جست‌وجوی استاد و پژوهشگر

Sonia Petroneمشاهده پروفایل

استاد

• Bayesian Statistics
• Predictive Modeling
• Bayesian Nonparametrics
• +۱ مورد دیگر

Dr. Sonia Petrone is a Full Professor of Statistics at Bocconi University's Department of Decision Sciences. She earned her PhD in Statistics from Bocconi University and has held academic positions at the University of Pavia and University of Insubria before joining Bocconi. Her extensive international experience includes research visits across North America, Latin America, Europe, India, and Russia. Her research specializes in Bayesian statistics, with contributions to foundational theory, predictive modeling, Bayesian nonparametrics, and stochastic processes. She currently directs the Bocconi Summer School in Advanced Statistics and Probability and previously led the PhD program in Statistics (2011-2018). Her research portfolio demonstrates consistent focus on Bayesian nonparametric methods, predictive modeling, and applications to complex data structures. Recent work explores urn processes, time series analysis, and network modeling using innovative Bayesian approaches. Awards & Honors: IMS Medallion Lecture Award (2018) ISBA Foundational Lecture Award (2016) Fellow of International Society for Bayesian Analysis Fellow of Institute of Mathematical Statistics Fellow of European Laboratory for Intelligent Systems Fellow of Bocconi Institute of Data Science She has held editorial leadership positions as Editor of Statistical Science (2020-2022) and Bayesian Analysis (2010-2014), and served as President of the International Society for Bayesian Analysis (2014).

Giuseppe Santucciمشاهده پروفایل

دانشیار

• Visual Analytics
• Information Visualization
• Human-Computer Interaction
• +۳ مورد دیگر

Giuseppe Santucci is an Associate Professor at the Department of Computer, Control and Management Engineering Antonio Ruberti at Sapienza University of Rome. He teaches courses on Fundamentals of Computer Science, Software Engineering, and Visual Analytics. His office is located in Room B218 at Via Ariosto 25, Rome, and his contact email is santucci@diag.uniroma1.it. Dr. Santucci's research focuses on Visual Analytics, Information Visualization, Human-Computer Interaction, and Information Retrieval. His work spans theoretical aspects of visual query languages for semantic models to practical applications in visual analytics for cybersecurity, cryptocurrencies, and deep learning explainability. He has published over 130 articles in international journals and conferences, demonstrating his significant contributions to these fields. His recent publications show a strong trend toward applying visual analytics to increasingly complex domains including cybersecurity, cryptocurrencies, and explainable AI. The work demonstrates an evolution from theoretical foundations of visual query systems to practical applications that help users understand complex data and systems. His research bridges the gap between theoretical computer science and practical user-centered solutions. Dr. Santucci has received notable recognition including: IEEE VizSec 2018 Best Paper Award Human-Computer Interaction Cybersecurity Awards 2018 He actively mentors students through thesis projects focused on information visualization and visual analytics. His PROMISE project provides a framework for students to engage in cutting-edge research in information retrieval and visual analytics. He has supervised work on topics including visual evaluation techniques, visual mappings optimization, and user studies for Infovis systems. Dr. Santucci leads the A.WA.RE (Advanced Visualization & Visual Analytics REsearch) group at Sapienza University. This group conducts research on visual analytics tools for information retrieval evaluation, cybersecurity analysis, and deep learning explainability. Their work includes developing frameworks like CryptoComparator for cryptocurrency analysis and BUCEPHALUS for cybersecurity platform analysis.

• 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.

• Climate
• Climate change
• Climate dynamics
• +۹ مورد دیگر

Jost-Diedrich Graf Von Hardenberg is a Full Professor in the Department of Environmental, Land and Infrastructure Engineering (DIATI) at the Polytechnic University of Turin. He serves as the Energy and Climate Change Area Coordinator and is a Scientific Advisor of the HPC-AI Advisory Council. His research focuses on climate science and geophysical fluid dynamics, with significant contributions to understanding climate change impacts and Earth system modeling. Professor Von Hardenberg's research interests span multiple areas of climate science, including climate dynamics, geophysical fluid mechanics, hydrological cycle analysis, numerical climate modeling, and precipitation downscaling. His work particularly emphasizes climate tipping points and extremes, Rayleigh-Bénard convection in geophysical contexts, high-resolution Earth-system climate modeling, and stochastic approaches to precipitation downscaling. His research integrates theoretical, computational, and observational approaches to address fundamental questions about climate system behavior and change. His recent publications demonstrate a strong focus on Atlantic Meridional Overturning Circulation (AMOC) dynamics, climate extremes in Alpine regions, urban climate effects, and interdisciplinary applications of climate science to ecological and conservation challenges. His work bridges fundamental climate dynamics with practical applications for climate adaptation and environmental management. Among his notable recognitions are the Research in Paris award from the Maire de Paris (2009) and Fellowships at the London School of Economics and Political Science (2001-2002, 2004-2006). He has participated in numerous research networks including the European Geosciences Union section 'Nonlinear Processes in Geophysics' (2004-2012), the EC-Earth Consortium (2012-present), and COST Action ES0805 TERRABITES 'The terrestrial biosphere in the earth system' (2010-2014). Professor Von Hardenberg actively supervises PhD students including Marianna Albanese, Maria Clara Corda, Sara Filippini, and Jacopo Grassi, among others. He leads multiple significant research projects such as ROTurb (Resolving Ocean Macroscale Turbulence), LocClima (Impact of LOCal conditions on Italian microCLIMAtes), CRAWL (Carbon Release in A Warming cLimate), and CliMOC (Climate Impacts of the Atlantic Meridional Overturning Circulation), with funding from EU, national programs, and commercial contracts. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, where he contributes expertise in climate data analysis and modeling. His collaborative work extends to multiple institutions through non-commercial agreements with the National Research Council and various international research consortia focused on climate system understanding.

• Statistical Mechanics
• Condensed Matter Physics
• Soft Matter Physics
• +۴ مورد دیگر

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.

Mauro Barniمشاهده پروفایل

استاد

• Multimedia Security
• Digital Forensics
• Machine Learning
• +۳ مورد دیگر

Mauro Barni serves as a Full Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, where he teaches Cybersecurity, Information Theory, and Mathematical Statistics. His office hours are held Fridays from 3:00 PM to 5:00 PM via online appointment, reflecting his active engagement with students. Professor Barni's research spans multimedia security and digital forensics, with emphasis on deep learning applications for digital watermarking, deepfake detection, and synthetic image attribution. His work addresses critical challenges in adversarial machine learning, steganography, and image manipulation detection, contributing significantly to cybersecurity and intellectual property protection frameworks. Analysis of his 2021-2025 publications reveals dominant trends in neural network watermarking robustness, synthetic media detection, and defenses against backdoor attacks. His research consistently bridges theoretical foundations with practical implementations, focusing on real-world applications like printer source attribution and physical-domain adversarial scenarios. He leads the VIPP (Vision, Image Processing, and Pattern Recognition) research group, which maintains dedicated virtual classrooms for collaborative projects in computer vision and multimedia security. The group actively develops methodologies for image forensics, synthetic media analysis, and security countermeasures against emerging threats.

• Cognitive Neuroscience
• Developmental Neuroscience
• Multisensory Perception
• +۵ مورد دیگر

Ambra Ferrari is a Research Fellow at the Interdepartmental Center for Mind/Brain Sciences (CIMEC) within the University of Trento. Her work focuses on cognitive development, multisensory perception, and neuroimaging techniques. She teaches courses such as Cognitive neuroscience of infant development and contributes to the Cognitive Neuroscience program in the Department of Psychology and Cognitive Sciences. Her research integrates methodologies from neuroscience and psychology to study infant cognition, social development, and sensory integration. She develops computational tools like the WTools MATLAB toolbox for analyzing infant neural data. Ferrari's work bridges developmental psychology, psycholinguistics, and sensory neuroscience, emphasizing how prior expectations guide perception during communication. In teaching, she employs journal clubs and seminars to foster critical analysis of empirical studies and contemporary theories in cognitive development. Her courses aim to equip students with skills to evaluate experimental research and understand neurobiological foundations of cognition. Her laboratory (CIMEC) focuses on adaptive behavior, cross-modal plasticity, and embodied communication. Current projects explore statistical learning mechanisms, attention modulation in multisensory perception, and the role of gesture-prosody interactions in language comprehension.

Sebastiano VASCONمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۴ مورد دیگر

Sebastiano Vascon is an Associate Professor at Ca' Foscari University of Venice's Department of Environmental Sciences, Computer Science and Statistics (DAIS), and affiliated with the European Center for Living Technology. He earned his PhD in 2016 from the Italian Institute of Technology and University of Genoa, focusing on evolutionary game theory in pattern analysis and computer vision. His postdoctoral work spanned institutions like the Technical University of Munich and ETH Zurich, where he specialized in Active Learning and multi-object tracking. His research merges AI with interdisciplinary challenges, including climate change, environmental science, and cultural heritage preservation. Key areas include graph neural networks, computer vision, and game-theoretic models. He leads projects like RePAIR (AI for cultural heritage reassembly) and EasyWalk (AI-driven mobility solutions), and contributes to initiatives like MEMEX (digital storytelling). Teaching spans courses in Deep Learning, Machine Learning for Environmental Applications, and AI in Cultural Management. Research projects include: RePAIR: AI-driven 3D puzzle solving for artifact reconstruction EasyWalk: Socially-aware navigation systems MEMEX: AI for inclusive digital storytelling Climate modeling with IceBoost framework Publications highlight innovations in trajectory forecasting, environmental risk assessment, and graph-based methods. He actively reviews for top conferences (CVPR, ECCV) and journals.

Dipanwita Thakurمشاهده پروفایل

استادیار

• Green Artificial Intelligence
• Federated Learning
• Smart Healthcare
• +۴ مورد دیگر

Dr. Dipanwita Thakur serves as Assistant Professor at the Department of Computer Engineering, Modeling, Electronics and Systems (DIMES) at the University of Calabria, Italy since July 2023. She is an active member of the European Cooperation in Science & Technology (COST Action CA22104) focusing on cybersecurity and serves in the IEEE Future Networks Working Group for Artificial Intelligence/Machine Learning. Previously, she held a 15-year Assistant Professor position at Banasthali University, Rajasthan, and has industry experience at TechMahindra and C-DAC. Education: Ph.D. in Smart Healthcare from West Bengal University of Technology, Kolkata M.Tech. in Software Engineering from Banasthali Vidyapith MCA from NIELIT, Government of India B.Sc. from University of Calcutta Her research pioneers Green Artificial Intelligence with emphasis on energy-efficient federated learning and smart healthcare applications. She develops privacy-preserving human activity recognition systems using multimodal data fusion, focusing on performance evaluation and environmental sustainability. Her work bridges theoretical machine learning with practical healthcare solutions, optimizing AI systems for reduced carbon footprint while maintaining clinical efficacy through hardware-algorithm co-design and quantization techniques. Recent publications reveal a strong trajectory toward sustainable AI, with increasing focus on energy-aware federated learning frameworks, multimodal medical segmentation, and non-IID data handling. Her work consistently addresses the critical balance between model accuracy, convergence speed, and energy consumption across edge devices, with growing emphasis on quantization techniques and hardware-algorithm co-design for real-world deployment. Scientific Awards: Elevated to IEEE Senior Member (2024) Dr. B.C. Roy Memorial Scholarship for outstanding 10th Board results (1992) Student Science Seminar Award by West Bengal Government (1990) Dr. Thakur actively mentors students as evidenced by her congratulations to advisee Farwa for paper acceptances. She serves as Associate Editor for Information Fusion (Elsevier) and IEEE Sensors Journal, and holds editorial roles at Scientific Reports. Her research is advanced through COST Action CA22104 and IEEE working groups, though specific grant details aren't listed in the source material. She has organized key workshops including Green-Aware AI 2024 and Green Federated Learning at IJCNN 2025. She leads research within the MONAI community on data quality and federated learning, and contributes to IEEE IoT and Future Networks initiatives. Her work with the COST Action CA22104 Behavioral Next Generation in Wireless Networks connects cybersecurity with sustainable AI development, while her Missouri S&T visiting scholar position focuses on energy optimization for federated learning systems.

• Structural Health Monitoring (SHM)
• Smart / self-sensing cementitious composites
• Bridge engineering and life-cycle assessment
• +۶ مورد دیگر

Filippo Ubertini is Professor of Civil and Environmental Engineering at the University of Perugia, Italy, where he coordinates the International Doctoral Programme in Civil & Environmental Engineering and represents the University inside the FABRE national bridge-research consortium. He leads the Structural Health Monitoring Laboratory ( SHM-Lab ) and is the primary contact for assignments linked to smart-infrastructure research. Education: While explicit degrees are not listed in the supplied text, his role as programme coordinator and full professor implies completion of a PhD and habilitation in Civil Engineering. Research focus: Ubertini’s work sits at the intersection of smart materials and data-driven infrastructure management . He develops self-sensing cementitious composites doped with carbon micro-fibers or graphene nano-platelets that can measure strain, cracking and moisture in real time, turning whole bridges and buildings into distributed sensors. Complementary research threads include low-cost acquisition electronics, UAV & InSAR remote sensing, Bayesian & adversarial machine-learning algorithms for damage detection, digital twins and life-cycle cost analysis of bridge networks. Publication trends (2024-2025): Roughly 30 peer-reviewed items per year concentrate on (i) AI-enhanced operational modal analysis and transfer-learning damage classification across bridge populations, (ii) experimental characterisation of 3D-printed and cast self-sensing concrete, (iii) full-scale validation on curved box-girder, masonry and railway bridges, and (iv) integration of satellite radar data with numerical collapse simulations to predict residual service life of landslide-affected viaducts. Scientific awards & recognition: No specific prizes or fellowships are mentioned in the provided text. Doctoral supervision & grants: The text does not enumerate individual students or funded projects; however, his coordination of an international PhD programme and numerous experimental campaigns imply sizeable supervisory and funding responsibilities. Laboratory & team: Ubertini heads the SHM-Lab at UniPg, maintaining facilities for material mixing, 3D concrete printing, electrical impedance tomography, UAV photogrammetry, and large-scale structural testing, while collaborating with the European FABRE consortium and multiple EU projects.

Andrea Sottorivaمشاهده پروفایل

استاد

• Cancer Evolution
• Computational Biology
• Genomics
• +۴ مورد دیگر

Andrea Sottoriva is the Head of the Computational Biology Research Centre at Human Technopole , Milan, Italy, and holds the title of Professor of Cancer Genomics and Evolution . His work bridges computational biology, evolutionary theory, and clinical oncology to predict cancer progression and design adaptive treatment strategies. University of Bologna – BSc in Computer Science (2006) University of Amsterdam – MSc in Computational Sciences (2008) University of Cambridge – PhD in Computational Biology (2012) Dr. Sottoriva's research focuses on cancer evolution , applying machine learning and population genetics to decode tumor heterogeneity through multi-omics data. His lab integrates patient-derived organoids and spatial genomics to understand how genetic and epigenetic factors drive cancer progression. The 15 most recent publications demonstrate a consistent emphasis on subclonal dynamics (7/15), computational methods (6/15), and evolutionary modeling (5/15). Key themes include adaptive mutability in colorectal cancer , immune editing in post-transplantation relapses, and deep learning applications for tumor heterogeneity. Scientific recognition includes: Cancer Research UK Future Leaders in Cancer Research Prize (2016) His lab currently trains PhD students and postdoctoral researchers in computational oncology, maintaining a living biobank of patient-derived models while pioneering AI-mechanistic hybrid models for clinical translation.

Domenico Cicchellaمشاهده پروفایل

دانشیار

• Geochemistry
• Environmental Monitoring
• Soil Contamination
• +۷ مورد دیگر

Domenico Cicchella is an Associate Professor in the Department of Science and Technology at the University of Sannio, Italy, specializing in Geochemistry and Volcanology (GEO/08). With over two decades of academic experience, he has established himself as a leading researcher in environmental geochemistry, particularly in soil and water contamination studies in the Campania region of southern Italy. His research interests span multiple critical areas of environmental geochemistry: Urban and regional geochemical mapping Heavy metal and potentially toxic element (PTE) analysis in soils Environmental risk assessment methodologies Application of advanced statistical techniques to geochemical data Water pollution monitoring and assessment Integration of compositional data analysis with machine learning approaches Geochemical background determination Analysis of his publication record reveals a strong focus on developing innovative methodologies for environmental assessment, particularly through the "Campania Trasparente" project - a comprehensive multimedia monitoring initiative. His work increasingly incorporates advanced data analysis techniques including compositional data analysis, multivariate statistics, and machine learning applications to address complex environmental challenges in urban and regional settings. His research spans from fundamental geochemical studies to practical applications for environmental management and public health protection. Professor Cicchella maintains an active research profile with numerous collaborations across Italy and internationally, contributing significantly to our understanding of environmental contamination patterns and developing practical approaches for risk assessment and management. His work has appeared in leading journals including Journal of Geochemical Exploration, Applied Geochemistry, and Science of the Total Environment, demonstrating both academic rigor and practical relevance to environmental challenges.

Silvia BOZZAمشاهده پروفایل

دانشیار

• Forensic Statistics
• Bayesian Statistics
• Evidence Evaluation
• +۴ مورد دیگر

Silvia BOZZA is an Associate Professor in the Department of Economics at Ca' Foscari University of Venice, where she also serves as Department Delegate for Teacher Training for High Schools. Her academic profile is centered around Statistics (SSD STAT-01/A), with a strong focus on forensic applications of statistical methods. She maintains dual institutional affiliations, working within both the Department of Economics (based in San Giobbe) and the Interdepartmental School of Economics, Languages and Entrepreneurship for International Exchanges (located in Treviso - Palazzo San Paolo). Professor BOZZA's research primarily explores the application of Bayesian statistics to forensic science and legal evidence evaluation. Her work demonstrates a consistent trajectory from early publications on spatio-temporal models to her current specialized focus on forensic statistics. She has developed expertise in probabilistic graphical models, Bayes factors, and statistical decision theory as applied to evidence interpretation. Her research addresses critical questions in forensic science regarding how to properly evaluate and communicate statistical evidence in legal contexts, with particular attention to handwriting analysis, DNA evidence, and authorship attribution. Her publication record shows remarkable consistency and productivity, with over 90 publications spanning from 2001 to 2025. Recent work (2022-2025) demonstrates her ability to address contemporary challenges, including AI authorship discrimination using Bayesian methods for distinguishing human from ChatGPT-generated text. Her articles frequently appear in high-impact forensic and statistical journals including Law, Probability & Risk, Forensic Science International, and Annual Review of Statistics and its Application. Professor BOZZA actively supervises undergraduate and graduate theses involving data analysis, requiring knowledge of statistical software including the R programming language used in the Statistics for Economics Laboratory course. She encourages students to propose topics while offering guidance to refine research questions. Her office hours show she maintains regular availability for student consultations, indicating active engagement in academic mentoring.

Marianna Succurroمشاهده پروفایل

دانشیار

• Applied Microeconomics
• Industrial Organization
• Environmental Economics
• +۵ مورد دیگر

Marianna Succurro serves as Associate Professor in the Department of Economics, Statistics and Finance (DESF) at the University of Calabria, Italy, where she has been faculty since 2010 following her PhD completion at the same institution. Her academic journey includes a Master's degree from Bocconi University (2002) and extensive postdoctoral research experience. Education: Master Degree in Economics, Bocconi University, 2002 PhD in Economics, University of Calabria, 2004 Her research program bridges applied microeconomics with industrial organization, environmental economics, and tourism studies through rigorous econometric analysis. Current investigations focus on green innovation competitiveness indices, regulatory impacts on SME digital transformation, and tourism-driven development in Southern Italy. She examines how environmental policies, banking structures, and digital adoption influence firm dynamics and regional growth. Analysis of her 2019-2025 publications reveals three dominant threads: (1) Environmental economics research increasingly centers on quantifiable sustainability metrics; (2) Banking studies emphasize institutional heterogeneity during crises; (3) Tourism economics investigates cultural heritage as economic catalyst. Her methodological approach consistently combines theoretical frameworks with empirical validation using Italian and European datasets. Scientific Recognition: Multiple PostDoc fellowships from Italian research institutions Active referee for international economics journals Member of prominent academic societies including SIE (Italian Economic Society) She advises graduate students while leading research within DESF's 'Crescita, risorse ed ambiente' group. Current projects investigate green innovation policy effectiveness and digital transformation barriers for regional SMEs. Her teaching portfolio includes advanced courses on digital markets and industrial economics across multiple graduate programs. Research Infrastructure: She directs the 'Laboratorio di Analisi Economica' where empirical work on environmental economics and firm dynamics is conducted, collaborating closely with the department's research group on sustainable growth and resource economics.

Violetta Lonatiمشاهده پروفایل

استادیار

• Formal Languages and Automata
• Computer Science Education
• Theoretical Computer Science
• +۲ مورد دیگر

Violetta Lonati is an Assistant Professor at the University of Milan 's Department of Computer Science since 2005. Her research spans Formal Languages and Automata (operator precedence languages, Wang automata, tiling systems) and Computer Science Education . She co-authored over 15 publications in theoretical computer science and education, focusing on 2D language recognition, logic characterization of automata, and pattern statistics in stochastic models. Education : PhD in Computer Science (2005) and Laurea in Mathematics (2001) from University of Milan Research Groups : ALaDDIn Lab for Didactics and Dissemination of Informatics, Bebras International Initiative Her work on Wang automata established their equivalence to tiling systems while introducing deterministic variants. In education, she designed workshops for schools and contributed to Italy's national computing curriculum proposal (2019). She held leadership roles at ACM ITiCSE (WG5 leader 2022), served as Associate Program Chair (2019-2022), and reviewed for top venues like ICER and SIGCSE TS. She received Google CS[4]HS and Informatics Europe awards for her educational contributions. Key Publications (2017-2001): Input-driven locally parsable languages (TCS 2017) Operator precedence logic characterization (SICOMP 2015) Snake-deterministic tiling systems (MFCS 2009) Graph fibrations and PageRank (RAIRO 2006) Pattern statistics in rational models (STACS 2005) Scientific awards include Google CS[4]HS (2011, 2017, 2019) and the Informatics Europe Best Practices in Education (2016). As part of ALaDDIn, she developed teacher training programs and graduate courses on computing education. Her teaching experience covers Algorithms & Data Structures (2013-2023), Computer Science Teaching (2014-2023), and courses for Biotechnology and Geological Sciences programs (2005-2007).