Cristina Masoller’s research projects

Marie Curie ITN CAFE: Climate advanced forecasting of sub-seasonal extremes (March 2019-February 2023, H2020-813844)

Web page: http://www.cafes2se-itn.eu/

Partners: Centre de Recerca Matemàtica (Spain, Coordinator), Univ. Politècnica de Catalunya (Spain), Technische Universitaet Bergakademie Freiberg (Germany), Potsdam Institut für Klimafolgenforschung(Germany), Aria Technologies (France), Meteo-France, CSIC (Spain), Max-Planck-Institute For Complex Systems (Germany), Universidad de la República (Uruguay), European Centre for Medium-Range Weather Forecasts (UK).


Principal Investigator in UPC: Prof. Cristina Masoller


Summary: Forecasting climatic extreme events on the sub-seasonal time scale (from 10 days to about 3 months) is very challenging because of the poor understanding of phenomena that may increase predictability in this time scale. The CAFE network will provide top-level training to 12 young researchers that will enable them to advance the state of the art of subseasonal predictability. The students will receive training on a wide range of disciplines, including climate science, meteorology, statistics and non-linear physics.

Kick-off meeting of the CAFE project (March 2019)


Complex dynamical systems and advanced data analysis tools (ComDynSys)


Ministerio de Ciencia, Innovación y Universidades, PGC2018-099443-B-I00


Description: The aim of this project is to improve the understanding of nonlinear phenomena in complex systems by the use of various data analysis tools, with the long-term goal of exploiting nonlinear phenomena for innovative applications. The phenomena to be studied are interdisciplinary and include the spiking output of laser diodes, neuronal signal encoding and processing, extreme events in atmospheric dynamics, brain signals and retina images, among many others. The research involves experiments, numerical simulations and data analysis.


ICREA ACADEMIA (2016-2020)

Funded by Institució Catalana de Recerca i Estudis Avançats (ICREA), Generalitat de Catalunya.

Principal Investigator: Cristina Masoller


The research funded by ICREA ACADEMIA is aimed at i) exploiting nonlinear dynamics for novel applications and ii) developing advanced analysis tools for studying the output signals of complex systems. A first research objective is aimed at exploiting the optical spikes generated by a semiconductor laser with feedback, for implementing photonic neurons that mimic biological ones. A second goal is to exploit the analysis tools developed by the LINC project to advance a crucial problem of climate dynamics: predictability in the sub-seasonal time-scale, which lies between the well-established application of weather forecast and that of the seasonal forecast.



Previous projects:

BE-OPTICAL: Advanced biomedical imaging and data analysis


EU-H2020 Marie Skłodowska-Curie Innovative Training Network

October 2015-September 2019


Coordinator: Prof. Cristina Masoller

Project Manager: Dr. Jordi Tiana

PhD students: D. Halpaap, P. Amil


Summary: The main goals of the BE-OPTICAL project were

1) To provide top-level multi-skill training to 14 early stage researchers (ESRs) in a wide range of optical imaging technologies and signal processing tools, including fluorescence spectroscopy and microscopy, optical coherence tomography (OCT), optogenetics, engineered nanomaterials and signal processing tools.

2) To develop cutting-edge research in the fields of optical imaging, nanotechnology, computer science, complex systems and data analysis (the specific research goals of the ESR projects are listed below).

3) To bring together interdisciplinary team of physicists, engineers and medical doctors, with complementary expertise, and engage them in successful long-term collaborations.


The research projects of the two PhD students supervised by Prof. C. Masoller were

-       Donatus Halpaap: to develop new approaches for reducing speckle in double pass images.

PhD thesis: Experimental study of speckle generated by semiconductor light sources: application in double pass imaging (2019, co-supervised with M. Vilaseca, DF-UPC News)




D. Halpaap, C. E. Garcia-Guerra, M. Vilaseca, C. Masoller, “Speckle reduction in double-pass retinal images”, Sci. Rep. 9, 4469 (2019).


D. Halpaap, J. Tiana-Alsina, M. Vilaseca, C. Masoller, “Experimental characterization of the speckle pattern at the output of a multimode optical fiber”, Opt. Express 27, 27738 (2019).


-       Pablo Amil: to develop novel algorithms for the analysis and classification of complex biomedical images.

PhD thesis: Machine learning methods for the characterization and classification of complex data (February 2020)



P. Amil, L. Gonzalez, E. Arrondo, et al.

Unsupervised feature extraction of anterior chamber OCT images for ordering and classification

Scientific Reports 9, 1157 (2019). This work was featured in local and national newspapers (read more here).


P. Amil, F. Reyes-Manzano, L. Guzmán-Vargas, I. Sendiña-Nadal and C. Masoller

Network-based methods for retinal fundus image analysis and classification

PLoS ONE 14, e0220132 (2019).


P. Amil, N. Almeira, C. Masoller

Frontiers in Physics 7, 194 (2019).

Outlier mining methods based on network structure analysis


Members of BE-OPTICAL team at UPC (Oct. 2016)



Picture taken during the first BE-OPTICAL school (Nov. 2016)


BE-OPTICAL was featured in national and local newspapers (Nov. 2016): La Vanguardia, El Periodico, Diario de Terrassa


BE-OPTICAL was featured in the Success Stories web page of the European Comission (Sep. 2017).



Complex physical and biophysical systems: towards a comprehensive view of their dynamics and fluctuations (ComPhysBio)

Ministerio de Economía y Competitividad, Spain (2016 – 2018, FIS2015-66503-C3-2-P)

Principal Investigator at UPC: Cristina Masoller. Coordinator at UPF: J. Garcia Ojalvo


This coordinated project (which involves three research teams at UPF, UB and UPC) studies nonlinear and stochastic phenomena in a broad class of systems including information processing by optical networks, extreme events in complex systems, neuronal excitability and brain dynamics, among many others.

Workshop on Recent Advances on Stochastic and Nonlinear Dynamics of Complex Systems, organized at the end of the project, in honor of Prof. Carme Torrent (February 4, 2019).

LINC: Marie Curie Initial Training Network (ITN) Learning about Interacting Networks in Climate

Marie Curie Initial Training Network (2011-2015, FP7-289447)

Principal investigator and Coordinator: Cristina Masoller

The results of the LINC project were published in the European Commission web page (Oct. 2016).

Summary: EU-funded LINC project was aimed at transferring modelling and analysis techniques used in other disciplines to climate science in a bid to improve predictions of climate events like El Niño. The research results contributed to better understand complex weather patterns and their impact on the environment, economic activities and society.


Description: The Earth’s climate is a highly complex system that scientists are trying to unpick. Research by the EU-funded project LINC was aimed at advancing state-of-the-art climate know-how with a new approach that draws from fields such as transport and neural networks.

LINC joined the dots between techniques used in different fields and applied them to climate science. It aimed to improve the forecasting of major climate events, including El Niño. The researchers developed a new approach for climate modelling and data analysis. They also developed new modelling software for use by the scientific community and for assessing the predictability of extreme weather.


Modelling El Niño

A main innovation of the project was to apply complex networks and nonlinear data analysis tools already used to model systems including transport networks, social networks, brain networks, and the internet and ecosystems, and to study climate phenomena. Using the complex network approach combined with nonlinear time-series analysis, the project analysed how El Niño — Southern Oscillation (ENSO) the most important dynamic phenomena in our climate — affects climate.

While El Niño originates in the Pacific Ocean, its effects are global and include altering the frequency of hurricanes in the Atlantic and the monsoon in India. The new methodology helped model this, potentially improving predictions of ENSO’s effects.

LINC researchers came up with new methods to identify geographical regions that share similar climate dynamics. These regions — known as climatic communities — are not necessarily geographically close.


Extreme weather forecasting

LINC also developed new software — PyUnicorn and Par@Graph — which will be used extensively by the complex system scientific community. These tools could also be used to assess the sub-seasonal predictability of extreme events such as flooding, heatwaves and cold surges.


Under the EU’s Marie Skłodowska-Curie fellowship programme, LINC trained 12 early stage researchers and 3 young experienced researchers in the complete set of skills required to undertake a career in physics and geosciences with expertise in climatology, networks and complex systems.

Final LINC conference, Viena, Austria, 2015




NETT: Neural Engineering Transformative Technologies

EU FP7 Marie Curie Initial Training Network (2012-2016) –Coordinator: Prof. Coombes (Nottingham); PI Prof. García Ojalvo

NETT will provide training to young researchers in Neural Engineering, a new discipline that coalesces engineering, physics and neuroscience for the design and development of brain–computer interface systems, cognitive computers and neural prosthetics. In our lab, the work of the PhD student Carlos Quintero is funded by NETT.

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SILICOS: Stochasticity in Nonlinear Complex Systems (2013-2015)

This project involved the study of a wide range of stochastic and nonlinear phenomena in physical and biological systems, including transport processes, intracellular coupling, bacterial stress, signaling in immune system pathways, pattern formation in biological tissues, neuronal oscillations, visco-elasticity, mixed-mode fracture, symbolic dynamics, polarization dynamics and extreme events in lasers. Funded by the Ministerio de Economía y Competitividad (Spain, FIS2012-37655-C02-01) –PI: J. García Ojalvo

Semiconductor laser complex dynamics: from optical neurons to optical rogue waves (2014-2015)

This project, funded by the European Office of Aerospace Research & Development (EOARD, grant number FA9550-14-1-0359) was aimed at improving our understanding of the complex dynamics in semiconductor lasers induced by external perturbations. A specific goal was to exploit the spiking behavior of semiconductor lasers induced by optical feedback or optical injection for implementing optical neurons which could be building blocks of optical information processing systems. This project was the continuation of previous grants (FA9550-07-1-0238, FA-8655-10-1-3075, FA8655-12-1-2140) which are described below.

ICREA ACADEMIA (2009-2014)

This project was aimed at studying the interplay of noise, delays and nonlinearities in semiconductor lasers, with the ultimate goal of exploiting noise, delays and nonlinearities for novel applications, using them for enhancing the laser performance. In recent years there has been a growing interest in the potential exploitation of noise and delays for controlling the operation of nonlinear devices; from nanoscale systems to opto-electronic devices. In the specific case of vertical-cavity surface-emitting lasers (VCSELs), which are key devices in photonics, nanotechnology, optical signal processing and optical networks, important nonlinear dynamic processes of interaction of light with matter take place, and the unavoidable presence of noise, due to spontaneous emission, and delays, due to finite light propagation time, can significantly degrade the dynamic response of the laser, but on the other hand, these stochastic and nonlinear effects can also be exploited for novel applications.

Funded by Institució Catalana de Recerca i Estudis Avançats (ICREA), Generalitat de Catalunya.

Spiking excitable semiconductor laser as optical neurons: dynamics, clustering and global emerging behaviors (2012-2013)

This project was aimed at exploiting the nonlinear dynamics of semiconductor lasers for novel applications, such as all-optical switching and brain-inspired photonics information processing.

Detailed experimental and numerical studies have been performed, focusing on the interplay of noise and nonlinear dynamics. We used a method of time-series analysis, referred to as symbolic ordinal analysis, to demonstrate that serial correlations present in the output intensity of a semiconductor laser with optical feedback operating in the low-frequency fluctuations regime share common features with serial correlations present in the inter-spike-intervals (ISIs) of biological neuronal systems. The symbolic dynamics underlying the sequence of inter-dropout-intervals in the laser intensity has the same statistical features, in terms of distribution of symbolic patterns, as in ISI sequences of biological neurons. Therefore, semiconductor laser-based optical neurons could provide a novel, inexpensive and controllable experimental set up that could allow for improving our understanding of neuronal activity.

Other topics of research included the analysis of extreme events in the form of ultra-high pulses in the output intensity of semiconductor lasers with continuous-wave (cw) external optical injection or optical feedback. Rogue waves, earthquakes of high magnitude and financial crises are all rare and extreme events corresponding to abrupt changes of environmental or socio-economic conditions with potentially catastrophic consequences. Semiconductor lasers under external perturbations can display a dynamical regime where extreme pulses occasionally occur and thus, they are optimal devices for investigating novel methods for predicting extreme events (revealing early warning signals) and novel methods for controlling these events.

Regarding novel applications, we proposed the implementation of an all-optical stochastic logic gate based in the interplay of polarization bistability and noise in optically injected vertical-cavity surface emitting lasers (VCSELs). We also demonstrated a novel method of sub-wavelength position sensing that exploits the regime of quasiperiodic dynamics of semiconductor lasers with optical feedback from two external cavities.

Funded EOARD, grant number FA8655-12-1-2140.

Stochastic and nonlinear effects in semiconductor lasers (2010-2011)

This project was aimed at contributing to a better understanding of the interplay of noise and nonlinearities in nano-cavity semiconductor lasers, which might result in intrinsic (internal) noise as well as external noise being exploited for novel applications of these devices, and using the potentially beneficial role of noise for optimization of the performance of the next generation of nano-cavity lasers.

In recent years there has been a growing interest in the potential exploitation of noise for controlling the operation of nonlinear devices; from nanoscale systems to opto-electronic devices, noise is gaining a lot of attention for its potentially beneficial role.

In the specific case of vertical cavity semiconductor lasers (VCSELs), which are key devices in photonics, nanotechnology, optical signal processing and optical networks, important nonlinear dynamic processes of interaction of light with matter take place, and the unavoidable presence of noise, due to spontaneous emission, can significantly degrade the dynamic response of the laser, but on the other hand, noise can also be exploited for novel applications.

A first objective of the research project was to study the possibility of controlling the polarization of the optical pulses emitted by a VCSEL by using a properly chosen asymmetric shape for the modulation current and/or by tuning the amount of externally added noise (current or optical noise).

The interplay of nonlinearity and noise can yield logic behavior, and specifically, a noise-controlled logic gate. A second project objective was demonstrating that an optical noise-controlled logic gate can be implemented using a VCSEL, which is naturally a two-state system because the light emitted by a VCSEL can be linearly polarized along two orthogonal directions, usually associated with crystalline orientation or stress.

A third objective of the research project was to investigate the generation of square-wave optical pulses by coupling two VCSELs, such that the mutually injected light has a polarization that is orthogonal to polarization of the natural lasing mode in each VCSEL. The study of the dynamics of such coupled lasers is relevant not only for applications in optical communications but also for analyzing coupling phenomena between nonlinear oscillators.

Funded by EOARD, grant number FA-8655-10-1-3075.

Nonlinear dynamics of novel types of semiconductor lasers (2007-2009)

This project focused on modeling VCSEL nonlinear dynamics, with the objective of improving our understanding of some of nonlinear features. Specific objectives of the project were the study of 1) polarization instabilities due to cavity anisotropies (such as dichroism and birefringence), 2) the interplay of polarization and transverse effects when VCSELs are subjected to external perturbations that induce instabilities (such as current modulation, optical injection, optical feedback) and 3) synchronization phenomena in unidirectional and mutually coupled VCSELs with different types of coupling (through one polarization, both polarizations, and polarization-rotated orthogonal coupling).

Funded by AFOSR, grant number FA9550-07-1-0238.

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