EthnoHack

EthnoHack 2026 is a week-long, 100% online hackathon focused on Ethnopharmacology & Health, taking place from November 2–8, 2026. Organized under the ETHCSTWIN framework, the event brings together data scientists, AI researchers, computer scientists, bioinformaticians, pharmacognocists, botanists, historians, anthropologists, pharmacologists, ecologists, clinicians, and students to explore how computational methods can unlock the potential of traditional medicine.

Participants will work across four challenge tracks using open datasets, scientific literature, biodiversity data, chemical information, and digital health technologies:

• Traditional Knowledge: Use NLP and AI to extract medicinal knowledge from historical, folklore texts, and ethnobotanical studies. Tasks include mapping plant names across eras, identifying therapeutic uses, and connecting ancient knowledge to modern pharmacology.
• Natural Products and Drug Discovery: Apply machine learning and cheminformatics to identify promising plant-derived compounds for specific disease targets. Participants will build predictive models, knowledge graphs, and screening pipelines.
• Biodiversity and Sustainability: Leverage geospatial and ecological datasets to map medicinal plant diversity, identify conservation risks, and develop tools for sustainable harvesting.
• Digital Health and Phytotherapy: Design apps, decision-support tools, or recommendation engines that connect phytotherapy evidence to clinical or patient-facing contexts.

The hackathon encourages interdisciplinary teams; participants do not need to be experts in every field but should bring a research question, technical skill, domain expertise, or curiosity. Collaboration occurs primarily asynchronously via Discord, with scheduled mentoring, presentations, Q&A sessions, and a final pitch event (Primary time zone: CET).

Requirements and Deliverables Teams must build a working prototype, computational pipeline, model, application, analysis, or digital tool addressing one of the four tracks. Projects should demonstrate a clearly defined problem, a computational approach, a working result, supporting evidence, clear documentation, and real-world relevance. Submissions via Devpost require a project page, a public GitHub repository with source code and instructions, a maximum 10-minute pitch video, and a presentation deck of up to 10 slides.

Prizes Awards are given for 1st Prize in each of the four tracks, as well as categories for Best AI Solution, Best Student Team, Best Scientific Rigor Award, Most Innovative Application, Best Community Impact, and Best Collaboration Prize.

Judging Criteria Projects are evaluated based on Scientific Relevance, Innovation, Technical Implementation, Data Science Quality, Feasibility, Impact, and Presentation.