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Professor Carlo Pappone is a Full Professor of Cardiology at Vita-Salute San Raffaele University (since 2019) and Director of the Arrhythmology Department at IRCCS Policlinico San Donato Hospital (since 2015). He has held previous academic/clinical leadership roles at IRCCS San Raffaele Hospital (2000-2010), Villa Maria Cecilia Hospital (2010-2015), and University of Naples Federico II (1990-2000). With 212 publications in top journals like NEJM, JAMA, and Circulation, he has made significant contributions to cardiac arrhythmia research. Current Positions Vita-Salute San Raffaele University (2019-present): Full Professor of Cardiology IRCCS Policlinico San Donato Hospital (2015-present): Director of Arrhythmology Department Previous Roles University of Naples Federico II (1990-2000) University of Michigan Ann Harbor (1990-2000) IRCCS San Raffaele Hospital (2000-2010) Villa Maria Cecilia Hospital (2010-2015) Research Focus: Specializing in cardiovascular diseases, his work spans atrial fibrillation ablation techniques, Brugada syndrome pathogenesis, heart failure device therapy, and ion channel disorders. His H-index of 53 and 18,407 citations reflect his substantial academic impact. Notable Scientific Contributions Author of 44 patents Principal Investigator in 14 clinical trials (clinicaltrials.gov) Developed circumferential pulmonary vein ablation technique Innovator in biventricular pacing systems for heart failure Pioneered research on non-excitatory current for cardiac contractility Scientific Recognition Awarded as Elite Reviewer of JACC (2005) Editorial Board Member of 6 leading journals Reviewer for NEJM, JAMA, Lancet, and Nature Medicine Education Medical Doctorate: University of Naples Federico II

• Cardiology
• Electrophysiology
• Cardiac Arrhythmias
• +4 more

Gaetano Valenza is an Associate Professor of Bioengineering at the University of Pisa, Italy, where he leads the Neuro-Cardiovascular Intelligence Lab at the Enrico Piaggio Research Centre. He holds affiliations with the Neuroscience Statistics Research Laboratory at MIT and has served as a Research Fellow at Harvard Medical School and Massachusetts General Hospital. His academic work spans bioengineering, computational physiology, and affective computing. His research focuses on statistical and nonlinear biomedical signal and image processing , cardiovascular and neural modeling , and physiologically interpretable artificial intelligence . He develops wearable systems for physiological monitoring, with applications in autonomic nervous system assessment, brain-heart interactions, and mental health. His work has led to novel metrics such as the Sympathetic and Parasympathetic activity indices derived from ECG. The 15 most recent publications reflect a consistent trend in brain-heart interplay , complexity analysis of physiological signals , explainable AI in healthcare , and virtual reality applications in mental health . His work integrates advanced signal processing, nonlinear dynamics, and machine learning to decode emotional and cognitive states from physiological data. Dr. Valenza is a Senior Member of IEEE and serves on several technical committees. He is an active editorial leader, currently serving as Associate Editor for IEEE-EMBC , Plos One , Complexity , and Scientific Reports , and has guest-edited special issues in Philosophical Transactions of the Royal Society A and IEEE Journal of Biomedical and Health Informatics . He has led or participated in numerous international research projects, including FP7 and H2020 initiatives such as NEVERMIND and EXPERIENCE. He teaches courses in Biostatistics, Probability & Biostatistics, and Advanced Image Processing at the University of Pisa. As lab head and project coordinator, he leads a multidisciplinary team working on neuro-cardiovascular intelligence, wearable systems, and AI-driven mental health interventions.

• Biomedical Signal and Image Processing
• Cardiovascular and Neural Modeling
• Physiologically-interpretable Artificial Intelligence systems
• +5 more

Teresa Bonacci is an Associate Professor in the Department of Biology, Ecology and Earth Sciences at the University of Calabria (UNICAL), where she conducts research and teaches in zoology with a focus on entomology. She is also the Scientific Director of the Zoology Museum within the university's museum system (SIMU). Her academic affiliations include membership in the PhD School of Life Science and Technology and leadership roles in degree program coordination. Laurea in Natural Sciences, University of Calabria PhD in Animal Biology, University of Calabria Socrates/Erasmus Scholarship, University of Kiel, Germany Research Grant (Assegno di ricerca), SSD BIO/05, University of Calabria National Scientific Qualification for Full Professor (I fascia) Her research spans applied and medico-veterinary entomology, forensic entomology, and conservation biology. She investigates saproxylic beetles (e.g., Cucujus spp.), pollinators (bees, flies, beetles), and insect behavior, especially in forensic contexts such as post-mortem interval estimation and myiasis. Her work integrates taxonomy, morphology, ecology, and chemical signaling, often in collaboration with chemists, legal experts, and conservation agencies. She has published extensively in high-impact journals, with over 80 scientific publications and strong citation metrics. The most recent articles reflect a multidisciplinary trend, combining taxonomy, forensic science, biodiversity monitoring, and veterinary entomology. Topics include the discovery of new insect species in Italy, the role of beetles in decomposition, insect damage in cultural heritage, and myiasis in domestic and wild animals. These works highlight her expertise in both fundamental zoological research and practical applications in forensics and conservation. Scientific Contributions: Over 80 scientific publications Scopus h-index: 15; Google Scholar h-index: 20 Key researcher in saproxylic beetle conservation Pioneer in forensic entomology studies in Southern Italy Active collaborator with legal and medical institutions She supervises numerous PhD and master's students and has directed over 90 theses. Her teaching responsibilities include courses in Zoology, Entomology, Forensic Entomology, and Medical-Veterinary Entomology. She is deeply involved in student mentorship, thesis supervision, and academic service, including examination boards and curriculum development. She also leads biodiversity monitoring projects in Calabrian national parks and has contributed to the development of machine learning tools for insect identification. Her research team collaborates with national and international institutions, including the CNR, University of Milan, and forensic pathology units. She leads projects on bioindicators, insect-plant interactions, and the impact of climate change on mountain species. The Zoology Museum under her direction supports both research and public outreach.

• Zoology
• Entomology
• Applied Entomology
• +13 more

Luca Sebastiani is a Full Professor in Horticultural Sciences (AGR/03) at Scuola Superiore Sant'Anna in Pisa, Italy, since 2014. He currently coordinates the PhD Course in AgroBioSciences and has previously served as Director of the Institute of Life Sciences (2016-2021). His academic career includes roles as Associate Professor (2002-2014) and Assistant Professor (1998-2002) at the same institution. PhD in Plant Biology from Scuola Superiore Sant'Anna (1996) MSc in Agricultural Sciences from University of Pisa (cum laude, 1991) Postdoctoral research in agricultural biotechnology (1996-1998) Research Interests: Focus on plant-environment interactions, particularly abiotic and biotic stress responses in crops. Key areas include: Physiological and molecular responses to climate change stressors Nutraceutical enhancement of food crops Plant germplasm conservation using molecular markers Agriculture 4.0 integrating AI, IoT, and robotics Phytoremediation using poplar and Brassica species Scientific Contributions: His work bridges molecular mechanisms (aquaporin function, heavy metal transport) with ecosystem-level applications (precision irrigation, contaminant phytoremediation). Recent publications emphasize genome sequencing, stress tolerance modeling, and nutraceutical food development. ISHS Medal for SapFlow Workshop organization (2011) Giovanni Spitali Foundation Award for PhD dissertation (1998) Collaborations: Extensive international collaborations with institutions like Beijing Forestry University, Comenius University, and Purdue University. Currently supervises projects in plant phenotyping, omics technologies, and sustainable crop management.

• Plant Physiology
• Molecular Plant Stress Responses
• Nutraceuticals in Plants
• +3 more

Pietro Liò is a Full Professor in the Department of Computer Science and Technology at the University of Cambridge, where he is also a member of the Artificial Intelligence group. His work bridges computer science and biomedical applications, with a strong focus on advancing AI methods for healthcare. Research Interests: His research is centered on developing Artificial Intelligence and Computational Biology models to unravel the complexity of diseases and support personalized and precision medicine. A current emphasis is on Graph Neural Network modeling, leveraging topological data structures to represent biological and medical systems. His interdisciplinary background enables innovative approaches at the intersection of machine learning and life sciences. The trends in his research, though no specific articles are listed, indicate a strong focus on AI-driven biomedical discovery, particularly using deep learning on structured data for health applications. This includes modeling biological networks, disease mechanisms, and patient-specific conditions through advanced neural architectures. Scientific Awards: As a principal investigator and academic leader, Pietro Liò likely supervises PhD and postdoctoral researchers and secures research grants in AI for health, though specific advisees and funding details are not mentioned in the text. His dual PhD background and affiliation with a leading AI group suggest a robust research program with significant grant involvement. He is associated with AI research activities at Cambridge, including seminars and software development, possibly contributing to or leading a research lab or initiative focused on AI applications in biology and medicine, though no formal lab name is provided beyond the general AI group membership.

• Artificial Intelligence
• Computational Biology
• Graph Neural Networks
• +5 more

Michele Salvi is an Associate Professor in Mathematics at Università degli Studi di Tor Vergata in Rome. He previously held a Marie Skłodowska-Curie fellowship, conducting research in Berlin, Munich, and Paris. His work focuses on Probability Theory, with emphasis on random processes in random media, random graphs, and statistical mechanics, bridging applications in Physics, Computer Science, and Biology. Random processes in random media Random graphs Mathematics of Neural Networks Stochastic homogenization Mixing times for Markov chains Statistical mechanics Salvi’s recent publications highlight interdisciplinary trends, particularly in the spectral analysis of deep neural networks, scale-free percolation dynamics, and spanning tree geometry in random environments. His collaborations span Europe, with projects involving probabilistic models in epidemiology, reinforcement learning, and stochastic homogenization. He has received the Marie Skłodowska-Curie fellowship, reflecting his international research experience. His work is aligned with the Department of Mathematics at Tor Vergata, which holds the "Department of Excellence" MatMod@TOV 2023-2027 grant.

• Probability Theory
• Random Processes in Random Media
• Random Graphs
• +4 more

Roberto Pastres is an Associate Professor at the Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice. He specializes in ecology, with a focus on coastal ecosystems, aquaculture sustainability, and environmental modeling. His research integrates interdisciplinary approaches to address challenges in marine resource management, including aquaculture impacts, water quality, and climate change adaptation. Teaching: He teaches Environmental Modelling (Master's level) and Ecology courses in Environmental Engineering and Cultural Heritage programs. Recent teaching roles include: Environmental Modelling (6 cfu) for M.Sc. in Environmental Sciences Ecology of Cultural Heritage (6 cfu) for M.Sc. in Conservation Science Research Interests: Pastres' work spans ecological modeling, sustainable aquaculture practices, and ecosystem services valuation. Key projects include: Leading the GAIN H2020 project for green aquaculture intensification Contributing to EU-funded initiatives like BeBlue (aquaponics) and FORCE (Egyptian fisheries) Modeling coastal zone management strategies for the Venice Lagoon Grants & Projects: He coordinates or participates in multiple EU and national grants, including: H2020 GAIN (2018-2022): €6M for sustainable aquaculture innovation Interreg BeBlue (2023-2025): Promoting sustainable aquaponics Life12 NAT/IT/000331: Restoring Venice Lagoon seagrass beds Labs/Teams: Active in the Research Institute for Green and Blue Growth and the Interconnected Nord-Est Innovation Ecosystem. Collaborates with international teams on digital twin systems for aquaculture and precision farming tools.

• Marine Ecology
• Aquaculture Sustainability
• Environmental Modeling
• +3 more

Gabriella Casalino is an Assistant Professor at the University of Bari Aldo Moro, Department of Computer Science, and a key researcher at CILAB - Computational Intelligence Lab. Her work focuses on Computational Intelligence methods for interpretable data analysis, particularly in eHealth, Data Stream Mining, and eXplainable Artificial Intelligence (XAI) within medical and educational domains. She has contributed to innovative approaches in smartphone-based health monitoring, fuzzy logic applications, and remote vital sign detection via photoplethysmography. Education : Ph.D. in Computer Science, with advanced training at institutions like Universitat de Girona and Université de Mons. Research Trends : Recent publications highlight applications of evolving granular computing, neuro-fuzzy systems, and explainable AI in hypertension prediction, bipolar disorder monitoring, and educational data analysis. Key subfields include remote health monitoring, medical data streams, and hybrid AI models. Grants : Research funded by AIRC (Italian Cancer Research Foundation), focusing on computational methods for healthcare challenges. Labs & Collaborations : Active in CILAB, collaborating on projects involving mHealth solutions, cardiovascular risk assessment, and intelligent educational systems.

• Computational Intelligence
• eHealth
• Data Stream Mining
• +5 more

Damiano Piovesan is Associate Professor in Bioinformatics (SSD BIO/10) at the Department of Biomedical Sciences , University of Padua , Italy. Since March 2022 he has held this rank, having previously served as Assistant Professor (2022) and PostDoc researcher (2019) in the same department. Education 2013 – PhD in Biotechnology, Pharmacology and Toxicology, University of Bologna 2009 – MSc in Bioinformatics, University of Bologna 2007 – BSc in Biotechnology, University of Bologna Research Focus Piovesan’s research integrates machine-learning approaches with structural bioinformatics to advance understanding of intrinsically disordered proteins (IDPs) and protein function prediction . He develops widely used resources such as MobiDB for disorder annotation, DisProt for functional curation of disordered regions, and RING for residue interaction networks. Additional interests include tandem repeat proteins , cancer-related IDP targets , and community benchmarking initiatives (CAFA, CAID, CAGI). Publication Trends His 2024–2025 output is dominated by updates to flagship databases ( InterPro , DisProt , MobiDB ), next-generation disorder predictors leveraging deep learning ( PredIDR , MobiDB-lite 4.0 ), and large-scale genomics challenges ( CAGI6 ). Across the decade, recurring themes include methodological advances in disorder prediction, creation of interoperable bioinformatics platforms, and rigorous benchmarking to ensure community-wide reliability. Scientific Awards No specific awards are listed in the provided materials. Advising & Grants No individual students or grant details are explicitly supplied; however, his leadership in multi-institutional consortia (e.g., InterPro, DisProt, CAFA) implies substantial supervisory and funding coordination roles. Labs & Teams Piovesan is affiliated with the BioComputingUP Lab ( https://biocomputingup.it/ ) at the University of Padua, a hub for computational biology and bioinformatics tool development.

• Protein function prediction
• Intrinsically disordered proteins (IDPs)
• Machine learning in bioinformatics
• +5 more

Donato Romano serves as Associate Professor at The BioRobotics Institute of Scuola Superiore Sant'Anna, Italy, where he coordinates the Bio-Robotic Ecosystems Lab and co-founded the spin-off company HUBILIFE srl. His interdisciplinary work bridges robotics, biology, and AI to develop biohybrid systems for biodiversity preservation, sustainable environmental management, and life support in extreme scenarios including space exploration. With over 90 publications and an H-index of 27 (Scopus, March 2025), he has established significant academic leadership through editorial roles across 12+ international journals. Romano's educational foundation includes advanced degrees with honors: an M.Sc. in Agriculture Science and Technologies (2014) and a PhD in BioRobotics (2018), both from Scuola Superiore Sant'Anna. His academic journey includes visiting scholar positions at Khalifa University and substantial industry-academia collaboration through HUBILIFE srl, which commercializes bioinspired devices for human daily life improvement. His research program focuses on bioinspired and biomimetic robotics with particular emphasis on animal-robot interaction, biohybrid systems, and natural intelligence. Key projects address critical global challenges: SENSORBEES develops biohybrid environmental surveillance for ecological monitoring; REGOLIFE investigates lunar soil-terrestrial organism interactions for space agriculture; and OCEAN ROBOCTO explores marine ecosystem solutions. This work demonstrates a strategic progression from fundamental behavioral studies toward applied ecological and extraterrestrial systems. Analysis of his recent publications reveals strong trends in AI-driven behavioral analysis, with deep learning increasingly applied to entomological studies and pest management. The research spans agricultural applications (precision monitoring traps, larval detection systems), ecological conservation (biodiversity surveillance), and extreme-environment adaptation (lunar regolith studies). A distinctive feature is the consistent integration of biohybrid approaches where living organisms and robotic systems create synergistic capabilities exceeding either component alone. Romano's scientific recognition includes election as Junior Fellow of the Italian Academy of Engineering and Technology (2025), the Lucani fuori dal Comune award (2024), and multiple best-thesis prizes. His editorial leadership spans high-impact journals including IEEE Transactions on Medical Robotics and Bionics and Pest Management Science, where he serves as Associate Editor. As principal investigator, Romano coordinates major international projects totaling over €15M in funding: HORIZON-EIC's SENSORBEES (2024-2029), ASI's REGOLIFE (2024-2027), National Geographic's OCEAN ROBOCTO (2024-2026), and PRIN's COSMIC (2023-2025). His teaching portfolio includes PhD courses in Biosystems for Biorobotics and M.Sc. instruction in Bionics Engineering at Scuola Superiore Sant'Anna and University of Pisa. The Bio-Robotic Ecosystems Lab under Romano's direction pioneers biohybrid technologies where living organisms and robotic systems create integrated solutions. Current initiatives include SENSORBEES' environmental monitoring swarms, REGOLIFE's moonworm colonization systems, and HUBILIFE's commercial vector-control devices. The lab maintains active collaborations with space agencies, agricultural institutes, and conservation organizations, positioning biohybrid systems as next-generation tools for planetary-scale challenges.

• Bioinspired Robotics
• Biomimetic Robotics
• Animal-Robot Interaction
• +8 more

Andrea Passerini is a Full Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy, where he also serves as Coordinator of the PhD programme in Information Engineering and Computer Science (Ministerial Decree 45/2013). His academic footprint spans multiple departments including Mathematics, Sociology, Cellular Biology, and Industrial Engineering, reflecting deep interdisciplinary engagement across computational sciences and life sciences. His research centers on Machine Learning and Data Mining with specialized expertise in Neuro-Symbolic AI , Probabilistic Reasoning , and Statistical Relational Learning . He pioneers methods for graph-based learning, medical AI applications, and explainable systems, with significant contributions to bioinformatics (particularly RNA-protein interactions) and healthcare diagnostics. His work bridges theoretical rigor with practical implementations in critical domains. Analysis of his 2025 publications reveals dominant trends in neuro-symbolic integration for graph data, human-AI collaboration in medical decision-making, and robust recommender systems. His research increasingly focuses on interpretable AI for high-stakes applications like surgical planning and physician support, while advancing foundational techniques in graph neural networks and concept-based modeling. As PhD programme Coordinator, Professor Passerini mentors doctoral candidates across AI and computer science disciplines. His collaborative network extends to medical researchers at CIBIO (Cellular, Computational and Integrative Biology department) and industrial partners, though specific lab structures aren't documented in available materials. Current projects emphasize medical AI validation, temporal network modeling, and LLM integration with structured reasoning frameworks.

• Machine Learning
• Data Mining
• Bioinformatics
• +11 more

Davide Cassi serves as Associate Professor of Physics of Matter at the University of Parma's Department of Mathematical, Physical and Computer Sciences since 2001, following his appointment as Researcher in Theoretical Physics (1995-2001). With over 30 years of academic service, he teaches Condensed Matter Physics, Soft Matter Physics, and Physics Applied to Gastronomy across undergraduate and graduate programs in Physics and Gastronomic Science. His educational background includes: Ph.D. in Physics, University of Parma (1988-1992) Master’s degree in Materials Science and Technology, University of Parma (1986-1988) Degree in Physics, University of Parma (1982-1986) Cassi's research integrates statistical mechanics with real-world applications through two primary lenses: complex network theory for ecological and social systems, and soft matter physics applied to culinary processes. His work on biodiversity loss prediction in agricultural networks and food preservation technologies demonstrates exceptional interdisciplinary reach. Recent publications reveal a strategic pivot toward AI-driven biodiversity conservation and network robustness modeling. Analysis of his 15 most recent publications (2023-2025) shows dominant themes in network vulnerability analysis (68% of works) and food-physics applications (27%), with emerging focus on machine learning integration for ecological modeling. His research bridges theoretical physics with practical solutions in food safety and ecosystem management. Key recognitions include: Grand Prix de la Science de l'Alimentation from Académie Internationale de la Gastronomie (2012-2013) Dual National Scientific Qualifications for Full Professorship (2022) in Theoretical Physics of Fundamental Interactions and Matter Cassi's academic contributions extend beyond publications to two international patents in food preservation technology and editorial leadership since 2007 for World Scientific's Series on Advances in Statistical Mechanics . His research program demonstrates consistent translation of theoretical physics into practical applications across gastronomy and ecology, with growing emphasis on AI-enhanced network analysis for sustainability challenges.

• Statistical Mechanics
• Condensed Matter Physics
• Soft Matter Physics
• +4 more

Pasquale Cascarano is a fixed-term Assistant Professor at the University of Bologna , affiliated with the Department of the Arts . His research bridges computer science with creative industries (cinema, art, fashion) and biomedical applications, focusing on Artificial Intelligence and Extended Reality paradigms. He collaborates with national and international institutions on interdisciplinary projects. Institutional Affiliation: University of Bologna Academic Role: Assistant Professor (fixed-term) Research Interests center on integrating AI and XR into creative sectors and healthcare, with emphasis on: Generative AI for immersive environments Medical imaging and diagnostics Digital heritage preservation XR-based educational tools 3D visualization techniques Creative technology applications Recent Publications highlight trends in: Medical XR for surgical training AI-driven image restoration LLM integration with AR/VR Privacy in collaborative AR Fashion and cultural heritage digitization Deep learning for video enhancement

• Artificial Intelligence
• Extended Reality
• Computer Science
• +3 more

Hugo Georges Victor Lavenant serves as Assistant Professor in the Department of Decision Sciences at Bocconi University, Milan, where he has held a faculty position since 2020. Previously, he completed a postdoctoral fellowship at the University of British Columbia (2019-2020) under the Pacific Institute of Mathematical Sciences and earned his PhD in Mathematics from Université Paris-Sud (2016-2019) under Filippo Santambrogio's supervision. His academic foundation includes: PhD in Mathematics, Université Paris-Sud (2016-2019) Studies at École Normale Supérieure (2012-2016) covering mathematics, physics, history, and philosophy of science Classes préparatoires in mathematics and physics (2010-2012) Lavenant's research centers on optimal transport theory and its applications across mathematical disciplines. He investigates geometric structures in Wasserstein spaces, develops numerical methods for dynamical optimal transport, and bridges theoretical advances with Bayesian statistics. His work demonstrates particular innovation in trajectory inference for biological data and dependence measures for random measures, connecting pure mathematics with computational statistics. Recent publications reveal accelerating interdisciplinary impact, with 2024-2025 works extending optimal transport to machine learning (kernel methods, variational inference) and data science (opinion dynamics, single-cell analysis). This trajectory shows increasing methodological sophistication in handling measure-valued mappings and non-smooth geometries while maintaining computational tractability. Award recognition includes: Pacific Institute of Mathematical Sciences Postdoctoral Fellowship Lavenant actively mentors early-career researchers through formal advising relationships and collaborative projects. He currently supervises two PhD candidates (George Kanchaveli and Francesco Mascari, co-advised with Marta Catalano) and has guided Master's students including Mathis Hardion and Niccolò Bargellini. His teaching portfolio spans advanced analysis, optimization, and real analysis courses at Bocconi, reflecting his commitment to mathematical rigor in education. He operates within Bocconi's Decision Sciences ecosystem while maintaining international collaborations with researchers at UBC, Université Paris-Sud, and statistical groups worldwide. Current projects focus on entropy-based transport methods and geometric approaches to nonparametric statistics, positioning his work at the intersection of theoretical mathematics and data-driven applications.

• Optimal Transport
• Calculus of Variations
• Convex Analysis
• +3 more

Davide Previtali is an Assistant Professor at the University of Bergamo's Department of Engineering. His research focuses on control systems, black-box and preference-based optimization, and lithium-ion battery technologies. He teaches the 'Data science and automation' course (6 CFU). Education: Master’s in Computer Science Engineering (2019), PhD in Engineering and Applied Sciences (2022), both from University of Bergamo Research interests include model predictive control, thermal systems optimization, regenerative braking systems, and integration of biological models with neural networks. Recent work emphasizes energy-efficient industrial processes and algorithms for preference-based optimization with convergence guarantees. Publications span industrial oven modeling, shrink tunnel control systems, and advanced optimization algorithms. He leads the Control systems and Automation Laboratory, focusing on practical applications of control theory in manufacturing and energy systems. Labs/Teams: Control systems and Automation Laboratory

• Control Systems
• Black-Box Optimization
• Preference-Based Optimization
• +4 more