BSC CNS
El clima en Europa en 2050
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rtificial intelligence is increasingly integrated into scientific discovery, but two key challenges remain: the integration of domain knowledge into models and the generation of explainable outputs that are scientifically relevant.
This talk explores the role of neurosymbolic AI in addressing these challenges through the lens of biomedical research with a particular focus on protein-protein interaction prediction and drug repurposing. It highlights the limitations of current techniques, which often require a trade-off between explainability and predictive performance, and examines recent advances in explainable approaches that explore knowledge graphs.
It concludes with a vision of the future of scientific research, where artificial intelligence systems are able to generate scientifically meaningful outcomes grounded in domain knowledge, verifiable against existing evidence, and capable of advancing understanding.
Further information here: bsc.es/research-and-development/research-seminars/sorswomeninbsc-neurosymbolic-ai-explainable-scientific-discovery
Marisol Monterrubio y Josep de la Puente:
“Se ha demostrado la capacidad de los supercomputadores para asistir en la evaluación del impacto de catástrofes. El Servicio Sismológico Nacional de México ha incorporado nuestros resultados en su reporte oficial del simulacro. Los resultados se han publicado de forma abierta y pública. Estamos muy satisfechos de esta colaboración tanto a nivel interno en BSC como con nuestros colegas del SSN y de Mondaic”.
In-memory processing has emerged as a promising paradigm to overcome the memory bottleneck in modern computing systems by reducing data movement between memory and processors. DRAM, as the dominant main memory technology, offers unique architectural and physical features that can be exploited to perform computation within the memory itself. In this talk, we explore how specific characteristics of DRAM—such as differential cell access using paired bitlines, the structure and behavior of sense amplifiers, and the inherent dynamic nature of charge leakage in DRAM cells—can be leveraged to enable efficient bitwise operations directly inside DRAM arrays. We highlight the fundamental challenges of implementing logic operations in commodity DRAM devices and present some of our previous works that demonstrate innovative techniques for in-DRAM computation. These approaches show the potential of DRAM not only as a storage medium but also as an active computational substrate, paving the way for more energy-efficient and data-centric computing architectures.
Further information here: bsc.es/research-and-development/research-seminars/sors-leveraging-dram%E2%80%99s-intrinsic-features-memory-processing
Despite not being a formal discipline, knowledge integration (KI) activities play a crucial role across various fields, including climate science and public health. In this seminar, I will introduce the Knowledge Integration team at the Met Office, the UK’s national meteorological service and a world leader in climate science research. I will talk about who we are, who we work with, and how we work with them, with a particular focus on UK Government and policymaking at both national and international levels. I will also provide examples of our recent and ongoing work at the science-policy interface, including areas of overlap between work at BSC and at the Met Office.
Further information here: bsc.es/research-and-development/research-seminars/sors-knowledge-integration-the-met-office
⭕Further information here: www.bsc.es/4Zk
Más información aquí: bsc.es/es/noticias/noticias-del-bsc/pa%C3%ADses-de-todo-el-mundo-sufren-subidas-de-precios-de-alimentos-por-extremos-clim%C3%A1ticos-seg%C3%BAn
🙌Happy to welcome you!
Se observan interacciones positivas, en las que una enfermedad favorece la aparición de otra, como entre el asma y el párkinson; y negativas, en las que algunos grupos de pacientes de una enfermedad podrían estar protegidos del desarrollo de otras, como entre el cáncer y la enfermedad de Huntington.
Esta plataforma interactiva de acceso público muestra la red de conexiones entre enfermedades y propone interacciones aún no descritas, como entre el Síndrome de Down y el lupus, abriendo así las puertas a nuevas estrategias terapéuticas.
Más información aquí: bsc.es/es/noticias/noticias-del-bsc/el-bsc-crea-un-m%C3%A9todo-computacional-que-revela-conexiones-hasta-ahora-ocultas-entre-enfermedades
DRAM-based main memory is a critical component in modern computing systems. Data movement from the DRAM to the CPU incurs long latency and consumes a significant amount of energy. These costs are often exacerbated by the fact that much of the data brought into the caches is not reused by the CPU or accelerators, providing little benefit in return for the high latency and energy cost, partly due to the coarse-grained nature of DRAM data transfers and DRAM row activation.
Further information here: bsc.es/4kf
DRAM chips are increasingly vulnerable to read disturbance phenomena (e.g., RowHammer and RowPress), where repeatedly accessing or keeping open a DRAM row causes bitflips in nearby rows, due to DRAM technology scaling. Even though many prior works develop various RowHammer solutions, these solutions incur non-negligible and increasingly higher system performance, energy, and hardware area overheads as RowHammer vulnerability worsens. In this talk, we will present recent cutting-edge experimental studies of and solutions to read disturbance.
Further information here: bsc.es/4kN
The study of soot has become important with thegrowing concerns for environment. Soot is one of the major byproducts of hydrocarbon combustion contributing to air pollution. Also, soot has harmful effects on the health of humans. In addition, soot affects the performance of combustors as well. Numerous models have been developed to study soot in various conditions.
Further information here: bsc.es/4kG
Patient heterogeneity makes cancer treatment and drug development difficult and costly. Therefore, the development of computational methods to find prognostic markers for individualised treatment and drug screening is urgently needed. To address this problem, we employ both network/pathway-based simulation (mechanistic modelling) and molecular-based simulation (molecular dynamics (MD) simulation).
Mechanistic modeling of gene networks using ordinary differential equations (ODEs) is regarded as a promising approach to uncover regulatory mechanisms and identify drug targets in human diseases. We developed Pasmopy (Patient-Specific Modelling in Python), a computational framework for patient stratification based on in silico signalling dynamics. With this framework, we constructed a comprehensive mechanistic model of the ErbB receptor - c-Myc signalling network, trained on phospho-proteomics data from breast cancer cell lines. We then performed a simulation of 377 breast cancer patients using transcriptome data from The Cancer Genome Atlas (TCGA) as the model's initial value. Through this approach, we successfully predicted the key maker genes associated with poor prognosis of triple-negative breast cancer (TNBC) based on the time-course patterns of in silico signalling dynamics, using deep learning method.
In this study, we also developed a new computational tool called Text2model, which transforms the descriptions of biochemical reactions into mechanistic models. Building on Text2Model, we are currently developing natural language processing (NLP) methods to automatically construct mathematical models from the literature and public databases, and to predict gene-drug interactions.
Further information here: bsc.es/research-and-development/research-seminars/sorswomeninbsc-multi-scale-cancer-signaling-network-modeling-using-natural-language-processing
In this talk, we will address three key questions: 1) How do we automatically determine what high-quality data across domains look like? And 2) How do we automatically and efficiently find or create these best high-quality data for training or improving behemoth models? And lastly, 3) How can we lower overall compute and training costs by reducing massive datasets into smaller sets without loss or even gain in performance? The recent emergence of powerful foundation models has sparked a new wave of applications across multiple disciplines, from healthcare to biology. This has led to an insatiable demand for data across many disciplines. To keep up with the demand, data is aggressively consumed and labeled when abundant, and auto-labeled or generated by foundation models when scarce. Typically, the focus remains on data with high quality annotations or data from high quality sensors or generation. However, this limited view on quality can introduce several biases and fails to reduce massive datasets into manageable amounts.
Further information here: bsc.es/news/events/bsc-ai-factory-talk-%E2%80%9Cless-more-accelerating-ai-advanced-data-strategies%E2%80%9D-jos%C3%A9-alvarez-and-nadine
🌐At BSC, we believe a diverse, multicultural, and international research staff is the driving force behind groundbreaking advancements in science and society.
Adriana Rué, from our HR team, is dedicated to ensuring a smooth transition, offering mobility services➕relocation support to help newcomers integrate perfectly into both BSC and vibrant Barcelona.
Ready to be part of our innovative research❓
🔗 http://bsc.es/join-us
#BSCTalent #job #talent #AI @EuraxessCat
Welcome and introduction to the webinar: Emanuele Emili (BSC) and Sara Basart (WMO)
* The use of satellite observations in the CAMS dust forecasts - Melanie Ades (ECMWF)
* Impact of NOAA-20 VIIRS assimilation on mineral dust predictions - Emanuele Emili (BSC)
* Mineral dust retrievals with MetOP IASI - Sophie Vandenbussche (Royal Belgian Institute for Space Aeronomy)
* Satellite based neural network predictions of Saharan dust: DustNet - Trish Nowak (Exeter University)
* Special talk: SDS warnings in Africa - Amadou Diakite (Mali Météo)
Round table: Questions and Answers
Closing:
Ana Vukovic (Chair of the WMO SDS-WAS NAMEE node, University of Belgrade)
Slobodan Nickovic (Vice-Chair of the WMO SDS-WAS NAMEE node, Republic Hydrometeorological Service of Serbia)
Més informació aquí: https://projecteaina.cat/
🌐 We're actively seeking talented individuals from around the world to join our innovative research projects.
Ready to be part of our innovative research❓
Explore opportunities❗
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#BSCTalent #job #talent #AI
Simulation is a critical tool for hardware design but its current slow speed often bottlenecks the entire design process. Simulation speed becomes even more crucial for agile and open-source hardware design methodologies, because the designers not only want to iterate on designs quicker, but they may also have less resources with which to simulate them.
In this work, we survey our various techniques for accelerating hardware (RTL) simulation. We explore the challenge of efficiently detecting opportunities for reuse due to low activity factors, and we demonstrate streamlined techniques to profitably exploit them. We take advantage of the replication that is common in large designs to increase scalability. We parallelize simulation for multicore and achieve super-linear speedups. Throughout our work, we leverage insights about both the application workload and the host platform. Many of our innovations are enabled by novel graph partitioning algorithms or optimizations for the host processor. Our simulators outperform both leading open-source and industrial simulators, and we use performance counters to analyze our performance advantages.
Further information here: bsc.es/research-and-development/research-seminars/sors-accelerating-rtl-simulation-vertically-integrated-approach
⭕ BSC offers a future rich in opportunities growth on a personal ➕ professional level.
🌐 We are looking for talent from around the world to join our innovative research.
💫 Be a part of it!
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#BSCTalent
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We are looking for international research talent❗
🔥 You will have the opportunity to integrate into a team of international scientific reputation, researching in a wide range of fields
⭕ BSC offers you mobility services ➕ relocation support
🌐 www.bsc.es/join-us
🔝 Desde 2022, el BSC cuenta con una unidad de Equidad, Igualdad e Inclusión en el área de RRHH ➕ el grupo @bsc_queer
. Nuestro objetivo es fomentar un entorno laboral inclusivo, respetuoso y seguro.
#PRIDE2025 #Orgullo #Diversity #EquityinBSC #LGBTIAQ+ #Pride #PrideDay
When we talk about sex- and gender-sensitive research, most researchers assume it is sufficient to report how many men and women have participated in a study. While this is an important first step, sex- and gender-sensitive research means much more.
In this seminar I will first focus on sex-sensitive research. I will point out why this needs to be considered at every step of the research process and where potential pitfalls lie. What could possibly go wrong if it is not done? Then, we will move on to gender-sensitive research and discuss which approaches are currently being developed, where to find resources and how to apply them to your work.
But what are the consequences of this paradigm? Do biological differences (sex) and sociocultural factors (gender) influence cardiovascular risk, prevention, diagnosis, or outcomes? Do women receive the same care as men — or is there evidence of inequality, even discrimination? And how does mental health intersect with cardiovascular health in women?
In his talk, Dr. Bueno will explore the intricate relationship between sex, gender, and cardiovascular health. He will discuss data gaps, systemic biases, and what these mean for both clinical care and future research — including the role of computing and AI in closing these gaps.
Speaker: Héctor Bueno. Cardiology Department of Hospital Universitario 12 de Octubre, Madrid. Researcher at the Spanish National Cardiovascular Research Center (CNIC).
Further information here: bsc.es/research-and-development/research-seminars/sors-women-health-similar-different-unequal-or-discriminated-the-case-cardiovascular-disease
In this talk, I will discuss how emerging fields such as pangenomics, pathogen surveillance, wastewater epidemiology, comparative genomics, and metagenomics are resulting in new waves of genomic data and applications. I will also discuss the various computational and storage challenges this data presents and how at Turakhia lab, we are using a combination of new algorithms, software, FPGA, GPU, and high-performance computing (HPC) solutions to address them.
Further information here: bsc.es/research-and-development/research-seminars/sors-algorithms-software-and-hardware-accelerators-the-next-wave-genomic-data
Originally from Galicia’s misty coast, Julia now calls Barcelona home—where she combines her background in applied mathematics with high-performance computing at the CASE Department.
She began her journey in mathematics at the University of Barcelona, earned a PhD in applied maths in the United Kingdom, and continued with a postdoc in the United States, at the Massachusetts Institute of Technology (MIT), in the Department of Aeronautics and Astronautics. In 2024, she returned to Barcelona and joined BSC for the second time.
At BSC, Julia develops adaptive mesh refinement algorithms—smart tools that allow simulations to focus computational power precisely where it’s needed most. Think of it as zooming in only where the action happens: around turbulence, near the ground, or within atmospheric layers.
💻 Watch the full interview to discover more about Julia’s scientific path and how her work is shaping the future of simulation.
#HPC #ComputationalFluidDynamics #NumericalSimulation #MeshRefinement #AdaptiveAlgorithms #Supercomputing #WomenInSTEM
Guillermo's fascination with mathematics began in high school—not because it was easy, but precisely because it wasn’t. Struggling with mathematical proofs sparked his curiosity and motivated him to go deeper. That challenge led him to pursue a degree in mathematics at the Universitat Politècnica de Catalunya, a PhD at BSC, a year in France, and then back to the Geometry and Meshing for Simulation group at BSC in 2024.
His work focuses on curved high-order finite element methods #𝗙𝗘𝗠, a powerful tool to improve the accuracy and efficiency of aerodynamic simulations. In practical terms? He develops advanced computational methods that combine curved geometries with high-fidelity physical simulations for future hashtag#aircraft design, which are closer to reality than traditional straight-sided ones.
🧠 The goal? To make simulations more precise and computationally efficient, which in turn helps next generation aircraft design.
Guillermo is currently working in preconditioners—analysing complex mathematical systems to reduce computational costs in large-scale simulations. Though his work doesn’t directly use supercomputers like hashtag#MareNostrum5 (yet), it lays the foundation for future applications in high-performance computing (HPC).
💻 Watch the full interview to hear more about Guillermo’s research journey!
#HPC #ComputationalMathematics #Aerodynamics #AircraftDesign #FiniteElementMethods #NumericalSimulation #AIforScience #FutureOfFlight #ResearchInnovation
The talk presents the latest advances in open-source high-level synthesis (HLS) for FPGA and ASIC design, focusing on the Bambu HLS tool developed at Politecnico di Milano. The presentation explores compiler-driven innovation via the integration of Bambu with MLIR, enabling high-level optimization and synthesis of machine learning applications. Further, it describes customizable floating-point formats, an HLS extension for parallel multi-threaded accelerators written in OpenMP, and a novel system-level co-simulation environment. The seminar concludes with insights into future work on ASIC support and architectural simulation integration via gem5.
More info: bsc.es/research-and-development/research-seminars/sorswomeninbsc-open-source-high-level-synthesis-research-automated-fpgaasic-acceleration%E2%80%8B
🔝 We're actively seeking talented individuals from around the world to join our innovative research projects
⭕ BSC makes it easy for you to move ➕ relocate
Ready to be part of our innovative research❓
🌐 www.bsc.es/join-us
#BSCTalent
@euraxess #job #talent #AI
🟢La emisión de algunas partículas, como el hierro, al depositarse en el océano, actúa como fertilizante y estimula el crecimiento del fitoplancton, el cual absorbe CO2 de la atmósfera, y su incremento podría tener un impacto significativo en el Atlántico Norte
➡http://bsc.es/Zty
🔥 At BSC you will have the opportunity to integrate into a team of international scientific reputation, researching in a wide range of fields.
⭕ BSC offers you mobility services ➕ relocation support.
We are looking for talent from around the world to join our innovative research. 𝗕𝗲 𝗮 𝗽𝗮𝗿𝘁 𝗼𝗳 𝗶𝘁!
🌐 www.bsc.es/join-us
hashtag#BSCTalent
Modern processors still struggle with the memory-wall—the widening the gap between core speed and main-memory latency. Hardware data prefetchers mitigate this bottleneck by predicting future memory accesses and fetching their cache lines early. Berti is a recently published first-level-cache prefetcher that outperforms state-of-the-art designs by tracking local deltas —the difference between the cache line addresses of two demand accesses from the same instruction— and issuing only high-confidence requests.
This talk tells the story of taking Berti from paper to reality. We begin by modelling a Sargantana-like core in a cycle-accurate simulator and building a comprehensive prefetching interface. Next, we adapt Berti’s algorithm to the interface of Sargantana, refining its delta selection to respect the core’s constraints. A tailored “Berti-for-Sargantana” version is then evaluated. Finally, we describe the ongoing integration of this design into Sargantana’s RTL, closing the loop between research insight and deployable hardware.
Further information here: bsc.es/research-and-development/research-seminars/sors-research-reality-integrating-the-berti-prefetcher-sargantana
We present a scalable methodology for uncertainty quantification (UQ) in high-dimensional problems involving advanced progressive damage models for composite materials. The approach combines bootstrapping and Bayesian UQ to robustly characterize the distribution of structural Quantities of Interest (QoIs), such as load-displacement curves and failure loads. Applied to a realistic 40-dimensional case study—Open Hole Tension and Compression specimens with variability in material properties, geometry, and ply orientations—the method delivers consistent and efficient predictions of QoI distributions. This approach is highly suited for industrial applications, and its computational scalability makes it ideal for leveraging supercomputing resources to handle complex models and large ensembles, ultimately accelerating the design and certification of next-generation composite structures.
Further information here: bsc.es/research-and-development/research-seminars/sors-scalable-uncertainty-quantification-progressive-damage-models-composite-structures
Algorithms play a central role in determining who gets what—and why—in a wide range of allocation problems. In the context of education, school assignment algorithms impact the opportunities and outcomes of millions of students worldwide. As administrative capacity to collect large-scale data and centralize decisions has grown, so has the potential to design better, fairer, and more efficient systems.
In this lecture, we will explore school choice as a case study to illustrate how economic theory, behavioral experiments, rich datasets, and computational tools come together to inform the design of real-world matching algorithms. We will discuss how different designs can lead to vastly different outcomes, how evidence can uncover unintended consequences, and how iterative processes combining theory and empirical work can help create systems that are more transparent, equitable, and effective.
Further information here: bsc.es/research-and-development/research-seminars/sorswomeninbsc-algorithm-design-the-case-school-choice
Modern systems-on-chip employ numerous accelerators to scale performance and efficiency, with many user applications seeing significant gains. However, as we move to accelerate other parts of our system stack, particularly runtime and kernel system services, we find that existing operating systems lack mechanisms for seamless accelerator integration beyond offloading.
As a solution, we present a new operating system design, the Blended OS. Going beyond offloading and kernel bypass, the Blended OS enables the programmer to reshape the software stack by defining their bespoke system graph of user, runtime, and system components to communicate directly with each other. To enable this, we identify three critical design principles, Liberty, Equality and Collaboration, and provide a hardware system substrate enabling standard queue-based APIs and direct data structure access by services.
To evaluate our design, we build and run experiments on Pengwing, a Blended OS prototype. Pengwing is a 9 tile SoC that includes 3 RISC-V cores and 6 accelerators, including a hardware network stack, memory allocator, garbage collector, key-value store, and encryption units. Our evaluation on several workloads demonstrates both speedups and new system capabilities.
Further information here: bsc.es/research-and-development/research-seminars/loca-seriesreading-club-pengwing-novel-blended-os-heterogeneous-socs
Breadth First Search (BFS) plays a key role in computational science, networking, and artificial intelligence applications. Although the BFS approach has been extensively studied, particularly in its direction-optimized form, existing implementations still present three main issues: (1) high memory footprint; (2) the under-realized lightweight representations using bitmaps; and (3) the underuse of modern hardware such as Tensor Cores Units (TCUs).
In this paper, we propose BerryBees, an efficient algebraic BFS algorithm that leverages the Matrix Multiply-Accumulate (MMA) instructions of TCUs. The novelty of BerryBees lies in (1) the Binarized Row Slice (BRS) format, which encodes the adjacency matrix by using bitmaps to represent non-empty row segments; and (2) a warp-level algorithm that leverages TCUs for accelerating both SpMV and SpMSpV operations for enhanced BFS performance. The experimental results on three latest NVIDIA GPUs show that BerryBees outperforms five state-of-the-art BFS methods: GAP, Gunrock, Enterprise, GSWITCH, and GraphBLAST, and delivers average speedups of 1.42 ×, 1.97×, 5.05×, 1.24×, and 3.74× (up to 9.99×, 13.66×, 114.07×, 13.97×, and 24.74×), respectively.
The application of computational approaches in the humanities has been scarce but for a few areas and specific applications such as NLP and textual analysis, geospatial analyses, and quantitative historical approaches. This is related to multiple causes including current academic field divisions and traditions, economic interests and, perhaps more interestingly, the nature of humanities' data types.
This presentation will briefly discuss these factors, investigate the nature of data within the humanities, and analyse their potential to contribute to major research topics beyond the humanities. A series of multidisciplinary case studies will illustrate how the combination of HPC, ML, and other computational approaches has the potential to unlock complex and unstructured humanities data and, by doing so, contribute to the understanding of human nature and improve humanity's future.
Further information here: bsc.es/research-and-development/research-seminars/sors-computational-research-the-humanities-current-state-and-future-potential
Feedback control is a fundamental principle of life, essential for maintaining homeostasis across biological scales. To better understand and design feedback mechanisms in cellular systems, we developed CoRa (Control Ratio)—a general computational framework that quantifies the contribution of feedback by comparing a system with feedback to an otherwise identical one without it. This controlled comparison isolates feedback effects while accounting for biomolecular constraints. CoRa provides an intuitive metric that can be applied broadly, regardless of network complexity, and evaluates both steady-state and dynamic responses to perturbations. Its simplicity and interpretability enable systematic, high-throughput analysis of diverse control architectures, revealing unexpected trade-offs and unifying principles across strategies. Applied to synthetic biology designs, CoRa helps identify key structural features underlying robust control. Overall, CoRa offers a powerful, scalable approach for dissecting and engineering biomolecular feedback systems.
Further information here: bsc.es/research-and-development/research-seminars/sorswomeninbsc-understanding-feedback-control-biological-systems
El Departament de Territori, Habitatge i Transició Ecològica de la Generalitat de Catalunya i el Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) han impulsat una nova eina clau per predir i gestionar la qualitat de l’aire. Es tracta de CALIOPE-Urban, un sistema innovador capaç de pronosticar la concentració de diòxid de nitrogen (NO₂) a nivell de cada carrer de la ciutat de Barcelona, amb una resolució de fins a 20 metres i amb 24 o 48 hores d’antelació. L’eina, desenvolupada pel BSC i finançada per la Generalitat, suposa una nova fase del sistema de modelització CALIOPE de previsions de qualitat de l'aire per a la península Ibèrica, Catalunya i la ciutat de Barcelona.
Les dades, disponibles ja en obert al portal CALIOPE, permetran, tant a les administracions com a la comunitat investigadora i a la ciutadania en general, accedir a prediccions horàries de la concentració d’NO2, un dels principals contaminants de l’aire, provinent sobretot del trànsit rodat. Aquesta informació serà essencial per dissenyar polítiques més efectives de protecció de la salut pública, de mobilitat, i de planificació urbana. Cal tenir en compte que el pronòstic de la qualitat de l’aire permet, per exemple, identificar episodis de contaminació, modelitzar escenaris de futur de qualitat de l’aire o valorar l’eficàcia de mesures de reducció.
🥹 No os lo podéis perder…
Última pregunta sorpresa a los protagonistas de esta serie, que están en el BSC desde sus inicios:
🫶 Qué significa el BSC para ti❓
(IV/IV) 𝗘𝗹 𝘀𝗲𝗻𝘁𝗶𝗱𝗼
❤ #emoción #esfuerzo #familia #valentía #compromiso #ciencia #tecnología #innovación #retos
Algunas de las personas que están en el BSC desde sus inicios nos cuentan…
🔮 𝗖ó𝗺𝗼 𝘀𝗲𝗿á 𝗲𝗹 𝗕𝗦𝗖 𝗲𝗻 20 𝗮ñ𝗼𝘀❓
Air pollution is the biggest environmental risk to human health. It causes over 4 million premature deaths per year, as well as respiratory issues and other diseases. The effects of air pollution depend on the mix of substances and the amount, size and type of particles in the air. When particles are inhaled, they can penetrate the lungs and other organs,causing serious health effects. Among these particles with significant implications for our health is desert dust. It can travel from deserts to populated areas and contribute to urban air pollution increasing the toxicity of the air we breathe.
We presented the three main research lines of our team, Air Quality Services: modeling air quality levels at regional, urban, and microscale domains; developing post-processing techniques for these estimations through projects like uncertAIR (earth.bsc.es/shiny/uncertAIR/); and evaluating the impact of air pollution through factors such as indoor exposure estimation, mobility, and vulnerability.
This project aims to develop a digital twin of the digital media environment to analyse its impact on democratic processes. This research will test potential regulatory policies and provide evidence-based insights to inform media governance frameworks.
🔝 7 de las personas que están en el BSC desde el principio nos explican cuál, a su entender, ha sido el principal logro del centro en todo este tiempo.
✨ 𝗤𝘂é 𝗵𝗮 𝘀𝗮𝗯𝗶𝗱𝗼 𝗵𝗮𝗰𝗲𝗿 𝗯𝗶𝗲𝗻 𝗲𝗹 𝗕𝗦𝗖?
Martina's journey began with a deep curiosity about the world around her, which led her to study physics at the University of Zaragoza. Eager to apply her scientific knowledge, she pursued a master’s degree in renewable energy in Barcelona. Now, Martina is contributing to cutting-edge research at BSC, focusing on combustion at high temperatures and pressures.
Her research is key to developing advanced energy cycles, such as supercritical CO2 cycles, which promise higher energy efficiency for turbines used in the transport sector, including aviation. By studying real gas equations and comparing them with ideal gas models, Martina is helping improve simulations that can revolutionise the way we approach energy production.
🌱 The goal? To contribute to the decarbonisation of the transport industry through innovative technologies.
💻 Watch the full video to learn more about Martina’s inspiring work at BSC!
#InnovationInEnergy #Decarbonisation #RenewableEnergy #EnergyEfficiency #SupercriticalCO2 #AviationTechnology #PhysicsInAction #FutureOfTransport #SustainableEnergy
The digital twins of the Earth from the Destination Earth EU initiative will enable society to adapt to climate change in an unprecedented manner by using state-of-the-art, high-resolution Earth system models.
BSC researchers explain a method to improve the parallel efficiency of a simulation by allocating resources in a dynamic manner. This method is a joint effort between the CASE and Computer Science Departments.
📆Hasta el 8 de mayo bsc.es/ZFp
#MareNostrumOna #QuantumDay #WorldQuantumDay
Acompañadnos en esta serie de 4 vídeos con algunas de las personas que están en el BSC desde que todo empezó
(I) 𝗟𝗼𝘀 𝗶𝗻𝗶𝗰𝗶𝗼𝘀. Qué recuerdas del inicio del BSC?


