Pedro Lind

Pedro Gonçalves Lind (født 23. mars 1976 i Lisboa) er en tysk-portugisisk fysiker og professor ved Institutt for informasjonsteknologi ved Oslomet – storbyuniversitetet. Han er også nestleder ved Oslomet Artificial Intelligence Lab (AI Lab).Linds fremste forskningsinteresser er stokastisk modellering, komplekse ikke-lineære systemer, maskinlæring, avansert statistikk og dataanalyse, optimaliseringsmetoder og stabilitetsanayse, samt modellering og simulering av prosesser innenfor fagområdene fornybar energi, finans, biologi og samfunnsfag.


== Utdanning og yrkeskarriere ==
I 2003 fikk Lind en doktorgrad i matematisk fysikk fra universitetet i Lisboa. Året etter ble han ansatt som postdoktor ved Institutt for beregningsfysikk ved universitetet i Stuttgart, der han senere ble forfremmet til forsker. I 2007 tok han så en forskerstilling ved det tyske forskningsrådet Deutsche Forschungsgemeinschaft , og året etter tiltrådte han nok en forskerstilling - denne gangen ved universitetet i Lisboa. Deretter arbeidet han som forsker ved henholdsvis universitetet i Oldenburg og universitetet i Osnabrück, før han ble ansatt som professor ved Oslomet – storbyuniversitetet i 2019.


== Utmerkelser ==
I 2009 ble Lind utnevnt til Outstanding Referee av American Physical Society (APS). Utmerkelsen gis til forskere som har gjort en ekstraordinær innsats som fagfelle for tidsskrifter utgitt av APS.


== Vitenskapelige publikasjoner ==
Et utvalg av Linds publikasjoner:

Krohn, Otthar; Varankian, Vako; Lind, Pedro; Melo, Gustavo (2020). Implementation of an inexpensive eye-tracking system for educational purposes. Stepahnidis, C.; Antona, M. (Ed.). Universal Access in Human-Computer Interaction, Applications and Practice. Article. p. 60-78. Springer Nature.Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (2020). EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality. Castillo, Pedro A.; Laredo, Juan Luis Jiménez; de Vega, Francisco Fernández (Ed.). Applications of Evolutionary Computation. p. 133-148. Springer.Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (2020). A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality. Cognitive Neurodynamics.Kampers, Gerrit; Waechter, Matthias; Hoelling, Michael; Lind, Pedro; Queiros, Silvio D.A.; Peinke, Joachim (2020). Disentangling stochastic signals superposed with periodic oscillations. Physics Letters A. Vol. 384.Fuchs, Andre; Queiros, Silvio D.A.; Lind, Pedro; Girard, Alain; Bouchet, Freddy; Wächter, Matthias; Peinke, Joachim (2020). Small scale structures of turbulence in terms of entropy and fluctuation theorems. Physical Review Fluids. Vol. 5.Garcia, Constantino; Lind, Pedro; Wächter, Matthias; Otero, Abraham; Peinke, J. (2019). ON THE EXISTENCE AND CHARACTERIZATION OF EXTREME EVENTS IN WIND DATA. EUROPEAN CONFERENCE ON RENEWABLE ENERGY SYSTEMS ECRES 2019. N.A.. p. 320-327.Sim, So-Kumneth; Maass, Philipp; Lind, Pedro (2019). Wind Speed Modeling by Nested ARIMA Processes. Energies.Schmietendorf, Katrin; Kamps, Oliver; Wolff, Matthias; Lind, Pedro; Maass, Philipp; Peinke, Joachim (2019). Bridging between load-flow and Kuramoto-like power grid models: A flexible approach to integrating electrical storage units. Chaos. Vol. 29.Wolff, Matthias; Schmietendorf, Katrin; Lind, Pedro; Kamps, Oliver; Peinke, Joachim; Maass, Philipp (2019). Heterogeneities in electricity grids strongly enhance non-Gaussian features of frequency fluctuations under stochastic power input. Chaos. Vol. 29.Sequeira, Joao; Louca, Jorge; Mendes, Antonio; Lind, Pedro (2019). Transition from endemic behavior to eradication of malaria due to combined drug therapies: an agent-model approach. Journal of Theoretical Biology. Vol. 484.Richter, Yvonne; Lind, Pedro; Maass, Philipp (2018). Optimized adjustment of a reaction-diffusion model to case-specific atrial physiology. PLOS ONE.Traphan, Dominik; Wester, Tom; Gülker, Gerd; Peinke, Joachim; Lind, Pedro (2018). Aerodynamics and percolation: unfolding the laminar separation bubble on airfoils. Physical Review X.Wolff, Matthias; Lind, Pedro; Maass, Philipp (2018). Influence of heterogeneities in the frequency stability of power grids. Chaos.Scholz, Teresa; Raischel, Frank; Lopes, Vitor; Lehle, Bernd; Wächter, Matthias; Peinke, Joachim; Lind, Pedro (2017). Parameter-free resolution of the superposition of stochastic signals. Physics Letters A. Vol. 381.Richter, Yvonne; Lind, Pedro; Seemann, Gunnar; Maass, Philipp (2017). Anatomical and spiral wave reentry in a simplified model for atrial electrophysiology. Journal of Theoretical Biology. Vol. 419.Curral, Luis; Leitao, Paulo; Gomes, Catarina; Marques-Quinteiro, Pedro; Lind, Pedro (2017). How complexity leadership and cohesion influence team effectiveness. Rev. Psicol., Organ. Trab. Vol. 17.Schiel, Christoph; Lind, Pedro; Maass, Philipp (2017). Influence of intermittency of wind power on the statistics of transmission line outages in power grids. Scientific Reports. Vol. 7.Estevens, Joana; Rocha, Paulo; Boto, Joao; Lind, Pedro (2017). Stochastic modelling of non-stationary financial assets. Chaos. Vol. 27.Lind, Pedro; Vera-Tudela, Luis; Wächter, Matthias; Kühn, Martin; Peinke, Joachim (2017). Normal Behaviour Models for Wind Turbine Vibrations: Comparison of Neural Networks and a Stochastic Approach. 14 p. Energies. Vol. 10.Richter, Yvonne; Lind, Pedro; Lenk, Claudia; Seemann, Gunnar; Maass, Philipp (2017). Optimized adjustment of a reaction-diffusion model to case-specific atrial physiology: towards clinical implementation. Computing in cardiology.Hadjihossein, Ali; Lind, Pedro; Mori, Nobuhito; Hoffmann, Norbet; Peinke, Joachim (2017). Rogue waves and entropy consumption. Europhysics letters.Mendes, Maria; Gomes, Catarina; Marques-Quinteiro, Pedro; Lind, Pedro; Curral, Luis (2016). Promoting learning and innovation in organizations through complexity leadership theory. Team Performance Management. Vol. 22.Lencastre, Pedro; Raischel, Frank; Boto, Joao; Lind, Pedro (2016). From empirical data to time-inhomogeneous continuous Markov processes. Physical review. E. Vol. 93.Rocha, Paulo; Raischel, Frank; Boto, Joao; Lind, Pedro (2016). Uncovering the evolution of non-stationary stochastic variables: the example of asset volume-price fluctuations. Physical Review E. Statistical, Nonlinear, and Soft Matter Physics. Vol. 93.Rinn, Philip; Lind, Pedro; Wächter, Matthias; Peinke, Joachim (2016). The Langevin Approach: An R Package for Modeling Markov Processes. Journal of Open Research Software (JORS). Vol. 4.Curral, Luis; Marques-Quinteiro, Pedro; Gomes, Catarina; Lind, Pedro (2016). Leadership as an emergent system: Insights from a laboratory experiment. PLOS ONE. Vol. 11.En fullstendig liste over Linds publikasjoner finnes på OsloMets ansattside.


== Referanser ==


== Eksterne lenker ==
«Pedro Lind». Oslomet – storbyuniversitetet. Besøkt 12. oktober 2020.