Curriculum Vitae
Francisco Richter Mendoza
Postdoctoral researcher specializing in statistical modeling, complex networks, and phylogenetic inference. I bridge applied research, interdisciplinary collaboration, and teaching across data science, artificial intelligence, and biodiversity topics.
Education
PhD in Computational Statistics
University of Groningen, Netherlands (2016–2021)
Thesis: Inferring the Drivers of Species Diversification
Mathematical Engineer
Universidad Técnica Federico Santa María, Chile (2005–2012)
Thesis: Mathematical Modelling Applied to Photometric Correction in Astronomical Observations
Career Timeline
A trajectory focused on solving complex problems through advanced mathematical and statistical tools.
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2026 – Present
Scientific Collaborator · Università della Svizzera italiana
Scientific collaborator within the Statistical Frontiers in Dynamic Network Modeling project at USI, advising research partners and translating methods into decision tooling.
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2024 – 2025
Lecturer · Università della Svizzera italiana
Designed and delivered graduate-level courses in computational science and AI, mentoring students and coordinating curriculum updates.
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2021 – 2023
Postdoctoral Fellow · Università della Svizzera italiana
Postdoctoral researcher on statistical models for complex networks and dynamical systems, focusing on diversity-dependent diversification and graduate teaching.
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2016 – 2021
Doctoral Researcher · University of Groningen
Doctoral work with Rampal Etienne and Ernst C. Wit on species diversification using mathematical and statistical frameworks.
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2013 – 2016
Data Scientist · Evalueserve, Chile
Operational risk analyst applying extreme value theory and stochastic modeling to evaluate financial portfolios.
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2013
Research Assistant · European Southern Observatory
Developed photometric correction methods for astronomical observations as part of the engineering thesis.
Academic Activities
Lecture teaching (USI)
- Analysis of Social Networks — MSc in Computational Science (elective, year 2), Autumn 2024–2025.
- Introduction to Ordinary Differential Equations — MSc in AI & Computational Science (elective, years 1–2), Autumn 2024–2025.
- Introduction to Data Science — BSc in Informatics (core, year 2), Autumn 2025.
- Probability & Statistics — BSc in Informatics (core, year 2), Autumn 2023–2025.
- Numerical Computing — MSc in Computational Science, Spring 2025.
- Stochastic Methods — MSc in AI & Computational Science, Spring 2024–2025.
Detailed syllabi: franciscorichter.github.io/teaching
Individual supervision
- Mattia Colbertaldo — Machine Learning for Species Diversification Dynamics, Politecnico di Milano (defended 13 Jun 2024).
- Lodovico Mazzei — Stochastic Learning for Species Diversification Dynamics, USI (defended 5 Sep 2023).
- Oscar A. Silva Castellanos — Inferring Phylogenetic Diversification Parameters Using Deep Learning, USI (defended 27 Nov 2023).
- Lovnesh Bhardwaj — Causal Discovery in Dynamic Interaction Networks, USI (ongoing, defense Dec 2025).
- Federica Marini — Deep Generative Models for Macroevolutionary Scenarios, USI (ongoing, defense Jul 2024).
Other academic activities
Associate Editor, Statistica Neerlandica, Wiley Online Library (2023–Present).
Research & Communications
Publications
- 2025: Richter, F., Rigana, K., Wit, E. Neural Causal Regularization: Extending Causal Invariance to Deep Models. In Statistics for Innovation I. Springer. DOI: 10.1007/978-3-031-96736-8_17.
- 2024: Zhou, Y. et al. Stereo 3D Cloud Motion from Tandem Satellites. Mathematics in Industry Reports. DOI: 10.33774/miir-2024-51r3q.
- 2024: Vinciotti, V., Wit, E.C., Richter, F. Random Graphical Model of Microbiome Interactions in Related Environments. JABES.
- 2021: Hendriks, K.P. et al. Microbiome and Environment Explain the Absence of Correlations Between Consumers and Their Diet in Bornean Microsnails. Ecology. DOI: 10.1002/ecy.3237.
- 2021: Hendriks, K.P., Richter, F.J. et al. Plant Diets of Land Snail Community Members Are Similar in Composition but Differ in Richness. Journal of Molluscan Studies.
- 2021: Richter, F. et al. Detecting Phylodiversity-Dependent Diversification with a General Phylogenetic Inference Framework. bioRxiv.
- 2020: Richter, F. et al. Introducing a General Class of Species Diversification Models for Phylogenetic Trees. Statistica Neerlandica.
- 2019: Hendriks, K.P. et al. Fieldwork to Sample Microsnails... Malacologist.
Conference presentations
- 2026: 9º Workshop de Modelamiento Matemático de Sistemas Biológicos (MatBio UTEM), Santiago, Chile. Inferring the Drivers of Species Diversification Processes.
- 2026: Universidad Técnica Federico Santa María Colloquium, Valparaíso, Chile. Robust and Fair Prediction under Distribution Shift: Extending Causal Invariance to Deep Models.
- 2025: Italian Statistical Society Conference — SIS 2025 · Statistics for Innovation, Genoa, Italy. Neural Causal Regularization: Extending Causal Invariance to Deep Models.
- 2023: International Conference on Complex Networks (CompleNet), Aveiro, Portugal. Detecting Complex Diversity-Dependent Diversification with a Novel Phylogenetic Inference Framework.
- 2023: World Conference on Natural Resource Modeling, Amsterdam, The Netherlands. Phylodiversity-Dependent Diversification: A General Framework for Investigating the Role of Phylogenetic Diversity.
- 2022: Conference on Complex Systems, Palma de Mallorca, Spain. Inferring the Drivers of Species Diversification Processes.
- 2020: World Conference on Natural Resource Modeling, Valparaíso, Chile. Including Phylodiversity in Diversity-Dependent Diversification Models.
- 2018: Mathematics for Planet Earth Meeting, Utrecht, The Netherlands. A Statistical Approach to Species Diversification Dynamics.
- 2018: Conference on Complex Systems, Thessaloniki, Greece. Generalizing Species Diversification Models.
- 2017: Mathematical Models in Ecology and Evolution, London, United Kingdom. Generalizing Species Diversification Models.
- 2017: International Workshop on Statistical Modelling, Groningen, The Netherlands. A General Statistical Framework to Study the Diversification of Species.