جست‌وجوی استاد و پژوهشگر

• Software Engineering
• Deep Learning
• Human-Computer Interaction
• +۷ مورد دیگر

Prof. Dr. Chunyang Chen is a full professor in the Department of Computer Science at the Technical University of Munich (TUM) in Heilbronn, Germany, and an adjunct professor at Monash University, Australia. He is a core member of the Munich Data Science Institute, board member of Heilbronn Data Science Center, and fellow at Fortiss. His research spans Software Engineering, Deep Learning, and Human-Computer Interaction (HCI), focusing on AI/ML, NLP, and program analysis applications. PhD from Nanyang Technological University (NTU), Singapore His research explores three primary domains: AI-Driven Mobile App Development : Focused on requirement elicitation, UI design, code generation, and GUI testing using LLMs, NLP, and lightweight program analysis. Software Repository Mining : Involves library/API migration, collaborative editing, query reformulation, and thesaurus construction. Deep Learning Security : Examines robustness and security in mobile apps, including on-device model attacks, backdoor attacks, phishing attacks, and defense mechanisms. His recent publications highlight trends in LLM applications for software testing, bug replay, accessibility, and dataset construction. Awards include Best Paper Honorable Mention at CHI 2024, DECRA, ACM SIGSOFT Early Career Award, multiple Distinguished Paper Awards, and the Chinese Government Award for Outstanding Self-financed Students Abroad. PhD students: Shengcheng Yu, Yanqi Su, Mark Huasong Meng, Wenchao Gu, Zhen Tao, Kai Huang, Sidong Feng, Yujin Huang, Jian Gu Master/Bachelor students: Dustin Minh Duc Vu, Jason Siu, Ruiqi Dong, Minh Nguyen, An-Chieh Chang, Chao Wu, Yujin Huang, Ishan Joshi, Xinyan Li Chunyang Chen has supervised numerous students across institutions including TUM, Monash University, Chinese Academy of Sciences, ANU, and others. His teaching portfolio includes courses on Generative AI, software engineering, and programming foundations. He actively contributes to academic service as a guest editor, program committee member, and reviewer for top-tier conferences and journals.

Luca Demetrioمشاهده پروفایل

استادیار

• Adversarial Machine Learning
• Malware Detection
• Cybersecurity
• +۳ مورد دیگر

Luca Demetrio is an Assistant Professor at the University of Genoa, Italy, specializing in adversarial machine learning and cybersecurity. Previously, he was a Post-doctoral Researcher at the PRA Lab within the Department of Electrical and Electronic Engineering at the University of Cagliari. He holds bachelor's (2015), master's (2017), and Ph.D. (2021) degrees from the University of Genova, with his doctoral thesis focusing on formalizing evasion attacks against security detectors. His research emphasizes enhancing the robustness of machine learning models against adversarial attacks, particularly targeting malware detectors, SQL injection defenses, and Windows security systems. He leads the development of SecML Malware, a Python library for generating adversarial Windows malware, and contributes to the SecML framework. His work has been published in top-tier journals like ACM TOPS and IEEE TIFS. Key research interests include adversarial example generation, malware analysis, and cybersecurity defense mechanisms. He has explored query-efficient attacks on phishing detectors, certified adversarial robustness via randomized smoothing, and robust synthetic data-driven threat detection. His recent studies (2023–2025) address challenges in hardening machine learning models against evasion attacks, adversarial SQL injection countermeasures, and securing autonomous driving systems from adversarial reinforcement learning attacks.

Andrea Saracinoمشاهده پروفایل

دانشیار

• Cybersecurity
• Privacy-Preserving Technologies
• Machine Learning Applications
• +۳ مورد دیگر

Andrea Saracino is an Associate Professor specializing in cybersecurity, privacy-preserving technologies, and machine learning applications. His research focuses on enhancing security in IoT systems, smart homes, and mobile devices, with a particular emphasis on Android malware detection and usage control frameworks. He has received the IEEE TCCPS Early-Career Award 2023 for his contributions. Key projects include the SIFIS-Home initiative for privacy in globalized smart homes and the ACE framework for access control. His work addresses challenges in balancing privacy, utility, and explainability in machine learning models, particularly in image and tabular data analysis. He actively explores cybersecurity in emerging domains like software-defined vehicles and industrial control systems.

Li Liمشاهده پروفایل

استاد

• Mobile Software Engineering
• Intelligent Software Engineering
• Software Security
• +۶ مورد دیگر

Li Li is a Professor of Software Engineering at Beihang University , China. Previously, he served as an ARC DECRA Fellow and Senior Lecturer at Monash University , leading the SMart software Analysis and Trustworthy computing (SMAT) research lab at the Department of Software Systems and Cybersecurity. His academic journey includes a Ph.D. in Software Engineering from the University of Luxembourg (2016), supervised by IEEE Fellow Prof. Yves Le Traon and Dr. Jacques Klein. Research Interests Li's research focuses on Mobile Software Engineering (Mobile Security, Quality Assurance) and Intelligent Software Engineering (SE4AI, AI4SE). He applies static code analysis , dynamic program testing , and machine/deep learning to enhance software security and reliability. Key areas include Android API evolution, automated patch validation, and multi-language code analysis frameworks like Scalpel for Python. Scientific Recognition ARC DECRA Fellowship Rising SE Research Star Top-5 Most Impactful Early Career SE Researchers (2020, 2017) 5 Best/Distinguished Paper Awards across PLDI, WWW, ASE, MSR, and SANER Academic Contributions He has contributed to foundational Android analysis tools (e.g., AndroZoo++, DroidRA) and developed scalable systems for distributed program analysis (Seads). His work appears in top venues like ICSE, ESEC/FSE, ASE, ISSTA, POPL, and TSE.

• Information Visualization
• Visual Analytics
• Human-Computer Interaction
• +۸ مورد دیگر

Paolo Buono is Associate Professor at the Department of Computer Science, University of Bari Aldo Moro, Italy. He holds a PhD in Computer Science with specialization in Visual Data Analysis. His research focuses on Information Visualization, Visual Analytics, Human-Computer Interaction, and Mobile Applications. Co-founder and CEO of LARE (2010), a university spinoff providing real-time surgical support through audio-video telestration Member (since 2002) and computer science coordinator at METEA Research Center for environmental protection Visiting scientist at AVIZ (France), University of Maryland (USA), and Fraunhofer IPSI (Germany) His work spans multiple application domains including: Cultural Heritage through interactive exploration systems Healthcare with smart therapeutic devices Environmental Monitoring via CET system IoT-based Smart Interactive Experiences He has contributed to: Dynamic hypergraph visualization techniques End-User Development frameworks (EUDroid) Usability evaluation methodologies Mobile health applications As project leader, he has coordinated: EU-funded VisMaster Coordination Action (2008-2010) Italian Ministry-funded LOGIN project (2014-2015) Apulia Region environmental projects His professional engagements include: Co-chair roles at INTERACT, AVI, IS-EUD conferences Program committee participation in VIS series and HCI conferences Member of ACM, IEEE, and SIGCHI Italy

Barbara Carminatiمشاهده پروفایل

استاد

• Access Control
• Adaptable Collaboration
• Compatibility-driven
• +۱۶ مورد دیگر

Barbara Carminati is a Professor at the Department of Theoretical and Applied Science, University of Insubria, Italy. Her work focuses on security, privacy, and trust management in decentralized systems, particularly online social networks, IoT, and emerging technologies like blockchain and digital twins. She has contributed extensively to access control, risk assessment, and collaborative frameworks. Her research spans trust modeling , privacy-preserving mechanisms , and malware detection , with a strong emphasis on decentralized social networks and UAV security . She actively explores the application of blockchain for secure workflows and information sharing. Recent publications highlight her engagement with large language models for security optimization, IoT botnet detection , and metadata leakage analysis . Her work bridges theoretical foundations with practical implementations in cybersecurity, social network management, and edge computing. Contact: barbara.carminati@uninsubria.it

Maurizio Leottaمشاهده پروفایل

استادیار

• Software Engineering
• Test Automation
• Empirical Software Engineering
• +۷ مورد دیگر

Maurizio Leotta is an Assistant Professor in Computer Science at the University of Genova, Italy, where he has been employed since 2018. He is a member of the Department of Computer Science, Bioengineering, Robotics, and Systems Engineering (DIBRIS) within the School of Mathematical, Physical and Natural Sciences. Additionally, he serves on the School Council and the Department Board of DIBRIS. Dr. Leotta received his PhD in Computer Science from the University of Genova in 2015, with a thesis on Automated Web Testing under the supervision of Prof. Filippo Ricca. His doctoral work was revised by Prof. Massimiliano di Penta (Università del Sannio, Italy) and Prof. Ali Mesbah (University of British Columbia, Canada). Before his academic career, he worked as an IT Technician in various companies and participated in research and industrial projects funded by organizations such as Finmeccanica S.p.A. and the Italian Space Agency. Dr. Leotta's primary research focuses on Software Engineering, with particular emphasis on Test Automation, which is his main research topic. He collaborates with Prof. Paolo Tonella from USI, Switzerland on this area. His other significant research interests include Empirical Software Engineering, Requirements Engineering, Business Process Modelling, and Model-Driven Software Engineering. His work often addresses practical challenges in web and mobile application testing, with a growing interest in applying AI and gamification techniques to improve software testing processes. His recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional software testing methodologies, particularly in end-to-end web testing. He has made significant contributions to improving test robustness, addressing flakiness in test execution, and developing tools for better test maintenance. His work also shows increasing interest in gamification approaches to engage developers and students in software testing activities, as well as applications of large language models to enhance test automation. Dr. Leotta has received multiple prestigious awards for his research, including: Best Paper Award at ICST 2025 (Short Papers, Vision and Emerging Results) Distinguished Paper Award at ICST 2023 (Industry Papers) Best Paper Award at QUATIC 2022 (Full Papers) Best Paper Award at ICST 2022 (Demo and Testing Tool Papers) Best Paper Award at QUATIC 2020 (Full Papers) Best Student Paper Award at ICWE 2016 (Full Papers) Dr. Leotta has advised numerous graduate students, including three PhD candidates who have completed their degrees (Andrea Fasciglione in 2024, Dario Olianas in 2023, and Diego Clerissi in 2020). He currently supervises multiple Master's students working on topics related to software testing, web accessibility, and AI applications in software engineering. He has also served as a postdoctoral advisor for researchers including Diego Clerissi and Dario Olianas. Beyond advising, Dr. Leotta has secured research funding through collaborations with industry partners and has been involved in multiple research projects focused on software testing and verification. He co-directs the Software Engineering for Healthcare (SEH) Laboratory, which has been partially supported by Janssen Italia (previously by Actelion Pharmaceuticals Italia). The lab focuses on applying software engineering techniques to healthcare applications, particularly in the areas of wearable technology for patient monitoring and medical data analysis. Dr. Leotta is also active in the Gamify research community, organizing workshops on gamification in software development, verification, and validation.

Luca Verderameمشاهده پروفایل

دانشیار

• Mobile Security
• Android Security
• IoT Security
• +۳ مورد دیگر

Luca Verderame is an Associate Professor in the Department of Computer Science, Bioengineering, Robotics, and Systems Engineering (DIBRIS) at the University of Genoa. His academic role includes teaching advanced courses such as Mobile Security, Mobile Programming, and Mobile Programming Module 2 at both undergraduate and master's levels. Research focuses on cybersecurity, particularly in mobile ecosystems, IoT firmware integrity, and application security testing tools. Key research contributions include MarvelHideDroid (2025) for Android data anonymization, kernel-level obfuscation analysis (2024), and SEBASTIAn, a cross-platform security testing tool (2023). His work bridges theoretical cybersecurity principles with practical implementations in embedded systems and cloud environments. Contact: luca.verderame@unige.it

Luca Arditoمشاهده پروفایل

دانشیار

• Software Engineering
• Mobile Computing
• Gamification in Education
• +۳ مورد دیگر

Luca Ardito is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) of Politecnico di Torino. His research focuses on software engineering methodologies, mobile computing, and gamification strategies in education and testing. His work integrates technical domains such as Android development, GUI testing automation, energy efficiency in software systems, and IoT security. Ardito is a core member of the SoftEng research group, contributing to projects like SIFIS-home for privacy-preserving smart home systems. Research Interests: Advanced GUI testing techniques for Android and web applications Application of gamification in software education and quality assurance Energy-aware software development and green computing practices Certification frameworks for IoT device firmware and cybersecurity His recent work emphasizes empirical studies on gamification in UML modeling education, Kotlin adoption in Android ecosystems, and innovative approaches to firmware certification. Ardito has pioneered tools like Umlegend for gamified UML learning and Bipmin for BPMN education. Grants & Collaborations: Leading multidisciplinary projects combining computer science with agriculture (e.g., UAV-based hazelnut tree characterization) Active in industry partnerships for mobile testing frameworks (e.g., TOGGLE library) Labs & Teams: Core contributor to Politecnico's SoftEng Research Group , collaborating on projects like SIFIS-home (FP7/ERC-funded).

Rida Ghafoorمشاهده پروفایل

استادیار

• Machine Learning
• Medical Artificial Intelligence
• Security Systems
• +۳ مورد دیگر

Rida Ghafoor is an active PhD student in Smart Computing at the University of Florence, supervised by Professor Marco Gori. She is concurrently an Assistant Professor at the National University of Computer and Emerging Sciences (FAST), Faisalabad, Pakistan, currently on study leave to pursue her doctoral research. Her academic journey includes a bachelor’s and master’s in Software Engineering from the University of Engineering and Technology, Taxila, Pakistan, with her master’s research conducted in collaboration with the University of East London. Education: PhD in Smart Computing, University of Florence (2020–present) MSc in Software Engineering, University of Engineering and Technology, Taxila (2015) BSc in Software Engineering, University of Engineering and Technology, Taxila (2013) Her research centers on the foundations of machine learning, aiming to develop robust modeling frameworks with applications in medical science and security systems. She is particularly interested in interdisciplinary approaches that integrate mathematics with AI to solve real-world problems. Her past work has explored intelligent mobile applications and machine learning models for dementia patient analysis. The recent articles reflect a strong focus on applied machine learning, especially in healthcare and software security. Her work bridges theoretical modeling with practical implementation, evident in publications ranging from Android-based intelligent systems to clinical data analysis. The interdisciplinary nature of her research is supported by collaborations across institutions and domains. Scientific Awards: 1st position in Security based Software Projects at Youth Festival Punjab, Pakistan Rida Ghafoor has supervised multiple student projects in machine learning during her tenure at FAST-NUCES, Faisalabad. While specific grants are not mentioned, her full scholarship during her master’s and active PhD enrollment suggest institutional funding support. Her academic trajectory demonstrates a commitment to both teaching and advanced research in artificial intelligence. Rida is affiliated with the Siena Artificial Intelligence Lab (SAILab), where her current PhD research is being conducted under the supervision of Professor Marco Gori. This lab serves as the primary environment for her ongoing work in smart computing and foundational machine learning.

• Computer Science
• Security
• Distributed Systems
• +۳ مورد دیگر

Giuseppe Cattaneo is an Associate Professor at the Department of Computer Science , University of Salerno. His research spans multiple domains including Computer Security Distributed Systems Bioinformatics Mobile Communication Security Algorithm Engineering His work has produced significant contributions in cryptographic file systems, secure mobile messaging, and Hadoop-based bioinformatics solutions. Key research trends include Security protocols for mobile environments Scalable genomic data analysis Dynamic graph algorithm optimization Digital forensic countermeasures He has developed frameworks like GRACE for cryptographic visualization and FASTdoop for bioinformatics data processing. Professional activities involve Collaboration with international researchers Development of secure communication protocols Participation in algorithm engineering studies His recent 2021 publications focus on medical data analysis and thyroid cancer outcome prediction.

• Human-Centered AI
• Virtual and Augmented Reality
• Social Robotics
• +۶ مورد دیگر

Giuliana VITIELLO is a Full Professor at the Department of Computer Science, University of Salerno. Her research focuses on Human-Centered AI, Social Robotics, Virtual/Augmented Reality, and Gender-Inclusive Language Technology. She has contributed to the design of AI-based tools for institutional communication, therapeutic robotics, and immersive educational environments. Current affiliation: University of Salerno Email: gvitiello@unisa.it Office: Fisciano Campus, Building F2, Room 083 Her recent publications highlight trends in: AI ethics and inclusivity Robot-assisted cognitive therapy Metaverse collaboration tools IoT-driven healthcare systems Immersive educational applications

Giorgio Fumeraمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Video Surveillance
• +۳ مورد دیگر

Giorgio Fumera is an Associate Professor of Computer Engineering at the University of Cagliari. His research focuses on statistical pattern recognition, machine learning, and their applications in video surveillance, particularly in person re-identification, adversarial robustness, and uncertainty quantification. He has authored over 100 papers in leading journals and conferences, and serves as an associate editor for Pattern Recognition and Pattern Analysis and Applications . He is a member of IEEE and IAPR. His work explores cutting-edge topics such as synthetic data for surveillance systems, adversarial training defense mechanisms, and Bayesian inference for crowd counting. Recent contributions include studies on the robustness of machine learning models against adversarial attacks and the application of neural networks in microwave medical imaging. His research also emphasizes practical applications in cybersecurity, medical diagnostics, and ethical AI systems like the IMMAGINA project. Fumera’s publications span domains like ensemble methods, human-in-the-loop systems, and sparse learning. Despite extensive contributions, no specific awards or grants are explicitly mentioned in the provided materials. His research team actively collaborates on interdisciplinary projects, blending computer vision, medical imaging, and trustworthy AI principles.

Angelo Sotgiuمشاهده پروفایل

استادیار

• Machine Learning Security
• Adversarial Machine Learning
• Cybersecurity
• +۳ مورد دیگر

Angelo Sotgiu is an Assistant Professor at the University of Cagliari's Department of Electronic and Computer Engineering. His research focuses on machine learning security, adversarial attacks, and malware detection. He holds an MSc in Telecommunication Engineering and a PhD in Electronic and Computer Engineering from the University of Cagliari. During his PhD (2019–2023), he conducted a visiting research period at CISPA Helmholtz Center for Information Security (Saarbrücken, Germany). He has worked as a Research Collaborator for the National Interuniversity Consortium for Informatics (CINI) from 2022–2023. His work emphasizes adversarial robustness, AI security, and practical defenses against attacks on machine learning systems. Key contributions include the ImageNet-Patch dataset for adversarial patch benchmarking, the secml Python library for secure ML, and frameworks like Fader for fast adversarial example rejection. His research bridges theoretical advancements with real-world cybersecurity applications.

Mariano Ceccatoمشاهده پروفایل

دانشیار

• Security Testing
• Penetration Testing
• Code Hardening
• +۵ مورد دیگر

Mariano Ceccato is an Associate Professor in the Department of Computer Science at the University of Verona, Italy. With a PhD in Computer Science from the University of Trento (2006), he has led numerous publicly funded and industrial research projects. His expertise includes security testing, penetration testing, code hardening, and empirical studies. Principal Investigator in multiple research initiatives Visiting Research Scientist at the University of Luxembourg Author/co-author of over 100 peer-reviewed papers Research Focus His work spans Android security, Ethereum smart contracts, REST APIs, and software protection techniques. Key contributions include: Security testing frameworks using reinforcement learning Advanced static analysis for Ethereum bytecode Novel obfuscation strategies for Java/Android Empirical studies on security report usability Comparative analysis of malware detection techniques Scientific Contributions He has received multiple awards including the Best Paper at IEEE ICST 2022, Best Research Paper at IEEE/ACM ICSE 2023, and ACM Distinguished Paper awards.