My Curriculum Vitae is here, and a list of my publications is here. My main lines of research are the following (click on each item for a detailed description):

  • Development of food web models of fresh water ecosystems and implementation in HPC platforms.

    The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and The Fund for Lake George – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake’s food web and overall water quality. Scientific insights and technology created for the project will not only help manage and protect one of America’s most famous lakes, but will create a blueprint to preserve important lakes, rivers and other bodies of fresh water around the globe.

    Sensor deployment at Lake George
  • Application of machine learning techniques to epidemiological processes.

    Global climate change has accelerated our need to understand disease dynamics. Diseases transmitted among hosts by small invertebrates such as mosquitoes or ticks (vectors) are on the rise across the world but links to climate change are unclear. Climate change can impact vector-borne disease transmission directly by shifting the occurrence of competent hosts and vectors, or a parasite, or more subtly by changing the timing or nature of their interaction. Predicting the response of vector-borne diseases to climate change requires both an understanding of how all the species involved are likely to be affected as well as new ways to identify and predict how they interact and furthermore how they and their interactions may evolve. My role in this project consists on the application of clustering algorithms on a database on the response of endangered Hawaiian honeycreepers to airborne avian malaria. This database contains environmental, genetic and epidemiological data. The clustering results are integrated across each one of these features to construct a multivariate predictive model. This research will answer important questions in epidemiology by measuring and integrating evolutionary changes in hosts, vectors and parasites into predictive models of disease dynamics under future climate scenarios.

    Hawaiian honeycreeper
  • Design and development of simulators for bio-inspired computing models, with special emphasis on P systems.

    These massively-parallel models pose a demanding challenge in terms of computational efficiency. Hence, High Performance Computing (HPC) plays a paramount role for this purpose. GPUs, using GPGPU and CUDA, are massively data-parallel processors well suited to simulate P systems.

    NVIDIA logo
  • Interplay between evolutionary computing and membrane computing.

    This interaction pays off in the design of genetic algorithms for the task of optimizing P systems, as well as the introduction of new models of evolutionary computing on non-conventional paradigms. Other areas in which I am interested are genome assembly and annotation, along with the work-flow tools required of the automation of such processes.

    A P system
  • Simulation systems on HPC platforms for bio-inspired robotics.

    In mechanical and control engineering, there is an ongoing trend which looks into nature as an inspiration for problem-solving in robotics. These approaches are often based on the interaction of a massive number of robots towards the achievement of a set of objectives. An example of this is the rise of swarm robotics inspired by the emerging behaviour of social insects. The large number of agents involved in these paradigms entails the need for powerful computing resources. I am interested in the simulation of collaborative robotics using high performance computing, as well as in the development of parallel algorithms for control engineering.

    A robotic arm
  • Computational modelling of omics networks.

    The aim of this line of research is to unravel relationships among genes and proteins, thus understanding their interactions, by means of simulations of these computational models. I believe that its results can shed light in the intrincated cellular processes which direct the dynamics of live beings, ranging from unicellular organisms such as bacteria and yeast to more complex life forms such as plants (Arabidopsis thaliana) or even human beings. Applications of this work include synthesis of bio-fuel and protein-targeted vaccines for viruses.

    Protein interaction network of Treponema pallidum
  • Computational modelling of the regenerative processes of Planaria sp. worms.

    This research focuses on unveiling the dynamics of the regenerative processes of Planaria species, which are known to be able to regenerate all types of severed parts, including head, tail, eye, brain, etc., by means of bio-inspired models. The products from this research can contribute to a better understanding of cellular growth processes, from tumoral dynamics to regeneration of lost body parts in complex organisms.

    A planarian worm
  • Modelling of population dynamics phenomena in ecology.

    There is a wide variety of species currently endangered, according to WWF, and the ecological processes associated with the evolution of their population are of paramount importance for the conservation and recovery of these species. Some of the species on which I am working include the bearded vulture (Gypaetus barbatus) in the Catalan Pyrenees (Spain) and the white mustard butterfly (Pieris oleracea) in northeastern United States. On the other hand, there are invasive, uncontrolled species which are wreaking havoc in the habitats they invade. Their effects include extinction of autoctonous species (partially due to competition or predation) and economic losses, as they interfere with human-made facilities for exploitation of natural resources. One of the species in which I am working is the zebra mussel (Dreissena polymorpha), an invasive species at Ribarroja dam (Aragon, Spain). Moreover, the study of complex ecological systems as a whole is also an essential part of my research. In particular, I am interested in understanding the complex dynamics which drive the relationships of inter-dependent fisheries species (Paleomonetes sp., Menidia beryllina, Fundulus grandis and Anchoa mitchilli) in the Wax Lake Delta, a unique habitat which emerged from an artificially-engineered channel built to divert the Atchafalaya River to the Gulf of Mexico and reduce flood stages at Morgan City, LA, USA. The terrain features (i.e., inundation, bathymetry, etc.) of each region in the delta heavily influence the population of these species, prodiving shelter from predators and feeding areas which boost species’ productivity.

    Gypaetus barbatus