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Marco MesitiView profile

Associate Professor

• Data Management
• Big Data Visualization
• Data Integration
• +6 more

Marco Mesiti is an Associate Professor at the Department of Computer Science, University of Milan, Italy. He holds a PhD and Laurea in Computer Science from the University of Genova. His research focuses on data management, big data visualization, and bioinformatics, particularly in biomolecular networks and IoT data. He is a member of AnacletoLAB and has contributed to developing tools like UNIPred-Web for biomolecular network analysis. Education: PhD in Computer Science, University of Genova, 2003 MSc in Computer Science, University of Genova, 1998 Laurea (BSc equivalent) in Computer Science, University of Genova (cum laude) Research Interests: His work spans XML data handling, semistructured data, and applications in bioinformatics, IoT, and credit worthiness. He explores approaches to manage heterogeneous data, including visualization techniques and knowledge graph construction. Recent projects include RNA-centered knowledge graphs and GPU-based algorithms for large networks. Publications: Recent work includes advancements in machine learning for protein design, RNA interaction analysis, and multi-omics data integration. His research emphasizes scalable methods for biomolecular networks and visual analytics tools. Grants & Collaborations: Involved in projects like ELISE and MUSE. Collaborates internationally on bioinformatics and computational biology initiatives. Labs & Teams: Member of AnacletoLAB, focusing on machine learning and data science applications.

• Combinatorics on Words
• String Algorithms
• Data Mining
• +3 more

Gabriele Fici is an Associate Professor at the Department of Mathematics and Computer Science, University of Palermo (Unipa). His research focuses on combinatorics on words, string algorithms, and algorithmic pattern matching. He teaches courses in text sequence analysis, data mining, and software development. Research Interests : Combinatorial pattern matching, Abelian repetitions, digital convexity, and theoretical foundations of string processing. Key Contributions : Pioneering work on Lyndon words, de Bruijn sequences, and jumbled pattern matching algorithms. Publications : Extensive publications in top-tier conferences like CPM and journals, with a focus on 2013-2025 trends in algorithmic complexity and computational linguistics.

• Computational Logic
• Answer Set Programming
• Bioinformatics
• +6 more

Alessandro Dal Palu' is an Associate Professor at the Department of Mathematical, Physical, and Computer Sciences at University of Parma. He holds a PhD in Computer Science from University of Udine and has been with University of Parma since 2005, transitioning from Researcher to Associate Professor in 2014. His teaching portfolio includes courses on Computer Architecture, Constraint Programming, and Algorithms & Data Structures. His research spans computational logic, bioinformatics, and GPU computing. Notable achievements include the 2007 GULP award for his Ph.D. thesis and the ICLP 2010 best paper award. He has led Italian INdAM-GNCS research projects on GPU applications (2011) and Logic Programming in cancer genomics (2016). Recent publications focus on explainable AI frameworks, bioinformatics applications, and sustainable logistics solutions. His work integrates Answer Set Programming with biomedical challenges like protein structure analysis and cancer genome evolution. He chairs the International Conference on Logic Programming (ICLP 2018) and has organized multiple international workshops on constraint programming. 2007 GULP Award ICLP 2010 Best Paper PI for INdAM-GNCS projects (2011, 2016) Program Committee member for international conferences

• Computer Graphics
• Geometry Processing
• Computational Topology
• +4 more

Michela Spagnuolo is a Research Director at the Italian National Research Council’s Institute of Applied Mathematics and Information Technology (CNR-IMATI-GE) since 2001. Her work bridges Computer Graphics , Geometry Processing , and Computational Topology , with applications in 3D Shape Analysis , Cultural Heritage , and Bioinformatics . Co-supervised 6 PhD theses (plus 2 ongoing) Associate Editor for journals like The Visual Computer and Computers&Graphics Chair of conferences including Shape Modeling International and EG Workshops on 3D Object Retrieval Research Interests : Focus on geometric and semantic modeling of 3D objects , computational topology for shape analysis , and structural/similarity evaluation . Her work enables advanced 3D search engines , semantic annotation , and medical imaging applications . Article Trends : Recent publications emphasize mesh quality indicators for Virtual Element Methods in engineering simulations and semantic-driven 3D model analysis for medical diagnostics and cultural heritage . Key subtopics include topological decomposition , data processing services , and multi-scale modeling . Scientific Awards : Fellow of the Eurographics Association (2014) Notable Contributions : Led projects like IQmulus (geospatial data analytics) and MultiScaleHuman (medical shape modeling). Pioneered CIDOC CRMdig for cultural heritage documentation and developed techniques for kernel computation in polyhedra .

• Artificial Intelligence
• Machine Learning
• Pattern Recognition
• +6 more

Giosuè Lo Bosco is a Full Professor of Computer Science (SSD INFO-01/A) at the Department of Mathematics and Computer Science, University of Palermo, Italy. He teaches courses such as Artificial Intelligence and Deep Learning, Programming and Laboratory, and Biomedical Research Methodology across multiple schools including the School of Basic and Applied Sciences, the Polytechnic School, and the School of Medicine and Surgery. His research interests include artificial intelligence, machine learning, pattern recognition, bioinformatics, natural language processing, and soft computing. These areas reflect his interdisciplinary approach, bridging computer science with biomedical and data-intensive applications. He serves as an associate editor for the journals Information Sciences (Elsevier) and BMC Bioinformatics (Springer Nature), indicating active engagement and recognition in the international research community. While no specific scientific awards are listed, his editorial roles and sustained teaching and research activities underscore his academic contributions. He advises students and contributes to academic supervision, although no named advisees are mentioned in the available text. He is involved in multiple academic units and maintains an active presence through office hours and institutional contact. There is no indication of part-time status, retirement, or former staff designation.

Achille GIACOMETTIView profile

Professor

• Theoretical Physics
• Soft Matter Physics
• Polymer Physics
• +3 more

Achille GIACOMETTI is a Full Professor at Ca' Foscari University of Venice, affiliated with the Department of Molecular Sciences and Nanosystems and the European Center for Living Technology (ECLT) , where he serves as Director. His research focuses on theoretical physics, soft matter, and biophysics, with a strong emphasis on polymer physics, protein structures, and self-assembly processes. Key roles include leadership at ECLT, a multidisciplinary research center exploring living technology and complex systems. His work bridges physics and biology, addressing topics like phase transitions in colloids, solvent effects on polymers, and computational modeling of protein interactions. Recent projects include studies on crystalline order in charged rods, embodied intelligence in soft materials, and solvent-driven oligomer folding. Publications highlight contributions to understanding polymeric systems, phase behavior, and nanoscale self-assembly. Collaborative efforts span international partners, reflecting his commitment to interdisciplinary research. No awards explicitly listed, but his extensive publication record underscores academic impact.

Luigi PalopoliView profile

Professor

• Hybrid Systems
• Real-Time Scheduling
• Quality of Service Control
• +12 more

Luigi Palopoli is a Full Professor and Director at the Department of Information Engineering and Computer Science (DISI), University of Trento, Italy. He is also a member of the University Council. His research spans hybrid systems, real-time scheduling, quality of service control, robotics, embedded systems, and cyber-physical systems. His research interests include: Hybrid Systems and Real-Time Scheduling Service and Assistive Robotics for Elderly Support AI Applications in Robotics and Embedded Systems Outlier Detection and Anomaly Explanation Audio Super-Resolution and Signal Processing Biological Network Analysis and Graph Alignment His recent publications reflect a strong interdisciplinary focus, combining AI, robotics, real-time systems, and bioinformatics. Trends show increasing work in explainable AI, assistive technologies, and multimodal learning (e.g., vision transformers for audio). He has made notable contributions to robotic navigation for the elderly, real-time embedded systems, and logic-based outlier detection. Scientific awards include: Outstanding Paper Award at RTAS 2017 He advises students and collaborates widely, especially with Daniele Fontanelli, Luca Abeni, and other researchers in robotics and AI. He maintains an active research group, evidenced by a dedicated YouTube channel for the Embedded Intelligence and Robotic Systems group. He is involved in teaching, including courses on Robot Planning and Real-Time Operating Systems, and participates in AI seminar series. There is no indication of retirement or former status; he is actively engaged in research, teaching, and academic service.

• Algorithms on strings
• Formal language theory
• Bioinformatics
• +3 more

Chiara Epifanio is a researcher (INFO-01/A) at the University of Palermo , based in the Department of Mathematics and Computer Science . She holds regular office hours on Tuesdays 14:30–17:00 in Room 104, first floor, Via Archirafi 34, and can be reached at chiara.epifanio@unipa.it . Over the past fifteen years she has designed and taught a diverse portfolio of courses spanning Programming , Bioinformatics , Advanced Programming , Teaching Methodologies and Techniques for Computer Science and Pattern Discovery for Life Sciences . These offerings serve degree programmes in Mathematics, Computer Science, Statistics & Data Science, and the recently launched curricula in Data, Algorithms & Machine Intelligence and Computer Science & Artificial Intelligence . Her research lies at the intersection of combinatorics on words , string algorithms , and bioinformatics . She has made sustained contributions to the design of alignment-free distances for biological data, the theory of Sturmian words and their associated graphs, suffix automata tolerant to mismatches, and compact data structures such as linear-size suffix tries. The work repeatedly draws on deep results from formal language theory, automata theory, and discrete mathematics to solve practical problems in sequence analysis. Publications trend: From 2004 onward she has produced a steady stream of peer-reviewed articles that move from foundational combinatorial results on Sturmian words and critical factorization theorems toward application-driven studies on approximate string matching and genomic data mining. A marked acceleration is visible in the 2023 publications addressing k-Hamming and k-edit distances, reflecting current demands in large-scale biological data analytics. Scientific awards: None explicitly mentioned in the provided material. Advising & grants: No PhD or Master’s students are listed in the supplied pages, and no funded project descriptions are available. Laboratories & teams: While no specific lab is named, her teaching and research are embedded within the Department of Mathematics and Computer Science, which hosts groups in algorithms, discrete mathematics, and bioinformatics, and provides access to the university’s ATeN Center and other research infrastructures.

• Computational Biology
• Bioinformatics
• Data Compression
• +7 more

Raffaele Giancarlo is a Full Professor in the Department of Mathematics and Computer Science at the University of Palermo. His office hours are held on Mondays and Thursdays from 2:30 PM to 5:30 PM in Room 106 of the DMI (Dipartimento di Matematica e Informatica) or via TEAMS. He can be reached at raffaele.giancarlo@unipa.it. Research Focus: Computational Biology, Bioinformatics, Data Compression, and Algorithm Design. Key Contributions: Development of agile platforms for genomic data analysis, optimization of Bloom filters, and innovative text indexing techniques.

Francesca Marta Lilja Di LascioView profile

Associate Professor

• Copula-based stochastic models
• Clustering techniques for dependent data
• Statistical methods for spatial/time series data
• +5 more

Francesca Marta Lilja Di Lascio is an Associate Professor of Statistics at the Faculty of Economics and Management, Free University of Bozen-Bolzano. Her research focuses on copula-based statistical methods for complex data analysis, including dependence modeling, clustering algorithms, and applications in environmental science, energy economics, and medical statistics. She obtained her PhD in Statistical Methodology for Scientific Research from the University of Bologna (2008) and holds a National Scientific Qualification for Full Professor (2023-2034). Her academic roles include Vice-director of the Bachelor in Economics and Social Sciences, Coordinator of the BEMPS working paper series, and member of the Quality Committee. She has organized over 20 international conferences and workshops on statistical methods and data science, including the 2022 Workshop on Statistical Learning and Econometrics. Research interests span copula-based clustering, spatial-temporal modeling, and imputation techniques for missing data. She has secured grants totaling over €3.5M, including the €2M 'Agritech National Research Center' (PNRR funded) and the €182k 'Techno-economic methodologies for sustainable energy scenarios' project. She develops statistical software packages like CoClust (copula-based clustering) and PanelTM (dynamic threshold models). Teaching includes graduate courses on multivariate statistical methods and PhD-level quantitative research methods. She has published 40+ peer-reviewed articles in journals like Risk Analysis , Computational Statistics & Data Analysis , and Environmental and Ecological Statistics . Key Awards: Full Professor Qualification (2023), Associate Professor Qualification (2017) Recent Projects: EXTReme Events in Mountain Environments (€120k), Detecting Effects of Experimental Therapies (€82k) Professional Memberships: Italian Statistical Society (SIS), International Biometric Society (IBS), International Statistical Institute (ISI)

• Artificial Intelligence
• Bioinformatics
• Machine Learning
• +7 more

Enrico Blanzieri is an Associate Professor at the University of Trento's Department of Information Engineering and Computer Science. His research focuses on artificial intelligence, bioinformatics, quantum computing, machine learning, and computational biology. He actively contributes to interdisciplinary projects such as Vitis OneGenE for gene network analysis and quantum machine learning pipelines. His teaching includes courses like Algorithms for Bioinformatics, Quantum Machine Learning, and Data Mining. Blanzieri's work bridges theoretical foundations and practical applications, with notable contributions in quantum annealing-based algorithms, gene network expansion using distributed computing, and socially-competent artificial agents. His research integrates computational methods with biological systems, addressing challenges in precision agriculture and systems biology. His recent publications emphasize quantum machine learning advancements, causal role attribution in gene networks, and ethical AI frameworks for language models. Collaborative projects include the GENE@HOME volunteer computing initiative for bioinformatics tasks. Blanzieri also engages in educational activities, supervising courses that blend theoretical computer science with real-world applications.

Alfredo PulvirentiView profile

Professor

• Bioinformatics
• Biomedicine
• RNA Interference
• +9 more

Alfredo Pulvirenti is a Full Professor of Computer Science at the University of Catania, Italy. He holds a joint appointment with the Department of Clinical and Experimental Medicine and the Department of Mathematics and Computer Science. Born in 1974, he earned his Laurea (1999, summa cum laude), PhD (2003), and post-doc (2004) in Computer Science from the University of Catania. His academic career includes roles as Assistant Professor (2005-2014), Associate Professor (2014-2023), and Full Professor since 2023. His research bridges Bioinformatics and Biomedicine , focusing on RNA interference (microRNAs, long non-coding RNAs) via stochastic and network-based inference methods. Key contributions include subgraph matching , motif finding , and multiple network alignment using Monte Carlo techniques for analyzing biological networks . He also applies time series analysis to seismic and infrasonic signals through collaborations with Italy's National Institute of Geophysics and Volcanology (INGV). Recent publications highlight advancements in graph algorithms (e.g., MultiGraphMatch, ArcMatch) and systems biology tools like MITHrIL and SPECifIC. He co-directs the Jacob T. Schawartz International School for Scientific Research and leads national/regional projects on Bioinformatics and Big Data in Cancer . His group includes 3 researchers, 1 post-doc, and 3 PhD students in Complex Systems. Awards and Leadership : Best Paper Award at CBS 2009 Guest Editor for BMC Bioinformatics, Briefings in Bioinformatics, Elsevier Program Committee Member for major international conferences International Collaborations span institutions like NYU, Ohio State University Wexner Medical Center, Brown University, Tel Aviv University, Toronto University, and Università di Ancona.

• Artificial Neural Networks
• Medical Image Processing
• Wearable Electronic Devices
• +6 more

Eros Gian Alessandro Pasero is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) , Politecnico di Torino , and a member of the PolitoBIOMed Lab (Biomedical Engineering). He has held visiting Associate Professor roles at institutions including Tongji University and Turin Polytechnic University in Tashkent. His research spans artificial neural networks , medical image processing , and wearable devices , with applications in cardiology, industrial optimization, and environmental monitoring. His work focuses on ECG signal analysis for Brugada syndrome risk stratification, deep learning for biological imaging, LSTM models for photovoltaic forecasting, and transformer architectures in clinical diagnostics. He has pioneered the G-EXIN neural network for nonstationary data and Mini Green Radio Sonde for atmospheric sensing. Scientific Awards : Four Design-In Awards , Premio Innova S@alute2017 (TEVA), and President of SIREN (Italian Society of Neuronic Networks) since 2014. Research Projects : MUSMET (2024-2028): Musical Metaverse innovation lab via EU-EIC. ENTWINED (2023-2025): Neural digital twins for electrical drives. BrS-AI-ECG (2021-2024): AI in Brugada diagnostics (ERC). Patents : Inclusive sound card, wearable ECG device, and radio sonde technologies.

FRANCO SCARSELLIView profile

Professor

• Graph Neural Networks
• Machine Learning
• Artificial Intelligence
• +3 more

FRANCO SCARSELLI is a Full Professor at the University of Siena, affiliated with the Department of Information Engineering and Mathematical Sciences. His primary research focuses on Graph Neural Networks (GNNs), machine learning applications in IoT, blockchain, bioinformatics, and medical imaging. He has contributed extensively to the theoretical foundations of GNNs, including their expressive power and VC dimensions. His teaching roles include courses on Advanced Machine Learning for the Master's program in Artificial Intelligence and Automation Engineering, as well as Information Systems for undergraduate Management Engineering students. He has been actively involved in curriculum development since at least 2021/2022. Research highlights include interdisciplinary work on agrifood supply chain traceability using IoT and blockchain, molecular property prediction with GNNs, and semantic analysis of diffusion models. Key collaborations involve institutions like the University of Siena and industry partners in smart logistics and healthcare. His publications span over two decades, with recent contributions emphasizing the theoretical underpinnings of GNN architectures and their applications in dynamic graphs, medical diagnostics, and industrial fault detection. He has also pioneered open-source tools like GNNKeras for graph neural network implementations.

• Bioinformatics
• Natural Computing
• Computational Genomics
• +3 more

Giuditta Franco is an Associate Professor at the Department of Computer Science, University of Verona. Her research focuses on Bioinformatics , Natural Computing , and Computational Genomics , with expertise in algorithmic modeling of biological processes and DNA computing. Academic Sector: IINF-05/A - Information Processing Systems Research Areas: ERC PE6_13 (Bioinformatics, Bio-inspired Computing) and PE6_4 (Theoretical Computer Science, Formal Methods) She teaches courses such as Discrete Biological Models and Natural Computing in the Bioinformatics and Medical Bioinformatics degree programs. Her office is located at Ca' Vignal 2, Floor 1, Room 72.