About Me

I am an Applied Mathematician at the Delft Institute of Applied Mathematics (DIAM), TU Delft. I combine differential and integral equations, numerical analysis, and data science to tackle complex, interdisciplinary challenges and bridge advanced theory with real-world solutions.

My work focuses on two core domains: Industrial Mathematics and Mathematics for Agriculture, where I uncover underlying physical phenomena and transform intricate datasets into predictive tools.

🔥 Recent Highlights

🔬 Featured Publications

• [Cover Article] 📑 Our latest research has been featured on the cover of Nature Microbiology! Read the full paper here.
  
• [Machine Learning] 🚀 Our new foundational paper on geometric interpretation of overparameterized multiple linear regression is published in Machine Learning: Science and Technology! Read the full paper here.

🎯 Research Focus Pillars

🌾 Mathematics for Agriculture

I develop and apply biology-informed and data-driven mathematical models to solve pressing challenges in agriculture. I serve as a Principal Investigator (PI) within the CropXR Institute Potato satellite program, collaborating closely with 12 industrial partners, specifically within the HIP consortium, to engineer climate-resilient crop solutions through smart breeding.

• Key Areas: crop growth modeling, genomic prediction and discovery, data-driven plant resilience.
• Impact: Helping the agricultural sector optimize yields, reduce resource consumption, and adapt to climate challenges using rigorous mathematical frameworks.

🏭 Industrial Applications of Mathematics

I am a Board Member of the European Consortium for Mathematics in Industry (ECMI) that helps to translate abstract mathematical theories into actionable engineering software and solutions.

• Key Areas: Computational physics, inverse scattering, wave propagation, and imaging technologies.
• Impact: Accelerating product development cycles and optimization for engineering firms, tech companies, and industrial consortia.

🤝 Collaboration & Opportunities

• For Industry Partners: I am always open to exploring contract research, joint consortia, or consulting on complex modeling problems.
• For Students (BSc/MSc/PhD): If you want to see how deep mathematics solves real-world food security and industrial challenges, I am actively seeking students for thesis projects in:
  • 📊 Project Track A: Mathematical modeling for CropXR potato resilience datasets.
  • 📉 Project Track B: Overparameterized regression problems.
  • 🎛️ Project Track C: Computational wave propagation and industrial inverse problems.