Zürich Metropolitan Area
Complex Systems Scientist with a PhD in Physics. My academic research focused on statistical physics of disordered systems, network science, and complex systems, studying phenomena such as protein folding, epidemic spreading, opinion dynamics and information diffusion on complex networks. In industry, I develop analytics and AI applications in the financial sector. These include risk prediction, marketing efficency models, NLP of large-scale unstructured data, and speech-to-text audio analytics pipelines, translating data science methods into reliable decision-making. I am co-founder of Maika, a startup exploring the intersection of biometrics, AI and music to support relaxation, focus and emotional wellbeing.
• Defined the tech and scientific roadmap for a startup exploring how biometric signals and generative AI can support emotional regulation through music. • Designed machine learning pipelines to analyze physiological signals and infer emotional states, enabling personalized music interventions. • Built early prototype and signal-processing systems integrating biometric data, emotion modeling, and music generation. • Translated bio signals and physiological modeling research into product prototypes and deployable components. • Coordinated interdisciplinary work across AI research, engineering, and product development.
Invited guest lecturer in the CAS Machine Learning in Finance & Insurance program at ETH Zürich, delivering lectures on applied machine learning and deep learning in banking and financial services. Topics include: • Churn prediction and customer behavior modeling • Practical deployment of ML models in regulated environments • Model evaluation, interpretability, and business impact • Translating advanced AI methods into real-world decision systems The program targets industry professionals and senior practitioners, focusing on bridging academic methodology with practical implementation.
Leading applied AI initiatives in a banking environment, focusing on operationalizing machine learning and enabling business teams to adopt data-driven decision-making. Championed adoption of LLMs and generative AI across business units, advising senior leadership on practical AI opportunities. Coordinated cross-functional teams (data engineering, analytics, business stakeholders) to deploy ML solutions into production workflows. Established data quality and governance frameworks improving reliability and reducing operational costs. Mentored colleagues and led internal workshops to build AI literacy across the organization.
• Delivered endtoend ML solutions for a digital education startup: from problem scoping with founders to model deployment and stakeholder training. • Built NLP pipelines for sentiment analysis and conducted A/B testing to optimize product performance.
• Conducted research on complex systems and network science, focusing on diffusion, contagion, opinion dynamics and information spreading on networks, using tools from statistical physics, stochastic processes, and computational modeling. • Developed computational simulations and analytical models to study emergent behavior in large-scale networked systems. • Built predictive epidemiological models for COVID-19 incidence forecasting, supporting comparative analysis of policy responses across countries. • Taught Network Science (Master’s level) and supervised graduate and undergraduate research projects in complex systems and data-driven modeling. • Led Swiss National Science Foundation grant proposals and authored peer-reviewed publications on network dynamics, blockchain, and predictive modeling of large-scale complex systems.