جستجوی استاد راهنمای دانشگاهی

Matteo Sonza Reorda is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Automatic Control and Computer Science (DAUIN). He holds roles such as Partnership Agreement Coordinator with SMAT and has served as Vice-Rector for Research (2021–2024). His research focuses on fault tolerance, hardware reliability, and AI acceleration, with contributions to GPU/CNN reliability, self-test libraries, and defect-oriented testing. Education: M.S. in Electronics Engineering, Politecnico di Torino (1986) Ph.D. in Computer Engineering, Politecnico di Torino (1990) Research Interests: His work spans automatic test equipment, circuit reliability, GPU fault tolerance, neural network hardening, and embedded systems safety . He leads the Electronic CAD & Reliability Group and collaborates with institutions like the ISI Foundation and the National Research Council (CNR). Publications & Impact: With over 180 publications, his recent work emphasizes AI accelerator reliability, fault injection techniques, and safety-critical systems. Key trends include GPU resilience for CNNs, self-test library optimization, and radiation fault modeling in neural networks. Awards & Recognition: IEEE Fellow (2016–) Multiple best-paper awards at IEEE conferences (DDECS, DATE, etc.) Grants & Collaborations: Coordinator of EU projects (RESCUE, TUTORIAL) Partnerships with EDF, Marelli Europe, and SMAT Lead on National HPC/Quantum Computing Spoke 1 (2022–2025) Labs/Teams: Leads the CAD Group and collaborates with the French-Italian LIA LAFISI lab on hardware-software integration.

• Computer Engineering
• Circuit Design
• Fault Tolerance
• +۶ مورد دیگر

Giulia Giordano is a Full Professor in the Department of Industrial Engineering at the University of Trento, Italy, where she leads the Dynamical Networks and Systems Biology research group. She also holds a dual appointment as Visiting Professor and Delft Technology Fellow at the Delft Center for Systems and Control, Delft University of Technology, The Netherlands. Her career includes previous positions as Assistant Professor at Delft University of Technology (2017-2019), Postdoctoral Research Fellow at Lund University, Sweden (2016-2017), and Research Fellow at the University of Udine, Italy (2016). Giulia earned her Ph.D. in Industrial and Information Engineering: Automation (Excellent) from the University of Udine with a thesis titled "Structural Analysis and Control of Dynamical Networks." She completed her M.Sc. and B.Sc. in Electrical Engineering (both Summa cum laude) at the same institution. She also undertook research visits at Caltech (2012) as a SURF Fellow and at the University of Stuttgart (2015) as a DAAD Research Scholar. Her primary research focuses on the analysis and control of dynamical networks with applications in systems biology, mathematical ecology, and mathematical epidemiology. She develops mathematical frameworks that bridge control theory, network theory, and dynamical systems to address complex problems in biological systems. Her recent work spans epidemic modeling, opinion dynamics, biochemical networks, and neurological disorders, with a particular emphasis on structural analysis of networked systems. She employs both theoretical and computational approaches to understand system behavior under uncertainty. Giulia's publications reveal a strong interdisciplinary focus, spanning from theoretical control systems to practical applications in epidemiology and biology. Her recent work shows increasing emphasis on epidemic modeling (particularly related to mpox and SARS-CoV-2), network synchronization, and the application of control theory to biological phenomena like fibromyalgia pathogenesis and opinion formation. Many of her papers appear in top-tier control journals including Automatica and IEEE Transactions on Automatic Control. 2024: Outstanding Service as Associate Editor of IEEE Control Systems Letters 2021: SIAM Activity Group on Control and Systems Theory Prize 2020: Outstanding Reviewer, Annals of Internal Medicine 2017: NAHS Best Paper Prize and EECI PhD Award 2016: Outstanding TAC Reviewer, IEEE Transactions on Automatic Control Giulia actively mentors students and postdoctoral researchers, currently supervising five postdoctoral researchers and two Ph.D. students at the University of Trento. She has advised numerous M.Sc. and B.Sc. students on topics ranging from bio-inspired modeling to optimal control of epidemic systems. Her research is supported by competitive grants including the ERC Starting Grant INSPIRE (Integrated Structural and Probabilistic Approaches for Biological and Epidemiological Systems). She serves as Associate Editor for IEEE Control Systems Letters and Automatica, and is a Senior Member of IEEE and the Control Systems Society. Giulia leads the Dynamical Networks and Systems Biology research group at the University of Trento, which maintains strong international collaborations across Europe and North America. The group's work combines theoretical advances in control theory with practical applications to pressing problems in public health and biological systems, demonstrating the power of mathematical approaches to understanding complex phenomena in the life sciences.

• Automatic control
• Complex networks
• Control systems
• +۱۲ مورد دیگر

Eleonora Vacca is a PhD student and Research Fellow in the Department of Automatic Control and Computer Science (DAUIN) at the Polytechnic University of Turin. She holds a B.S. in Electronic Engineering from the University of Palermo (2018) and an M.S. in Electronic Engineering-Embedded Systems from Politecnico di Torino (2021). Her research focuses on digital hardware design, reliability engineering, reconfigurable devices, and AI applications in aerospace and safety-critical systems. She is a member of the Aerospace and Safety Computing Lab and the CAD - Electronic CAD & Reliability Group (DAUIN). Her work addresses challenges such as radiation effects mitigation in space missions, fault-tolerant AI accelerators, and real-time anomaly detection in satellite telemetry. She has contributed to projects like the RAMSES CubeSat-1 Development (2025-2026), funded by commercial contracts. In 2024, she won the Best Student Paper Award at the NEWCAS Conference for her research on radiation effects in space missions. Vacca collaborates on teaching, including assisting in the course 'Electronic Calculators' for Computer Engineering students. Her recent publications explore AI resilience in RISC-V ecosystems, radiation environment analysis for space missions, and gesture recognition systems for smart cities. She actively contributes to conferences such as the ACM International Conference on Computing Frontiers and the IEEE International Smart Cities Conference.

• Digital Hardware Design
• Reliability Engineering
• Reconfigurable Devices
• +۳ مورد دیگر

Massimo Canale is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , and a member of the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His academic career spans over two decades, focusing on control systems engineering with applications in automotive technology. Scientific Branch: Systems and Control Engineering (IINF-04/A) ERC Sectors: Automotive Engineering, Control Engineering, Control Theory Dr. Canale's research bridges theoretical advancements in Model Predictive Control (MPC) with practical applications in autonomous vehicles , hybrid/electric propulsion , and active suspension systems . His work integrates reinforcement learning and dynamic programming for optimizing vehicle performance and energy efficiency. Recent publications demonstrate trends in autonomous driving architectures (2024), sliding mode control for highway scenarios (2024), and energy management for sustainable mobility (2023-2024). He has developed patented solutions for semi-active suspension control and autonomous vehicle guidance. Award: IEEE Transactions on Control Systems Technology Outstanding Paper Award (2011) Editorial Roles: Associate Editor, IEEE Open Journal of Control Systems (2022–present) Dr. Canale supervises PhD students like Francesco Cerrito and teaches courses on digital control technologies , automatic control , and reinforcement learning at Politecnico di Torino. His research is funded through competitive grants (e.g., MPC4AVP 2021-2022) and commercial contracts (AD Shuttle 2024).

• Control and Systems Engineering
• Automotive Engineering
• Model Predictive Control
• +۱۰ مورد دیگر

Giuseppe Bruno Averta is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN), Polytechnic University of Turin, and a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He is affiliated with the College of Computer, Film and Mechatronics Engineering and contributes to national and international research in artificial intelligence and robotics. Averta has held a Visiting Researcher position at the Massachusetts Institute of Technology (MIT) from January to June 2019. His research interests include Computer Vision, Deep Learning, Robotics, Neural Architecture Search, Egocentric Vision, Embodied Intelligence (Edge/Tiny ML), and Human-Robot Collaboration . His work is aligned with ERC sectors in Artificial Intelligence, Machine Learning, and Robotics, and contributes to UN SDGs such as Good Health and Well-being, Industry Innovation and Infrastructure, and Responsible Consumption and Production. The recent publication trends highlight his focus on vision-language models (e.g., CLIP), egocentric action recognition, efficient neural architectures (e.g., BiSeNet, MaskFormer), and robust deep learning. His research bridges theoretical advances with practical robotics applications, including grasping and manipulation. Scientific Awards and Recognitions: Georges Giralt PhD Award (euRobotics AISBL, 2021) Wiley Best Reviewer (Wiley, Italy, 2021) Best Paper Award, ICUMT 2015 (2017) Fellow, ELLIS Network of Excellence (2022–) Fellow, DAAD AInet (2022–) DAAD AInet Fellowship Advising and Grants : Averta supervises multiple PhD students in the Artificial Intelligence and Computer and Systems Engineering doctoral programs at Politecnico di Torino. He is involved in teaching at both the master’s and doctoral levels, including courses on Robot Learning and Machine Learning and Deep Learning. He is also a co-inventor on a national and international patent for a method and algorithm for the automatic design of neural networks through machine learning, indicating active research funding and innovation. Labs and Research Groups : He is a member of the SmartData@PoliTO center and contributes to research in the VANDAL PoliTO lab (as indicated by his student Davide Buoso). His work is deeply integrated with teams working on egocentric vision, embodied AI, and neural architecture search.

• Computer Vision
• Deep Learning
• Robotics
• +۹ مورد دیگر

Fabio Furini is an Associate Professor at the Department of Computer Science, Automatics, and Management (DIAG) at Sapienza University of Rome since September 2021. Prior to this position, he served as a CNR researcher at IASI-CNR in Rome (2020-2021), Maître de Conférences at Université Paris-Dauphine, France (2013-2019), postdoctoral researcher at Université Paris-13, France (2012-2013), and research fellow at the University of Bologna (2011-2012). His educational background includes a Ph.D. in Control Engineering and Operations Research from the University of Bologna in 2011. He further obtained the Habilitation à Diriger des Recherches (HDR) in France in 2017 and the National Scientific Qualification for Full Professor in Operations Research in Italy in 2019. Fabio Furini conducts theoretical and methodological research on Combinatorial Optimization and Operations Research. His primary focus is on developing exact algorithms based on decomposition and reformulation techniques for integer linear programming problems. His research spans various applications including network optimization, graph theory, and combinatorial problems such as the maximum clique problem, bin packing problem, and vertex separator problem. His work often bridges theoretical developments with practical applications in transportation, logistics, and network security. His recent publications demonstrate a strong focus on exact algorithms for combinatorial optimization problems, particularly in network interdiction, bin packing with temporal constraints, and graph-based problems. His work consistently combines integer programming techniques with combinatorial search methods to develop novel formulations and efficient solution approaches that advance the state-of-the-art in these domains. Among his notable scientific awards are the Prime d'encadrement doctoral et de recherche (PEDR), which he received annually from 2014 to 2020, recognizing him among the top 15% of researchers in the French university system. He also holds the prestigious Habilitation à Diriger des Recherches from France (2017) and the National Scientific Qualification for Full Professor in Operations Research from Italy (2019). Fabio Furini has been actively involved in supervising PhD students and has served as principal investigator for numerous national and international research projects. His extensive network includes over 60 co-authors across European and American universities. He is also a member of the editorial boards for three prestigious international journals: Omega, Annals of Operations Research, and Discrete Applied Mathematics. His research activities include collaborations with various institutions across Europe and the United States, including Imperial College London and the University of Colorado. These collaborations have resulted in a robust research program focused on advancing the theoretical foundations and practical applications of combinatorial optimization.

• Combinatorial Optimization
• Operations Research
• Integer Linear Programming
• +۳ مورد دیگر

Gabriella Casalino is an Assistant Professor at the University of Bari Aldo Moro, Department of Computer Science, and a key researcher at CILAB - Computational Intelligence Lab. Her work focuses on Computational Intelligence methods for interpretable data analysis, particularly in eHealth, Data Stream Mining, and eXplainable Artificial Intelligence (XAI) within medical and educational domains. She has contributed to innovative approaches in smartphone-based health monitoring, fuzzy logic applications, and remote vital sign detection via photoplethysmography. Education : Ph.D. in Computer Science, with advanced training at institutions like Universitat de Girona and Université de Mons. Research Trends : Recent publications highlight applications of evolving granular computing, neuro-fuzzy systems, and explainable AI in hypertension prediction, bipolar disorder monitoring, and educational data analysis. Key subfields include remote health monitoring, medical data streams, and hybrid AI models. Grants : Research funded by AIRC (Italian Cancer Research Foundation), focusing on computational methods for healthcare challenges. Labs & Collaborations : Active in CILAB, collaborating on projects involving mHealth solutions, cardiovascular risk assessment, and intelligent educational systems.

• Computational Intelligence
• eHealth
• Data Stream Mining
• +۵ مورد دیگر

Roberto Garello is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino . He specializes in Communication Systems , Satellite Networks , and Channel Coding , with a focus on 5G/6G Technologies and Non-Terrestrial Networks . His work aligns with the School of Master’s Programmes and Lifelong Learning . Research Interests: Satellite communications systems, Direct-to-Satellite IoT constellations, Mega-constellation services in space, and physical layer advancements for 5G/6G. Teaching: Offers courses like Information Theory for Data Science , Communication and Network Systems , and Space Exploration and Resources , while supervising Applied Signal Processing Laboratory . Projects: Leads initiatives such as DitDSSS (satellite localization), RESTART (future telecommunications), and TESL@ (ICT energy efficiency). Scientific Awards: Received Best Paper Awards at CTRQ 2010 and COCORA 2013. Students: Supervises PhD candidates including Alessandro Compagnoni, Agbotiname Lucky Imoize, and Riccardo Tuninato, focusing on topics like Wireless Communication, Machine Learning, and Non-Terrestrial Networks. Publications: His recent work explores OTFS vs. OFDM, spectrum sensing algorithms, MIMO with cylindrical arrays, and 5G NTN synchronization, reflecting trends in satellite IoT and machine learning integration.

• Telecommunications
• Communication Systems
• Satellite Communications
• +۷ مورد دیگر

Saverio Mascolo is a Full Professor at the Polytechnic University of Bari , Department of Electrical and Information Engineering. He leads the Control of Computing and Communication Systems Lab (C3Lab) and contributes to IEEE/ACM Transactions on Networking as an Associate Editor. His research focuses on Future Internet, network congestion control, and real-time communication systems. Laurea in Electronic Engineering, Politecnico di Bari (1991) PhD in Electronic and Automatic Control, Politecnico di Bari (1995) Visiting researcher roles at UCLA (1995, 1999), INRIA (2004), and FTW (2004) Research spans network congestion control , adaptive video streaming , and real-time communication . His lab develops protocols like TCP Westwood+ and contributes to WebRTC standards. Current projects include low-delay protocols for immersive video streaming and autonomous systems control. Recent publications emphasize adaptive threshold mechanisms in congestion control, millimeter-wave radar datasets , and immersive teleoperation systems . Projects integrate nonlinear control , time-delay analysis , and cloud-based multimedia delivery . Scientific recognition includes: Elevated to IEEE Fellow (2018) for congestion control contributions Google Faculty Award (2014) for WebRTC research Cisco Research Award (2013) for video streaming control Best paper awards at MMSYS (2025, 2024, 2016) Grants fund research in cloud-based video platforms (MISE, 2017-2020), WebRTC optimization (MIUR, 2012-2015), and network control algorithms. His lab collaborates with institutions like Uppsala University (since 2001) and industry partners.

• Network Congestion Control
• Real-time Communication Systems
• Adaptive Streaming Protocols
• +۴ مورد دیگر

Andrea Garulli is a Professor in Control Systems at the Department of Information Engineering and Mathematics (DIISM), University of Siena. He served as Dean of the Faculty of Engineering (2011-2012) and Director of DIISM (2015-2021). His research focuses on control systems, including system identification, state estimation, robust control, multi-agent systems, and aerospace applications. He co-authored the book *Homogeneous Polynomial Forms for Robustness Analysis of Uncertain Systems* and developed the LFR_RAI toolbox for robustness analysis of uncertain models. Garulli has led projects like ACANTO (social robot navigation) and DALi (autonomous navigation for elderly care). His teaching includes courses on system dynamics, state estimation, and filtering. He is an Associate Editor for *Automatica* and has contributed to initiatives like the Automatic Control Telelab for remote experiments with mobile robots.

• Control Systems
• Aerospace Engineering
• Robotics
• +۵ مورد دیگر

Federica FERRAGUTI is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. Her research focuses on robotics, control systems, and automation, with a particular emphasis on collaborative robotics, surgical robotics, and industrial applications. She teaches courses such as Industrial and Collaborative Robotics, Automatic Controls, and Collaborative Robotics for Smart Industry. Her work integrates advanced control strategies, safety protocols, and human-robot interaction principles to enhance automation in both industrial and medical contexts. Research Interests: Federica’s research spans robotics control, human-robot collaboration, surgical robotics, and safety-critical systems. She develops novel algorithms for motion planning, trajectory generation, and real-time control, with applications in manufacturing and healthcare. Her recent work includes AI-driven augmented reality systems for surgery, energy-efficient safety frameworks, and intuitive robot-assisted welding solutions. Publications: Over 40 peer-reviewed articles in journals and conferences, including work on collaborative robotics safety, real-time surgical AR integration, and industrial automation. Key contributions include high-velocity walk-through programming for industrial robots and energy-based control architectures for shared autonomy. Labs/Teams: Active in the ARSControl research group, focusing on advanced robotics systems. Collaborates with industry partners on projects like MyWelder, an intuitive welding system for SMEs. Engages in EU-funded initiatives like the SARAS project for surgical teleoperation.

• Robotics
• Control Systems
• Automation
• +۳ مورد دیگر

Giovanni Indiveri is an Associate Professor at the Department of Computer Science, Bioengineering, Robotics, and Systems Engineering (DIBRIS) under the Polytechnic School of the University of Genova . He serves as the Director of the Interuniversity Research Center for Integrated Systems for the Marine Environment (ISME) and is a member of the Technical-Scientific Committee of the University's Strategic Center for Marine Engineering. His work bridges theoretical and applied research in maritime autonomous systems. Research interests focus on Robotics , Control Systems , and Autonomous Vehicles , particularly for marine environments. His contributions include motion planning algorithms, cooperative system design, and navigation optimization for autonomous underwater and surface vehicles. This aligns with broader themes in Systems Engineering and Artificial Intelligence . Recent publications highlight advancements in multi-vehicle motion planning , dynamic scenario navigation , and cooperative autonomous systems . Keywords across his work include Robotics , Control Systems , and Marine Engineering , with subfields like Bearing-Only Tracking and Formation Control . Indiverii is involved in institutional leadership, directing ISME and advising on strategic marine research initiatives. He teaches courses such as Control of Multi-Variable Systems and Automatic Controls for Robotics and Computer Engineering programs. Office hours are available by email appointment.

• Robotics
• Control Systems
• Autonomous Vehicles
• +۳ مورد دیگر

Marco Buzzelli is an Assistant Professor at the Department of Informatics, Systems and Communication (DISCo) at the University of Milan-Bicocca, where he also obtained his PhD in Computer Science in 2019. His academic career is centered around cutting-edge research in signal, image, and video processing with a specialized focus on color imaging and machine learning applications. Dr. Buzzelli's research interests span multiple interconnected domains within computer vision and image processing. He has established himself as a leading researcher in color constancy, with numerous publications exploring illuminant estimation, white balance algorithms, and perceptual aspects of color imaging. His work extends to video restoration, particularly addressing challenges in low-light conditions and HEVC-compressed video processing. Additional research areas include hyperspectral imaging applications for historical document analysis, food authentication technologies, and neural architecture search for various computer vision tasks. His publication record demonstrates a clear evolution from foundational work in logo recognition and saliency detection toward increasingly sophisticated approaches to color science and video processing. Recent work shows strong emphasis on uncertainty estimation in color constancy, Bayesian optimization for night photography, and multimodal approaches combining spectral information with traditional RGB imaging. His research often bridges theoretical advances with practical applications across diverse domains including cultural heritage preservation, food safety, and computational photography. As an active ELLIS member, Dr. Buzzelli maintains significant European collaborations with institutions including Universitat Autònoma de Barcelona, Universidade Nova de Lisboa, Université Jean Monnet, and Universidad de Granada. His research group participates in major challenges such as the NTIRE series on night photography rendering and spectral recovery, contributing both methodological innovations and comprehensive surveys of the field. His laboratory work focuses on developing practical imaging solutions with real-world applications, particularly evident in projects addressing food authentication, historical document analysis, and vision-based monitoring systems. The integration of traditional image processing techniques with modern deep learning approaches characterizes his methodological approach across multiple research domains.

• Signal Processing
• Image Processing
• Video Processing
• +۳ مورد دیگر

Prof. Bruno Siciliano is a full Professor of Automatics and Robotics at the University of Naples Federico II's Department of Electrical Engineering and Information Technology (DIETI). He directs the PRISMA Lab and chairs the Scientific Council of the ICAROS Center. His research focuses on robotics, automation, and human-robot interaction, with notable contributions to medical robotics, deformable object manipulation, and AI integration. He has received prestigious awards such as the 2024 IEEE RAS Pioneer Award and is a Fellow of multiple international organizations. Affiliations: Director, PRISMA Lab Chair, ICAROS Center Scientific Council Member, ACN Technical-Scientific Committee Research Interests: His work spans robotics education, surgical robotics, non-prehensile manipulation, and AI-driven robotic systems. Notably, his projects include the ERC-funded EndoTheranostics initiative for robotic colonoscopy and RoDyMan for dynamic manipulation. His contributions bridge robotics with healthcare, automation, and cognitive systems. Awards & Honors: 2024 IEEE RAS Pioneer in Robotics and Automation Award Genio Award (2024) for pioneering Italian robotics Fellowships: IFAC, IEEE RAS, and international AI associations Grants & Leadership: ERC Synergy Grant (2023, 10M€) and Advanced Grant (2013) Leadership roles in IEEE RAS and international robotics initiatives Labs & Teams: PRISMA Lab focuses on robotics paradigms like design, knowledge, and human-robot interaction, with projects in medical robotics and autonomous systems.

• Robotics
• Automation
• Control Systems
• +۴ مورد دیگر

Diego Regruto Tomalino is an active Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Polytechnic University of Turin, Italy, with contact details +39 0110907077 and diego.regruto@polito.it. He holds leadership roles in the IEEE Control Systems Society as Scientific Committee member of the Technical Committee on System Identification and Adaptive Control (2008-present) and served as its President (2013-2015). His work spans academic research, teaching, and international collaboration within control engineering. Education : Laurea in Electronic Engineering, Politecnico di Torino (2000) Ph.D. in Systems Engineering, Politecnico di Torino (2004) Research Interests : System Identification : Specializing in set-membership, sparse, and LPV techniques for nonlinear systems with applications in automotive and biomedical domains. Optimization & Control : Developing convex relaxation methods for model predictive control, robust control algorithms, and electrified vehicle propulsion systems. Control Education : Innovating through remote laboratories and industrial platforms to enhance engineering pedagogy globally. Publication Trends : Recent work (2021-2024) focuses on sparse optimization for cyber-physical security and electrified vehicles, extending set-membership identification to continuous-time systems, and educational frameworks. Dominant fields include control theory, optimization, and automotive applications with increasing emphasis on data-driven methods and sparse computing. Scientific Awards : No specific prizes, medals, or fellowships were documented in the provided texts. Advising and Grants : PhD Supervision : Alice Re (2024-present, sparse optimization for identification), Francesco Ripa (2023-present, electric vehicle propulsion management), Simone Pirrera (2021-2025, dynamical systems learning). Research Projects : Principal investigator for OpThermEV (2021-2022) on thermal management of electric vehicles, plus corporate-funded automotive research initiatives. Labs and Teams : Core member of the SIC (System Identification & Control) research group and LAB 11 at DAUIN. Leads international control education collaborations, notably a remote laboratory partnership between Asian and European institutions.

• System Identification
• Robust Control
• Convex Relaxation Techniques
• +۵ مورد دیگر