جست‌وجوی استاد و پژوهشگر

• Software Engineering
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Fabio Palomba is an Associate Professor at the Department of Computer Science , University of Salerno, Italy. He earned a European PhD in Management & Information Technology (2017), funded by University of Salerno and University of Molise, under advisor Prof. Andrea De Lucia. His research spans software maintenance and evolution , empirical software engineering , and ML systems quality . Recipient of IEEE Computer Society Best PhD Thesis Award (2017) Multiple Distinguished Paper Awards from ACM/SIGSOFT and IEEE/TCSE Recipient of prestigious SNSF Ambizione grant (2019) and IEEE Rising Star Award (2023) His work investigates fairness-aware practices in ML , technical debt in AI systems , and LLM applications in software engineering . Recent studies focus on automated requirements generation via RECOVER, quantum software engineering , and socio-technical community smells in ML-enabled systems, with empirical analyses across large datasets. Key editorial roles include Elsevier's Information and Software Technology Journal (2022-), Springer's Empirical Software Engineering Journal (2021-), and IEEE Transactions on Software Engineering (2020-). He has served as program co-chair for SANER 2024 , ICPC 2021 , and multiple conference tracks. 16 Distinguished Reviewer Awards for his refereeing work Co-authored 80+ journal papers , 100+ conference papers , and advised 300+ theses

Giovanna Guerriniمشاهده پروفایل

دانشیار

• Data Management
• Large Scale Data Management
• Semantic Data Management
• +۱۵ مورد دیگر

Giovanna Guerrini is an Associate Professor in the Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS) at the University of Genoa, Italy. She is actively involved in research, teaching, and academic service, with leadership roles in major conferences such as EDBT (Executive Board Member and Treasurer), SOFSEM (Track Chair), and UMAP (Workshop Chair). Her research interests include: Data Management Large Scale and Semantic Data Management Approximate and Adaptive Query Processing Linked Data and Ontology Matching Graph Matching and Geospatial Ontologies Spatio-Temporal Data and Location Inference Computer Science Education and Computational Thinking Her recent publications show a growing focus on computer science education, particularly in using gamified and extended reality environments, Sonic Pi for teaching concurrency, and AI-driven tools for enhancing computational thinking. This reflects a shift toward pedagogical innovation and student-centered learning methodologies. She has been recognized through active participation in top-tier program committees (SIGMOD, ISWC, ICDE) and organizing key workshops and schools (EDBT School 2017, APCSE at UMAP). No formal scientific awards are listed in the provided text. She advises multiple PhD students, both current and past, and contributes to academic grants and collaborative projects, particularly in database education and data science initiatives. She is affiliated with research groups including the DaMA Research Group, Data Science and Engineering Research Program, Big Data Interest Group UniGe, and CINI Big Data Research Lab.

Stefano CALZAVARAمشاهده پروفایل

دانشیار

• Web Security
• Machine Learning
• Formal Methods
• +۴ مورد دیگر

Stefano CALZAVARA is an Associate Professor at the Department of Environmental Sciences, Computer Science and Statistics, Ca' Foscari University of Venice. His expertise spans web security, machine learning, and formal methods. He holds a Ph.D. in Computer Science from his alma mater, following a B.A. and M.A. in the same field. His research focuses on secure web protocols, vulnerability detection, and adversarial machine learning. He teaches courses like Web Security and Computability, and contributes to the Research Institute for Complexity Communications. Notable work includes verifying tree ensembles against evasion attacks and analyzing web session security at scale. Education: Ph.D. Computer Science, Ca' Foscari University of Venice (2010-2012) M.A. Computer Science, Ca' Foscari University of Venice (2007-2009) B.A. Computer Science, Ca' Foscari University of Venice (2004-2007) Research Interests: Web security, including session integrity and content policies Machine learning robustness and certification Formal methods for protocol verification Adversarial attacks and defenses Recent Articles Trends: His recent work emphasizes securing machine learning models against adversarial attacks, formal verification of web protocols, and empirical analysis of web storage vulnerabilities. Publications appear in top venues like ACM CCS and IEEE Security Symposiums. Awards: None explicitly listed. Advising & Grants: Postdoctoral research at Ca' Foscari (2013-2015) and Saarland University (2015). Active in teaching and ethical research governance as an Ethics Commission member. Labs/Teams: Part of the Research Institute for Complexity Communications, focusing on interdisciplinary security challenges.

Salvatore ORLANDOمشاهده پروفایل

استاد

• Computer Science
• Machine Learning
• Data Mining
• +۴ مورد دیگر

Salvatore Orlando is a Full Professor and Director of the Department of Environmental Sciences, Computer Science and Statistics at Ca' Foscari University of Venice. He holds academic roles including membership in the University Scientific Instrumentation Service Center (CSA) Management Committee and the Academic Senate. His research focuses on machine learning, information retrieval, and data mining, with notable contributions to learning-to-rank algorithms, decision tree ensembles, and adversarial machine learning. Key areas include efficient algorithms for large-scale systems, model interpretability, and fairness in AI. Orlando’s work bridges theoretical advancements with practical applications in database technology and cybersecurity. His recent publications emphasize optimizing ranking models, enhancing algorithm resilience, and addressing ethical considerations in AI systems. He is actively involved in organizing international conferences and serves on program committees, further contributing to the academic community.

Markus Zankerمشاهده پروفایل

استاد

• Information Systems
• Knowledge-based Decision Support Systems
• Personalization
• +۳ مورد دیگر

Markus Zanker is a full professor at the Faculty of Computer Science , Free University of Bozen-Bolzano (Italy), where he previously served as vice dean for studies and director for study programmes. He held associate professorship at Alpen-Adria-Universitaet Klagenfurt, Austria (2011-2016). Research Focus : Knowledge-based decision support systems, personalized information filtering/retrieval, product recommendation, conversational sales advisor systems, and product configurators Current Projects : Causal discovery in recommender systems, medical recommendation systems (insulin dosing, drug combinations), explainable AI for tourism and news recommendation The 15 most recent publications (2016-2025) cover topics including: Deep reinforcement learning for medical applications Causal modeling in tourism and online decision-making Explainable recommendation frameworks Session-based news and video recommendations Evaluation of open-source recommendation libraries His work also explores user interaction patterns through studies on bimodal rating statistics, collaborative explanations, and proactive recommendation engagement.

• Game Theory
• Multi-Agent Reinforcement Learning
• Cooperative Multi-Agent Systems
• +۳ مورد دیگر

Karl Tuyls is a Professor of Computer Science at the University of Liverpool's School of Electrical Engineering, Electronics and Computer Science, with additional research affiliation at DeepMind. His work bridges theoretical game theory and practical multi-agent reinforcement learning systems. His research focuses on cooperative multi-agent systems, where he pioneers value decomposition techniques and emergent communication protocols. Key contributions include frameworks for handling team reward structures, analyzing inequity aversion in social dilemmas, and developing differentiable game mechanics that separate potential and Hamiltonian game dynamics. Analysis of his 2017-2019 publications reveals dominant trends in cooperative multi-agent reinforcement learning, particularly value decomposition architectures and emergent communication systems. These works span artificial intelligence, game theory, and behavioral economics, with specific focus on fair reward allocation, relational inductive biases in deep learning, and open-source framework development for experimental validation. Professor Tuyls leads collaborative research between the University of Liverpool and DeepMind, directing projects on multi-agent coordination and social dilemma modeling through frameworks like OpenSpiel that enable reproducible experimentation in complex game-theoretic scenarios.

Leonardo Impettمشاهده پروفایل

استادیار

• Digital Humanities
• Computational Humanities
• Computer Vision
• +۶ مورد دیگر

Leonardo Impett serves as Assistant Professor in Digital Humanities at the University of Cambridge's Faculty of English and Bye-Fellow in Digital Humanities at Selwyn College, Cambridge. He also leads a research group at the Bibliotheca Hertziana. Previously, he was Assistant Professor of Computer Science at Durham University and Digital Humanities Scientist at the Bibliotheca Hertziana - Max Planck Institute for Art History in Rome. His research uniquely bridges artificial intelligence and art history, focusing specifically on bias and visual ideology in AI systems from an art historical perspective. With a background in information engineering and machine learning, he combines technical expertise with deep humanities knowledge to develop novel approaches for analyzing visual culture through computational methods. His recent publications reveal a strong trend toward interdisciplinary work connecting computer vision with art historical analysis, particularly examining how AI systems interpret and potentially bias visual cultural heritage. His research spans technical AI development, art historical analysis, and critical examination of digital methodologies in cultural institutions. Digital Humanities Fellow at Villa I Tatti – Harvard University Center for Italian Renaissance Studies (2018) Scientific Assistant/Scientist at Bibliotheca Hertziana (2018-2020) PhD in Computer Vision for Art History at EPFL Impett actively collaborates with major cultural institutions including the Liverpool Biennial, Royal Opera House, and Whitney Museum of American Art, applying machine learning to practical challenges in arts and culture. His work demonstrates how technical AI research can be meaningfully integrated with humanities scholarship to produce insights valuable to both domains.

Alessandro Checcoمشاهده پروفایل

استادیار

• Crowdsourcing
• Human Computation
• Distributed Systems
• +۷ مورد دیگر

Alessandro Checco is an Assistant Professor in the Computer Science Department at University of Rome La Sapienza. His research focuses on crowdsourcing, distributed systems, and privacy-preserving technologies, bridging theoretical computer science with practical applications that consider human factors in technological systems. He has established himself as a significant contributor to the field of human computation and privacy-aware systems. His educational background includes: 2020: Fellowship of Higher Education from The University of Sheffield, Higher Education Academy 2015: Ph.D. in Mathematics from Hamilton Institute (Design of decentralised algorithms applied to channel/code selection and convex optimisation for throughput fairness of 802.11 networks) 2010: M.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) 2009: Erasmus Scholarship at Universiteit Gent, Department of Telecommunications 2007: B.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) Checco's research spans multiple areas at the intersection of computer science and social implications of technology. He is particularly interested in Crowdsourcing for Human Computation, Distributed Private Recommender Systems, Information Retrieval, Data Privacy, Distributed Systems, User Data Obfuscation in Web Systems, Societal and Economic Analysis of Online Work, Crowd Workers Unionisation, and Algorithmic Bias. His work often examines how technological systems can be designed to respect user privacy while maintaining functionality, and how crowd work can be structured to be more equitable for workers. His recent publications demonstrate a clear evolution in research focus, beginning with foundational work in wireless networks and distributed algorithms, then shifting toward human computation and privacy-preserving systems. His most recent work increasingly addresses the societal implications of crowd work, including investigations into crowd worker unionization and cooperative models. Several publications examine gender bias in algorithmic systems, reflecting growing attention to fairness and ethical considerations in his field. Among his notable achievements: All That Glitters is Gold-An Attack Scheme on Gold Questions in Crowdsourcing (Best Paper Award) Checco has secured significant research funding and led important projects including the H2020-funded FashionBrain project as Research Director and the EPSRC-funded BetterCrowd project as Research Associate. His work on the FashionBrain project demonstrates his ability to lead large-scale, interdisciplinary research initiatives. He has also received the Technology Innovation Development Award (TIDA) from Science Foundation Ireland. His research has practical applications across multiple domains including recommendation systems (BLC: Private Matrix Factorization Recommenders), peer review assistance using AI, smart farming technologies, and cooperative models for crowd workers (CrowdCO-OP). He has developed frameworks for understanding worker behavior in crowdsourcing platforms and created methods for improving quality control in human computation systems.

Gabriele Tolomeiمشاهده پروفایل

دانشیار

• Machine Learning
• Explainable AI
• Adversarial Machine Learning
• +۵ مورد دیگر

Gabriele Tolomei is an Associate Professor of Computer Science at Sapienza University of Rome. He leads the HERCOLE Lab (Human-Explainable, Robust, and Collaborative Learning) and focuses on advancing AI systems that are interpretable, robust, and decentralized. His research spans machine learning, computer security, and adversarial learning. PhD in Computer Science, Ca' Foscari University of Venice (2011) MSc in Computer Science, University of Pisa (2005) BSc in Computer Science, University of Pisa (2002) His research interests are centered on Explainable AI , Robust Machine Learning , and Collaborative Learning . He has contributed to areas such as counterfactual explanations for graph neural networks, community membership privacy, and fairness in graph algorithms. His work intersects Web Search and Mining with Computational Advertising , emphasizing user engagement and post-click satisfaction. He teaches courses like Operating Systems for BSc Computer Science and Big Data Computing for MSc Computer Science. Current PhD students under his supervision include Edoardo Gabrielli, Fabiano Veglianti, Flavio Giorgi, Matteo Silvestri, and Vittoria Vineis. The HERCOLE Lab, established in 2021, promotes interdisciplinary research on human-centered AI, adversarial resilience, and edge computing. Collaborators include Fabrizio Silvestri (Full Professor), Federico Siciliano (Postdoctoral Researcher), and Ziheng Chen (Research Scientist at Walmart Labs).

• Philosophy of Science
• Logic
• Philosophy of Language
• +۵ مورد دیگر

Floris Mara is a Fixed-term Researcher in the Faculty of Philosophy at Vita-Salute San Raffaele University, Milan, specializing in Logic and Philosophy of Science (PHIL-02/A). Her interdisciplinary work bridges theoretical philosophy with practical applications in healthcare communication, gender studies, and cognitive science. She teaches Master's-level courses including Philosophical Skills for Organizations, Teaching Methodologies, and Bibliographic Training across Philosophy and Arts programs. Research Focus: Mara investigates narrative structures in historical interpretation, doctor-patient communication breakdowns using philosophy of language tools, and gender-fair language policies in Italian. Her work on bodily representations in anorexia nervosa and scientific disinformation demonstrates deep engagement with medical humanities and public understanding of science. She employs experimental methodologies in infant cognition studies while analyzing contemporary issues like AI gender bias and pancreatic cancer patient engagement. Publication Trends: Her 2022-2025 output reveals three converging trajectories: (1) Medical-philosophical interfaces examining communication in oncology and eating disorders; (2) Gender studies analyzing linguistic policies and bias in AI; (3) Epistemological investigations into scientific disinformation and narrative knowledge. This triad reflects her commitment to applying philosophical rigor to urgent societal challenges through empirical and theoretical lenses. Scientific Engagement: As a SIFA Directive Committee member (2023-2025) and SWIP Italia member, she organizes academic events including the 2025 Italian Society for Analytic Philosophy conference. Her public outreach features the Gender Lunch Seminars collaboration between Philosophy and Psychology faculties, and the "Segnala(bufa)la!" initiative training school students to identify scientific fake news. Professional Activities: Mara co-organizes public events addressing testimonial injustice (Corriere.it), participates in school partnerships like MEETme@School, and contributes to summer schools on philosophical conflicts. Her work with Liceo Cavour on "Parole in punta di piedi" demonstrates commitment to bringing philosophical inquiry into secondary education through practical PCTO programs.

Aris Anagnostopoulosمشاهده پروفایل

استاد

• Stochastic Analysis of Dynamic Processes
• Modeling and Mining in Social Networks
• Data Mining and Algorithms for the WWW
• +۳ مورد دیگر

Aris Anagnostopoulos is a Professor at the Department of Computer, Control, and Management Engineering (Dipartimento di Ingegneria Informatica, Automatica, e Gestionale) at Sapienza University of Rome since April 2012. His academic journey includes a Marie-Curie fellowship at Sapienza University and a postdoctoral position at Yahoo! Research in Santa Clara, CA. His educational background includes: Ph.D. in Computer Science, Brown University, Providence, RI Sc.M. in Applied Mathematics, Brown University, Providence, RI Sc.M. in Computer Science, Brown University, Providence, RI Diploma in Computer Engineering and Informatics, University of Patras, Patras, Greece Professor Anagnostopoulos's research focuses on the design and analysis of algorithms with applications in data mining and data science. His work spans stochastic analysis of dynamic processes, social network modeling and mining, WWW algorithms, randomized and approximation algorithms, information retrieval, and information security. His research has evolved to address contemporary challenges in federated learning, knowledge graphs, and ethical AI considerations in recommendation systems. His recent publications demonstrate a strong trend toward addressing real-world applications of data science and machine learning, particularly in healthcare, social media analysis, and privacy-preserving techniques. His work shows increasing interdisciplinary collaboration, especially with medical researchers, while maintaining strong theoretical foundations in algorithm design. Among his notable scientific awards are: Google Focused Research Award (1 of 6 PIs), 1M USD Junior Fellow, School for Advanced Studies, Sapienza University of Rome Personal research grant, Swedish Research Foundation, 200K euro, 2011 (declined) Best Poster Award, 4th International Conference on Web Search and Data Mining (WSDM 2011) Marie Curie International Incoming Fellowship, 160K euro, 2010 Paris Kanellakis Fellowship, Brown University Runner Up, Best Paper Award, 14th International World Wide Web Conference 2005 (WWW 2005) Professor Anagnostopoulos serves as the academic responsible for mobility (RAM) for the Data Science master's program and has developed comprehensive teaching materials for data science education. He teaches courses including Social Networks and Online Markets, Algorithmic Methods of Data Mining, Data Mining, and Algorithm Design. His teaching approach emphasizes both theoretical foundations and practical applications, with extensive use of AWS and Python-based tools to prepare students for industry certification.

Daniele Proverbioمشاهده پروفایل

پژوهشگر ارشد

• Complex Systems
• Mathematical Biology
• Mathematical Epidemiology
• +۷ مورد دیگر

Daniele Proverbio is a Research Fellow in the Department of Industrial Engineering at the University of Trento, where he teaches the "Mathematical epidemiology - modelling, parametrization and applications" course for PhD students. Previously, he was a Postdoc at the University of Luxembourg and contributed as a modeling consultant to the Luxembourg National COVID-19 taskforce. His educational background includes: PhD in Sciences de l'Ingénieurs with Specialization in Computational Sciences from the University of Luxembourg Laurea Magistrale in Physics of Complex Systems (110/110 cum laude) from the University of Turin and University of Western Piedmont Master in Business and Administration from Collège des Ingénieurs (Turin, Munich, Paris) Excellence school diploma from Scuola di Studi Superiori di Torino "F. Rossi" Daniele's research focuses on the robustness and resilience of complex systems, with applications spanning mathematical epidemiology, biological pathways, and neural networks. His work integrates models with empirical data using approaches from network science, multi-agent systems, and information theory. He has particular interest in critical transitions in natural systems and the ethics of AI, contributing to the field through both theoretical frameworks and practical applications in public health and biomedical contexts. His recent publications demonstrate a strong interdisciplinary approach, bridging computer science, biology, and social sciences. The research shows increasing focus on AI ethics, game-theoretic approaches to complex systems, and applications of mathematical modeling to epidemiology and biological systems. Notably, his work on Physarum polycephalum (slime mold) and critical transitions reveals innovative approaches to understanding complex adaptive behaviors. His scientific recognition includes: Winner of Best Thesis Award 2023 (University of Luxembourg) Winner of ESOF Travel Grant 2022 Winner of DESCOM Science Writing Competition 2021 Top 10 in COVID-19 Lung CT Lesion Segmentation Challenge 2020 Best presentation award at Euron + PhD Days conference 2019 International finalist at PLANKS 2017 Daniele serves as a reviewer for prestigious journals including PNAS and the Journal of the Royal Society B. He is a co-founder of Swarm Ethics and member of the editorial board of House of Ethics, focusing on actuable ethics for complex systems. His consulting work includes advising startups S-eye-S and Farmelody, and he has been actively involved in science communication through platforms like Instagram. As a member of multiple scientific societies including the Complex Systems Society and Network Science Society, Daniele contributes to the broader academic community through conference organization and editorial roles. He co-organized international workshops and serves on program committees for major conferences in complex networks and system theory.

• Labor Law
• International Labor Law
• EU Labor Law
• +۵ مورد دیگر

Marco Tufo is a Research Fellow in Labor Law at the Department of Law, University of Urbino Carlo Bo, where he teaches International and EU Labor Law and Immigration and International Protection Law. He holds a National Scientific Qualification for Associate Professor (2025) and serves as Contract Professor of Trade Union Law at the University of Siena. PhD in Labor Relations, University of Modena and Reggio Emilia - Marco Biagi Foundation (2017) LL.M. in Labor Law with honors, University of Siena (2013) Visiting Doctoral Candidate, School of Law, University of Warwick (2016) His research focuses on evolving labor paradigms including digital remote work, crowdwork regulation, international labor standards, and wage regulation mechanisms. His work bridges theoretical legal frameworks with practical implications for contemporary labor markets, particularly examining how traditional labor protections adapt to platform-based and transnational work arrangements. Recent publications demonstrate particular expertise in legal referral techniques, collective interest representation in digital labor, and the judicial application of international labor norms. National Scientific Qualification for Associate Professor (12/B2 - Labor Law), 2025 Tufo has participated in nationally and internationally significant research projects while maintaining an active legal practice. Since 2017 he has worked as an attorney specializing in Labor and Social Security Law (since 2025). His dual academic-practitioner perspective informs both his scholarly contributions and teaching methodology, particularly regarding the practical implementation of labor regulations in complex employment scenarios.