Yacoub Hendi

Ph.D. Student in Mathematics
Uppsala University, Sweden

📧 Email: yacoub.hendi@math.uu.se
📄 Download CV

Research Interests

My research explores the intersection of machine learning and geometry. On one hand, I apply machine learning techniques to compute numerical approximations on manifolds such as Ricci-flat metrics on Calabi–Yau manifolds. On the other hand, I study the geometric properties of neural networks to better understand their efficiency.

Education

Ph.D. in Mathematics (2023– )
Uppsala University
Advisor: Prof. Magdalena Larfors

Master of Mathematics (2021–2023)
Thesis: Computation of the superpotential for monotone Lagrangian submanifolds in products of complex projective lines
Advisor: Assoc. Prof. Luis Diogo

Bachelor of Mathematics (2018–2021)
Thesis: On The Prime Number Theorem
Advisor: Prof. Andreas Strömbergsson

Bachelor of Computer Science (2018–2021)
Thesis: Parameterized Verification under The Total Store Order Memory Model is EXPTIME-Complete
Advisor: Prof. Parosh Abdulla

Activities

2026 – DANGER: Data, Numbers, and Geometry Workshop
The Banff International Research Station, Banff
2025 – London Geometric Machine Learning Workshop (LOGML)
Imperial College London, London
2025 – GeUmetric Deep Learning Workshop
Umeå University, Umeå
2025 – Summer School on Singular Kählerian Metrics and Hermitian Geometry
Rényi Institute, Budapest
2025 – Summer School: Invitation to Complex Geometry
Rényi Institute, Budapest
2024 – GeUmetric Deep Learning Workshop
Umeå University, Umeå

Talks

2026 – Learning Theory and Covering Numbers
PhD seminar series, Uppsala University, Uppsala
2026 – The Geometry of Polynomial Group Convolutional Neural Networks
Applied CATS Seminar, KTH, Stockholm
📑 Slides
2025 – Approximating Ricci-Flat Metrics on Calabi–Yau Manifolds with Neural Networks
Summer School: Invitation to Complex Geometry, Rényi Institute, Budapest
2024 – Learning Group Invariant CY Metrics
GeUmetric Deep Learning Workshop, Umeå

Publications & Papers

The Geometry of Polynomial Group Convolutional Neural Networks
Y. Hendi, D. Persson, M. Larfors
Link
Licentiate thesis: Geometry and Learning under Group Symmetries
Y. Hendi
Link
Learning group invariant Calabi–Yau metrics by fundamental domain projections
Y. Hendi, M. Larfors, M. Walden
Machine Learning: Science and Technology, 6(1), 015050 (2025) Link
Parameterized Verification under TSO with Data Types
P.A. Abdulla et al.
TACAS 2023, LNCS 13993, Springer (2023) Link