Putri, Alef Sterk, and 1 more author

2024

Bib HTML

@misc{nakamura2024wellposedness,
  title = {Well-posedness results for general reaction-diffusion transport of oxygen in encapsulated cells},
  author = {Nakamura, Yuma and Putri, Kharisma S. and Sterk, Alef and Jong, Thomas G de},
  year = {2024},
  eprint = {2401.09863},
  archiveprefix = {arXiv},
  primaryclass = {math.AP},
}

MLNCP

Virtual reservoir acceleration for CPU and GPU: Case study for coupled spin-torque oscillator reservoir

Thomas G de Jong, Nozomi Akashi, Tomohiro Taniguchi, and 2 more authors

In NeurIPS: ML with New Compute Paradigms Workshop , 2023

Bib HTML

@inproceedings{de2023mlncp,
  title = {Virtual reservoir acceleration for CPU and GPU: Case study for coupled spin-torque oscillator reservoir},
  author = {Jong, Thomas G de and Akashi, Nozomi and Taniguchi, Tomohiro and Notsu, Hirofumi and Nakajima, Kohei},
  booktitle = {NeurIPS: ML with New Compute Paradigms Workshop },
  year = {2023},
  organization = {NeurIPS},
}

CHA

How neural networks learn to classify chaotic time series

Alessandro Corbetta¹, and Thomas G de Jong¹

Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023

Bib HTML PDF

@article{corbdejon2023neural,
  author = {Corbetta<sup>1</sup>, Alessandro and Jong<sup>1</sup>, Thomas G de},
  title = {{How neural networks learn to classify chaotic time series}},
  journal = {Chaos: An Interdisciplinary Journal of Nonlinear Science},
  volume = {33},
  number = {12},
  pages = {123101},
  year = {2023},
  doi = {10.1063/5.0160813},
}

arXiv

Holder regularity for the trajectories of generalized charged particles in 1D

Thomas G de Jong, and Patrick van Meurs

2023

Bib HTML

@misc{dejong2023holder,
  title = {Holder regularity for the trajectories of generalized charged particles in 1D},
  author = {Jong, Thomas G de and Meurs, Patrick van},
  year = {2023},
  eprint = {2311.08739},
  archiveprefix = {arXiv},
  primaryclass = {math.DS},
}

arXiv

Reaction-diffusion transport into core-shell geometry: Well-posedness and stability of stationary solutions

Thomas G de Jong, Georg Prokert, and Alef E Sterk

2023

Bib HTML

@misc{dejong2023reactiondiffusion,
  title = {Reaction-diffusion transport into core-shell geometry: Well-posedness and stability of stationary solutions},
  author = {Jong, Thomas G de and Prokert, Georg and Sterk, Alef E},
  year = {2023},
  eprint = {2305.03397},
  archiveprefix = {arXiv},
  primaryclass = {math.AP},
}