SOS Research Unit
Translating nature into adaptive futures
Who we are
The Research Unit of the Sustainability of Sustainability Foundation (SOS) is co-directed by Cong Liu and Wei-Ping Chan, two interdisciplinary scientists working across ecology, evolutionary biology, data science, and artificial intelligence.
The unit focuses on translating biological, computational, and social systems to enable more adaptive and resilient approaches to sustainability. Rather than optimizing for fixed outcomes, its research explores how knowledge from natural systems can be structured, interpreted, and applied across domains under conditions of uncertainty.
To support this, the unit develops integrated pipelines that combine diverse hardware systems, data acquisition processes, and machine learning methods to capture and analyze nature at scale. These workflows span data collection through automated analysis, forming the foundation for phenomics and large-scale nature digitization.
By linking physical environments, data infrastructure, and analytical models, the unit works to transform nature collections and field observations into structured, accessible knowledge. This enables new forms of cross-domain application: conservation, bioinspired design, and beyond.
Meet the Research Directors
Overlapping yet complementary — spanning hardware, field collection, lab work, software development, AI-driven analysis, and real-world application.
What we study
Four overlapping themes where both directors contribute, and three complementary areas.
Nature Digitization & Bioinspired Translation
Developing integrated pipelines that translate natural systems into structured, computationally accessible data and extend them into real-world applications. This includes large-scale digitization workflows, imaging and spectral acquisition, and the use of machine learning to enable the Internet of Bioinspiration (IoBI). These pipelines further support the discovery and prototyping of bioinspired materials and structures by connecting biological patterns with engineering and design contexts.
Knowledge Infrastructure & Digital Ecosystems
Building data infrastructures that connect biological observations, environmental context, and computational models across scales. This includes standardized data collection pipelines and curated biodiversity databases — alongside Mountain Digital Twins (MDT), one of our flagship projects that creates integrated, multi-layer representations of mountain ecosystems by linking biotic and abiotic data. Together, these digital ecosystems enable repeatable analyses, interoperable datasets, and long-term monitoring frameworks supporting both fundamental research and conservation.
Conservation & Species Decline
Insects are declining globally, yet causes and trajectories remain poorly resolved. This theme takes a multi-evidence approach — combining population genomics with long-term behavioral and light-trap time series to track changes in abundance and community composition, integrating molecular, observational, and ecological data to disentangle the roles of habitat loss, climate change, and chemical pollution.
Evolutionary Biology & Functional Morphology
Eco-evolutionary perspectives on mutualism and dispersal combined with deep morphological expertise — converging on bioinspiration and understanding how evolved structures inform sustainable design.
Climate Change & Mountain Ecosystems
Climate velocity frameworks and environmental variability models applied to biodiversity datasets to predict community turnover under future climate scenarios and mountain ecosystem shifts.
Biosecurity & Invasion Biology
Monitoring online wildlife trade platforms to quantify the movement of non-native species and assess invasion risk pathways. This work develops surveillance frameworks for detecting high-risk organisms in e-commerce networks before they establish in new environments — combining large-scale data scraping, species identification, and risk modelling.
Publication record
Co-director names appear in bold. Full lists on personal websites.
- Nature MethodsKatzke J, …, Liu C, et al. (2026). High-throughput phenomics of global ant biodiversity.
- ScienceLiu C, et al. (2025). Genomic signatures indicate massive decline of endemic island insects.
- PNASVidal MC, Liu C, et al. (2025). Partner dependency alters patterns of coevolutionary selection in mutualisms.
- NatureChan WP, et al. (2024). Climate velocities and species tracking in global mountain regions.
- Communications BiologyChan WP, et al. (2022). A high-throughput multispectral imaging system for museum specimens.
- ScienceChan WP, et al. (2016). Seasonal and daily climate variation have opposite effects on species elevational range size.
Prospective Students & Collaborators
We welcome inquiries from students and researchers at all career stages.
We are open to collaboration with students and researchers interested in biodiversity informatics, digitization, climate–biodiversity dynamics, evolutionary morphology, and bioinspiration. Inquiries are welcome at all career stages — from middle and high school through undergraduate, graduate, and postdoctoral.
Please reach out through the SOS Foundation main site, or directly through the personal websites of the Research Directors.