1. Rock–Paper–Scissors dynamics on lattices

This project explores how classic cyclic competition behaves when species are arranged on a lattice. By introducing hierarchy among the competing agents, you investigate how dominance structures reshape spatial patterns. Long-range connections further complicate the dance, creating unexpected pockets of stability and chaos. The aim is to reveal how simple rules give rise to rich ecological and evolutionary dynamics.

2. Epidemics and rumor spreading in networks

Here you blend data-driven insights with mathematical models to understand how diseases and rumors travel through real-world networks. The project compares different spreading mechanisms to uncover what accelerates or slows transmission. Network structure—communities, hubs, bottlenecks—plays a starring role in shaping outcomes. Ultimately, the goal is to design smarter strategies for early detection and mitigation.

3. Seizure propagation through a network lens

This work treats the brain as a complex network to study how seizures originate and spread. By modeling neural interactions, you explore why some regions stay resilient while others fail dramatically. The approach highlights how structural connectivity shapes functional vulnerability. The broader aim is to move toward predictive and personalized seizure-mitigation strategies.

4. Stability of large graphs: from ecology to brain

This project investigates how stability emerges—or collapses—in massive interconnected systems. From food webs to neural networks, you examine how interaction strengths and topology determine resilience. Mathematical tools from dynamical systems help reveal tipping points and fragile motifs. The ambition is to build a unifying framework that explains stability across very different domains.

5. Entropy analysis of EEG data in stroke patients

By applying entropy measures to EEG signals, this project uncovers hidden patterns in neural activity after stroke. The goal is to detect signatures of disruption, compensation, and recovery. Entropy offers a compact way to quantify complexity and irregularity in brain dynamics. This line of work may ultimately support better diagnostic markers and rehabilitation strateg