جستجوی استاد راهنمای دانشگاهی

Dino Pedreschiمشاهده پروفایل

استاد

• Big Data Analytics
• Social Network Analysis and Mining
• Analysis of Human Mobility
• +۱۷ مورد دیگر

Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.

Diego Calvaneseمشاهده پروفایل

استاد

• Knowledge Representation and Reasoning
• Virtual Knowledge Graphs
• Ontology-based Data Access and Integration
• +۷ مورد دیگر

Diego Calvanese is a Full Professor in Computer Engineering at the Faculty of Engineering of the Free University of Bozen-Bolzano, Italy. He serves as Spokesperson of the Institute of Computer Science and Artificial Intelligence and Director of the Smart Data Factory technology transfer lab at NOI Techpark. As Coordinator of the Intelligent Integration and Access to Data (In2Data) research group, part of the Research Centre for Knowledge and Data (KRDB), he leads significant research initiatives in knowledge representation and data management. Calvanese's research focuses on virtual knowledge graphs for data access and integration, ontology-based data access, description logics, semantic web technologies, graph data management, and verification of data-aware processes. His work bridges theoretical foundations with practical applications through the Ontop framework, which enables SPARQL query answering over OWL 2 QL ontologies connected to external data sources. His research has substantial practical impact, powering the South Tyrol Open Data Hub Knowledge Graph and supporting numerous European and national research projects. With more than 400 refereed publications and over 39,000 citations (h-index 80), Calvanese's recent work demonstrates continued leadership in virtual knowledge graphs, ontology-based data federation, explainable AI through knowledge representation, and integration of complex data types including 3D city models and raster data. His publications show a clear trajectory from theoretical foundations toward increasingly practical and applied research addressing real-world data integration challenges across multiple domains. ACM Fellow (2019) EurAI Fellow (2015) AAIA Fellow Program Chair of PODS 2015 and KR 2020 General Chair of ESSLLI 2016 Calvanese has secured significant research funding through numerous competitive projects including EU H2020 INFRAEOS Project (INODE), Italian PRIN Project (HOPE), FESR Project (IDEE), and EU FP7 IP Project (Optique), totaling close to 6.4M Euro. As an originator and co-founder of Ontopic, the first spin-off of the Free University of Bozen-Bolzano, he has successfully translated research into commercial applications. He serves as Associate Editor of Artificial Intelligence (AIJ) and has participated in over 200 program committee roles for international conferences. As Director of the Smart Data Factory technology transfer lab and coordinator of the In2Data research group, Calvanese bridges academic research with industry applications, focusing on practical implementations of knowledge graph technologies. His work with the KRDB Research Center has established Bozen-Bolzano as a significant hub for knowledge representation and data management research in Europe.

• Social Network Analysis
• Network Science
• Data Science
• +۷ مورد دیگر

Giacomo Fiumara is an Associate Professor at the University of Messina, Department of Mathematical and Computer Sciences, Physical Sciences and Earth Sciences. He holds academic rank since October 2021. Previously, he served as a Permanent Researcher (2008–2021) and secondary school teacher (1997–2008). He earned a Doctorate in Physics (1993) and a Degree in Physics (1989), both from the University of Messina. He is an associate member of the Accademia Peloritana dei Pericolanti and qualified as an associate professor in INF/01 and ING-INF/05 sectors. His research focuses on social network analysis, network science, data science, criminal networks, knowledge representation, bioinformatics, and computational modeling. He has supervised over 170 theses and advised PhD students in Mathematics and Computational Sciences. Key collaborations include work with Prof. Pasquale De Meo on criminal networks and complex systems, and international projects with institutions in the US, UK, China, and Australia. Teaching includes courses on Algorithms, Data Structures, Bioinformatics, and Machine Learning across Computer Science, Engineering, and Medical programs since 2000. He also contributed to international programs at Lviv Polytechnic, Birzeit University, Cluj-Napoca, and Murcia. His editorial roles include Associate Editor of IEEE Access and Academic Editor of Complexity. He holds a patent for predictive analysis of criminal organizations' social structures and has received FFABR research funding. Key awards include FFABR funding (2017) and recognition in the FFABR Unime 2020 II edition. He organized conferences like Crimenet 2014 and participated in high-profile events such as the 2022 Complex Networks conference in Palermo, presenting on quantum walks for criminal network analysis.

• Flood Hydrology
• Hydrology
• Water Resources
• +۸ مورد دیگر

Alberto Viglione is an Associate Professor at the Politecnico di Torino , Department of Environment, Land and Infrastructure Engineering (DIATI), and a member of the Interdepartmental Center SmartData@PoliTO. He has been a faculty member since 2019, following a decade as a Research Fellow at the Vienna University of Technology. University: Politecnico di Torino Department: DIATI – Department of Environment, Land and Infrastructure Engineering Rank: Associate Professor Email: alberto.viglione@polito.it His research focuses on flood hydrology, water resources, and hydro-meteorological extremes , integrating statistical analysis, climate change impacts, land use dynamics, and socio-hydrological modeling. He investigates the spatio-temporal dynamics of climatic, hydrological, and human processes in river basins and their implications for extreme event risks. His work emphasizes data integration, conceptual modeling, and risk assessment across scales. The recent publications highlight a strong trend in analyzing European flood dynamics , the impacts of climate change , and the development of socio-hydrological frameworks that incorporate human behavior and societal memory into flood risk modeling. His research spans from statistical hydrology in ungauged basins to large-scale assessments of climate-flood interactions. Scientific Awards and Honors: AMGA Award for best PhD thesis on water resources (2009) Editorial and Professional Service: Associate Editor, Water Resources Research (2014–present) Associate Editor, Hydrological Sciences Journal (2012–2018) Associate Editor, WIRES Water (2012–2020) Associate Editor, Journal of Hydrology and Hydromechanics (2019–present) Scientific Committee Member, European Geosciences Union (2019–2023) Secretary, International Commission on Water Resources Systems, IAHS (2015–present) Teaching and Advising: He teaches courses such as Bayesian Inference , Applied Hydrology , Fundamentals of Environmental Geosciences , and Hydro-meteorological Risk Assessment . He is a PhD supervisor and member of multiple PhD colleges in Civil and Environmental Engineering at Politecnico di Torino. He currently advises PhD students including Tsion Ayalew Kebede , Emanuele Mombrini , Luigi Cafiero , Luca Lombardo , and Matteo Pesce . His research is supported by grants from national (PRIN), EU, and commercial sources, including projects like Clim2FlEx , RETURN , and ATO4WATER . Research Labs and Teams: He is affiliated with the SmartData@PoliTO laboratory, focusing on big data and data science applications in hydrology and environmental systems.

• deep learning
• convolutional neural network
• deep features
• +۵ مورد دیگر

Fabrizio Falchi is a researcher at the Artificial Intelligence for Media and Humanities (AIMH) Lab of the Institute of Information Science and Technologies (ISTI) within Italy's National Research Council (CNR). He also maintains an associate position at the Biorobotics Institute of Scuola Superiore Sant'Anna. His work focuses on developing advanced multimedia retrieval systems, with the VISIONE platform being his most notable contribution, which has won international competitions including the Video Browser Showdown in 2024 and placed second in 2023. Falchi's educational background includes: Ph.D. in Information Engineering from University of Pisa (Italy) Ph.D. in Informatics from Faculty of Informatics of Masaryk University of Brno (Czech Republic) M.B.A. from Scuola Superiore Sant'Anna in Pisa His research spans deep learning, convolutional neural networks, deep features extraction, similarity search algorithms, distributed indexing systems, multimedia information retrieval, computer vision applications, and peer-to-peer systems. Falchi has made significant contributions to fine-grained visual understanding, cross-modal retrieval (particularly image-text matching), and robustness of deep learning systems against adversarial attacks. His work demonstrates a strong focus on practical applications of these technologies, particularly in video retrieval systems and safety monitoring solutions. Analysis of Falchi's recent publications reveals a strong focus on video and image retrieval systems, with the VISIONE platform being central to his work. His research shows increasing emphasis on fine-grained understanding in computer vision, cross-modal retrieval, and addressing practical challenges like cross-resolution face recognition. Recent work demonstrates innovation in making these systems more efficient through techniques like knowledge distillation (ALADIN) and leveraging virtual worlds for training data. His publications consistently bridge theoretical advances with practical applications in surveillance, safety monitoring, and multimedia search. Falchi's work has received significant recognition: Best paper award at CBMI 2024 for 'Is ClLIP the main roadblock for fine-grained open-world perception?' VISIONE 2024 won the Video Browser Showdown competition in Amsterdam VISIONE obtained second place at Video Browser Showdown 2023 in Bergen Best Paper Award for 'Learning Safety Equipment Detection using Virtual Worlds' at CBMI 2019 Falchi collaborates extensively with researchers at ISTI-CNR, particularly within the AIMH Lab. His work on VISIONE involves collaboration with Giuseppe Amato, Paolo Bolettieri, Fabio Carrara, Claudio Gennaro, Nicola Messina, Lucia Vadicamo, and Claudio Vairo. As co-chair of Ital-IA 2023, the 3rd National Conference on Artificial Intelligence, he plays an active role in the academic community. He is a member of ACM (since 2012), the Computer Vision Foundation, the Italian Association for Computer Vision Pattern Recognition and Machine Learning (CVPL), and the CINI Lab on Artificial Intelligence and Intelligent Systems. Falchi is a key member of the Artificial Intelligence for Media and Humanities (AIMH) Lab at ISTI-CNR, where he leads research on video retrieval systems. The lab has developed the award-winning VISIONE platform, which combines multiple scientific results in content-based video retrieval. His team focuses on developing systems that enable users to search for target videos using textual prompts, drawing objects and colors, or images as query examples. The lab's work demonstrates strong interdisciplinary collaboration, bridging computer science with practical applications in media, safety monitoring, and urban environments.

• Big data analytics
• Data analysis
• Data management
• +۸ مورد دیگر

Daniele Apiletti is an Associate Professor at the Polytechnic University of Turin , affiliated with the Department of Control and Computer Engineering (DAUIN). He serves as a member of the Interdepartmental Center SmartData@PoliTO and acts as Academic Advisor for the Master's degree program in Data Science and Engineering. Research Groups: DBDM - Database and Data Mining Group (DAUIN) ERC Sectors: Algorithms, Artificial Intelligence, Machine Learning, Web and Information Systems Research Interests span Big Data Analytics, Data Science, Machine Learning, Computer Vision, and Quantum Computing. His work focuses on integrating data-driven and theory-guided approaches for heterogeneous data querying, cloud continuum machine learning, and spatio-temporal models for crisis management. Recent Publications highlight trends in medical image segmentation, predictive industrial modeling, and fault-tolerant data systems. Key subfields include AI in healthcare, scalable manufacturing analytics, and vision-language models for game tutorials. Teaching roles include course ownership of Big Data: Architectures and Data Analytics and Internships across multiple academic years. He has collaborated on courses in Data Science, Database Technologies, and Data Management. PhD Students Supervised: Etibar Vazirov (Cloud Continuum Machine Learning) Gabriele Scaffidi Militone (Cloud Storage Microservices) Daniele Rege Cambrin (Spatio-Temporal Ecology Models) Simone Monaco (Theory-Guided Data Science) Research Projects include commercial contracts on: - Natural language querying of corporate research archives - National tourism ecosystem platforms - AI for thermotechnical system design - Machine Learning in clinical trials and supply chains

Anna Monrealeمشاهده پروفایل

دانشیار

• Privacy-Preserving Data Mining
• Big Data Analytics
• Social Network Analysis
• +۷ مورد دیگر

Anna Monreale is an Associate Professor in the Department of Computer Science at the University of Pisa and a key member of the Knowledge Discovery and Data Mining Laboratory (KDD-Lab), a joint research group with the Information Science and Technology Institute of the National Research Council (ISTI-CNR) in Pisa. Her academic career is rooted in the University of Pisa, where she completed her Bachelor's, Master's, and Ph.D. in Computer Science. Her research focuses on privacy-preserving data analytics, with core interests in big data analytics, social network analysis, spatio-temporal mining, and explainable AI. She is particularly known for her work on privacy-by-design in data mining and evaluating privacy risks in analytical processes. Her research bridges technical innovation with ethical and legal considerations in data science. Her recent publications reveal a strong trend toward explainable AI, privacy in federated learning, and risk assessment in mobility and health data. She actively contributes to developing methods for explaining black-box models, assessing privacy exposure, and balancing privacy, utility, and fairness in AI systems. Privacy by Design Ambassador (2014) ISTI-CNR Young++ Researcher Award (2014) Monreale has advised and co-chaired several international workshops, including PriSMO, PinSoDa, and MoKMaSD, and serves on editorial boards such as Transactions on Data Privacy. She teaches advanced data mining, big data ethics, and database systems across multiple graduate and undergraduate programs. She is involved in major EU projects like SoBigData, XAI, TAILOR, and HumMingBird, reflecting her leadership in data science and AI ethics. She is affiliated with the KDD-Lab, a prominent research group focused on knowledge discovery, social mining, and big data analytics, contributing to both theoretical advances and real-world applications in privacy-aware data science.

Maria Laura CARRANZAمشاهده پروفایل

استاد

• Ecology
• Remote Sensing
• Plant Invasion Dynamics
• +۵ مورد دیگر

Prof. Maria Laura CARRANZA is a Full Professor at the University of Molise, Department of Biosciences and Territory. Her work focuses on ecology, remote sensing, and environmental conservation, particularly in Mediterranean coastal ecosystems. She leads the Envix Lab, emphasizing vegetation mapping, invasive species dynamics, and climate change impacts. Her research integrates multi-source remote sensing (e.g., Sentinel, UAVs) with field data to assess biodiversity, dune ecosystems, and human-environment interactions. Key projects include monitoring plant invasions (e.g., Acacia saligna), coastal resilience, and citizen science contributions to ecological data collection. Education background and formal qualifications are not explicitly detailed in the provided text. Her research spans over 15 years, with recent emphasis on Mediterranean dunes, urban biodiversity, and global change effects on alpine grasslands. She collaborates internationally, notably in Argentina (Gran Chaco forests) and Pakistan (yak herding dynamics). Research interests include functional traits of plant communities, spectral diversity metrics, and conservation strategies for threatened ecosystems. Her work highlights the role of protected areas in mitigating litter accumulation and preserving cultural services. She has contributed to policy frameworks like Natura 2000 and the EU’s Invasive Species Directive through applied research. Publications emphasize the synergy between remote sensing and field ecology, with over 30 peer-reviewed articles since 2016. Her work on Acacia saligna invasion models and dune eco-geomorphology via UAVs has advanced management practices. She also explores educational innovations, such as online course efficacy for field subjects like bird recognition.

• Climate adaptation
• Spatial databases
• Urban dynamics
• +۹ مورد دیگر

Chiara Cortinovis is a Researcher at the Department of Civil, Environmental and Mechanical Engineering, University of Trento. Her work focuses on urban planning, ecosystem services, and climate adaptation, integrating Geographic Information Systems (GIS) and Strategic Environmental Assessment (SEA) into sustainable development frameworks. Current research emphasizes nature-based solutions, urban green infrastructure, and spatial databases for territorial planning. Recent publications analyze ecosystem service hotspots, geodesign methodologies, and policy instruments for sustainable peri-urban landscapes. Teaches Introduction to Urban Planning and Ecological Land Planning Specializes in GIS applications, environmental sustainability, and urban-climate resilience

Enrico Franconiمشاهده پروفایل

استاد

• Knowledge Representation
• Artificial Intelligence
• Semantic Technologies
• +۶ مورد دیگر

Enrico Franconi is a tenured full Professor in the Faculty of Engineering at the Free University of Bozen-Bolzano, Italy. He is the founder and director of the KRDB Research Centre for Knowledge-based Artificial Intelligence, established in 2002. His research focuses on applying database, AI, and semantic technologies to address challenges in information systems design, data integration, and big data analysis. He holds leadership roles including former Vice-Rector for Research (2005-2006) and director of the European Masters Program in Computational Logic (2004-2019). His academic contributions span Description Logics, knowledge representation, and ontology engineering, with a strong emphasis on theoretical foundations and practical applications. He has led numerous EU-funded projects, including ONTORULE and SeWAsIE, and contributed to international conferences as a program committee member and keynote speaker. His work bridges theory and practice, aiming to translate foundational results into real-world solutions. He is a prolific author with an h-index of 42 and has mentored researchers in areas like semantic web technologies and conceptual modeling. Key achievements include advancing ontology-driven data integration, developing tools like ICOM for conceptual modeling, and contributing to standards for semantic web languages. He is affiliated with the Computational Logic community and actively participates in international research networks such as CAIRNE. His research has been recognized through ANVUR evaluations ranking his department among Italy’s top computer science faculties.

• Database Systems
• Healthcare Information Systems
• Artificial Intelligence
• +۵ مورد دیگر

Carlo Combi is a Full Professor at the Department of Computer Science, University of Verona. He serves as Department Director and holds roles in various academic committees, including the Faculty Board of PhD in Computer Science and the Computer Science Teaching Committee. His research focuses on databases, healthcare information systems, temporal data mining, and business process management. He leads the STARS laboratory and has contributed to projects like PREPARE (prostate cancer evaluation) and EDIPO (neuroimaging genetics). His teaching spans courses on biomedical databases, software engineering, and Python programming. Combi's work integrates ethical considerations into process models and addresses challenges in healthcare workflows, temporal analytics, and AI applications in medicine. Education: Not explicitly listed in provided texts. Research Projects: Includes 30+ projects since 2008, emphasizing healthcare informatics, temporal systems, and data warehousing. Labs/Teams: STARS (Semistructured Temporal clinical Geographical Systems) and collaborations with CBMC (Computational Biomedicine Center). Grants: Multiple national/international grants, including funding for temporal data mining and healthcare process modeling. Awards: None explicitly mentioned, though his leadership roles and extensive publications highlight academic recognition. His research bridges clinical processes, temporal databases, and AI, with applications in acute kidney injury prediction, BPMN extensions for healthcare, and explainable AI in medical systems. Combi actively contributes to open-source solutions for clinical data analysis and integrates ethical frameworks into process management.

• Computer Science
• Artificial Intelligence
• Reinforcement Learning
• +۶ مورد دیگر

Eric Eaton is a prominent researcher in Computer Science, specializing in Artificial Intelligence, Reinforcement Learning, and Federated Learning. His work bridges theoretical advancements with practical applications in healthcare, robotics, and educational technology, as evidenced by his collaborations with institutions like the Vector Institute and co-authors such as Marcel Hussing and Amir-massoud Farahmand. Research Focus: Lifelong Learning, Object-Centric Representation, and Algorithmic Fairness Key Contributions: ELLA algorithm, Distributed Continual Learning frameworks, and AI integration in surgical video analysis His recent publications address critical challenges in high update ratio reinforcement learning, federated learning for surgical data, and ethical considerations in algorithmic fairness. These works highlight his interdisciplinary approach, combining AI with healthcare and education. Eaton's leadership in projects like FORLA and Slot-BERT demonstrates innovation in unsupervised learning and temporal coherence. His involvement in the CS2023 curriculum design underscores his commitment to advancing computer science education.

• Process-oriented Information Systems
• Healthcare Information Systems
• Semi-structured Data Management
• +۵ مورد دیگر

Barbara Oliboni serves as an Associate Professor in the Department of Computer Science at the University of Verona's School of Science and Engineering. Her academic appointments include membership on the Computer Science Department Council, Computer Science Teaching Committee, and Faculty Board of PhD in Computer Science. She also holds administrative roles as Chair of the Commission for Quality Assurance for the Master's Degree in Computer Engineering and Science, and as Departmental Orientation Representative. Her research focuses on three primary areas: Process-oriented Information Systems (modeling business processes with emphasis on temporal aspects and conceptual data modeling); Healthcare Information Systems (managing multimedia and temporal clinical data, visualization of clinical information); and Semi-structured Data Management (XML document modeling with attention to temporal aspects, versioning and evolution of documents). Her work intersects with artificial intelligence, human-computer interaction, and web information systems as reflected in her ERC research sector classifications (PE6_7, PE6_9, PE6_10). Dr. Oliboni participates in multiple research projects including SHIELD (Securing Decentralized Finance and Remote Healthcare Systems), NOMEN (Novel Methodologies and Tools for Next Generation Cyber Ranges), and previously led work on temporal clinical process modeling and bioinformatics platforms for temporal knowledge discovery. Her laboratory affiliations include the STARS Laboratory (Semistructured Temporal clinicAl GeogRaphical Systems). She teaches across multiple degree programs including Master's in Computer Science and Engineering, Bachelor's in Bioinformatics, and Bachelor's in Human Centered Medical System Engineering. Her current courses for 2025/2026 include Business Intelligence, Databases and WEB, Database Systems for Bioinformatics, and Information Systems.

Frank Wolterمشاهده پروفایل

استاد

• Knowledge Representation and Reasoning
• Logic in Computer Science
• Description Logic
• +۹ مورد دیگر

Frank Wolter is a Professor for Logic and Computation at the University of Liverpool's Department of Computer Science. His research focuses on Knowledge Representation and Reasoning, Logic in Computer Science, Description Logic, and related areas. He has held significant editorial roles, including co-editing the Handbook of Modal Logic (2007) and multiple conference proceedings. He has been recognized with numerous awards, including Best Paper Awards at KR 2000, KR 2008, KR 2010, ISWC 2013, and PODS 2017, as well as the Elected EurAI Fellow (2023). His work includes foundational contributions to ontology-based data access and query answering, with a focus on computational complexity and formal methods. Wolter has supervised multiple PhD students, including Oliver Kutz, Sebastian Bauer, and Hadrien Pulcini. He has been involved in projects funded by EPSRC (e.g., Dynamic Ontologies, Knowledge Representation and Reasoning about Distances, and quantMD), addressing challenges in combining logics and modular ontologies. He actively participates in academic events, serving on program committees for conferences like IJCAI, AAAI, and KR, and has organized workshops on topics such as Craig Interpolation and the Decision Problem in First-Order Logic.

Manuela Balzaroloمشاهده پروفایل

پژوهشگر

• Climate Change
• Remote Sensing
• Ecosystem Monitoring
• +۲ مورد دیگر

Manuela Balzarolo is a senior scientist at the Euro-Mediterranean Center on Climate Change Foundation (CMCC), working in the Institute for Climate Resilience within the Division on Impacts on Agriculture, Forests and Ecosystem Services. She has over 15 years of expertise in remote sensing applications for terrestrial ecosystem monitoring, focusing on the impact of climate change and extremes on ecosystem functions and carbon cycle. Manuela Balzarolo holds the following educational qualifications: Master’s degree in Environmental Sciences from the University of Milano-Bicocca, Italy PhD in Forest Ecology from the University of Viterbo, Italy Her research interests center on climate change impacts on terrestrial ecosystems, utilizing remote sensing technologies. She specializes in modeling ecosystem functions and carbon cycle dynamics under climate extremes. Her work involves fieldwork, data analysis, and modeling at various scales, from plant to ecosystem levels, and from seasonal to annual time frames. Balzarolo Manuela's recent publications reflect a strong focus on remote sensing applications for ecosystem monitoring and climate change impact assessment. Key themes include net primary production, phenology, forest fire detection, and vegetation carbon uptake. Her work leverages satellite data (such as Sentinel-1 and Sentinel-2) and addresses challenges in Mediterranean and sub-arctic regions, contributing to global databases and monitoring principles. Manuela Balzarolo has not been mentioned to have received any scientific awards in the provided text. As a Principal Investigator, Manuela Balzarolo has led international research projects in Belgium and Spain for over a decade. Her work involves assessing ecosystem services through fieldwork, data analysis, and modeling at multiple spatial and temporal scales. She is part of the Division on Impacts on Agriculture, Forests and Ecosystem Services at the CMCC Foundation, collaborating with international research groups in Belgium and Spain.