Find Academic Supervisors

• Renewable Energy
• Thermodynamics
• Heat Transfer
• +3 more

Prof. Sebastiano Tomassetti is a Researcher at the Department of Industrial Engineering and Mathematical Sciences (DIISM) , Università Politecnica delle Marche (UNIVPM) , specializing in Industrial Technical Physics (IIND-07/A). His work focuses on renewable energy systems, thermodynamics, and refrigerant properties. Scientific sector: IIND-07/A - Industrial Technical Physics Institution: UNIVPM, College of Engineering Email: s.tomassetti@univpm.it Research Interests include: Solar energy systems, particularly solar cookers and dryers Thermophysical properties of low-GWP refrigerants Phase change materials for thermal storage Machine learning applications in thermal conductivity modeling Thermodynamic equilibrium in industrial fluids Experimental validation of energy systems Publications Trends show consistent focus on renewable energy technologies (2017-2025), with recent emphasis on low-GWP refrigerants and solar cooker innovations . His work combines experimental analysis with machine learning modeling , addressing both industrial thermodynamics and sustainable energy solutions . Contact: s.tomassetti@univpm.it

• Computer Vision
• Robotics
• Drone Technology
• +3 more

Halar Haleem is a Research Fellow at the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) within the University of Genoa. Their research spans interdisciplinary domains at the intersection of computer vision, robotics, drone technology, and wireless systems. Academic Rank: Research Fellow Affiliation: University of Genoa, Department of Naval, Electrical, Electronic, and Telecommunications Engineering Contact: halar.haleem@edu.unige.it Research interests focus on drone technology , computer vision , and wireless surveillance systems . They explore applications in traffic monitoring, aerial object detection, and energy-efficient drone operations, with recent work on AI-enabled medical IoT and biomechanical monitoring using smart glasses. Key article trends include: Drone-based traffic analysis using deep learning and image segmentation Privacy-preserving Wi-Fi monitoring systems Monocular vision for activity recognition in makerspaces RF/WiFi signal utilization for UAV surveillance Energy-accuracy trade-offs in drone video processing Trimetallic nanoparticle electrocatalysts for hydrogen production

Lucio MarcenaroView profile

Associate Professor

• Autonomous Systems
• Bayesian Inference
• Signal Processing
• +7 more

Lucio Marcenaro is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, where he serves as Coordinator of the Bachelor's Degree Course in Electronic Engineering and participates in university research committees. His teaching responsibilities span undergraduate and graduate programs including Fundamentals of Telecommunications and Signal Processing, Multimedia Signal Processing for Autonomous Systems, and Pervasive Dynamic Electronics across Computer Science, Electronic Engineering, and Internet and Multimedia Engineering curricula. His research centers on autonomous systems with emphasis on Bayesian inference frameworks and active inference methodologies. Key investigation areas include vehicle localization using dynamic Bayesian networks, anomaly detection in vehicular networks through generative models, UAV trajectory optimization, and resource allocation in cognitive radio systems. His work integrates signal processing, machine learning, and robotics to develop self-aware systems capable of real-time adaptation in dynamic environments, particularly focusing on explainable AI implementations for autonomous agents. Analysis of his 2024-2025 publications reveals a dominant trend toward generative Bayesian models for autonomous systems, with consistent application across autonomous vehicles, UAV networks, and intelligent radios. His research demonstrates strong interdisciplinary integration of probabilistic modeling with physical layer implementations, showing particular innovation in explainable decision frameworks and anomaly detection systems that bridge theoretical AI with practical engineering constraints in mobile networks.

Giuliano VernengoView profile

Associate Professor

• Naval Architecture
• Marine Hydrodynamics
• Seakeeping
• +5 more

Giuliano Vernengo is an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa. He teaches Experimental Naval Architecture, Ship Dynamics, Geometry of Floating Bodies, and Yacht Dynamics for Master's programs in Naval Engineering and Yacht Design. His research centers on Naval Architecture and Marine Hydrodynamics , with emphases on seakeeping , ship resistance , computational fluid dynamics , and yacht design . He develops advanced numerical methods for hydrodynamic analysis while pioneering AI integration in maritime applications like wake detection and metocean data processing. His work bridges theoretical modeling with practical ship design optimization. Analysis of recent publications (2022-2025) reveals three dominant research thrusts: (1) AI-enhanced maritime surveillance (UEIKAP framework for satellite-based wake detection), (2) Advanced CFD methodologies for ship hydrodynamics and optimization, and (3) Renewable energy applications including floating wind turbine stability. His interdisciplinary approach combines fluid dynamics, AI, and naval structural analysis. Dr. Vernengo actively collaborates on international projects involving ship performance prediction, submarine maneuverability, and hydrofoil propulsion systems. His research demonstrates strong industry relevance for naval architects, maritime safety agencies, and renewable energy developers.

Jacopo AleottiView profile

Associate Professor

• Robotics
• Computer Graphics
• Virtual Reality
• +3 more

Jacopo Aleotti is an Associate Professor at the Department of Engineering and Architecture, University of Parma. His research focuses on robotics, computer graphics, and virtual reality, with significant contributions to robot perception, haptic interfaces, and 3D reconstruction. Graduated in Electronic Engineering (2002), University of Parma PhD in Information Technology (2006), University of Parma From 2003 to 2006, he was a Marie Curie Fellow at Orebro University and a postdoctoral fellow at the University of Parma's Department of Information Engineering. His research interests include robotics , computer graphics , and virtual reality , with applications in industrial automation, haptic teleoperation, and 3D scene understanding. His recent publications explore topics like probabilistic motion planning, sensor fusion for VR tracking, and deep learning for object pose estimation. Notable scientific awards include the MIMOS award (2006) and the Marie Curie Fellowship (2003) . He leads research at the Robotics Laboratory (RimLab) at the University of Parma, contributing to projects involving autonomous systems, augmented reality interfaces, and underwater robotics. His teaching includes courses on object-oriented programming and virtual reality systems.

• Control Systems
• Robotics
• Optimization
• +3 more

Luca Consolini is an Associate Professor at the Department of Engineering and Architecture , University of Parma. His academic career focuses on Control Systems , Robotics , and Optimization , with applications in Pharmacokinetics , Intelligent Vehicles , and Mechanical Engineering . Teaching courses like Model Identification and Data Analysis and Control Systems for Industrial Automation for Master's Degree in Computer Engineering and Mechanical Engineering cohorts since 2013. Research spans Virtual Holonomic Constraints , Multi-Agent Pathfinding , and Speed Planning with applications in anesthesia, autonomous vehicles, and industrial automation. Recent publications (2024-2025) emphasize PK/PD modeling , traffic estimation , and nonlinear control . No scientific awards or advising details were explicitly mentioned in the provided texts.

• Operations Research
• Combinatorial Optimization
• Vehicle Routing Problems
• +6 more

Demetrio Salvatore LAGANA' is an Assistant Professor in Operations Research at the Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria , Italy. He has been teaching courses in Operations Research, Optimization, and Transport Systems since 2003 and has held visiting researcher positions at Georgia Tech, HEC Montréal, and University of Valencia. He supervises multiple PhD and Master’s students, collaborates internationally, and serves on scientific committees and editorial boards. Education : Master’s in Engineering (1992, Università Mediterranea di Reggio Calabria); Graduate School in Transport Terminal Infrastructures (1996, Università Federico II di Napoli); PhD in Operations Research (2006, University of Calabria). Research interests focus on combinatorial optimization and logistics , particularly arc routing problems , general routing problems , and inventory routing problems under deterministic and stochastic conditions. He develops algorithms for vehicle routing, supply chain optimization, and sustainable logistics, addressing constraints like capacity, time windows, and stock-out penalties. Recent publications highlight trends in multi-vehicle inventory routing , dynamic programming , stochastic optimization , and green logistics , including applications in bike-sharing systems, autonomous delivery robots, and integrated supply chain models. His work integrates exact methods, heuristics, and hybrid approaches. Academic responsibilities include membership in PhD committees (Mathematics and Computer Science, University of Calabria) and editorial boards (Advances in Operations Research, Hindawi). He has co-authored over 20 peer-reviewed articles and led research projects funded by national grants.

Maurizio RighettiView profile

Professor

• Hydraulic Engineering
• Water Resources Management
• Climate Change Impacts
• +2 more

Maurizio Righetti is a Full Professor at the Free University of Bozen-Bolzano within the Faculty of Agricultural, Environmental and Food Sciences. His research integrates hydraulic engineering, climate change adaptation, and sustainable water management, with a focus on Alpine environments. Research Interests: Righetti's work spans: Hydraulic systems optimization (e.g., sediment flushing, water distribution networks) Climate model bias correction for hydrological forecasting Renewable energy integration in water infrastructure Machine learning applications in ecohydraulics and resource management Impacts of hydropeaking and climate change on river ecosystems Recent Publications: His 15 most recent articles (2024-2025) demonstrate strong trends in: sediment dynamics modeling, AI-driven leak detection in water networks, climate data processing, and hybrid energy-water systems. Over 60% leverage machine learning, reflecting a shift toward data-centric environmental solutions. Engagement: He co-founded AIAQUA (unibz's water management spin-off) and leads public initiatives like "Action For Climate" to address climate-water linkages in Alpine regions.

Grimaldi GaiaView profile

Associate Professor

• Superconductivity
• Condensed Matter Physics
• Vortex Dynamics
• +4 more

Dr. Grimaldi Gaia serves as a Researcher III at the CNR-SPIN Institute (National Research Council of Italy) within the Department of Physical Sciences and Technologies of Matter, holding National Scientific Qualification as Associate Professor since 2018. She leads multiple national projects including PRIN PNRR 2022 as Principal Investigator and coordinates the SPIN Institute's Research Activity Theme on Superconductors for Energy Applications. Her laboratory leadership includes scientific responsibility for the MaSTER Lab equipped with a 16T Cryogen-Free Magnetic system and dilution refrigerator. Her educational background includes a Master's degree in Physics (110/110 with honors) and PhD in Physics from the University of Salerno, with doctoral research conducted at ENEA Frascati and Technical University of Munich. She has taught specialized courses including Superconductivity and Low-Temperature Physics at the university level. Dr. Grimaldi's research focuses on experimental superconductivity , particularly vortex dynamics in high-temperature superconductors under extreme conditions. Her work examines nonlinear dissipations in I-V characteristics to map magnetic field-temperature phase diagrams, investigate order-disorder transitions in Abrikosov vortex lattices, and analyze pinning influences on vortex dynamics. She specializes in electrical transport measurements at high currents and dissipation regimes to study high-speed vortex behavior. Analysis of her recent publications reveals consistent focus on iron-based superconductors (Fe(Se,Te)) and REBCO tapes , with emphasis on flux pinning mechanisms, critical current optimization, and dimensionality effects. Her work bridges fundamental physics with energy applications, particularly in quench current analysis for large-scale superconducting systems. Her technical expertise encompasses Vacuum and cryogenic measurement techniques LabView and Object-Bench programming for instrument control Electrical/structural characterization of superconducting films UV photolithography and CAD mask design Critical current measurements via Hall probe magnetometry Vibrating Sample Magnetometer analysis Dr. Grimaldi has secured substantial research funding including €216,654 for the PRIN PNRR 2022 project 'QUESTIONs' and managed multi-million euro collaborations with ENI and Joint Research Agreements. Her leadership extends to Institute Councilor responsibilities (2020-2024) and coordination of regional projects funded by Regione Campania. She directs the MaSTER Lab featuring advanced capabilities including: 16T Cryogen-Free Magnetic system Dilution refrigerator Double-axis rotator Thermo-electric effects measurement inserts supporting her research on superconductors for energy production, transport, and storage applications.

Fabio PolonaraView profile

Professor

• Thermal Engineering
• Heat Pump Systems
• Energy Efficiency
• +5 more

Prof. Fabio Polonara serves as a Full Professor at Universita Politecnica delle Marche (UNIVPM) within the Department of Industrial Engineering and Mathematical Sciences (DIISM). His academic specialization falls under the scientific sector IIND-07/A - Industrial Technical Physics, with his office located at Via Brecce Bianche where he maintains regular Wednesday office hours from 9:00-11:00. Prof. Polonara's research program centers on thermal energy systems optimization , with particular expertise in heat pump technologies, building energy management, and sustainable cooling solutions. His work spans from fundamental thermodynamic studies to system-level optimization of multi-energy networks, with increasing focus on energy flexibility in residential building clusters. His research methodology frequently employs multi-objective optimization techniques that consider the complex interplay between design parameters and control strategies in thermal systems. Analysis of Prof. Polonara's publication trajectory reveals a clear evolution from component-level investigations (such as capillary tube dynamics and refrigerant properties) toward integrated system analyses. His recent work demonstrates growing emphasis on the role buildings can play in grid stability through demand response, with particular attention to how long-term refurbishment strategies impact the energy flexibility potential of the Italian building stock. His research increasingly incorporates artificial intelligence techniques, particularly neural networks, for model predictive control in complex multi-energy systems. Prof. Polonara maintains active research in regional climate modeling specific to the Adriatic coast, demonstrating his commitment to understanding local environmental conditions that influence building energy performance. His work on sea-breeze patterns along the middle Adriatic coast provides context for his building energy research in the Marche region where UNIVPM is located.

• Financial Mathematics
• Investment Analysis
• Capital Budgeting
• +4 more

Carlo Alberto MAGNI is a Full Professor in the Department of Economics "Marco Biagi" at the University of Modena and Reggio Emilia. He teaches courses including General and Financial Mathematics and Principles and Models for Managerial Decisions for the Business Economics and Management degree program. Professor MAGNI's research focuses on financial mathematics, investment analysis, and capital budgeting. His work centers around the development of the Split-Screen Approach for project appraisal, which unifies financial planning and investment analysis into a single theoretical framework. His research spans corporate finance, accounting, operations research, and mathematical methods of economics, with particular emphasis on NPV-consistency of rates of return, project valuation methodologies, and financial modeling techniques. His publication record shows a consistent output of high-quality research, with numerous articles in top journals. His work demonstrates a strong integration between theoretical finance concepts and practical applications, particularly in Excel-based financial modeling. The Split-Screen Approach represents his signature contribution to the field, providing innovative methods for project appraisal and financial planning. Professor MAGNI has developed comprehensive teaching materials, including a videobook for his courses that combines video lectures with texts related to course topics. His educational approach emphasizes the application of mathematical tools in economic and business analysis, with focus on developing students' ability to model and evaluate long-term managerial decisions.

• Numerical Analysis
• Optimization
• Machine Learning
• +5 more

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

• Recommender Systems
• Machine Learning
• Information Retrieval
• +3 more

Ludovico Boratto is an Associate Professor of Computer Science at the University of Cagliari, Italy. His research focuses on recommender systems , particularly fairness, bias mitigation, and beyond-accuracy evaluation metrics. He has published over 60 papers in top-tier venues and contributed to book editing and journal editorial boards. Education: Ph.D. in Computer Science (2012, University of Cagliari) Prior Affiliation: Senior Research Scientist at Eurecat (2016–2021) His recent work explores fairness in graph neural networks (GNNs), privacy-preserving recommendation, and knowledge graph integration for explainability. He has co-organized workshops like RecSoGood 2024 and IRonGraphs 2024, emphasizing algorithmic accountability and robustness. Highlights of recent publications include fairness-aware GNNs, federated learning for privacy, and explainable educational recommendation frameworks. His 15 most recent articles span 2024–2025, reflecting trends in ethical AI and graph-based approaches. Eight outstanding contribution awards from ACM conferences Editorial roles at Information Processing & Management (Elsevier) and Journal of Intelligent Information Systems (Springer)

• Artificial Intelligence
• Machine Learning
• Robotics
• +5 more

Raffaello Camoriano is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Polytechnic University of Turin. He is also an Affiliated Researcher at the Istituto Italiano di Tecnologia. His academic work spans multiple roles including serving as an Editorial Board Member for MACHINE LEARNING journal (since 2024) and Associate Editor for IEEE ROBOTICS AND AUTOMATION LETTERS (since 2022). He is an active member of IEEE Robotics and Automation Society (since 2024) and ELLIS - European Laboratory for Learning and Intelligent Systems (since 2022). Dr. Camoriano's research focuses on the intersection of artificial intelligence, machine learning, and robotics. His work particularly emphasizes robot learning, incremental/lifelong learning, structured learning, and kernel methods. His research has significant applications in medical robotics, particularly in laser-based skincare procedures and prosthetic control systems. He has developed innovative approaches for federated learning, point cloud processing for robotics, and trajectory generation for humanoid robots. His work bridges theoretical machine learning with practical robotics applications, addressing challenges in resource efficiency, adaptation to changing environments, and human-robot interaction. His recent publications demonstrate a strong trajectory in advancing federated learning techniques, with particular emphasis on resource-efficient personalization and handling heterogeneous data. He has made significant contributions to robotics applications including upper-limb prosthetics using high-density sEMG, autonomous navigation using point clouds, and medical robotics for laser procedures. His work consistently combines theoretical machine learning advances with concrete robotics applications, showing expertise in both domains. Best PhD Thesis Award of the Computational Intelligence Society Italy Chapter 2017 Dr. Camoriano actively supervises PhD students in the Intelligenza Artificiale program, including Stephany Ortuno Chanelo, Andrea Protopapa, and Leonardo Iurada. He has led research projects including the ECML-PKDD 2023 International Workshop 'Adapting to Change: Reliable Learning Across Domains' and the International Workshop 'Learning Meets Model-based Methods for Manipulation and Grasping' (2023). His teaching portfolio includes Fundamentals of Artificial Intelligence, Machine and Deep Learning, and Algorithms and Programming across multiple engineering programs at Polytechnic University of Turin.

Lorenzo SeidenariView profile

Associate Professor

• Computer Vision
• Deep Learning
• Generative AI
• +4 more

Lorenzo Seidenari is an Associate Professor of Computer Engineering at the Department of Information Engineering, University of Florence . He earned his PhD in Computer Engineering (2012) and MEng in Artificial Intelligence (2008) from the University of Florence. As a member of the UNIMORE ELLIS Unit, he contributes to European AI excellence, and co-founded the startup Small Pixels for video processing solutions. PhD in Computer Engineering, University of Florence (2012) MEng in Artificial Intelligence, University of Florence (2008) His research focuses on deep learning applications in computer vision and robotics , particularly generative AI , model uncertainty , and robustness . Recent work includes trajectory forecasting for autonomous systems, 360° video streaming optimization, and synthetic data generation. Key projects like WILD.AI and IMRA-SD address real-world challenges in biodiversity monitoring and multi-agent prediction. Recent publications highlight trends in generative adversarial networks (GANs) , spatio-temporal modeling , and autonomous driving applications. He has received the ELLIS Scholar award and holds habilitations from MIUR for associate professorship in both Computer Science (01/B1) and Computer Engineering (09/H1). As a conference area chair for ACM MM and BMVC, he actively shapes AI research discourse.