CV

Education

• Ph.D in Version Control Theory, GitHub University, 2018 (expected)
• M.S. in Jekyll, GitHub University, 2014
• B.S. in GitHub, GitHub University, 2012

Work experience

• Spring 2024: Academic Pages Collaborator
  • GitHub University
  • Duties includes: Updates and improvements to template
  • Supervisor: The Users
• Fall 2015: Research Assistant
  • GitHub University
  • Duties included: Merging pull requests
  • Supervisor: Professor Hub
• Summer 2015: Research Assistant
  • GitHub University
  • Duties included: Tagging issues
  • Supervisor: Professor Git

Skills

• Skill 1
• Skill 2
  • Sub-skill 2.1
  • Sub-skill 2.2
  • Sub-skill 2.3
• Skill 3

Publications

When Quantum and Classical Models Disagree: Learning Beyond Mean Norm Least Square

Slimane Thabet, Léo Monbroussou, Eliott Z. Mamon, Jonas Landman. (2026). "When Quantum and Classical Models Disagree: Learning Beyond Mean Norm Least Square." Nature Partner Journal Quantum Information.

Constrained and Vanishing Expressivity of Quantum Fourier Models

Hela Mhiri, Leo Monbroussou, Mario H Gonzalez, Slimane Thabet, Elham Kashefi, Jonas Landman. (2025). "Constrained and Vanishing Expressivity of Quantum Fourier Models." Quantum, vol.9, p.1847.

Trainability and Expressivity of Hamming-Weight Preserving Quantum Circuits for Machine Learning

Léo Monbroussou, Eliott Z. Mamon, Jonas Landman, Alex B. Grilo, Romain Kukla, Elham Kashefi. (2025). "Trainability and Expressivity of Hamming-Weight Preserving Quantum Circuits for Machine Learning." Quantum, vol.9, p.1745.

Subspace Preserving Quantum Convolutional Neural Network Architectures

Léo Monbroussou, Jonas Landman, Letao Wang, Alex B. Grilo, Elham Kashefi. (2025). "Subspace Preserving Quantum Convolutional Neural Network Architectures." Quantum Science and Technology.

Quantum Vision Transformers

El Amine Cherrat, Iordanis Kerenidis, Natansh Mathur, Jonas Landman, Martin Strahm, Yun Y Li. (2024). "Quantum Vision Transformers." Quantum, vol.8, p.1265.

Quantum Fourier Networks for Solving Parametric PDEs

Nishant Jain*, Jonas Landman*, Natansh Mathur, Iordanis Kerenidis. (2024). "Quantum Fourier Networks for Solving Parametric PDEs." Quantum Science & Technology, vol.9, n.3.

Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Jonas Landman*, Slimane Thabet*, Constantin Dalyac, Hela Mhiri, Elham Kashefi. (2023). "Classically Approximating Variational Quantum Machine Learning with Random Fourier Features." Proceedings of ICLR 2023.

Quantum Methods for Neural Networks and Application to Medical Image Classification

Jonas Landman, Natansh Mathur, Yun Y Li, Martin Strahm, Skander Kazdaghli, Anupam Prakash, Iordanis Kerenidis. (2022). "Quantum Methods for Neural Networks and Application to Medical Image Classification." Quantum, vol.6, p.881.

Quantum Bayesian Neural Networks

Noah Berner, Vincent Fortuin, Jonas Landman. (2022). "Quantum Bayesian Neural Networks." AABI 2022.

Quantum Algorithms for Unsupervised Machine Learning and Neural Networks

Jonas Landman. (2021). "Quantum Algorithms for Unsupervised Machine Learning and Neural Networks." PhD Thesis.

Quantum Spectral Clustering

Iordanis Kerenidis, Jonas Landman. (2020). "Quantum Spectral Clustering." Physical Review A, Vol.103 Iss. 4.

Quantum Algorithms for Deep Convolutional Neural Networks

Iordanis Kerenidis, Jonas Landman, Anupam Prakash. (2020). "Quantum Algorithms for Deep Convolutional Neural Networks." Proceedings of ICLR 2020.

Q-means: A Quantum Algorithm for Unsupervised Machine Learning

Iordanis Kerenidis, Jonas Landman, Alessandro Luongo, Anupam Prakash. (2019). "Q-means: A Quantum Algorithm for Unsupervised Machine Learning." Proceedings of NeurIPS 2019.

Talks

Teaching

Service and leadership

• Currently signed in to 43 different slack teams