Henok Tenaw Moges

AI for Dynamical Systems & Scientific Machine Learning

University of Cape Town

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Henok Tenaw Moges

"When does physical structure help learning in dynamical systems and when does it fail?"

I am a Research Fellow in AI Systems at the University of Cape Town, working at the intersection of machine learning, numerical analysis, and nonlinear dynamics.

My research focuses on spatio-temporal graph neural networks (STGNNs), physics-informed machine learning, and scientific ML for predictive modelling of complex dynamical systems. I study how learning architectures interact with nonlinear instability in high-dimensional systems, with emphasis on predictability horizons, stability, and chaos.

My work asks how physical structure, instability, and data-driven models interact in complex dynamical systems.

Research Themes

Spatio-temporal Learning
Physics-informed Machine Learning
Nonlinear Dynamics & Chaos
Predictability in Complex Systems
Scientific ML & Benchmarking

Current Position

Research Fellow
Artificial Intelligence Research Unit (AIRU), University of Cape Town
Work Package Lead — AI & Modelling
Mi-Hy EU Project
AI-driven modelling, simulation, and digital twin design for microbial hydroponics systems

Selected Projects

ChaosNetBench

Benchmarking Spatio-Temporal Graph Neural Networks on Chaotic Lattice Dynamics

Lite-STGNN

Efficient spatio-temporal graph neural networks for long-term time series forecasting under resource constraints.

Physics-informed STGNNs

Models integrating physical structure and graph-based learning for forecasting complex dynamical systems.

Selected Publications

Full list on Google Scholar

Selected Talks & Conference Presentations

ICAART — Marbella, Spain, March 2026
Oral Presentation: “A Lightweight Spatial-Temporal Graph Neural Network for Long-Term Time Series Forecasting”
SACAIR — Cape Town, South Africa, December 2025
Poster: “Learning Dynamic Dependencies in Spatial-Temporal Systems for Efficient Forecasting”
UCT Faculty Postdoctoral Research Day 2025, Sep 2025 — Cape Town, South Africa
Poster: “Spatio-Temporal Graph Neural Networks for Predictive Modelling and Scientific Knowledge Discovery in Dynamical Systems”
ANDSC — Madrid, Spain, Jul 2024
Oral Presentation: “Quantification and Comparison of Magnetic and Kinetic Chaos in Toroidal Plasmas”
ICIAM — Waseda University, Tokyo, Japan, Aug 2023
Talk: “Anomalous diffusion in standard maps with extensive chaotic phase spaces”

Academic Service