Our Team

My research is focused on the development of efficient algorithms for graph signal processing and machine learning on graphs and simplicial complexes.

The topic of my PhD thesis (@ GSSI, Italy) was the topological and numerical stability of simplicial complexes.

I work on the intersection of Topological Data Analysis, Topological Signal Processing, and Network Science. In particular, I try to relate large-scale topological and geometric structure back to local(ised) information in complex data sets. My favourite animal is the cow.

Most of my research is focused on higher-order networks, specifically cell complexes. In this area, I have papers and python packages on both signal processing on and random models for cell complexes,

I am also working on control of power distribution systems using AI.

I develop machine learning methods to analyze the complex structure of biological systems using Optimal Transport. My goal is to provide interpretable models that explain how functional units (e.g., single cells) contribute to different global states of the system, such as a patient’s disease. Also, I like turtles.

I work on many-player games on networks, particularly collective action models and their relationship to community organizing methods.

My work is interdisciplinary, comprising NLP (LLMs and Knowledge Graphs), Robotics, and more recently, Multimodal Graph Learning. I leverage foundation models (esp., LLMs and VLMs) to extract information from multimodal data (i.e., image, text, video data) on both small-and-large scale. My goal is to enable Robots to understand Human Language.

I apply diverse mathematical tools—particularly Network Science, Complex Systems, Statistical Mechanics, Graph Theory, Dynamical Systems, and Topological Data Analysis—in multidisciplinary data-driven research.