معرفی
Elma Dervic is a Postdoctoral Researcher at the Section for Science of Complex Systems at the Medical University of Vienna and a resident scientist at the Complexity Science Hub Vienna. Her work integrates data science, network science, and machine learning to address complex challenges in healthcare, human migration, and supply chain resilience.
Research Interests:
- Machine Learning and Network Science for health data
- Modeling disease trajectories and comorbidity networks
- Systemic risk analysis in global supply chains
- Migration dynamics and refugee integration
- Agent-based modeling of healthcare systems
Her recent research has focused on unraveling cradle-to-grave disease trajectories using population-wide health data and analyzing systemic risks in antibiotic and food supply chains. Her publications span high-impact journals such as Nature Communications, Nature Human Behaviour, and Translational Psychiatry. The articles reflect a strong interdisciplinary trend, combining medical data with network theory and machine learning to uncover hidden patterns in disease progression, gender disparities in health outcomes, and structural vulnerabilities in critical systems.
Scientific Awards:
- Life Sciences Research Award 2024 – for breakthroughs in understanding disease trajectories
Elma has been actively involved in advising and collaborative research, contributing to major projects such as ASCII (Austrian Supply Chain Intelligence Institute), D4Dairy, and MigraCapax. She has also secured research visibility through TEDx talks and media coverage in outlets like International Business Times and US Pharmacist. Her work on data transparency in medical research has led to the creation of open datasets, including the CSH Covid-19 Control Strategies List.
Labs and Research Teams:
- Complexity Science Hub Vienna (CSH)
- Section for Science of Complex Systems, Medical University of Vienna
- Co-founder of BeeAnd.me – an IoT startup applying data science to beekeeping
- Core member of the Montenegrin AI Association (MAIA)
