جست‌وجوی استاد و پژوهشگر

Sergio Tessarisمشاهده پروفایل

استادیار

• Semantic Technologies
• Description Logics
• Knowledge Representation
• +۶ مورد دیگر

Sergio Tessaris is an Assistant Professor at the KRDB Research Center for Knowledge and Data, affiliated with the Faculty of Computer Science at the Free University of Bozen-Bolzano. His research focuses on semantic technologies, Description Logics, and data-aware workflows. University: Free University of Bozen-Bolzano School: Faculty of Computer Science Emails: Sergio.Tessaris@unibz.it, tessaris@inf.unibz.it Research Interests: His work centers on semantic technologies for data access and process management, including Description Logics reasoning algorithms, declarative business processes, and ontology-driven systems. He has contributed to temporal event data analysis, chatbot design for legal reporting, and SQL null value handling. Recent publications emphasize business process verification, constraint mining, and deep learning applications. Teaching Activities: Local coordinator of the European Masters Program in Computational Logic (EMCL) Lecturer for courses: Integrated Logic Systems, Computational Logic, Introduction to Artificial Intelligence, Non-monotonic Logics Teaching assistant for Semantic Web Technologies and XML/Semi-structured Databases Organisational Contributions: Co-organiser of DL 2007 and DL 2002 workshops Former member of Description Logic steering committee Program committee member for conferences including AAAI-06, ESWC, ISWC, and ODBASE

Michele Loretiمشاهده پروفایل

استاد

• Formal methods
• Concurrency theory
• Distributed systems
• +۴ مورد دیگر

Michele Loreti is Full Professor in Computer Science at the University of Camerino within the School of Science and Technology and serves as Director of the School of Advanced Studies. His career includes roles as Research Associate at University of Firenze (2002-2017) and Visiting Professor at IMT Institute for Advanced Studies (2012-2016). He holds a PhD in Mathematical Logic and Theoretical Computer Science from University of Siena (2001) and a Computer Science degree from University of Rome 'La Sapienza' (1997). Research interests: Formal tools for concurrent/distributed systems Quantitative analysis of collective adaptive systems Spatio-temporal model checking Process calculi and modal logics Programming languages for network-aware applications Runtime verification and dynamic system adaptation Article trends: His work focuses on formal verification of cyber-physical systems, spatio-temporal properties, stochastic process calculi, attribute-based communication, and tools like CARMA and muG for collective system analysis. Editorial roles: Assistant editor for Elsevier Journal on Logical and Algebraic Methods in Programming and member of the Reproducibility Board for ACM Transactions on Modelling and Computer Simulation.

Rosario Culmoneمشاهده پروفایل

استادیار

• Internet of Things
• Blockchain Technology
• Sensor Networks
• +۷ مورد دیگر

Rosario Culmone is an Assistant Professor at the University of Camerino, with a strong research focus in Internet of Things (IoT), sensor networks, and related technologies. His academic work spans multiple domains including smart city applications, blockchain implementations, and educational technology. Dr. Culmone's research interests center around IoT interoperability , sensor network optimization , and formal verification methods for intelligent environments. His work demonstrates a consistent focus on practical applications of distributed systems, with significant contributions to energy-efficient routing algorithms, blockchain-based certification systems, and ontology-driven frameworks for ambient assisted living. An analysis of his publication record reveals a clear trajectory from foundational work in wireless sensor networks and ECA rules verification toward more applied research in smart city technologies, food traceability using blockchain, and AI-enhanced educational systems. His most recent publications (2023-2025) show increased focus on practical implementations addressing real-world problems in security, education, and supply chain management. Dr. Culmone has developed several notable frameworks including the Share Pattern for IoT interoperability, NARUN for noise-adaptive routing, and IRON , a domain-specific language for programming IoT devices. His research bridges theoretical computer science with practical implementations across multiple application domains.

• Reaction Systems
• Bioinformatics
• Programming Languages
• +۵ مورد دیگر

Moreno Falaschi is a Professor at the University of Siena's Department of Information Engineering and Mathematical Sciences. He teaches Programming Fundamentals for Biotech Engineering, Models and Languages for Bioinformatics for Artificial Intelligence Engineering, Programming for Mathematics, and Information Processing Systems, with current responsibilities extending to the 2025/2026 academic year. His research centers on Reaction Systems as formal models for biochemical processes, applying rewriting systems, concurrency theory, and constraint logic programming to analyze biological systems. Key applications include comorbidity treatment strategies, hemostasis pathways, and T cell differentiation, bridging theoretical computer science with medical bioinformatics. Recent publications (2023-2025) demonstrate consistent innovation in dynamic slicing techniques, guarded reaction systems for medical applications, and quantitative extensions using SOS semantics. His work spans formal verification, computational biology, and biomedical AI, with significant contributions to journals like the International Journal on Software Tools for Technology Transfer.

Francesca Chiaromonteمشاهده پروفایل

استاد

• Statistics
• Bioinformatics
• Genomics
• +۷ مورد دیگر

Francesca Chiaromonte is a renowned statistician and professor holding dual faculty positions at the Sant'Anna School of Advanced Studies (Institute of Economics) and Penn State University (Department of Statistics). She is the scientific coordinator of the EMbeDS Department of Excellence and a key figure in interdisciplinary research, particularly at the interface of statistics, computation, and life sciences. Her work focuses on developing methods for analyzing high-dimensional, complex data, with applications in genomics, meteorology, and economics. Education: She earned a Laurea (cum laude) in Statistical and Economic Sciences from the University of Rome La Sapienza (1990s) and a Ph.D. in Statistics from the University of Minnesota (2000s). Her thesis work, under R. Dennis Cook, explored sufficient dimension reduction and envelope models. Research Interests: Methodological contributions include dimension reduction, functional data analysis, and computational techniques for significance assessment. Applied research spans Omics data integration, climate change socioeconomic impacts, and statistical validation of agent-based economic models. She has pioneered applications of statistical methods to meteorology, such as improving tropical storm forecasts and analyzing storm lifecycle dynamics. Awards: Elected Fellow of the American Statistical Association (2016) and Fellow of the Institute of Mathematical Statistics (2022), recognizing her contributions to statistical methodology and interdisciplinary training. Academic Leadership: Spearheads interdisciplinary training programs, including the PhD in Data Science (consortium with Scuola Normale Superiore and others) and the National Doctorate in Artificial Intelligence. Active in Penn State’s Huck Institutes of the Life Sciences and multiple research centers. Collaborations: Engages with institutions such as the Santa Fe Institute, UCLA’s Institute for Pure and Applied Mathematics, and the International Institute for Applied Systems Analysis.

• Performance Engineering
• Cloud Computing
• Machine Learning
• +۳ مورد دیگر

Emilio Incerto is an Assistant Professor at the IMT School for Advanced Studies Lucca, Italy. His research focuses on performance engineering, cloud computing, and formal methods applied to systems optimization. He specializes in developing frameworks for performance prediction, autoscaling solutions for microservices, and integrating machine learning techniques into performance modeling. Key research areas include: Performance modeling and optimization of distributed systems Autoscaling algorithms for dynamic cloud workloads Formal verification of real-time software systems AI-driven performance control mechanisms He has organized international workshops such as AIPerf (Artificial Intelligence for Performance Modeling), showcasing leadership in bridging AI and performance engineering. His work frequently explores reproducibility in performance studies and quantitative evaluation of complex systems like flocking behaviors in biological simulations. Notable contributions include μOpt (an efficient autoscaler for microservices) and μP (a performance prediction framework). His research emphasizes practical implementation of theoretical models through frameworks like SystemC-based environments for HW/SW co-design.

Riccardo Sistoمشاهده پروفایل

استاد

• Formal Methods
• Cybersecurity
• Network Security
• +۱۳ مورد دیگر

Riccardo Sisto is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he also leads the NetGroup research group and is a member of the SmartData@PoliTO and Cybersecurity National Laboratory. He has held academic positions continuously since 1991, progressing from Assistant to Full Professor by 2004. Education: PhD in Computer and Systems Engineering, Politecnico di Torino (1992) Graduate in Electronic Engineering, Politecnico di Torino (1987) Riccardo Sisto’s research focuses on formal methods applied to cybersecurity, particularly in formal verification of cryptographic protocols, security automation in cloud and virtualized networks, and secure code generation. His work bridges theoretical formal methods with practical network security applications in SDN/NFV and Kubernetes environments. The recent publications highlight a strong trend toward security automation , formal verification of network and cryptographic protocols , and policy management in virtualized infrastructures . His team develops frameworks like VEREFOO and VERIGRAPH to automate firewall and security function configuration, particularly in cloud-native and multi-cluster environments. Scientific Awards and Honors: ICICS Best Demo Award (2022) IEEE HPSR Best Paper Award Finalist (2014) High Honor Paper Award at IEEE AINA (2004) Fellow of the ACM (2010) Senior Member of the ACM Riccardo Sisto has supervised numerous PhD students and leads multiple competitive research projects funded by the EU (e.g., MIRANDA, VeTeSS) and industry. He serves on editorial boards such as ELECTRONICS and has held leadership roles in international conferences. His research includes both fundamental contributions in formal methods and applied work in industrial collaborations through commercial research projects. He is actively involved in advising PhD students and post-doctoral researchers such as Daniele Bringhenti, Simone Bussa, Francesco Pizzato, and Fulvio Valenza. His lab, NetGroup, focuses on building dependable and secure distributed systems using model-driven and formally verified approaches.

• Environmental Science
• Atmospheric Pollution
• Air Quality Modeling
• +۵ مورد دیگر

Eliana Pecorari is a Researcher at the Department of Environmental Sciences, Informatics and Statistics (DAIS) within Ca' Foscari University of Venice , holding a fixed-term contract since 2017. Her work integrates environmental science , air quality modeling , and hydronomy through field measurements, laboratory analysis, and mathematical modeling. Education : PhD in Environmental Hydronomy (2008, Padova University) with CNRS/Ecole Normale Supérieure collaboration; M.Sc. in Environmental Engineering (2004, Padova); 'Basic Aerosol Science' Summer School (2009, Vienna). Her research focuses on air pollution sources (airports, marine engines, industrial emissions) in Venice using Lagrangian/Eulerian models , PM2.5 dispersion , and odor impact studies . She developed the WATERBUS emission model for small boats and collaborated with SAVE Group , ACTV , and Port of Venice . Recent publications examine aircraft emissions at Venice-Treviso airports, PM2.5 source apportionment , and sustainability in water transport . She supervises 6 M.Sc. students and collaborates with PhD candidates. Her scientific awards include the Erasmus Mundi Grant (2001-2002) and 'Ing. Aldo Gini' foundation grant (2002).

Andrea Marrellaمشاهده پروفایل

دانشیار

• Computer Science
• Artificial Intelligence
• Business Process Management
• +۸ مورد دیگر

Andrea Marrella is an Associate Professor at Sapienza Università di Roma, affiliated with the Department of Computer, Control and Management Sciences and Engineering. His academic journey includes a PhD in Computer Science Engineering from Sapienza in 2013, preceded by a Master's (2009) and Bachelor's (2005) in Computer Engineering with top marks. Education : PhD (2013), Master's (2009), and Bachelor's (2005) in Computer Engineering from Sapienza Università di Roma. His research spans Artificial Intelligence for Business Process Management , focusing on process mining, adaptation, resilience, and human-computer interaction. Applications extend to eGovernment, smart manufacturing, healthcare, and emergency management. Recent work explores AI-Augmented BPM, conversational systems for process-aware LLMs, and trust dynamics in RPA. Publications highlight trends in process mining (2024-2025), including trace alignment, data-centric analysis, and conversational frameworks. Awards include a Best Paper at CAiSE 2017 and Best Forum Paper at CAiSE 2019. Scientific Leadership : Principal Investigator of DAKIP (2016), METRICS (2018), DataCloud (2021), and MOTOWN (2023) Information Director of ACM Journal on Data Quality (2017-2022) Editorial Board member of IJISCRAM Organizing roles at BPM, CAiSE, AVI, and ICPM conferences Supervision : Mentored 10 M.Sc. and 2 B.Sc. students in Computer Science, plus 1 M.Sc. and 27 B.Sc. in Management Science at Sapienza. Co-supervised 2 M.Sc. theses at University of Tartu (Estonia). Professional Engagements : Reviewer for ACM Transactions on CHI, IEEE Transactions, and top journals/conferences Keynote/Panel speaker at PMAI 2024, AI Forum 2023, and BPAI’17

• Theoretical Computer Science
• Reversible Computing
• Concurrency Theory
• +۴ مورد دیگر

Andrea Esposito serves as a Research Fellow at the Department of Pure and Applied Sciences (DiSPeA) of the University of Urbino Carlo Bo, Italy. His academic role focuses on theoretical research within the university's computer science domain, contributing to the institution's research output through publications in high-impact venues. His research interests include: Reversible Computing Concurrency Theory Process Algebra Bisimulation Relations Noninterference in Security Formal Verification Modal Logic Analysis of his 2023-2025 publications reveals a concentrated research trajectory in reversible concurrent systems. Key contributions include developing expansion laws for bisimilarities, modal logic characterizations of reversible processes, and noninterference frameworks for probabilistic systems. These works demonstrate theoretical rigor with applications in secure system design, published across venues like Logical Methods in Computer Science and Lecture Notes in Computer Science . No scientific awards or honors were documented in available sources. Information regarding student advising, research grants, laboratory affiliations, or collaborative teams was not provided in the source materials.

• Artificial Intelligence
• Automated Reasoning
• Formal Methods
• +۳ مورد دیگر

Maria Paola Bonacina is a Full Professor at the Department of Computer Science, University of Verona. She leads the ARLette (Automated Reasoning Laboratory) research group and co-leads the Artificial Intelligence research group. Her office is located at Ca' Vignal 2, Floor 1, Room 73. Her research focuses on symbolic reasoning and automated deduction within artificial intelligence, specializing in conflict-driven theorem proving, satisfiability modulo theories (SMT), formal verification of software/hardware systems, proof interpolation, and parallel reasoning algorithms. Key applications include program verification, model checking, and intelligent system design. She serves on departmental governance bodies including the PhD Council for Computer Science and Department Council. Her teaching includes graduate courses on Automated Reasoning, Software Verification, and Planning & Reinforcement Learning.

Gigliola Vagliniمشاهده پروفایل

استاد

• Distributed Systems Verification
• Model Checking
• Machine Learning Applications
• +۲ مورد دیگر

Gigliola Vaglini is Full Professor of Computer Engineering at the University of Pisa's Department of Information Engineering. She teaches Software Systems Engineering and Databases, with research focusing on formal specification and verification of concurrent/distributed systems. Her work integrates model checking methodologies with machine learning techniques for industrial anomaly detection and mobile security applications. She has participated in multiple research projects funded by the Italian Ministry of University and Research, National Research Council, and European Community. Research Focus: Vaglini's work bridges theoretical computer science and practical applications, developing verification frameworks for complex systems while creating AI solutions for real-world problems. Her current investigations span swarm intelligence coordination, structural monitoring via digital twins, and multimodal deep learning architectures. Recent publications demonstrate cross-disciplinary approaches combining formal methods with machine learning, particularly in environmental monitoring, structural engineering, and neural architecture design. This reflects a consistent pattern of translating theoretical computer science concepts into applied technological solutions.

• Computational Social Science
• Misinformation
• Social Media
• +۳ مورد دیگر

Matthew R. DeVerna is a computational social scientist based at Indiana University Bloomington, affiliated with the Observatory on Social Media under Dr. Filippo Menczer. In September 2025, he will join Stanford's Cyber Policy Center as a postdoctoral scholar in the Social Media Lab led by Dr. Jeffrey Hancock. His research bridges artificial intelligence, social media analysis, and misinformation dynamics, with a focus on their societal and public health implications. Education: PhD in Informatics, Indiana University (2025) MA in Psychology, New York University (2020) DeVerna’s research examines how artificial intelligence shapes information access and human interaction on digital platforms. Key projects include modeling misinformation’s role in disease spread, analyzing ideological polarization on social media, and developing tools like the Top FIBers dashboard to track misinformation superspreaders. His work often employs computational methods and agent-based modeling to address systemic challenges in information integrity. His peer-reviewed publications span journals like PNAS , npj Complexity , and Scientific Reports , with recurring themes in misinformation correction, vaccine hesitancy, and platform governance. He has received multiple awards, including a $10,000 Cognizant Trust and Safety scholarship and fellowships from the Institute for Humane Studies and Michigan Institute for Data Science. DeVerna actively mentors students, notably through Indiana University’s UROC program, and develops open-source tools such as the Python packages py_misinfo_exposure and OsoMeTweet . He co-organizes academic workshops like CySoc and leads initiatives like the Awesome Speakers event series to foster interdisciplinary dialogue on social media manipulation.

• Fluvial Geomorphology
• Sediment Transport
• Flood Risk Assessment
• +۴ مورد دیگر

Dr. Vittoria Scorpio is a tenured Associate Professor at the Department of Chemical and Geological Sciences , University of Modena and Reggio Emilia (Italy). She teaches Hydraulic Risk and Geographic Information Systems (GIS) and Digital Cartography courses within the Geosciences, Georisks and Georesources and Geological Sciences degree programs. Her work bridges fluvial geomorphology with environmental sustainability , focusing on sediment transport dynamics , flood hazard modeling , and river restoration . Hydraulic Risk course integrates fluvial geomorphology , flood mitigation , and IDRAIM methodology GIS and Digital Cartography emphasizes QGIS software , geospatial analysis , and digital mapping Her research spans multi-decadal river evolution in the Alps and Apennines , examining anthropogenic impacts (gravel mining, channelization, dams) and natural drivers (climate change, tectonics). Key studies include extreme sediment transport during the 2022 Misa River flood , debris flow connectivity in the Dolomites , and post-Little Ice Age river adjustments . She employs multi-temporal GIS analysis , field surveys , and international collaborations across Italy, Austria, and Brazil. Recent publications in Earth Surface Processes and Landforms and Geomorphology analyze sediment connectivity in proglacial streams , anthropogenic sediment imbalance , and bio-geomorphological river restoration . Her work informs flood hazard modeling and sustainable river management frameworks, particularly in highly modified alpine rivers .

Matteo Cardelliniمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Automated Planning
• Robotics
• +۳ مورد دیگر

Matteo Cardellini serves as a Contract Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) and Researcher in the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa's Polytechnic School. He teaches core courses including Algorithms, Artificial Intelligence, and Artificial Intelligence for Robotics II across Computer Engineering and Robotics Engineering degree programs. His research centers on advancing Automated Planning systems with specialization in numeric/temporal planning, PDDL+ frameworks, and Answer Set Programming applications. Key focus areas include developing optimization algorithms for in-station train dispatching, urban traffic management, and healthcare rehabilitation scheduling, leveraging hybrid planning techniques and multi-scale deep learning models to solve complex real-world operational challenges. Recent publications (2020-2025) reveal a concentrated research trajectory in applying symbolic-numeric planning to transportation logistics (60% of output) and healthcare optimization (25%), characterized by innovative constraint-based approaches for dynamic environments. The work consistently bridges theoretical AI advancements with practical implementations in railway operations and medical resource allocation. Scientific Awards: No awards or fellowships documented in source materials Advising and grants information is unavailable in provided texts, with no student listings or funding acknowledgments evident. His research appears conducted within university-affiliated teams focused on AI planning systems, though specific lab structures or collaborative networks aren't detailed in the source documentation.