جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Generative Artificial Intelligence
• Computational Models of Human Behavior
• +۳ مورد دیگر

Mirco Musolesi is a Full Professor of Computer Science at both University College London (UCL) and the University of Bologna. He leads the Machine Intelligence Lab at UCL, part of the UCL Centre for Artificial Intelligence. His research focuses on Machine Learning, Generative AI, and computational models of human behavior, with applications in ubiquitous systems and societal impacts of AI. Education: PhD in Computer Science from UCL (2007) and Laurea in Electronic Engineering from the University of Bologna (2002). Previous roles include positions at the University of Birmingham, Dartmouth College, and the Alan Turing Institute. Research spans multi-agent systems, reinforcement learning, and AI ethics. Notable awards include ACM UbiComp 10-Year Impact Award (2020/2024) and the NetExplorateur/UNESCO Top 100 Innovations (2011). His work on EmotionSense and CenceMe applications has been recognized with Test-of-Time awards. Recent publications (2024-2025) address moral alignment in AI agents, multi-agent environmental policy simulations, and creativity in LLMs. His labs explore AI-driven solutions for urban systems and ethical decision-making frameworks.

• 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.

Rocco OLIVETOمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Prof. Rocco OLIVETO is a Full Professor at the University of Molise, affiliated with the School of Biosciences and Territory. His research spans software engineering, artificial intelligence, cybersecurity, and healthcare technology. He focuses on empirical studies of developer practices, AI-driven code analysis, vulnerability detection in smart contracts, and human-centric computing. His work also addresses challenges in game development, mobile app optimization, and wearable health monitoring systems. Notable research areas include code readability assessment, machine learning applications in healthcare diagnostics, and the effectiveness of AI tools like GitHub Copilot. He has contributed to projects like QualAI (continuous quality improvement for AI systems) and 2Vita-B (cognitive and physical rehabilitation systems). His empirical studies often bridge academic research with real-world developer workflows, emphasizing practical applicability. Prof. Oliveto's recent work explores topics such as automated gameplay analysis for game debugging, detection of engagement issues in video games, and robust methods for identifying security vulnerabilities. He has also investigated Dockerfile quality, developer frustration metrics, and the ethical implications of AI in administrative document simplification.

• Deep Learning
• Medical Image Analysis
• Biomedical Engineering
• +۲ مورد دیگر

Maria Chiara Fiorentino is a Research Fellow at the Department of Information Engineering, Polytechnic University of Marche, Italy. Her work focuses on applying deep learning techniques to medical image analysis, particularly in ultrasound, MRI, and CT imaging. Education Master’s in Biomedical Engineering, Università Politecnica delle Marche (Honors) Ph.D. in Information Engineering, Università Politecnica delle Marche (Laude) Research Interests: Dr. Fiorentino specializes in deep learning for medical imaging, with applications in diagnosing neurodegenerative diseases like Parkinson’s, cardiovascular conditions, and musculoskeletal disorders. Her recent work includes federated learning for fetal ultrasound analysis, AI-driven vocal fold pose estimation, and domain adaptation in MRI segmentation. Scientific Awards: Paolo Marziali Thesis Prize for her Master’s research Gruppo Nazionale di Bioingegneria award for her Ph.D. thesis Publications: Dr. Fiorentino’s work spans fetal brain image synthesis, zero-shot learning robustness, and machine learning for catheterization management and stenosis detection.

• Flexible spacecraft
• Flight control systems
• Robotic systems
• +۷ مورد دیگر

Elisa Capello is a Full Professor of Flight Mechanics at Politecnico di Torino, Department of Mechanical and Aerospace Engineering (DIMEAS). She serves as Contact person for internationalization of innovation and technology transfer, Member of the Interdepartmental Center PIC4SeR (PoliTO Interdepartmental Center for Service Robotics), and Deputy Coordinator of the Doctoral College in Aerospace Engineering. With over 100 publications, her work spans aerospace engineering, control systems, and robotics. Her research focuses on flexible spacecraft, flight control systems, robotic systems, and unmanned aerial vehicles. She designs guidance, control and navigation systems for aircraft and spacecraft, develops control systems for wind turbines and wind farms, studies flight mechanics of fixed and rotary wing aircraft, tests unmanned aerial systems, and plans mission control for autonomous systems. Her work bridges theoretical control systems with practical aerospace applications, with strong emphasis on experimental validation. Her recent publications demonstrate a strong focus on advanced control techniques for aerospace applications, particularly in UAV control, spacecraft formation flying, and robotic systems. There's a clear trend toward integrating machine learning with traditional control methods, as seen in transformer-based MPC and multimodal learning approaches. Her work spans theoretical development, simulation, and experimental validation across multiple platforms. Member of the Editorial Board of IEEE Control Systems Society (2019-) Member of the Scientific Committee - IEEE Technical Committee Aerospace Control (2016-) International FAI Judge for Helicopter Championship (2009-2015) Professor Capello supervises numerous PhD students working on topics including autonomous aerial vehicles, path planning, risk analysis, spacecraft dynamics, and control. She leads multiple research projects including CREATEFORUAS (2019-2022), Assessment of drag free control systems for L3 gravity wave observatory (2018-2019), and Guidance, Navigation and Control algorithms for in-Orbit servicing (2020-2021). Her international collaborations include institutions in the USA, Japan, and Germany. She is actively involved with the Flight Dynamics, Control and Simulation research group at DIMEAS and the DRAFT (DRones Autonomous Flight Team) at PoliTo, where she mentors students in developing autonomous flight capabilities for various applications.

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.

• Electric Drives
• Electrical Machines
• Motor Control
• +۷ مورد دیگر

Sandro Rubino is a Fixed-term tenure-track Assistant Professor at the Department of Energy (DENERG) at Politecnico di Torino, where he is also a Member of the Interdepartmental Center PEIC - Power Electronics Innovation Center. His academic appointment falls under the scientific disciplinary sector IIND-08/A - Power Electronic Converters, Electrical Machines and Drives (Area 0009 - Industrial and Information Engineering). Dr. Rubino's research focuses on electric drives and electrical machines, with particular expertise in induction motor drives, synchronous motor drives, and advanced torque control techniques. His work spans from fundamental motor control theory to practical applications in electric vehicles and e-mobility systems. He has developed high-performance torque controllers for various types of electric motors including electrically excited synchronous motors, induction motors, and multi-three-phase motor configurations. His research addresses critical challenges in motor drive systems including fault tolerance, efficiency optimization, and performance derating under abnormal conditions. His publications reveal a strong focus on practical applications of motor control theory, particularly in the context of electric vehicles and sustainable transportation. The trend in his recent work shows increasing sophistication in control algorithms for multi-phase motor systems, with emphasis on fault tolerance and performance optimization under challenging operating conditions. His research bridges theoretical electrical machine modeling with practical implementation challenges in modern power electronic drive systems. Dr. Rubino has received multiple prestigious awards including the IAS-IDC ECCE Prize Paper Award in 2020, 2022, and 2024 from IEEE Transactions on Industry Applications, the IEEE Italy Section Power and Energy Society (PES) Chapter Best PhD Thesis Award in 2020, the IEEE Italy Section Industrial Electronics (IES) Chapter Best PhD Thesis Award in 2021, and the IAS-IDC Transactions Paper Award in 2024. He actively supervises PhD students including Nicola Macri', Alessandro Ionta, and Luisa Tolosano, focusing on advanced topics in multi-phase motor drives and torque control. Dr. Rubino leads or participates in several significant research projects including TEAMING - e-powerTrain prEdictive mAintenance using physics inforMed learnING (2023-2027), SUPERDRIVE - Superconductive Synchronous Machine Drives for High-Power Applications (2023-2025), and SEMDY - Sustainable and Efficient Motor Drive System for E-mobility Applications (2022-2025), where he serves as Scientific Responsible. Within the Power Electronics Innovation Center (PEIC), Dr. Rubino contributes to advancing the state-of-the-art in electric drive systems, with particular emphasis on applications supporting Sustainable Development Goals 7 (Affordable and Clean Energy), 9 (Industry, Innovation, and Infrastructure), and 11 (Sustainable Cities and Communities).

Luca Mottolaمشاهده پروفایل

استاد

• Battery-less IoT
• Mobile Space Robotics
• Smart Cities
• +۳ مورد دیگر

Luca Mottola is a Full Professor at Politecnico di Milano and Senior Researcher at RI.SE Sweden. He leads the Networked Embedded Software Lab (NESLab), focusing on next-generation IoT, battery-less systems, and mobile robotics. His work bridges embedded computing, wireless networks, and cyber-physical systems, with applications in smart cities and space robotics. Education: No explicit details provided in texts. Research interests include energy-harvesting IoT, drone communication, and real-time systems. Notable awards include the ACM SENSYS Test of Time Award (2022) and multiple Best Paper Awards at top conferences like MOBICOM and RTCSA. Grants/Projects: Overseen projects on battery-less IoT, drone localization, and energy-efficient systems. Editorial roles include IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Labs/Teams: NESLab, FlyZone Testbed for aerial drones, and collaborations with NXP Technologies, TU Graz, and USC.

Umberto Desideriمشاهده پروفایل

استاد

• Renewable Energy Systems
• Thermal Engineering
• Hydrogen Technology
• +۱۵ مورد دیگر

Umberto Desideri is a Full Professor of Thermal Machines at the University of Pisa since November 2014, following his tenure as Full Professor at the University of Perugia from 2004 to 2014. He has held leadership roles, including Head of the Department of Engineering at the University of Perugia (2014) and Head of the Department of Energy, Systems, Territory and Construction Engineering at the University of Pisa (2016–2020). He is actively involved in editorial boards, such as the ASME Journal of Fuel Cell Science and Technology (2005–2017), Journal Applied Energy (since 2007, Associate Editor from 2011, Senior Editor since 2022), and Journal Applied Thermal Engineering (since 2013). Additionally, he co-founded two spin-off companies in 2005: Tecnologie per la riduzione delle emissioni engineering srl and Biomasse e nuove tecnologie srl . Desideri obtained his MSc in Mechanical Engineering from the University of Florence in 1988 and his PhD in Energy Engineering from the same university in 1993. His academic career includes roles as Assistant and Associate Professor at the University of Perugia (1992–2004) before becoming a Full Professor there in 2004. His research focuses on renewable energy systems (geothermal, solar, biomass), hydrogen and fuel cell technologies, carbon capture and storage, and energy-efficient buildings. He explores polygeneration systems, sustainable energy storage, and decarbonization strategies for industries like tissue paper production. Recent work emphasizes the integration of renewables with thermal storage and CO2 utilization in circular energy systems. Awards: Fellow of the American Society of Mechanical Engineers (since 1994) Listed in the Top Italian Scientists in Engineering Recognized as a World Top 2% Cited Scientist In advising and grants, he has supervised over 200 Master’s theses and led EU-funded projects such as: H2020 COMPBAT (2020–2024): Computer-aided design for next-gen flow batteries H2020 Regen-by-2 (2020–2027): Multi-energy systems using two-phase fluids LIFE Augia (2020–2023): Sewage oxy-gasification for chemicals production He directed the Fuel Cell Laboratory (2007–2014) and Wind Tunnel (2010–2014) at the University of Perugia. His current work at the University of Pisa’s DESTEC department addresses hydrogen technologies, energy transition, and sustainable systems.

Stefano Braccoمشاهده پروفایل

دانشیار

• Power Systems
• Microgrids
• Renewable Energy Integration
• +۳ مورد دیگر

Stefano Bracco is an Associate Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa, Italy, serving on both the Department Board and the School Council of the Polytechnic School. He teaches advanced courses including Energy Transition and Power Systems Management for Master's programs in Energy Engineering, Management for Energy and Environmental Transition (MEET), and Engineering for Natural Risk Management, covering critical topics in sustainable power systems and infrastructure modeling. His research focuses on power systems engineering with emphasis on microgrid optimization, renewable energy integration, and electric vehicle infrastructure. Key contributions include energy management systems (EMS) for active/reactive power control in microgrids, vehicle-to-grid/home technologies, and sustainable energy community design. His work addresses grid stability challenges, economic optimization of distributed energy resources, and resilience enhancement in critical facilities through advanced mathematical modeling and real-world case studies. Analysis of his 15 most recent publications (2024-2025) reveals consistent application of mixed-integer linear programming (MILP) for microgrid optimization across diverse contexts including university campuses, industrial sites, and Italian municipalities. Dominant trends include integration of electric vehicle charging infrastructure with renewables, uncertainty handling in renewable communities, and multi-scale control frameworks for automated transportation. His research bridges theoretical optimization with practical implementation, frequently using the Savona University Campus as a living laboratory for sustainable energy solutions. No scientific awards were mentioned in the provided information. The available text did not specify any advised students or research grants, though his extensive publication record suggests active research supervision and project leadership. While no dedicated laboratories are explicitly attributed to him, his work frequently involves the Savona University Campus infrastructure, including the CN MOST Laboratory and microgrid test facilities, indicating collaboration with existing university energy research platforms.

Gemma Catolinoمشاهده پروفایل

استادیار

• Software Engineering
• Empirical Software Engineering
• Human Factors in Software Development
• +۱۰ مورد دیگر

Gemma Catolino is an Assistant Professor at the Department of Computer Science, University of Salerno, and affiliated with the Software Engineering (SeSa) Lab. She has also served as an Assistant Professor at Tilburg University and Eindhoven University of Technology through the Jheronimus Academy of Data Science from September 2022 to December 2023, and previously as a Postdoctoral Researcher at Delft University of Technology and Tilburg/Eindhoven institutions. PhD in Computer Science, University of Salerno (2020), supervised by Prof. Filomena Ferrucci MSc in Management and Information Technology, University of Salerno (2016, magna cum laude) BSc in Computer Science, University of Molise (2014) Her research centers on empirical software engineering, focusing on both technical and social aspects affecting software development. Key areas include code smells, defect prediction, testability, changeability, and the emerging concept of “Community Smells”—social dysfunctions in developer teams. She investigates how human factors, team diversity (especially gender), and developer experience influence software quality and maintenance effort, often using mining software repositories and machine learning techniques. Her recent publications span high-impact journals and conferences such as IEEE TSE, EMSE, JSS, ICSE, and ICSME, with a strong trend toward integrating social and technical metrics for just-in-time defect prediction in mobile applications, analyzing community dynamics, and applying software quality metrics to cybersecurity contexts like dark web analysis. She has also contributed to MLOps and serverless computing. She has received several honors including a DEI research grant (2020), Best Technical Paper at BENEVOL 2019, first and second place in ACM Student Research Competitions (2018, 2017), and the Best Master Thesis award from the Italian Software Metrics Association (2017). Gemma Catolino has been actively engaged in academic service as a referee for top journals like IEEE TSE, EMSE, JSS, and IST, guest editor for special issues, and program/organizing committee member for major conferences including ICSE, MSR, SANER, and MobileSoft, where she served as Program Co-Chair in 2022. She has also contributed as a teaching assistant, lecturer, and course coordinator in machine learning and software engineering courses. She leads and contributes to research projects involving international collaborations, particularly with researchers such as Prof. Filomena Ferrucci, Prof. Andy Zaidman, Prof. Willem-Jam van den Heuvel, and Prof. Alexander Serebrenik. Her work bridges empirical software engineering with practical tool development and socio-technical analysis, positioning her at the forefront of modern software engineering research.

• Digital Circuits and Systems
• Energy-Efficient Circuits and Systems
• Embedded Systems
• +۷ مورد دیگر

Massimo Poncino is a Full Professor at the Department of Control and Computer Science (DAUIN) within the Faculty of Engineering at Politecnico di Torino. He serves as Scientific Advisor for the STMicroelectronics partnership and coordinates basic engineering subjects. A Senior Member of IEEE since 2012 and Fellow since 2012, he has served on editorial boards for IEEE Transactions on Computer-Aided Design, IEEE Design & Test of Computers, and ACM Transactions on Design Automation. Education: Laurea in Electronic Engineering (1989) and PhD in Computer and Systems Engineering (1993) from Politecnico di Torino Academic Career: Visiting Scientist University of Colorado (1993-1994), Researcher at Politecnico di Torino (1995-2001), Associate Professor at University of Verona (2001-2004), Full Professor at Politecnico di Torino (2006-present) His research focuses on energy-efficient digital systems , including design automation of SoCs, hardware-aware AI, battery management, cyber-physical systems, and embedded systems. Recent publications highlight advancements in digital twins for batteries , low-power neural network deployment , and IoT privacy . Scientific Awards: Recognition of Service Award - ACM (2013) Certificate of Appreciation - IEEE Circuits and Systems Society (2006, 2008, 2009) IEEE Fellow (2012-) Research Involvement: EU H2020, VI/VII Framework Programs evaluator Scientific Director for projects: Approxim@ction, EMBAI, DISLO-MAN, DAMASCO Member of EDA research group Teaching: Course director for Energy Management for IoT (2019-2025) Lecturer for Computer Science courses (2003-2025)

Marco Portaمشاهده پروفایل

استاد

• Computer Vision
• Human-Computer Interaction
• Eye Tracking
• +۴ مورد دیگر

Marco Porta is a Full Professor at the University of Pavia, Department of Electrical, Computer and Biomedical Engineering. He teaches Web and Multimedia Technologies in the Computer Engineering Master's program and Web Design and Technologies in the interdepartmental CIM Bachelor's program. His research focuses on Eye Tracking, Vision-Based Perceptive Interfaces, and Human-Computer Interaction, with recent emphasis on AI applications for human-centered systems. He leads the Computer Vision & Multimedia Lab and chairs teaching councils for CIM and CoD programs. Education: Master's in Electronic Engineering (Polytechnic of Milan) and Ph.D. in Electronic & Computer Engineering (University of Pavia). Professional roles include vice-chair of IEEE's Technical Committee on Factory Automation. Over 118 publications in journals/conferences, with contributions to biometrics, e-learning interfaces, and industrial automation. Research highlights include gaze-based authentication systems, interactive museum interfaces, and ergonomic in-vehicle infotainment evaluations. Current projects explore gaze-driven intelligent tutoring systems and public space interaction frameworks.

• 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