About

I'm an assistant professor at the Mathematics Department of the Faculty of Science of the Vrije Universiteit Amsterdam in the Netherlands. I'm also a board member of the Examination Board Mathematics and Business Analytics, I chair the Business Analytics Outreach Committee (VPR), and I'm a researcher and lecturer in the area of (Non-parametric) Mathematical Statistics.

In the past I've been a board member of the MSc Internship board for the Business Analytics program at the VU Amsterdam, a board member of the Mathematical Statistics section of the VVSOR, and a co-organiser of the (International) Bayes Club. I've also been an assistant professor at the Department of Mathematics and Computer Science of the Eindhoven University of Technology for a few years. Before that, I was a postdoc for a year at the Korteweg-de Vries Institute of the University of Amsterdam, working as part of the NETWORKS project, funded under NWO's Zwaartekracht grant, and earlier I spent two years as a postdoc at the Institute for Mathematical Stochastics of the University of Göttingen, in Germany. A long time ago I was a junior researcher for a year at the CA3 group at UNINOVA, in Portugal, working on project NOMDIS developed for ESA/ESOC.

Updated: April 2026

Research Interests

I have a wide range of research interests within (non-parametric) Mathematical Statistics, including spline estimators, Bayesian non-parametrics and its frequentist properties, empirical Bayes, adaptation, non-standard asymptotic setups such as the ones that arise when working with periodically varying parameters, statistical tracking of time-varying parameters, non-parametric regression, quantile regression, and multi-stage estimation procedures and sequential testing procedures. Most of what I do involves Markov processes and Markov chains, Markov chain Monte Carlo, and Poisson processes. A lot of my work is theoretical, but I am also very interested in the implementation of algorithms and their practical applications, programming, and on-line (recursive) algorithms.

Updated: April 2026

Short Curriculum

Updated: July 2020

Publications

I only update these lists occasionally, so they are likely to be out of date.

Preprints

• [No link] M. Regis, and P. Serra. Return-to-baseline Testing (tentative).
• [No link] P. Serra, and J. Wang. DP inference on Dynamic on/off networks (tentative).

Papers, Patents, and Code

• 31.[Link] R. Kamphuis, M. Mandjes, and P. Serra. Road traffic estimation and distribution-based route selection. Electronic Journal of Statistics, 19, 2025.
• 30.[Link] R. Kamphuis, M. Mandjes, and P. Serra. Road traffic estimation and algorithmic routing in a spatially dependent network. Scandinavian Journal of Statistics, 2025.
• 29.[Link] T. Bakkes, E. Mestrom, N. Ourahou, M. Mischi, E. Korsten, P. Serra, A. Bouwman, and S. Turco. Predictive modeling of perioperative patient deterioration: combining unanticipated ICU admissions and mortality for improved risk prediction. Perioperative Medicine (to appear.) 2024
• 28.[Link] E. Mestrom, T. Bakkes, N. Ourahou, E. Korsten, P. Serra, L.J. Montenij, M. Mischi, S. Turco, and A. Bouwman. Prediction of postoperative patient deterioration and unanticipated intensive care unit admission using perioperative factors. PLOS One (to appear.) 2023
• 27.[Link] E. Belitser, P. Serra, and A. Vegelien. Robust oracle estimation and uncertainty quantification for possibly sparse quantiles. Journal of Nonparametric Statistics (to appear.) 2023
• 26.[Link] M. Regis, L.M. Eerikäinen, R. Haakma, E.R. van den Heuvel, and P. Serra. Robust probabilistic modelling of PPG signals. JRSSc (to appear.) 2023
• 25.[Link] T. Krivobokova, P. Serra, F. Rosales, and K. Klockmann. Joint non-parametric estimation of mean and auto-covariances for Gaussian processes. Computational Statistics and Data Analysis, 2022.
• 24.[Link] M. Regis, P. Serra, and E.R. van den Heuvel. Random autoregressive models: A structured overview. Econometric Reviews, 2021.
• 23.[No link] P. Serra, M. Regis, and L. Eerikäinen. International Application No. PCT/EP2020/054610, 2020.
• 22.[Link] P. Serra, and M. Mandjes. Estimation of Local Degree Distributions in Inhomogeneous Graphs. Computational Statistics and Data Analysis, 2019.
• 21.[No link] E. Belitser, N. Nurushev, and P. Serra. Robust estimation of sparse signal with unknown sparsity cluster value. 4th ISNPS, Salerno, Italy, June 2018, Springer, 2019.
• 20.[Link] P. Serra, and M. Regis. Automatic segmentation and probabilistic modelling of PPG signals. International Application No. PCT/EP2018/081322, 2018.
• 19.[Link] P. Serra, and M. Mandjes. Dimension Estimation Using Random Connection Models. Journal of Machine Learning Research, 18, 2018.
• 18.[Link] F. Rosales, P. Serra, and T. Krivobokova. eBsc (Version 0.9). Göttingen, Germany, 2018.
• 17.[Link] P.J. Serra, and A. Di Bucchianico. Discussion on "Semiparametric Bayesian Optimal Replacement Policies" by Merrick and Soyer. Applied Stochastic Models in Business and Industry, 33, 2017.
• 16.[Link] P. Serra, and T. Krivobokova. Adaptive empirical smoothing splines. Bayesian Analysis 12:219–238, 2016.
• 15.[Link] E. Belitser, and P. Serra. Recursive Tracking Algorithm for a Predictable Time-Varying Parameter of a Time Series. Mathematical Methods of Statistics 24:243–265, 2014.
• 14.[Link] E. Belitser, P. Serra, and H. van Zanten. Rate optimal Bayesian intensity smoothing for inhomogeneous Poisson processes. Journal of Statistical Planning and Inference, 166:24–35, 2015.
• 13.[No link] E. Belitser, and P. Serra. Recursive estimation of conditional spatial medians and conditional quantiles. Sequential Analysis, 33:519–538, 2014.
• 12.[Link] E. Belitser, and P. Serra. Adaptive priors based on splines with random knots. Bayesian Analysis, 9:859–882, 2014.
• 11.[No link] E. Belitser, P. Serra, and H. van Zanten. Estimating the period of a cyclic non-homogeneous Poisson process. Scand. J. Stat., 40:204–218, 2013.
• 10.[Link] E. Belitser, and P. Serra. On properties of the algorithm for pursuing a drifting quantile. Automation and Remote Control, 74:613–627, 2013.
• 9.[Link] P.J. de Andrade Serra et al. Up and beyond building a mountain in the Netherlands. Proceedings of the 84th European Study Group Mathematics with Industry, Eindhoven, 2012, pages 104–125, 2012.
• 8.[No link] S.H. Alavi, J. Jassbi, P. Serra, and R.A. Ribeiro. Defining fuzzy measures: a comparative study with genetic and gradient descent algorithms. Intelligent Engineering Systems and Computational Cybernetics, pages 427–437. Springer, 2009.
• 7.[No link] C. Coelho, and P. Serra. Fuzzy thermal alarm system (Version 1.0). Setúbal, Portugal, 2008.
• 6.[No link] C. Coelho, P. Serra, R.A. Ribeiro, R.A.M. Pereira, A. Dietz, and A. Donati. Fuzzy alarm system for laser gyroscopes' degradation. Intelligent Automation and Soft Computing, 14:351–365, 2008.
• 5.[No link] R.A.M. Pereira, R.A. Ribeiro, and P. Serra. Rule correlation and Choquet integration in fuzzy inference systems. IJUFKS, 16:601–626, 2008.
• 4.[Link] P. Serra, R.A. Ribeiro, R.A.M. Pereira, R. Steel, M. Niezette, and A. Donati. Fuzzy thermal alarm system for Venus express. Encyclopedia of Decision Making and Decision Support Technologies, pages 391–401. IGI Global, 2008.
• 3.[Link] J. Jassbi, S.H. Alavi, P. Serra, and R.A. Ribeiro. Transformation of a Mamdani FIS to first order Sugeno FIS. FUZZ-IEEE 2007, pages 1–6. IEEE, 2007.
• 2.[No link] R.A.M. Pereira, P. Serra, and R.A. Ribeiro. Choquet integration and correlation matrices in fuzzy inference systems. Computational Intelligence, Theory and Applications, volume 38, pages 15–18. Springer, 2006.
• 1.[No link] J. Jassbi, P.J.A. Serra, R.A. Ribeiro, and A. Donati. A comparison of Mamdani and Sugeno inference systems for a space fault detection application. World Automation Congress, WAC '06, pages 1–8, 2006.

Updated: April 2026

Teaching

I'm teaching the courses Master Seminar in Stochastics, Statistics for Business Analytics, and Stochastic Processes for Finance at the VU Amsterdam. I also teach the Mastermath course Bayesian Statistics.

You can find my Python with Jupyter Notebook introduction tutorial to Probability and Statistics here. I use this in my courses.

Right now I'm co-supervising three PhD students, one MSc student, two BSc students, and one MSc internship.

Updated: July 2023

Contact