**About the Editors**

#### **Matteo Convertino**

Matteo Convertino is an associate professor at Tsinghua University, Shenzhen International Graduate School, where he is the principal investigator of the fuTuRE EcoSystems Lab (TREES) and the Associate Director of the State Key Lab of Ecological Remediation and Carbon Sequestration. His expertise is in ecosystem patterns, networks and flows, ecosystem health, biocomplexity engineering, ecosystem data science and analytics, ecological forecasting, systemic risk and strategic portfolio management, biogeomorphology, and socio-eco-hydro-climatology. Convertino's work is focused on developing nature-based solutions to counter ecological imbalances, namely ecohydrological engineering for restoration and protection, and policies that enhance the water and carbon cycles and biodiversity. His work is based on the identification of optimal ecological connections and flows (dynamical trees) constituting the backbone of ecosystem health. The current applications focus on coastal and urban ecosystems from a holistic basin perspective where everything flows and can be positively engineered by trading off risks and decisions. Such research is performed via pattern-oriented theoretical and computational models based on information and network sciences which develop into digital ecosystem models for guiding scientific investigation and eco-engineering applications.

Dr. Convertino has produced 95+ publications and technical reports. Dr. Convertino, among others, was granted the Pengcheng Peacock Talents Award from the Shenzhen government (2022–2024), the Ministry of Science and Education Foreign Talents Award (2021), the SOUSEI top 20% performing scientist award from Hokkaido University, the 2016 Top 10 Team honorific mention for the Dengue and Influenza Forecasting Challenge sponsored by the Office of Science and Technology Policy (US White House), and the 2011 Young International Research Scientist Fellowship from the Chinese Academy of Sciences.

#### **Jie Li**

Jie Li is a postdoctoral researcher at the University of Amsterdam, where his research focus is on building information theoretical higher-order network models and applying the models to unravel the intricacies of multiplex disease networks within the scope of an EU-funded project. The major goal of the EU project is to understand the causative mechanisms underlying the comorbidity of cardiovascular diseases and depression and identify the significant biomarkers responsible for the development of the complex comorbidity. The core of his work is to infer higher-order interactions based on information theory and develop novel methods to analyze a comprehensive disease network combining high-order and pairwise interactions into one graph. Dr. Li's current research interests lie primarily in higher-order relationships, information theory, multiplex disease networks, and their applications in biomedical fields related to CVD and depression comorbidities. His expertise traverses a diverse spectrum, from bio-complexity engineering to ecological pattern forecasting, from digital signal processing, data analytics, and visualization to causal inference and network-based analyses. Dr. Li's research efforts have resulted in multiple impactful papers, technical reports within the project framework, and presentations at international conferences. Prior to being a postdoctoral researcher, he completed his Ph.D. at Hokkaido University, where he was involved in a research project on information dynamics for complex ecosystem prediction and design led by Dr. Matteo Convertino.
