جست‌وجوی استاد و پژوهشگر

• Control Theory
• System Identification
• Machine Learning
• +۵ مورد دیگر

Vito Cerone is a Full Professor at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin, Italy. His research focuses on control theory, system identification, machine learning, and optimization, with applications in vehicle dynamics, energy systems, and robust control design. Research Interests: Control Theory, System Identification, Machine Learning, Optimization, Cyber-Physical Systems. Scientific Contributions: Recent publications address convex optimization via feedback control, errors-in-variables system identification, and state estimation under sensor attacks. He has led numerous industry-funded projects on energy management in hybrid vehicles, transmission control strategies, and sea wave energy conversion. Professional Roles: He has served as Associate Editor for IEEE Transactions on Vehicular Technology (2019-2022) and is a member of IEEE and its Control Systems Society since 2006. He has taught graduate-level courses in Automatic Control and Modern Design of Control Systems across academic years 2019-2025.

Laura Palagiمشاهده پروفایل

استاد

• Nonlinear Optimization
• Mixed Integer Nonlinear Programming
• Semidefinite Programming
• +۷ مورد دیگر

Laura Palagi is a Full Professor at Sapienza University of Rome, Department of Computer, Automation, and Management Engineering "Antonio Ruberti". She has been with the institution since 1996, progressing from Researcher to Associate Professor in 2005, and Full Professor since March 2020. She currently serves as Coordinator of the PhD program in Automatic Control, Bioengineering and Operations Research (ABRO) since February 2024 and is the GEP committee representative at the DIAG Department. Her research focuses on developing and analyzing methods for solving nonlinear optimization problems with continuous and discrete variables. Key research themes include decomposition methods for training Support Vector Machines and Deep Networks, methods for Mixed Integer Nonlinear Programming (MINLP), Semidefinite Programming (SDP), standard quadratic problems (StQP), and convex quadratic constrained problems. She also develops predictive machine learning models for healthcare applications and surrogate models for engineering. Her recent publications span optimization methods, machine learning applications in healthcare, sustainability assessment, and network design. Her work demonstrates a strong integration of theoretical optimization with practical applications across multiple domains. Continuous Optimization Awards 2020 Member Best Paper Award from Journal of Global Optimization Honorable Mention from Marguerite Frank Award jury for Best EJCO Paper 2024 EURO Doctoral Dissertation Award Professor Palagi teaches multiple courses including Optimization and Decision Science, Laboratory of Decision Science, Optimization Methods for Machine Learning, and Optimization for Medical programs. She serves as thesis advisor for numerous Bachelor's and Master's students in Management Engineering, Mechanical Engineering, and Data Science programs.

• Computer networks and communications
• Cybersecurity
• Industry 4.0
• +۷ مورد دیگر

Guido Marchetto is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino , where he conducts cutting-edge research in computer networks, cybersecurity, machine learning, and Industry 4.0. He is a member of the NETGROUP - Computer Networks Group , the SmartData@PoliTO interdepartmental center, and leads research at ACS LAB and LABINF . He serves as Deputy Coordinator of the Doctoral College in Computer and Systems Engineering and is the Scientific Advisor for the European Technology Platform for High Performance Computing (ETP4HPC). PhD Students: Federico Rinaudi, Doriana Monaco, Antonino Angi Research Groups: NETGROUP, SmartData@PoliTO Labs: ACS LAB, LABINF His research focuses on intelligent network management, explainable AI for networking, reinforcement learning, federated learning, and softwarized networks. He has led multiple EU and commercial research projects such as MIRANDA and DESIRE , with applications in cybersecurity, edge computing, and digital twins. Marchetto’s recent publications reveal a strong trend toward integrating AI/ML techniques—especially reinforcement learning and language models—into network automation, traffic engineering, and IoT systems. His work bridges theoretical innovation with practical implementation in cloud, edge, and telco environments. Scientific Awards: Best Paper Award Finalist, IEEE HPSR (2014) Best Paper Award, IEEE ICC (2007) He is a Senior Member of IEEE and serves on the editorial board of IEEE Transactions on Vehicular Technology . He has also been a Contract Professor at the Turin Polytechnic University in Tashkent from 2012 to 2022. His extensive grant leadership includes EU Horizon projects and numerous commercial research contracts with a focus on network intelligence and automation. He is actively involved in doctoral education and curriculum development, contributing to multiple degree programs and supervising ongoing PhD research in AI-driven networking and cybersecurity.

Graziana Cavoneمشاهده پروفایل

دانشیار

• Automatic Control
• Model Predictive Control
• Cyber-Physical Systems Security
• +۵ مورد دیگر

Associate Professor Graziana Cavone is with the Department of Civil, Computer and Aeronautical Technologies Engineering at Roma Tre University, Rome, Italy. Her research integrates automatic control, optimisation and AI to guarantee safe, secure and efficient operations of cyber-physical systems ranging from industrial robots and drones to water networks and intermodal freight terminals. Education & affiliation: Department of Civil, Computer and Aeronautical Technologies Engineering, Roma Tre University Scientific disciplinary sector ING-INF/04 – Automatic Control Research interests revolve around four pillars: (i) model-predictive and data-driven control of complex dynamic systems, (ii) safe and ergonomic human-robot/human-drone interaction in logistics 4.0 environments, (iii) cyber-security and resilience of industrial control and water-supply networks, and (iv) stochastic optimisation and Petri-net modelling for railway traffic and intermodal freight terminals. Recent 2024-2025 publications exhibit a clear trend toward AI-enabled anomaly detection, digital-twin security frameworks, and socio-technical studies on robot acceptance, while earlier work concentrated on COVID-19 mitigation control and collaborative-robot motion planning. Scientific awards & editorial activity: Guest-editor for IEEE CASE 2018 special section, publicity chair for IEEE CASE 2023; specific prizes not listed in supplied text. Advising & grants: No explicit student lists or funded-project details are provided in the source. Labs & teams: No dedicated laboratory designation is mentioned; research is conducted within the departmental laboratories of Roma Tre University.

Gabriele Pannocchiaمشاهده پروفایل

استاد

• Process Modeling
• Control Systems
• Optimization Techniques
• +۳ مورد دیگر

Prof. Gabriele Pannocchia is a Full Professor at the Department of Civil and Industrial Engineering at the University of Pisa, where he has held roles from Assistant (2006–2015) to Associate (2015–2020) before becoming Full Professor in 2020. He also serves as President of the School of Engineering since November 2022. His research focuses on process modeling, control optimization, and advanced control strategies for industrial systems. He teaches courses in Reaction Engineering, Process Simulation, and Advanced Process Control at the MS level in Chemical and Energy Engineering programs. Education: Laurea (1998) and PhD (2002) in Chemical Engineering from the University of Pisa. PostDoc at the Department of Chemical Engineering (2002–2006). Key research interests include Model Predictive Control (MPC), process optimization, and data-driven modeling for energy systems, industrial automation, and sustainability. He has contributed to advancements in valve stiction mitigation, economic MPC formulations, and Industry 4.0 integration in chemical processes. Editorial Roles: Senior Editor for Journal of Process Control , Associate Editor for Automatica and Processes . Organized international conferences such as IFAC DYCOPS 2013 and IFAC ADCHEM 2021. His work integrates theoretical developments with practical applications in energy, chemical, and environmental engineering sectors. Notable projects include developing MPC tools for industrial PLCs, optimizing lithium-ion battery recycling, and enhancing sustainability of waste-to-energy systems through advanced control methodologies. His research emphasizes bridging computational models with real-world industrial challenges.

Antonio Liottaمشاهده پروفایل

استاد

• Machine Learning
• Intelligent Systems
• Internet of Things (IoT)
• +۷ مورد دیگر

Antonio Liotta is a Tenured Full Professor at the Faculty of Engineering of the Free University of Bozen-Bolzano, Italy. His research focuses on machine learning, intelligent systems, and network science with applications to smart cities, IoT, and cyber-physical systems. He leads an international team advancing micro-edge intelligence and miniaturized ML, contributing breakthroughs in neural networks and network science intersections. Education details are not explicitly provided in the text, but his academic roles and publications suggest significant expertise in computer science and data science. Research Interests: Intelligent systems and networks Data-driven smart sensing Embedded machine learning Network science applications Human-in-the-loop systems Publications reflect a focus on ML for IoT, edge computing, and environmental modeling. Notable contributions include hybrid surrogate models for hydrological prediction and federated learning for healthcare. He serves as Editor-in-Chief for Springer's IoT book series. Grants and collaborations are implied through his leadership roles and international projects but not explicitly listed. His lab works on AI-driven solutions for urban science and resilient systems.

• Operations Research
• Stochastic Programming
• Probabilistic Constraints
• +۴ مورد دیگر

Patrizia Beraldi is an Associate Professor of Operations Research at the Department of Mechanical, Energy and Management Engineering (DIMEG) , University of Calabria, Italy since 2003. She holds the National Qualification as Full Professor (2013) and earned her PhD in System Engineering and Computer Science from the University of Calabria in 2000. Her academic journey includes roles as Research Assistant (1999-2001) and Visiting Research Fellow at RUTCOR (Rutgers University) and Vancouver University. Education PhD in System Engineering and Computer Science (2000), University of Calabria Degree in Management Engineering (cum laude 1995), University of Calabria Her research focuses on stochastic programming with probabilistic constraints, network flow optimization , and decentralized decision modeling . Key application areas include energy systems (smart grids, renewable integration), healthcare logistics (operating room scheduling), financial engineering (risk management), and supply chain resilience . She leads the Financial Engineering and Risk Management Laboratory at DIMEG. Recent research trends involve bi-level optimization models for energy pricing, hybrid multigeneration systems for sustainability, and stochastic approaches to resource allocation in healthcare and energy sectors. Her work emphasizes computational methods and high-performance computing platforms . Scientific Awards : Best paper award of the 2015 IMA Journal of Management Mathematics Best presentation award at the ICEER Conference 2017 Best poster award of ICORES 2018 She supervises numerous PhD and Master's students , contributes to editorial boards as Associate Editor (TOP, Algorithms, IMA Journal), and leads research projects like PON Horizon 2020 initiatives on smart energy systems. Her teaching spans courses in Optimization, Financial Engineering, and Stochastic Programming at the University of Calabria.

• Control Engineering
• Biomedical Engineering
• Pharmacokinetics/Pharmacodynamics (PK/PD)
• +۵ مورد دیگر

Mattia Laurini is a Fixed-term Researcher at the Department of Engineering and Architecture , University of Parma. His academic work focuses on control engineering, biomedical applications, and optimization algorithms, with teaching assignments in Computer Engineering for Master's Degree programs since 2023. Research Interests: Control systems for anesthesia Pharmacokinetics/Pharmacodynamics (PK/PD) modeling Traffic flow estimation Dynamic programming applications Vehicle motion optimization Medical device automation Research Trends: Recent publications (2025) demonstrate interdisciplinary work merging control theory with biomedical applications, particularly in automating anesthesia delivery. Key methodologies include Branch and Bound optimization, dynamic programming for traffic systems, and hybrid control paradigms combining MPC with PID strategies. Research spans both theoretical advances (e.g., acceleration-constrained shortest path algorithms) and clinical applications (e.g., propofol/remifentanil co-administration optimization). Teaching: Laboratory of Control Engineering (2023-2025) Multivariable Systems (2023-2025) Reference teacher for Computer Engineering program Contact: mattia.laurini@unipr.it | Office: Building 1, Parco Area delle Scienze, 181/A 43124 Parma | Phone: 906183

• Numerical Analysis
• Optimization
• Machine Learning
• +۵ مورد دیگر

Federica Porta is an Associate Professor at the Department of Physical, Computer and Mathematical Sciences, University of Modena and Reggio Emilia. Her academic career focuses on numerical analysis, optimization, and stochastic gradient methods, particularly in machine learning and image restoration. Her research interests include: Numerical Analysis and Statistics for Computer Engineering Numerical Optimization for Artificial Intelligence Stochastic Gradient Descent with Variance Control Deep Image Prior Frameworks Regularization Techniques for Biomedical Imaging Federica's recent publications (2021–2025) demonstrate expertise in hybrid gradient projection methods, adaptive learning rate selection, and deep learning applications for image segmentation and classification. She collaborates extensively with researchers like Giorgia Franchini, Valeria Ruggiero, and Luca Zanni, applying these methods to both convex and non-convex optimization problems. She teaches courses such as Numerical Analysis and Statistics for Computer Engineering, Numerical Analysis for Mathematics, and Numerical Optimization for Artificial Intelligence. Her teaching emphasizes MATLAB/Python implementation of numerical methods, convergence properties, and computational complexity analysis. Contact: federica.porta@unimore.it | Office: Mathematics Building, Via Campi 213/b

• Machine Learning
• Artificial Intelligence
• Human-AI Collaboration
• +۳ مورد دیگر

Burcu Sayin Günel serves as a Research Fellow at the Department of Information Engineering and Computer Science, University of Trento, where she conducts cutting-edge research at the intersection of artificial intelligence and real-world critical systems. Her work bridges theoretical machine learning with practical implementations in high-stakes environments requiring human oversight. Her research portfolio centers on: Value-aware and cost-sensitive machine learning frameworks Human-AI collaboration mechanisms for medical diagnostics Safety-critical integration of ML in cyber-physical infrastructure Hybrid intelligence systems combining human cognition with algorithmic processing Active learning optimization for resource-constrained scenarios Economic valuation of machine learning models Analysis of her 2021-2025 publications reveals a consistent trajectory toward making AI systems more reliable, economically viable, and human-compatible. Key contributions include novel methodologies for prediction rejection in critical CPS, collaborative diagnostic tools like MedSyn for physician-AI teams, and value-based active learning frameworks that optimize data acquisition costs. Her work increasingly addresses medical domain challenges while maintaining strong foundations in cyber-physical systems safety. No scientific awards, grant funding details, or student supervision activities were documented in the available materials. Similarly, no specific laboratory affiliations or team leadership roles were mentioned within the provided institutional context.

Giuseppe Carlo Calafioreمشاهده پروفایل

استاد

• Convex Optimization
• Control Systems
• Randomized Algorithms
• +۶ مورد دیگر

Giuseppe Carlo Calafiore is a Full Professor at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin , where he has been since 1998. He has held visiting positions at institutions like Stanford University , University of California at Berkeley , and Vietnam National University . His research focuses on convex optimization , control systems , and randomized algorithms , with applications in finance , robotics , and machine learning . Education : Laurea in Electrical Engineering (1993) and Ph.D in Information and System Theory (1997) from Politecnico di Torino. Research Interests : Span large-scale optimization , robust portfolio optimization , and distributed algorithms , with emphasis on sparsity-based methods and data-driven control for autonomous systems. Recent Publications include works on nonlinear model predictive control , financial network robustness , and adaptive gain control in population games. His scientific awards include the IEEE CSS George S. Axelby Outstanding Paper Award (2008) and Fellow of the IEEE (2018) . He has advised students in artificial intelligence and communications engineering programs. His projects include research on smart energy allocation and financial risk modeling .

Antonio Violiمشاهده پروفایل

دانشیار

• Stochastic Programming
• Risk Management
• Energy Procurement
• +۴ مورد دیگر

Antonio Violi is an Associate Professor at the University of Sannio (UNISANNIO) in the Department of Law, Economics, Management and Quantitative Methods (DEMM). His research focuses on stochastic programming applications in industrial optimization, energy systems, and logistics. Key research areas include: Stochastic Optimization Risk Management Energy Procurement Smart Mobility Solutions Industrial Performance Modeling Logistics Network Optimization Recent publications (2024) address advanced models for: Production error prevention Dynamic performance evaluation systems Tourism car-pooling optimization Earlier works cover energy market modeling (2008-2021), logistics e-marketplaces (2018), and agri-food supply chain dynamics (2023).