جست‌وجوی استاد و پژوهشگر

Giorgio Kaniadakisمشاهده پروفایل

استاد

• Statistical Physics
• Theoretical Physics
• Complex Systems
• +۴ مورد دیگر

Giorgio Kaniadakis is a Full Professor at the Department of Applied Science and Technology (DISAT) of Politecnico di Torino. His research focuses on generalized statistics, theoretical physics, and complex systems, with a strong emphasis on κ-statistics and power-law distributions. Research interests include: κ-Statistics, Power-law Distributions, Quantum Computation, Nonlinear Kinetics, Statistical Physics of Complex Systems His recent publications (2024-2016) span urban scaling laws, epidemiological models, predator-prey dynamics, and quantum statistical mechanics, often applying κ-statistics to interdisciplinary problems in physics, biology, and economics. He has organized major conferences like SigmaPhi2014, SigmaPhi2011, and SigmaPhi2008 as Program Chair. He actively teaches courses in statistical mechanics and physics at both PhD and undergraduate levels. Key teams/groups: Institute of Fundamental Physics and Materials for Nanotechnology (DISAT), Generalized Statistical Mechanics of Complex Systems

• Optimization
• Manufacturing Systems
• Inventory Control
• +۳ مورد دیگر

Dario Bauso serves as Assistant Professor of Operations Research at the Engineering Faculty of the University of Palermo, Italy, with additional affiliation to the Department of Computer Science at the same institution. Education: Laurea in Aeronautical Engineering, University of Palermo, 2000 Ph.D. in Automatic Control and System Theory, University of Palermo, 2004 Visiting Scholar, Mechanical and Aerospace Engineering Department, UCLA, 2001-2002 Short-term Visiting Scholar, Lund University and MIT, 2010 Research Focus: His work bridges Optimization , Manufacturing Systems , Inventory Control , and Game Theory with emphasis on distributed decision-making. He investigates consensus mechanisms in adversarial multi-agent environments using mean-field game theory and nonlinear control frameworks, particularly addressing robustness against disturbances in networked systems. Publication Trends: His research demonstrates deep integration of control theory with noncooperative game dynamics, focusing on large-population regimes where legitimate and malicious agents interact. Key contributions include Riccati equation solutions for consensus problems and Nash equilibrium analyses in distributed control contexts, reflecting strong interdisciplinary connections between systems engineering and strategic decision theory. Professional Service: Member of IEEE Control Systems Society Conference Editorial Board (since 2010), Associate Editor for Dynamic Games and Applications (since 2011), and General Chair of the 6th Spain-Italy-Netherlands Game Theory Meeting (SING 6).

• optimization
• wireless sensor networks
• system level design
• +۲ مورد دیگر

Dr. Carlo Fischione is an Assistant Professor at the Royal Institute of Technology (KTH) in Stockholm, Sweden, affiliated with the School of Electrical Engineering and ACCESS Linnaeus Center. He holds a Ph.D. in Electrical and Information Engineering (2005) and a Dr.Eng. in Electronic Engineering (Summa Cum Laude, 2001) from the University of L'Aquila, Italy. His research includes positions at UC Berkeley and KTH. Research Focus: Dr. Fischione specializes in developing fast optimization algorithms for networked systems. His groundbreaking F-Lipschitz optimization theory enables efficient solutions for wireless networks, sensor systems, smart grids, and vehicular networks through novel centralized and distributed computational approaches that outperform traditional Lagrangian methods. Awards and Honors: IEEE Transactions on Industrial Informatics Best Paper Award (2007) IEEE MASS Best Paper Awards (2005, 2009) Ferdinando Filauro Award, University of L’Aquila Alta Formazione Award, Abruzzo Region Government Academic Contributions: He supervises graduate students at KTH and University of L'Aquila, has authored over 50 publications, holds a patent, and serves on conference committees and journal review boards. His industry collaborations include Ericsson, Synopsys, and United Technology Research Center. Research Environment: Leads research at the ACCESS Linnaeus Center, focusing on theoretical foundations and practical applications of optimization in networked systems.

Lorenzo Rosascoمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Robotics
• +۵ مورد دیگر

Lorenzo Rosasco is a Full Professor at the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa. He holds roles including University contact for the thematic area "Artificial Intelligence" and membership on the Department Board. His research focuses on machine learning theory, kernel methods, optimization, robotics, and their applications in control systems, domain adaptation, and interdisciplinary fields like biomedical engineering. His educational background includes advanced expertise in mathematical foundations of machine learning, though specific academic credentials are not detailed here. Teaching responsibilities include courses such as MACHINE LEARNING, SEQUENTIAL PREDICTION AND REINFORCEMENT LEARNING, and INFORMATION THEORY AND INFERENCE at both undergraduate and graduate levels. Research interests revolve around developing efficient algorithms for large-scale machine learning, including iterative regularization, transfer learning, and control systems using Koopman operator theory. Notable contributions include work on fast kernel methods, optimization in neural networks, and applications in robotics for tasks like humanoid locomotion and tactile sensing. Recent publications explore topics such as double descent phenomena, sim-to-real transfer learning, and adaptive control strategies. His work bridges theoretical insights with practical applications, emphasizing computational efficiency and interdisciplinary impact.

Agnese Seminaraمشاهده پروفایل

استاد

• Fluid Dynamics
• Biomechanics
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Prof. Agnese Seminara is a Full Professor in the Department of Civil, Chemical and Environmental Engineering (DICCA) at the University of Genoa, Italy. She specializes in fluid dynamics, biomechanics, and computational modeling, with research emphasizing turbulence, biological systems, and machine learning applications. Her work spans interdisciplinary areas such as fungal spore dispersal, odor navigation in turbulent environments, and the mechanics of biological tissues and sensory systems. Teaching: Seminara teaches advanced courses including Fluid Mechanics, Turbulence and CFD Models, and Mechanics of Sensory Systems at both undergraduate and graduate levels. Her courses are offered in English and focus on mechanical engineering and bioengineering disciplines. Research Interests: Her research integrates fluid dynamics with biological and environmental systems. Key areas include: (1) turbulence effects on odor transport and navigation strategies, (2) molecular mechanisms in fungal and marine organisms, (3) bioinspired robotics and control systems, and (4) computational modeling for public health challenges like airborne disease transmission. Recent projects explore machine learning applications for wind prediction and odor plume navigation. Publications Trends: Over 50 publications since 2005 highlight her contributions to fluid dynamics, biological systems, and interdisciplinary science. Recent work emphasizes machine learning integration with physical systems, evolutionary biology of sensory organs, and pandemic-related fluid mechanics. Labs/Teams: Collaborates with multidisciplinary teams in bioengineering, physics, and computational science. Active in international research networks focused on mycology, robotics, and environmental fluid mechanics.

Franco Milicchioمشاهده پروفایل

استادیار

• Computer Science
• Computational Mechanics
• Reverse Engineering
• +۷ مورد دیگر

Franco Milicchio is an Assistant Professor (tenured) at the College of Engineering, University Roma Tre. He holds a Ph.D. in Computer Science and Engineering from the same institution and has conducted postdoctoral research in structural engineering. His research spans computational mechanics, reverse engineering, bioinformatics, and mobile application development for cultural heritage accessibility. He has led projects such as the Palazzo Massimo LIS/ASL mobile app (awarded the European Excellence Award for Accessible Tourism) and has contributed to the NeuroLab project for EEG file format analysis. His academic roles include teaching courses like Computer Graphics, Mobile Computing, and Parallel and Distributed Systems. Education: Summa cum Laude Laurea Vecchio Ordinamento (2003), Ph.D. in Computer Science (2007). Advisor: Prof. Alberto Paoluzzi. Dissertation: 'Towards a topological unification of finite computational methods.' Research interests include fluid dynamics simulations, genetic sequence parsing via SIMD acceleration, and deformation analysis in 3D models. He has collaborated on grants such as the Air Force Office of Scientific Research projects on nanocomposites and the CINECA High-Performance Computing initiatives. Awards include the IBM EMEA Student Recognition (2003) and multiple grants for cultural heritage digitization. Key projects: 'Distributed Services with OpenAFS' (Springer, 2007), 'Ostia Antica Mobile for Deaf' (2016), and 'Bimillenary of Augustus' gesture-based app (2014). His work bridges computational methods with real-world applications in engineering, biology, and cultural preservation.

Matteo Scandellaمشاهده پروفایل

استادیار

• Control Systems
• System Identification
• Machine Learning
• +۳ مورد دیگر

Matteo Scandella is an Assistant Professor at the University of Bergamo , Italy, since February 2024. Previously, he served as a post-doctoral researcher at Imperial College London (2020–2024). He holds a PhD in Control Systems (2019) and advanced degrees in Computer Science Engineering from the University of Bergamo (Bachelor 2014, Master 2016). His research focuses on kernel-based machine learning techniques applied to system identification , nonlinear dynamics , and control systems , with emphasis on aerospace applications and mechatronics. He has developed methods for stable nonlinear system modeling, continuous-time system identification, and data-driven control strategies like SelfMPC. Education: Bachelor Degree in Computer Science Engineering (2014) – University of Bergamo Master Degree in Computer Science Engineering (2016) – University of Bergamo PhD in Control Systems (2019) – University of Bergamo Research interests span kernel methods (e.g., manifold regularization, RKHS), stability analysis of nonlinear systems, and data-driven control . His work bridges theoretical advancements with engineering applications such as health monitoring of aerospace actuators and urban traffic optimization. Recent publications highlight innovations in automated MPC tuning and graph-based system identification techniques. Teaching includes courses like Automatica (6 CFU) and laboratory modules in sustainable industrial systems. His research has been published in top journals like Automatica and conferences such as L4DC and SYSID.

• Bioengineering
• Artificial Intelligence
• Explainable AI
• +۷ مورد دیگر

Gloria Menegaz is a Full Professor of Bioengineering at the Department of Engineering for Innovation Medicine, University of Verona, where she directs the BraiNAVLab. She has been serving in this position since 2021, following her appointment as Full Professor in Computer Science in 2017. Previously, she held Associate Professor and Assistant Professor positions at the University of Verona, University of Siena, and University of Fribourg (Switzerland). Her research spans multiple interdisciplinary fields including bioengineering, artificial intelligence, machine learning, and neuroimaging. She specializes in explainable AI methods applied to biomedical data, with particular focus on brain connectivity analysis using multi-modal neuroimaging data (fMRI, EEG) integrated with genetic information. Her work has resulted in over 160 publications in prestigious journals including IEEE Transactions on Image Processing, IEEE Transactions on Medical Imaging, and Frontiers in Neuroscience. Her recent research trends emphasize the development of explainable AI frameworks for clinical applications, particularly in neurological disorder diagnosis and treatment planning. She has pioneered approaches for integrating structural and functional brain connectivity data with genetic markers to identify numerical biomarkers for various neurological conditions. Senior Member of IEEE (2017) Chair of Steering Committee of IEEE Transactions on Medical Imaging Member of IEEE-SPS Challenges and Data Collection Technical Committee Vice-Chair of IEEE Bioimaging and Signal Processing Committee Recipient of Rita Levi Montalcini grant Throughout her career, Professor Menegaz has secured over 1 million euros in research funding from international institutions including the European Commission (H2020, FP7), European Science Foundation, MIUR (PRIN, SIR, FIRB), and ANR (France). She maintains extensive international collaborations with Georgia Tech University, INRIA (France), EPFL (Switzerland), Queen Mary University, and University College London. Her laboratory, BraiNAVLab, focuses on developing advanced computational methods for brain imaging analysis and navigation.

• Robotics
• Automation
• Robotic Surgery
• +۵ مورد دیگر

Paolo Fiorini is a Full Professor at the Department of Engineering for Innovation Medicine, University of Verona, specializing in robotics, automation, and robotic surgery. His academic career spans multiple engineering disciplines with a focus on applying robotic technologies to unconventional areas such as medicine and surgery. Department: Department of Engineering for Innovation Medicine University: University of Verona Academic Sector: ING-INF/05 - Information Processing Systems Research Areas: Control Engineering, Robotics, Man-machine interfaces Professor Fiorini's research interests center around automation and robotics, particularly in medical applications. His work focuses on robotic surgery, developing new algorithms and designing surgical robots through a company he founded. He has expanded his research to apply medical robotics concepts to industrial applications through IoT and Industry 4.0 technologies. Current research directions include autonomous robotic surgery functions using big data analysis and machine learning methods to enable robots to collaborate with surgeons during interventions. His recent publications demonstrate strong trends in surgical robotics, autonomous systems, and the integration of AI techniques for medical applications. The research spans from fundamental control engineering to practical implementations in both medical and industrial settings, with particular emphasis on safety, human-robot collaboration, and real-time system performance. Professor Fiorini leads multiple research groups including: ForMe - Formal Methods for the Design of Engineering Systems Information Extraction for Robotic Surgery Robotics, Artificial Intelligence and Control He has secured significant research funding, including European Community grants for autonomous robotic surgery projects. His research portfolio includes numerous projects related to surgical robotics, industrial automation, and control systems, demonstrating both theoretical depth and practical implementation capabilities. Professor Fiorini directs the ALTAIR Laboratory and serves as the Internationalization Representative for his department. His teaching portfolio is extensive, covering courses in robotics, dynamic systems, and system theory across multiple degree programs including Computer Engineering, Bioinformatics, and Medicine.

• Artificial Intelligence
• Machine Learning
• Pattern Recognition
• +۳ مورد دیگر

Pietro Lovato serves as a Temporary Professor in the Department of Computer Science within the School of Science and Engineering at the University of Verona. His academic work focuses on Information Processing Systems (ING-INF/05), with active teaching responsibilities across multiple degree programs including Human Centered Medical System Engineering, Computer Science and Engineering, and Bioinformatics. Dr. Lovato's research centers on advancing beyond traditional text representation models, particularly through his BeBoW (Beyond the Bag of Words) project that examines structural and statistical perspectives in information processing. His work spans artificial intelligence, machine learning, pattern recognition, and information retrieval systems with applications in bioinformatics and medical text analysis. His research demonstrates a consistent focus on developing more sophisticated models that capture contextual and structural information beyond simple word frequency approaches. His publication record from 2010-2019 shows a progression from traditional information retrieval techniques toward more complex neural network architectures and structural analysis methods. This evolution reflects broader trends in the field moving from statistical models to deep learning approaches while maintaining a focus on practical applications in specialized domains. Dr. Lovato contributes to several research laboratories at the university including the Networked Embedded Systems (NES) Laboratory and the ALTAIR Laboratory, where his work intersects with electronic systems design and parallel computing. His teaching portfolio includes both theoretical coursework and laboratory components, indicating a hands-on approach to student education in artificial intelligence and machine learning.

Gianni Bianchiniمشاهده پروفایل

دانشیار

• Control Systems Theory
• Aerospace Control
• Smart Grids
• +۵ مورد دیگر

Gianni Bianchini is an Associate Professor at the University of Siena, affiliated with the Department of Information Engineering and Mathematics. His research focuses on control systems theory, aerospace control, smart grids, and haptics. He holds a PhD in Control Systems Engineering from the University of Bologna (2001) and a bachelor's degree in Electronic Engineering from the University of Florence (1997). He teaches courses on Advanced Control Systems and Digital Control at the master's and undergraduate levels. His research emphasizes Model Predictive Control (MPC), spacecraft trajectory optimization, renewable energy systems, and energy management in smart buildings. Notable contributions include robust MPC algorithms for autonomous rendezvous, optimal solar energy storage systems, and haptic interface design. His work often bridges theoretical control methodologies with practical applications in aerospace and energy sectors. Recent publications (2022–2025) highlight advancements in variable-horizon MPC for spacecraft guidance, solar battery optimization, and renewable energy communities. He collaborates with groups like the Systems and Control, Smart Grids, and Aerospace teams at his department. No scientific awards are explicitly mentioned, though his extensive publication record underscores his scholarly impact.

Angelo Cenedeseمشاهده پروفایل

دانشیار

• Robotics
• Control Systems
• Multi-Agent Systems
• +۵ مورد دیگر

Angelo Cenedese is an Associate Professor at the Department of Information Engineering (DEI), University of Padova, and leads the SPARCS Lab (Flying Arena and Mobile Robotics Laboratory). He co-leads the NAVLAB (Autonomous Navigation Laboratory) and holds senior roles in IEEE societies, including the Control Systems Society (CSS) and Robotics and Automation Society (RAS). His academic activities span teaching, editorial work as Associate Editor for IEEE Transactions on Industrial Informatics, and leadership in research projects focusing on robotics, control systems, and multi-agent networks. His research interests include robotics , control systems , multi-agent coordination , computer vision , autonomous navigation , and industrial automation . His recent publications emphasize machine learning for industrial vision systems, adaptive control in aerospace robotics, distributed state estimation , and secure UAV navigation under GNSS spoofing. Key trends involve edge computing , collaborative robotics , and AI-driven optimization . Scientific Awards: Award for 'Most Innovative Application' at Quality Control by Artificial Vision Conference (QCAV 2019) His projects include AI in Manufacturing (AIMS5.0), Sustainable Mobility (PNRR-MOST), and 6G Networking (PREDICT-6G), often in collaboration with Italian and international institutions. Teaching roles cover Robotics and Control , Networked Control Systems , and Computer Vision courses at both undergraduate and graduate levels.

Giulia De Pasqualeمشاهده پروفایل

استادیار

• Control Systems
• Social Network Analysis
• Optimization Algorithms
• +۳ مورد دیگر

Giulia De Pasquale is an Assistant Professor at the Department of Electrical Engineering, Eindhoven University of Technology, specializing in Control Systems. Her research focuses on social network interventions, optimization algorithms, and fairness in AI systems. She leads the Control Systems Group, addressing challenges in distributed control, hypergraph reconstruction, and ethical algorithm design. Her work integrates machine learning, network science, and control theory to develop fair and safe recommendation systems. Recent projects include hypergradient-based optimization for social network interventions and optimal transport approaches to fairness in influence maximization. She actively collaborates with institutions like Santa Fe Institute and UC San Diego. Giulia organizes interdisciplinary workshops on algorithmic fairness and has presented at NeurIPS, CDC, and NetSci. She advises PhD students like Alessandro Casu and hosts visiting scholars such as Camilla Quaresmini. Her research has been published in prestigious venues including Nature Communications and ICML.

Francesco Amigoniمشاهده پروفایل

پژوهشگر

• Robotics
• Multi-Agent Systems
• Machine Learning
• +۳ مورد دیگر

Francesco Amigoni is affiliated with the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. His research focuses on robotics, multi-agent systems, and machine learning, with applications in autonomous systems, anomaly detection, and energy systems. He has contributed to advancements in multi-agent coordination, path planning, and predictive maintenance through interdisciplinary approaches. Key research areas include: Multi-Agent Systems: Task allocation, cooperative robotics, and deadlock prevention in dynamic environments Machine Learning: Anomaly detection, transfer learning, and neural networks for battery lifecycle analysis Autonomous Robotics: Exploration strategies, SLAM algorithms, and map completeness estimation Data Mining: NLP-driven classification of road accidents and healthcare system analysis His work bridges theoretical foundations with real-world applications, addressing challenges in energy systems, environmental monitoring, and healthcare management. Recent studies highlight innovations in lithium-ion battery prognostics and swarm robotics fault detection.

Vincenzo Cagliotiمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• Image Processing
• +۵ مورد دیگر

Vincenzo Caglioti is a Professor at the Department of Electronics, Information and Bioengineering (DEIB) of Politecnico di Milano. His research focuses on computer vision, robotics, and image processing, with emphasis on motion analysis, sensor fusion, and multi-robot systems. He has contributed extensively to fields such as augmented reality, motion blur recovery, and uncalibrated camera systems. Key research areas include: Development of algorithms for 3D reconstruction from motion-blurred images Design of efficient exploration strategies for mobile robots Integration of sensor data for environmental monitoring and autonomous navigation Analysis of geometric properties in catadioptric systems His work spans theoretical advancements in computer vision alongside practical applications in robotics and surveillance. Over 30 years of publications demonstrate a sustained contribution to advancing perception systems for autonomous systems. No scientific awards explicitly listed in provided texts Labs/Teams: Likely affiliated with DEIB's Robotics and Computer Vision research groups, though specific lab names not explicitly stated in text.