Full Professors
Gustau Camps-Valls
My research is related to statistical learning for modeling and understanding the Earth system.
Jesús Malo
I’m interested in understanding human vision from information theoretic principles. This statistical view has implications in experimental and computational neuroscience. See the ex-cathedra statement
Luis Gómez-Chova
My interests are related to machine learning and signal and image processing. The application domains are remote sensing data analysis and hyperspectral images with special focus on cloud screening.
Associate Professors
Javier Calpe-Maravilla
My current research involves signal processing to develop new interactive man-machine interfaces and haptics, and real-time multispectral sensors and actuators. I’m also with Analog Devices Inc.
Jordi Muñoz-Marí
At present I’m focused on kernel methods, support vector machines, semi-supervised and active learning. The main application field is on remote sensing data. I have recently worked with one-class classifiers applied to hyperspectral images.
Assistant Professors
Ana B. Ruescas
I am a data scientist and project manager. As a remote sensing specialist I have experience in several application areas like ocean colour and thermal algorithm development and validation.
José Enrique Adsuara
Currently, I am working on learning parameters of differential equations, HPC for linear solvers, and causality. I am interested in machine learning, especially statistical learning and deep neural networks.
José J. Esteve-Taboada
I am developing computational models of the visual function based on functional Magnetic Resonance Imaging, psychophysics, and image statistics.
Julia Amorós
I’m working on image fusion, developing downscaling and pansharpening methods. The goal is to tackle multitemporal image fusion and change detection problems with improved resolution.
Maria Piles
My research interests include microwave remote sensing, estimation of soil moisture and vegetation biogeophysical parameters and development of multisensor techniques for enhanced retrievals with focus on agriculture, forestry, wildfire prediction, extreme detection, and climate studies.
Roberto Fernandez-Moran
My current research focuses on cloud screening in multispectral imagery using machine learning techniques. Previously I was also involved in the algorithm improvement for the retrieval of soil moisture and vegetation parameters from microwave observations.
Valero Laparra
I’m working in image statistics and vision science. I have developed several methods for density estimation, measure independence, manifold learning and visual quality assessment.
Senior Research Scientists
Veronica Nieves - Distinguished Researcher
My research at the interface of ocean sciences and climate informatics focuses on developing advanced algorithms to understand changing oceans and evaluate future climate risks. Follow my research activities on AI4OCEANS.
Álvaro Moreno Martínez
My research has been mainly focused on remote sensing applications in vegetation. I have been actively involved in the development of physical and statistical models and the implementation of operational methodologies for the study of vegetation cover through satellite imagery at different spatial/temporal scales.
Postdocs
Emiliano Díaz
My research interests include kernel methods, graphical models and causality, with the focus on Earth science applications.
Gonzalo Mateo-García
My background is in the field of applied machine learning. I am specially interested in applications to natural sciences like remote sensing and weather and energy forecasting. Currently I am working in transfer learning with convolutional neural networks applied to cloud and flood segmentation.
Jorge Vicent Servera
My interests are related to atmospheric radiative transfer models, statistical regression emulation methods and image processing algorithms development and optimization. The application domains are remote sensing data analysis and hyperspectral images with special focus on atmospheric correction and scene/satellite simulation.
Óscar Pellicer
During my PhD I employed machine learning for solving medical problems, focusing on medical image analysis for prostate cancer detection. I will now be applying the same techniques to satellite imaging, focusing on developing and explaining deep models for forecasting tasks.
Vassilis Sitokonstantinou
I develop machine learning methods that incorporate causality and explainability, using Earth observations, climate data, and land use information. I analyze the impact of agricultural practices on ecosystem services and attribute crop failures to climate events. My goal is to provide data-driven insights for sustainable agriculture, towards expanding the global carbon sink while addressing global food demand.
Is this you?
We are always looking for smart people! Send us your resume and ideas of collaboration!
Phd Students
César Luis Aybar
I am working on the development of machine learning techniques for super-resolution in the ESA OpenSR project. My background is in Earth Observation.
Cristina Radin
I am working on the development of statistical, physical and hybrid methods to study the regional effects of climate change in the oceans (MALOC project). I have a background in Earth observation data and machine learning methods.
Dan López
The main goal of my research is to develop automatic algorithms for the detection of clouds from remote sensing images. I mainly focus on the inclusion of prior knowledge and (spatial, temporal, angular) constraints in machine learning classifiers.
Deborah Bassotto
I am doing my PhD on causal inference and complex system characterization of climate extremes.
Enrique Portalés
I’m working on novel deep learning architectures for cloud detection from remote sensing images, with special focus on domain adaptation and transfer learning strategies.
Homer Durand
I have a background in Applied mathematics and Statistics and, actually, my research focuses on Causal Representation Learning and applications for Earth Sciences. I’m particularly interested in methods involving kernels and graphical models.
Inti Luna
I have a background in environmental sciences and experience working on remote sensing for vegetation studies (crops and forest monitoring). My research interests focus on monitoring and estimation of biophysical properties of vegetation (crop yield, crop water needs, forest biomass, and forest change detection) and soil moisture.
Javier Martínez Amaya
I am working on the development of machine learning techniques to assess precursor conditions for extreme hurricane development (MALOPH project). My background is in remote sensing techniques, analysis and applications.
Jordi Cerdà
I’m currently working on the development and testing of the CauseMe website, a platform to benchmark causal discovery methods. My background is in physics and data science.
Jordi Cortes
My research interests focus on kernel methods and the incorporation of physical knowledge in statistical methods to understand and improve Earth system modelling. My current research involves detection and attribution of climate change processes.
Jorge García
My research is about hyperspectral sensors and the estimation of water quality (WQ) parameters in optically complex waters to monitor coastal and inland biogeochemical dynamics, combining traditional bio-optical and radiative transfer models with novel machine learning techniques.
Jorge Vila Tomás
I’m currently working on introducing human-like behaviours in deep learning models and measuring perceptual distances. I’m interested as well in generative models and reinforcement learning.
Jose Maria Tárraga
My research interest is to study the impact of climate change on human mobility through machine-learning methods. At ISP I am working on the H2020 DeepCube Climate Induced Migrations use case.
Kai-Hendrik Cohrs
My general research interest lies in Bayesian inference, deep learning and how to incorporate prior knowledge into machine learning models. Currently I am working on hybrid modeling in physics and how to overcome equifinality issues.
Laura Martínez
I’ve worked with machine learning methods for crop yield estimation using climate and multi-sensor remote sensing data. My current research is now focused on the use of deep learning to upscale high resolution carbon fluxes.
Maria Gonzalez
I’m working on anomaly and extreme event detection from remote sensing images with attention networks and video prediction techniques.
Mengxue Zhang
I’m working on hybrid machine learning for drought and heatwave detection.
Moritz Link
My research focuses on modeling, characterizing and understanding microwave sensor data, with focus on soil moisture and vegetation optical depth. I’m actively involved in several ESA projects around the upcoming CIMR mission, and studying information-theoretic measures for observation-simulation intercomparison.
Pablo Hernández Cámara
I’m working on the inclusion of equivariant transformations, inspired by the human visual system, in the latest deep learning algorithms, with a focus on computer vision.
Paolo Pelucchi
I am pursuing my PhD thesis in the iMIRACLI project on hybrid and interpretable machine learning for cloud-aerosol interaction problems.
Simon Donike
I am working on the development of machine learning techniques for super-resolution in the ESA OpenSR project. My background is in Earth Observation.
Tristan Williams
I have a background in environmental sciences and remote sensing. I am pursuing a PhD within the XAIDA project where I will be using AI to attribute extreme climate impacts on European ecosystems.
Is this you?
We are always looking for smart people! Send us your resume and ideas of collaboration!
Visitors
Alice Re
I am a PhD student at Politecnico di Torino, Italy. My research focuses on preventive coastal flood assessment and mapping. During my research visit I will work on coastal flood susceptibility integrating remote sensing, GIS and ML.
Chen Ma
PhD student in Harbin Institute of Technology, now visiting ISP. My research focuses on large foundation models and the processing of hyper/multi-spectral imagery.
Fernando Iglesias
Research Associate in the German Aerospace Center (DLR), Ph.D. in Atmospheric Science from Lancaster University, UK. He works on combining causal discovery and deep learning methods to address systematic errors in climate models and improve climate projections.
Francesco Martinuzzi
PhD student at the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI) and the Remote Sensing Center for Earth system research (RSC4Earth), Leipzig University. My research interests lie in the exploration of nonlinear dynamics with machine learning, with a focus on applications to Earth sciences.
Ioannis Prapas
I’m a researcher at the Orion Lab, National Observatory of Athens and the University of Valencia. I am interested in Deep Learning for the Earth System sciences, aiming to improve fire prediction systems.
Jessenia Gonzalez
I am a PhD student at Leipzig University centered on understanding aerosol-cloud interactions directly from satellite observations using ML, bypassing the uncertainties inherent in traditional retrieval methods.
Shahine Bouabid
I am a final year PhD student in the Oxford Computational Statistics and Machine Learning group at the University of Oxford. I am interested in developing simple and interpretable statistical ML methodologies to address challenges that arise in climate science, in particular on climate model emulation using physically-informed models and statistical downscaling. I use mostly kernel methods and Gaussian processes.
Is this you?
We are always happy to host smart people! Send us your resume and ideas of collaboration!
Alumni
Eva Sevillano Marco
ISP Coordination & Project Manager. Ecologist by training. My research interests lie in Remote Sensing & GIS applications: multisensor support to forestry inventories, agriculture, land cover and change detection, geospatial data quality, Earth Observation products & services, etc. Collaborations with outstanding research groups and institutions, an asset. Onboard for new challenges!
Amparo Gil
In my MSc Thesis I developed cortical image representations that are simultaneously robust to neural noise and energy efficient.
Anna Maria Mateo
My current research focuses on developing machine learning algorithms for crop yield/production estimation using multi-scale remote sensing and climate data. Currently, I am working on anomaly detection in crop seasons and on the interpretability of the developed models.
Benyamin Kheradvar
I am working on convolutional versions of linear + nonlinear models of visual neuroscience and using those in visual prosthesis and image quality metrics.
Borja Galán
My research was tied to study feature representations that are sparse, interpretable and causal. At ISP I have been working in the Causal inference in the human-biosphere coupled system (SCALE) project funded by BBVA and the EC H2020 DeepCube project developing modules for interpretability and explainability in ML models.
Daniel Heestermans Svendsen
I am working on machine learning methods for remote sensing and earth observation data. My current focus is on kernel methods, and the incorporation of physical knowledge in statistical methods.
Devis Tuia
In my postdoc at the ISP group, I addressed a number of machine learning problems related to hyperspectral image processing including graph adaptation, active learning, and advanced kernel methods.
Diego Bueso
My research work is about machine learning and its application on remote sensing specifically in feature extraction and climate dynamics analysis. I am especially interested in soil moisture data analysis and climate teleconnections.
Emma Izquierdo
My PhD work included kernel-based nonlinear generalization of classical (linear) feature extraction techniques to improve classification results in remote sensing.
Fatih Nar
During my a year visit to IPL, I focused on processing optical images using kernel methods and variational methods, large scale anomaly change detection methods and digital terrain model (DTM) extraction. It was a joy to live in Valencia and life-time experience to work with productive and cheerful researchers in the IPL.
Francesca Bovolo
My work at the ISP group included the analysis of multi-temporal remote sensing image changes, and the definition of advanced one-class classifiers.
Gabriel Gómez
In my MSc work I applied accurate contrast perception models to improve Support Vector Regression in subjective domains for image coding.
Helena Burriel
At ISP I built virtual worlds of controlled spatial arrangement to study the effects of occlusion, perspective and view point in 2D shape statistics.
Irene Epifanio
My PhD work (best-thesis award in Physics and Maths 2003) was focused on perceptual and statistical image representations for image coding and texture classification.
Irene Martin
My research interests include machine learning and signal processing, especially deep neural networks and transfer learning. Currently I am working on applying physical constraints to ML models for better generalization, consistency and extrapolation capabilities.
J. Emmanuel Johnson
My research at ISP involved feature learning and dependence estimation using kernel methods and multivariate Gaussianization with applications in Earth observation.
Jose Antonio Padrón
My PhD thesis was about developing a new family of anomaly change detection algorithms for remote sensing image processing and geoscience time series analysis.
Jose Rovira
During my MSc work I contributed to develop nonlinear local-to-global Independent Component Analysis.
Juan Gutiérrez
In my PhD I applied advanced contrast perception models as regularization functionals to solve inverse problems such as image restoration and motion estimation and studied their connection to image statistics.
Koray Çiftçi
In my stay at IPL I addressed the problem of decoding the visual signals from simulated and real neural responses.
Luca Capobianco
My work at the ISP group included the development of target detection algorithms for remote sensing data analysis.
Luca Martino
My primary research interests lie in the area of Monte Carlo methods for Bayesian inference. My specialty is focused on the random number generation problem and computational methods for stochastic quadrature, such as rejection sampling, MCMC algorithms and importance sampling techniques.
Manuel Campos-Taberner
I’m with the UVERS group, doing my PhD thesis on biophysical parameter retrieval for crop monitoring, in particular in the FP7 ERMES project, and collaborating with ISP people on GP retrieval algorithms.
Mara Díez
While I was at ISP, I was conducting fMRI recordings of the visual brain using synthetic and natural images. I was director of the Optometry Clinic of the Universitat de Valencia, which has a range of experimental tools for vision research.
Marcelo Armengot
During my stay at ISP I used with Kernel Ridge Regression for image denoising assuming smoothness in the spatial domain.
Marina Martínez-García
At IPL I’ve been working on computational visual neuroscience, modelling the processes that take place in the brain from the retinal images until we get information out of them.
Mattia Marconcini
My work at the ISP group included the development of semi-supervised one-class classifiers for remote sensing data classification.
Michele Ronco
My research focuses on understanding how deep neural networks work by using explainable AI (XAI) methods. In particular, I am following two complementary lines of investigation. The former consists in shortening the gap between physics-based and data-driven models by applying XAI in the context of Earth sciences and human-biosphere interaction problems. In addition, I work on the integration of prior knowledge into the learning process by either optimizing penalized losses or modifying the network architecture. I am also interested in causal inference and machine learning for remote sensing.
Qiang Li
I worked on computational neuroscience via combined fMRI and image processing techniques to better understand the mechanism of the human vision system, which efficiently processes and extracts the information from the natural world.
Qiang Wang
My background and expertise is on microwave remote sensing for soil moisture estimation, and agricultural applications, from estimating crop health and soil properties.
Raul Santos-Rodríguez
My work at the ISP group included the development of multiinformation and divergence measures using Gaussianization transforms.
Sal Catsis
I’m working on causal discovery from observational data, and in particular to study climate-induced human migrations.
Sandra Jiménez
In my PhD years (best-MSc thesis award in Computer Science 2013) I analyzed the complexity of spatio-spectral signals for illumination invariant Bayesian reflectance estimation and hyperspectral image coding.
Soulivanh Thao
My current research interests are related to statistical methods for the detection and the attribution of climate change and especially for the attribution of extreme weather events. Attribution methods usually rely on the analysis of observations and climate model experiments.
Vicent Talens
In my MSc thesis I worked with a Kernel generalization of the SSIM image quality index well suited to be applied to hyperspectral images.
Yolanda Navarro
In my MSc thesis I applied nonlinear models of chromatic contrast perception in wavelet domains to improve png2000.