Stefano Passoni is a Researcher at Politecnico di Milano's NRGroup, focusing on nuclear engineering and computational fluid dynamics (CFD). His R&D spans since 2016, covering fuel performance modeling, GenIV reactors (e.g., MSR, LFR), compact heat exchangers, and reduced-order models. He holds a PhD (2018) and MSc (2013) from Politecnico di Milano, with thesis topics on nuclear fuel behavior and lead-cooled fast reactors. His research interests emphasize CFD applications in multiphase flow analysis, nuclear reactor thermal-hydraulics, and energy systems optimization. Recent work involves machine learning integration for void fraction estimation and experimental validation of compact heat exchangers. He advises multiple PhD/MSc students and collaborates on projects like the ELSMOR initiative. No scientific awards explicitly mentioned. His contributions include prototyping oxygen separation membranes and advancing wind turbine aerodynamics through CFD modeling. Active in NRGroup's R&D since 2016, he leads teams in GenIV reactor modeling and computational methods development.
جستجوی استاد راهنمای دانشگاهی
برای مسیر پژوهشیتان، استاد راهنما، استاد دانشگاه و پژوهشگر مناسب را پیدا کنید و با آنها ارتباط بگیرید.
نمایش ۷۳۶-۷۵۰ از ۸۲۸ استاد راهنما
اطلاعات پروفایلها از صفحات عمومی دانشگاهها گرفته شده و ممکن است بهروز نباشد.
Josie Esteban Rodriguez Condia is a Fixed-term Assistant Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. She is a member of the CARS@PoliTO Interdepartmental Center - Center for Automotive Research and Sustainable Mobility and serves as an invited member of both the College of Electronic, Telecommunications, and Physics Engineering and the College of Computer, Film, and Mechatronics Engineering. Her research focuses on computer architecture reliability, particularly in GPU and AI accelerator systems. Key areas include functional testing, general purpose graphics processing units (GPGPUs), hardware accelerators, hardware architecture, and parallel processing. Her work addresses critical challenges in reliability assessment of AI-based automotive systems, self-test libraries for tensor cores, and hardening techniques for neural networks on GPUs. Her recent publications demonstrate a strong trend toward reliability engineering for AI hardware, with particular emphasis on automotive applications and GPU-based neural network implementations. The research spans fault injection methodologies, error modeling, and architectural solutions to enhance system resilience against soft errors and permanent faults. Dr. Rodriguez Condia actively supervises PhD students including Gustavo Vilar De Farias, Giuseppe Esposito, and Robert Alexander Limas Sierra, all working on reliability evaluation and enhancement of neural networks. She is a member of the PNRR Research Group for the National Center for HPC, Big Data and Quantum Computing (2022-2025). She teaches multiple courses including GPU Programming and High Performance Computing for both Computer Engineering and Quantum Engineering programs. Her editorial work includes serving as Guest Editor for APPLIED SCIENCES in 2024.
- Quantum Computing
- Data Science
- Computer Vision
- +۳ مورد دیگر
Emanuele Dri is a PhD student in Quantum Computing at Politecnico di Torino, Italy, under the Department of Automatic Control and Computer Science (DAUIN). He also serves as an external teacher and teaching assistant, collaborating on courses in Computer Science and Quantum Engineering. His research focuses on quantum algorithms for financial applications, reliability of quantum circuits, and bridging academic research with industry needs. Education: M.Sc. in Data Science and Engineering from Politecnico di Torino (2021), with a thesis on Machine Learning for text classification. Research interests include quantum computing, data science, computer vision, AI, parallel systems, and financial applications. He has contributed to projects on quantum fault tolerance, algorithm optimization, and financial modeling with quantum circuits. Awards include a 2023 Teaching Quality Award (95.5% satisfaction) and 2024 Quality Awards. His teaching roles span courses in Computer Science and Quantum Computing modules for engineering programs. Publications highlight advancements in quantum finance, error propagation in quantum neural networks, and transpilation effects on quantum circuit reliability. Collaborations with institutions like Intesa Sanpaolo reflect his industry-oriented research.
Leonardo Giannantoni is a PhD Student in Control and Computer Engineering at the Polytechnic University of Turin (2021-2024) and a current Research Engineer at the same institution. His work focuses on bio-inspired and AI-driven algorithms for modeling, simulating, and optimizing complex systems, with applications in synthetic biology , structural biology , and healthcare technology . Education PhD in Control and Computer Engineering (2024, Polytechnic University of Turin) MSc in Computer Engineering (2016, Polytechnic University of Turin) BSc in Computer Engineering (2014, Polytechnic University of Turin) Giannantoni's research spans multiple domains, including reinforcement learning for genetic networks , co-simulation in biofabrication , and virtual reality rehabilitation systems for Parkinson's disease. His work integrates machine learning with biological modeling , leveraging parallel computing and software engineering principles. Recent publications highlight his expertise in AI-driven structural biology , synthetic oscillatory networks , and privacy tools like tracker blockers. His Biology System Description Language (BiSDL) provides a framework for multicellular synthetic biological systems design. Scientific Contributions Member of the Focus Group of Researchers (2023-) Giannantoni has served as a Teaching Assistant for courses on Systems Programming and Algorithms , and contributed to open-source projects like nwn-petrisim (Petri Nets simulator) and microgp4 (evolutionary computing toolkit). His work bridges academic research and practical software development for complex systems.
Matteo Lippi Bruni is a Full Professor in the Department of Economics at the University of Bologna, serving as Director of the Organisational Unit (UOS) in Forlì. His research focuses on healthcare economics, public policy, and health system efficiency, with particular emphasis on chronic disease management, emergency care utilization, and primary care optimization. He holds dual office locations in Forlì and Bologna, with appointments requiring prior email scheduling. His work bridges economic analysis and practical healthcare policy, addressing topics like pharmaceutical pricing, nursing home quality, and long-term care financing. Key research themes include analyzing the impact of primary care accessibility on emergency room overuse, evaluating the effects of patent expiration on drug prescription patterns, and studying the role of supplementary health insurance mechanisms. His publications span 20 years, demonstrating sustained engagement with issues such as diabetes care coordination, healthcare cost containment, and spatial disparities in healthcare resource distribution. While no specific scientific awards are noted, his contributions reflect significant scholarly engagement with healthcare economics. He advises on policy-relevant topics including hospital pricing behavior in regulated markets, the efficacy of extended primary care hours, and the delegation of elderly home care services. His work underscores the interplay between economic incentives and healthcare outcomes in public health systems.
Falko Dressler is a full professor and Chair for Telecommunication Networks at the School of Electrical Engineering and Computer Science, Technische Universität Berlin (TU Berlin). He holds a M.Sc. and Ph.D. from the University of Erlangen's Department of Computer Science (1998 and 2003). His roles include associate editor-in-chief for IEEE Trans. on Network Science and Engineering and IEEE Trans. on Mobile Computing , as well as chairing conferences like IEEE INFOCOM and ACM MobiSys. He was an IEEE and ACM Distinguished Lecturer, and authored influential textbooks such as Self-Organization in Sensor and Actor Networks and Vehicular Networking . Education: M.Sc. (1998), Ph.D. (2003) in Computer Science, University of Erlangen Professional Activities: Editorial roles across 8+ journals, conference leadership (e.g., IEEE GLOBECOM), academic fellowships (IEEE, ACM, AAIA) Research Interests: Focus on resilient wireless communication systems integrating distributed machine learning and edge computing. Key domains include IoT, cyber-physical systems, and bio-nano networks. His work bridges theoretical advances with practical applications in vehicular networks, 5G/6G systems, and tactile Internet. Publications: Over 300+ peer-reviewed papers spanning topics like multiband channel analysis, federated learning at edge networks, and O-RAN architecture. Recent work emphasizes 6G innovations, metaverse convergence, and explainable AI for network security. Awards: IEEE Fellow (2014), ACM Fellow (2019), AAIA Fellow (2022), German National Academy of Science member (acatech) Grants/Teams: Leads TKN (Telecommunication Networks) lab, co-organizing IEEE INFOCOM 2026. Supervised over 50 PhD students, many in vehicular/edge computing domains. Labs/Teams: Directs TU Berlin's Telecommunication Networks (TKN) group, collaborating internationally on projects like ReNeSys 2025 and IEEE MedComNet. Active in standardization efforts for Open RAN and vehicular VLC.
Elena Ferrari is Professor of Computer Science at the University of Insubria and research leader at STRICT SociaLab, recognized for significant contributions to data security and privacy. She received the 2021 SIGSAC Outstanding Contributions Award for her pioneering work in security technologies. Her research develops privacy-preserving frameworks for emerging technologies including blockchain systems, edge computing environments, human digital twins, and IoT networks. Current projects address malware detection, metadata leakage prevention, decentralized learning security, and privacy-aware access control. Publications demonstrate consistent innovation in security mechanisms for complex systems. Recent work features blockchain-based malware containment, context-aware privacy enforcement, and edge computing security solutions. Ferrari has chaired major security conferences and contributes to advancing privacy-preserving computation. No student advising details or laboratory affiliations are documented in available sources.
Daniel Casiniمشاهده پروفایل
استادیار
Dr. Daniel Casini is an Assistant Professor at the Department of Information Engineering and Computer Science, Sant'Anna School of Advanced Studies. His academic journey includes a PhD (2016–2019) and postdoctoral research (2019–2021) in Real-Time Systems. He specializes in real-time scheduling algorithms, edge computing, and embedded system predictability. His work focuses on optimizing latency, resource allocation, and security in cyber-physical systems. Education: PhD in Computer Science, Sant'Anna School of Advanced Studies (2016–2019) Postdoctoral Researcher in Real-Time Systems (2019–2021) Research Interests: Real-Time Scheduling (Partitioned/EDF/Gang Scheduling) Edge Computing and Predictable Virtualization Middleware Optimization (DDS/ROS 2) Hardware-Software Co-Design for Cyber-Physical Systems Security-Temporal Trade-offs in Critical Systems Key Contributions: Developed MATERIAL framework for edge real-time applications on QNX RTOS Pioneered analysis of QNX IPC predictability and Linux kernel noise Designed latency-optimized thread chains for DDS middleware Awards: IEEE TCCPS Early-Career Award 2023 Labs/Teams: Active contributor to the SPHERE project, developing heterogeneous multi-SoC architectures for next-gen cyber-physical systems.
Carol IMBRIANOمشاهده پروفایل
دانشیار
- Molecular Genetics
- Epigenetics
- Cancer Biology
- +۵ مورد دیگر
Carol IMBRIANO is an Associate Professor at the University of Modena and Reggio Emilia, Department of Life Sciences ex-Biology. She specializes in molecular genetics, epigenetics, and their applications in cancer biology and medical biotechnology. Her research focuses on transcription factors like NF-Y, particularly their roles in tumor progression, metabolic reprogramming, and epigenetic regulation. She also develops biosensor technologies using organic electrochemical transistors for DNA detection. Her teaching responsibilities include courses on molecular genetics and epigenetics for biosciences, genetics laboratory work for biotechnology students, and personalized therapy modules in medical biotechnology. These courses integrate theoretical and practical components, such as bioinformatics analysis and lab safety protocols. She emphasizes critical thinking and data interpretation through written and oral exams, often using international scientific literature. Research interests revolve around the molecular mechanisms underlying cancer aggressiveness, including NF-Y splicing dynamics in metastasis, estrogen receptor interactions in prostate cancer, and sigma-2 receptor targeting for melanoma therapy. She explores how epigenetic modifications (e.g., DNA methylation, histone variants) contribute to disease development and leverages nanomedicine for therapeutic delivery and diagnostic innovation. Her work bridges basic science with clinical applications in precision medicine and cancer stratification. Publications consistently highlight advanced topics in transcription factor biology, cancer metabolism, and nanosensor development. She collaborates with multidisciplinary teams on projects like EGOT biosensors and drug discovery for CRPC. Despite her extensive contributions, no scientific awards or grants are explicitly listed in the provided texts. She maintains an open-door policy for students via prior arrangement and uses digital platforms like Teams for course materials.
Letterio Gallettaمشاهده پروفایل
استادیار
Letterio Galletta is an Assistant Professor of Computer Science at IMT School for Advanced Studies Lucca, within the SySMA research unit. Previously, he held a postdoctoral researcher position at the University of Pisa's Department of Computer Science and earned his Ph.D. in Computer Science from the University of Pisa in 2014. His research focuses on language-based security, leveraging programming languages, compilers, and formal verification to address security challenges in adaptive software, IoT, firewalls, and blockchain technologies. Key research areas include secure compilation, access control policy analysis, smart contract formal models, and static analysis techniques. His work bridges theoretical foundations with practical applications, such as securing satellite communication systems (IRIS2) and enhancing firewall policy enforcement. Publications highlight contributions to blockchain transaction parallelism, IoT security metrics, and formal methods for SELinux configurations. He actively contributes to tools like FWS (Firewall Synthesizer) and VeriOSS for bug bounty protocols. His research emphasizes interdisciplinary approaches, combining cybersecurity with distributed systems and embedded computing.
Rossana Mastrandrea is an Assistant Professor at the IMT School for Advanced Studies Lucca, affiliated with the AXES Research Unit. Her work integrates complex network analysis with interdisciplinary research in Economics, Environmental Science, and Behavioral Studies. She holds a PhD in Economics from the Sant’Anna School of Advanced Studies (Pisa) and has conducted research at the Lorenz Institute of Theoretical Physics (Leiden, Netherlands) and the INET project on Macroeconomics Networks. Her research focuses on theoretical and empirical analysis of complex networks in economic, social, and biological systems. Current projects include studying pharmaceutical innovation through patent citation networks (PRIN project on mRNA vaccines), pro-environmental behavior using evolutionary game theory, and carbon emissions via network approaches. She also explores brain connectivity dynamics and global trade networks using statistical physics and agent-based modeling. Key themes in her work include network reconstruction, motif analysis, and the application of optimal transport methods. Her recent studies address topics like cooperation dynamics in structured populations, coalition formation in litigation, and the role of information load in functional brain connectivity. Rossana coordinates the PRIN project analyzing public and private roles in pharmaceutical innovations and has contributed to high-impact studies on environmental performance metrics, global value chains, and schizophrenia-related brain network alterations.
Eugenio Dragoni is a Full Professor at the Department of Engineering Sciences and Methods at the University of Modena and Reggio Emilia. His research focuses on mechanical design, smart materials (including shape memory alloys), structural analysis, and product optimization. He teaches courses on machine design and product development in the Mechatronics Engineering program. His work includes advancements in SMA actuators, fatigue testing of materials, and structural optimization of mechanical components. He leads projects involving anaerobic adhesives, bonded joints, and lightweight additive manufacturing. Dragoni’s consultancy spans structural analysis for industrial components like flywheels and hydraulic systems, demonstrating practical engineering applications of theoretical research. His publications emphasize analytical and numerical modeling, with notable contributions to stress distribution analysis, metamaterials, and SMA-based actuator design. He collaborates with industries on projects such as seat suspension mechanisms and torque transducers for agricultural machinery. Key technical skills include finite element analysis (FEA), design of experiments (DOE), and material characterization under thermomechanical loads. His Machine Design Group explores innovative solutions for mechanical systems, combining traditional engineering principles with smart material technologies.
Silvia Rossiمشاهده پروفایل
دانشیار
Silvia Rossi is an Associate Professor at the Department of Electrical Engineering and Information Technology (DIETI), University of Naples Federico II, Italy. She co-manages the PRISCA Lab focused on Intelligent Robotics and Advanced Cognitive Systems and coordinates the national project UPA4SAR (User-centered Profiling and Adaptation for Socially Assistive Robotics). Her research emphasizes Multi-agent Systems, Human-Robot Interaction, and Cognitive Architectures. She holds an M.Sc. in Physics from the University of Naples Federico II (2001) and a Ph.D. in Information and Communication Technologies from the University of Trento (2006). Professional experience includes roles at the ITC-irst (Italy), Institute of Cybernetics E. Caianiello (CNR, Italy), and visiting research at Oregon Health and Science University (USA). Research interests span socially assistive robotics, user profiling, and emotion recognition. Key contributions include adaptive robot behaviors for healthcare and education, transparent HRI, and multi-agent systems for smart environments. She teaches courses such as Multi-agent Systems, Distributed Intelligence, and Programming I. Her work integrates AI, robotics, and human-centered design to address challenges in assistive technologies and human-robot collaboration. Publications focus on socially assistive robotics, emotion-aware systems, and transparent AI. Projects include field trials of social robots for elderly care and pediatric emotional support. Awards and recognitions are not explicitly listed but reflect her leadership in socially impactful robotics research.
Stefania Santini is a Professor of Systems and Control Engineering at the University of Naples Federico II, leading the Distributed Automation Systems (DAiSY) Lab. Her research focuses on nonlinear control, cyber-physical systems, time-delayed systems, and their applications in automotive engineering, transportation, smart manufacturing, and energy. She has held roles in the Academic Senate (2013–2021) and serves as Senior Editor for IEEE Transactions on Intelligent Transportation Systems and Associate Editor for IEEE Transactions on Control Systems Technology. She actively collaborates with industry on national/international projects, emphasizing resilience and innovation in distributed control systems. Her research investigates distributed automation challenges in multi-agent systems, networked control, and cyber-physical security. Notable areas include fault-tolerant control for autonomous vehicles, resilient microgrid management under cyber-physical threats, and digital twin-based predictive maintenance. Recent work explores AI-driven solutions in smart manufacturing and energy systems, combining domain-specific expertise with advanced control methodologies. Publications span control theory advancements (e.g., time-delay systems stability, event-triggered control) and applied domains (autonomous vehicle platoons, telescope tracking, healthcare analytics). She leads projects addressing real-world challenges like eco-driving optimization for electric vehicles and cyber-resilient infrastructure. Current efforts emphasize sustainability in smart cities and railway automation through hybrid reinforcement learning and optimal control architectures. Her contributions include over 150 peer-reviewed articles and patents, with active engagement in IEEE ITS initiatives. Research outcomes are validated through industry partnerships, lab experiments, and high-fidelity cyber-physical platforms. Key projects involve SME collaboration on predictive maintenance frameworks and microgrid resilience under communication delays/attacks.
- Control Theory
- Network Dynamics
- Opinion Dynamics
- +۴ مورد دیگر
Francesco Lo Iudice is an Assistant Professor of Automatic Control at the University of Naples Federico II, Italy. His research focuses on control theory applied to complex networks, including network dynamics, opinion formation, power systems, and multi-agent systems. He explores topics such as synchronization, consensus protocols, pinning control strategies, and optimal control in renewable energy communities. His work bridges theoretical advancements with practical applications in smart grids, autonomous systems, and social network analysis. Key research themes include: Controllability and observability of complex networks Opinion dynamics in social-technical systems Design of distributed control algorithms for power systems Analysis of temporal and hypergraph networks His recent publications emphasize: Explosive synchronization phenomena Optimal recharge scheduling in automated systems Strategies for parallel power system restoration Modeling vaccine hesitancy via opinion dynamics Dr. Lo Iudice collaborates internationally on interdisciplinary projects combining control engineering with network science. His work has been applied to pandemic response modeling and smart energy management systems.
نمایش نتایج تا ۷۵۰ مورد اول. برای یافتن نتایج دقیقتر، جستجوی خود را با فیلترها محدود کنید.