Lead scientist · The spread of infection, information, computer malware, or any contagion-like process is often described by disease models on complex… · More networks with a time-varying topology. Recurrent, or flulike, spreading can be modeled accurately by taking an “individual-based” approach that focuses on nodes in a network. Here, we instead focus on the interactions—the links in a network—and present a contact-based model that accurately describes a second group of contagion processes: those that lead to permanent immunization. Taking this new perspective, we derive a criterion that separates local outbreaks from global epidemics, a crucial tool for risk assessment and control of, for instance, viral marketing.
Designed the study Performed the mathematical and numerical analysis Wrote the manuscript
Shared first author, Python, Pandas, Numpy · Forecast and control of global epidemic outbreaks such as SARS (2003), H1N1 (2009) and Ebola (2014) remain… · More a major challenge to public health institutions. A central information, in order to implement containment strategies is the time until the first infected individual arrives at a specific place. Here, we provide a mathematical framework that integrates air-traffic data and thus provides highly accurate predictions about the spreading dynamics. We demonstrate numerically that our approach outperforms the state-of-the-art method at a low computational cost.
Derived the main mathematical result. Provided most of the numerical simulations and visualizations.
Second author, Python, Pandas, Numpy · Animal trade plays an important role for the spread of infectious diseases in livestock populations. The central… · More question of this work is how infectious diseases can potentially spread via trade in such a livestock population. We address this question by analyzing the underlying network of animal movements.
We present a computationally efficient data-driven model
Lead scientist, Python, Numpy, Scipy · The spreading of rumors on Twitter, global epidemic outbreaks and, computer viruses can often be explained with… · More simple disease models. Here, we propose a novel data-driven model that integrates (time-stamped) contact data with a generic epidemic model. This approach is entirely based on elementary matrix operations and unifies the disease and network dynamics within one algebraic framework. As a consequence, our approach allows to integrate large data sets at a low computational cost and thus improves state-of-the-art predictive models.
Developed the mathematical model; Performed the computational analysis; Wrote the manuscript
What I Do
Enthusiastic physicist / data scientist. As PhD candidate at TU Berlin developed novel data-driven models that predict global epidemic outbreaks. Now, eager to turn experience into products with social and environmental impact.
Finished PhD with "summa cum laude" / "graduated with highest honors";
Publication in top 5 Physics journal (Physical Review X)
8 publications (currently 99 citations) + 2 currently under review;
11 talks at international conferences.
3 travel grants & stipends from German Academic Exchange Service (DAAD)
Raised funding for a 6 month research position in Ireland.
Organization of weekly seminars (3 semesters) and tutorials (4 semesters) with 20+ students, supervision of 7 final year projects.