Carlo Albert

Dr. Carlo Albert

Abteilung Systemanalyse, Integrated Assessment und Modellierung

Über mich

Head of the group Mathematical Methods in Environmental Research, at the  Department of Systems Analysis, Integrated Assessment and Modelling


Ph.D. in Theoretical Physics, Dr. Phys. ETH

M.Sc. in Mathematics, Dipl. Math. ETH


Modelling of environmental systems
I apply methods from statistical physics, nonlinear systems theory and statistics to detect and model predictable features of complex environmental systems. Of particular interest is a faithful quantification of uncertainty.

Selected publications

DD Giudice, M Honti, A Scheidegger, C Albert, P Reichert, J Rieckermann, Improving uncertainty estimation in urban hydrological modeling by statistically describing bias, Hydrology and Earth System Sciences 17 (10), 4209-4225, 2013.

Jager T., Albert C., Preuss T.G., Ashauer R., General Unified Threshold Model of Survival - a Toxicokinetic Toxicodynamic Framework for Ecotoxicology, Env. Science and Technology, 45, 2529-2540, 2011.
doi: 10.1021/es103092a

Calogovic J., Albert C., Arnold F., Beer J., Desorgher L., and Flueckiger E. O., Sudden cosmic ray decreases: No change of global cloud cover, Geophys. Res. Lett. 37,  2010.

Development of algorithms
Quantifying the parametric uncertainty of a model that needs to be calibrated to data is a computationally hard problem, in particular, if the model is slow or stochastic. Statistical physics and non-equilibrium thermodynamics offer some great tools to make parameter inference with stochastic models more efficient. Mechanistic emulators are an efficient way of speeding up slow simulators and make them amenable to simulation-intense tasks such as parameter inference.

Selected publications

Albert C., Ulzega S., Stoop, R., Boosting Bayesian parameter inference of nonlinear stochastic differential equation models by Hamiltonian scale separation, Phys. Rev. E 93, 2016.
doi: 10.1103/PhysRevE.93.043313, arXiv:1509.05305 [cs.DS]

Albert C., A Simulated Annealing Approach to Bayesian Inference,  2015.
arXiv:1509.05315 [stat.CO]

Albert C., Künsch HR., Scheidegger A., A Simulated Annealing Approach to Approximate Bayes Computations, Stat. Comput., 2014.
doi: 10.1007/s11222-014-9507-8, arXiv:1208.2157 [stat.CO]

Albert C., A Mechanistic Dynamic Emulator, J. Nonlinear Analysis B 13, 2747–2754, 2012.

doi:10.1016/j.nonrwa.2012.04.003, arXiv:1112.5304v2 [stat.ME].

Publications    Google Scholar

Teaching     Summer School in Environmental Systems Analysis

Workshop  History of Solar Activity Recorded in Polar Ice

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Komplexe Systemtheorie trifft auf Phytoplankton “Big Data”.
Towards a better understanding and more reliable predictions of complex systems dynamics.
Kalibrierung stochastischer Regen-Abflussmodelle mit Hilfe von Skalengesetzen für verbesserte Prognosen von Extremereignissen.

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Telefon: +41 58 765 5244
Fax: +41 58 765 5802
Adresse: Eawag
Überlandstrasse 133
8600 Dübendorf
Büro: FC D02

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Experte für

Ökologie, Modellierung, Transdisziplinäre Forschung

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