Find Academic Supervisors

Stefano Alberto MalanView profile

Assistant Professor

• Automatic Control
• Control Engineering
• Systems Engineering
• +10 more

Stefano Alberto Malan is a Tenured Assistant Professor at the Department of Electronics and Telecommunications (DET) , Politecnico di Torino, and a member of the CARS@PoliTO - Center for Automotive Research and Sustainable Mobility . His academic rank is Assistant Professor in the scientific disciplinary sector IINF-04/A - Systems and Control Engineering (Area 0009 - Industrial and Information Engineering). Educational Background : Laurea in Electrical Engineering (1988) from Politecnico di Torino. Control Engineer at FIAT Research Center (1988-1990). Research Interests : Stefano's work spans Automatic Control , Control Systems Engineering , and Dynamic Modeling , with a focus on model-based and sensor-based algorithms for combustion and emission control in diesel engines and Direct Virtual Sensors . He contributes to Robust Control via uncertainty model sets identification, Building Energy Management (e.g., WiFi4Energy, EcoThermo projects), and Automotive Systems (chassis dynamics, engine controls). His methodologies include Computer-Aided Control System Design using H-infinity and interval arithmetic, and Multi-objective Robustness Analysis . Article Trends : His publications since 2015 emphasize Control Systems (e.g., LiDAR for UAS precision spraying), Diesel Engine Emissions Management , Virtual Sensor Design , and Sustainable Mobility . Recent works integrate Machine Learning (e.g., recurrent neural networks) and Optimization Techniques (e.g., genetic algorithms) into automotive and energy systems. Teaching Contributions : He has taught Automotive Control Systems (2019–2025) and Automation and Planning of Production Systems (2020–2021) at Politecnico di Torino’s Master of Science in Computer Engineering . He is a member of the College of Computer, Film and Mechatronics Engineering . Patents : Co-inventor of two national patents: Gruppo contabilizzatore per impianti termici di riscaldamento o raffrescamento (2013, heating/cooling metering unit). Metering unit for heating or cooling systems (2010, PCT/IB2009/055912). Laboratories and Teams : Active in the Automatica Research Group at DET and the CARS@PoliTO center, Stefano collaborates on projects like WiFi4Energy and EcoThermo to advance sustainable mobility and energy efficiency.

• Radiation Dosimetry
• Medical Physics
• FLASH Radiotherapy
• +7 more

Maurizio Marrale serves as Associate Professor in the Department of Physics and Chemistry at the University of Palermo (Unipa), holding position PHYS-06/A. His office is located at the Department of Physics and Chemistry "Emilio Segre" (DIFC), Viale delle Scienze, Building 18, with regular office hours on Thursdays from 3:00 PM to 5:00 PM. His research spans radiation dosimetry, medical physics, and advanced imaging techniques. Key focus areas include FLASH radiotherapy verification using alanine/EPR dosimetry and silicon carbide detectors, transcranial magnetic resonance-guided focused ultrasound for neurological disorders (particularly essential tremor), and MRI-based dosimetry with Fricke gels. His work bridges physics principles with clinical applications in radiation oncology and diagnostic imaging. Analysis of his 15 most recent publications reveals strong emphasis on Ultra-high dose rate (UHDR) beam characterization for FLASH radiotherapy Development of novel dosimetry systems (SiC detectors, ionoacoustic sensors) Advanced neuroimaging techniques for thalamic targeting Diffusion correction methodologies in 3D dosimeters Clinical MRI applications for neurological disorders His research demonstrates consistent integration of computational modeling (Geant4, deep learning) with experimental validation. As principal supervisor, he has guided over 35 master's theses at Unipa between 2009-2024, primarily in Physics and Medical Radiology Techniques programs. His supervisory work focuses on radiation dosimetry applications, MRI physics, and radiotherapy technology validation.

• High Performance Computing
• Embedded Systems
• Medical Imaging
• +4 more

Elisa Marenzi is an Assistant Professor at the University of Pavia's Department of Industrial and Information Engineering. She holds a PhD in Bioengineering and Bioinformatics (2014) and master's/bachelor's degrees in Biomedical Engineering from the same institution. Her research focuses on High Performance Computing (HPC), embedded systems for biomedical monitoring, signal processing in rehabilitation/automotive fields, and cerebellar neural circuit modeling. Education: PhD in Bioengineering (2014): Thesis on pressure ulcer monitoring systems Master's in Biomedical Engineering (2010): Thesis on capacitive sensor systems Bachelor's in Biomedical Engineering (2007): Thesis on medical guideline formalization Research Highlights: Her work spans HPC optimization for hyperspectral imaging, wearable medical devices, and neurocomputational modeling of cerebellar circuits. Notable contributions include: STRATUM project: AI-driven 3D decision support tools for neurosurgery HBP (Human Brain Project) simulations of hippocampal dynamics Hyperspectral imaging applications in skin cancer diagnosis FPGA-based real-time medical signal processing systems Awards: ETIC Award (2014) for PhD thesis Lifebility Award (2012) for social tech innovation NVIDIA GPU Research Center accreditation (2016) Professional Activities: She has held roles including Systems Administrator (2020-2023) and post-doctoral research in neurocomputation (2017-2019). Active in editorial roles for Microprocessors and Microsystems and Frontiers in Computational Neuroscience. Co-chair for ASHWPA special session at Euromicro DSD 2024. Labs/Teams: Key affiliations include the Neurocomputation Laboratory (DBBS) and collaboration with NVIDIA GPU Research Center.

• Computer architectures and Computer aided design
• Data science
• Computer vision and AI
• +3 more

Walter Gallego Gomez is a PhD Student in Computer and Systems Engineering (39th cycle, 2023-2026) and an External Lecturer/Teaching Assistant at the Department of Control and Computer Science (DAUIN) of the Polytechnic University of Turin. His academic and research journey is supported by an EBRAINS-Italy research grant. Bachelor's in Electronic Engineering (University of Antioquia, 2015) Master's in Computer Engineering (Polytechnic University of Turin, 2018) His research intersects life sciences and computer science, focusing on bioinformatics algorithms, neuromorphic hardware (Loihi2/Lava), and their implementation. He collaborates with the Electronic Design Automation (EDA) group and external entities like Candiolo Oncology Center and Telluride Neuromorphic Cognition Engineering workshop. Teaching roles include System-on-chip architecture (2024/25) and Applied AI and machine learning (2023/24-2024/25) as a course collaborator. Recent publications highlight trends in somatic structural variant detection and neuromorphic ecosystem benchmarking. His work spans automotive embedded systems (Marelli, 2018-2021), academic research assistantship (2021-2023), and interdisciplinary collaborations.

• Algorithms
• Optimization
• Mathematical Programming
• +2 more

Federico Della Croce Di Dojola is a Full Professor at the Department of Management and Production Engineering (DIGEP) of Politecnico di Torino. He is also a member of the Interdepartmental Center Ec-L - Energy Center Lab. His academic career spans over two decades with international collaborations including a Visiting Researcher position at Université Paris Dauphine (2004-2005). Research Interests focus on algorithm development and optimization techniques, particularly in combinatorial optimization. His work applies to diverse areas including operations research, production scheduling, and mathematical programming, with connections to sustainable cities and communities (SDG Goal 11). Publications demonstrate expertise in exact algorithms, heuristic methods, and scheduling problems across multiple domains. Key contributions include advancements in transportation optimization, bilevel scheduling, and fuel treatment planning. Scientific Recognition : Member of Editorial Board, European Journal of Operational Research (2016-) Member of Editorial Board, Computers & Operations Research (2016-) Principal investigator in multiple research projects Academic Leadership includes: Director of Department of Control and Computer Science (2012-2015) Doctoral College Member (2003-2025) Course Lecturer at multiple degree levels PhD Supervision includes Quentin Schau (2024-in progress) focusing on Industry 4.0 scheduling problems.

• Additive Manufacturing
• Materials Science
• Finite Element Analysis
• +6 more

Francesca Campana is a Full Professor at Sapienza University of Rome, specializing in advanced manufacturing technologies and materials science. Her research focuses on additive manufacturing (e.g., L-PBF processes), material characterization, and biomechanical applications. She has pioneered studies on multi-material junctions, generative design approaches, and virtual reality systems for surgical planning. Her work integrates computational tools such as finite element analysis and machine learning to optimize material performance and design workflows. Key contributions include developing methodologies for optimizing L-PBF parameters, analyzing lattice structures, and applying generative design to cultural heritage conservation. Her research bridges engineering disciplines, addressing challenges in medical devices, aerospace components, and historical artifact restoration. Publications highlight trends in additive manufacturing workflows, material behavior under dynamic conditions, and the integration of AI into design processes. Awards and grants are not explicitly listed in the provided texts.

• Machine Learning
• Computer-Aided Design (CAD)
• Embedded Systems
• +3 more

Nicolo' Bellarmino is a Research Fellow and Research Assistant at the Department of Automatic Control and Computer Science (DAUIN) of Politecnico di Torino. His roles include teaching and collaborating in courses such as System Programming, Computer Science, and Future of Work across Computer Engineering and Aerospace Engineering programs. He is affiliated with the CAD - Electronic CAD & Reliability Group (DAUIN), focusing on research in machine learning, embedded systems, and hardware testing. His research interests center on computational intelligence applied to computer-aided design, particularly in machine learning techniques for microcontroller performance screening. He has also explored neural network resiliency, fault detection in CNNs, and device-aware testing methodologies. Recent work emphasizes compressed sensing, feature selection, and transfer learning in resource-constrained systems. Bellarmino's publications span conference proceedings and journals, addressing challenges in embedded systems testing, neural network optimization, and biomedical applications like COVID-19 detection via exhaled breath analysis. His contributions bridge theoretical machine learning advancements with practical hardware validation and optimization. He actively contributes to academic teaching, maintaining an email contact at nicolo.bellarmino@polito.it for professional inquiries.

Aime LAY EKUAKILLEView profile

Associate Professor

• Biomedical Engineering
• Environmental Monitoring
• Industrial Measurements
• +3 more

Aime LAY EKUAKILLE is an Associate Professor at the University of Salento's Department of Innovation Engineering, part of the Ecotekne Center in Lecce, Italy. His expertise spans instrumentation and measurement systems for biomedical, environmental, industrial, nanotechnology, machine learning, and photovoltaic panel aging applications. He is involved in interdisciplinary projects, such as smart sensors for telemedicine, energy-efficient robotic systems, and geothermal probe design. His research integrates advanced signal processing (e.g., wavelet transforms, machine learning algorithms) with sensor technology to address challenges in healthcare, environmental monitoring, and renewable energy. He has contributed to hardware-software solutions like solar-powered spectrophotometers and anti-theft systems for photovoltaic plants. Collaborations include international initiatives in nanotechnology, wearable devices, and IoT-based tele-rehabilitation. Key projects include: Development of a robotic arm for ball bearing sorting using size measurements and RFID. Designing a distributed edge computing architecture for leak detection in waterworks. Optimizing fertilizer dosing in smart fertigation pipelines through modeling and control. Investigating the magnetic behavior of nanosized contrast agents for medical imaging. He has presented at conferences such as IEEE MeMeA (2020), I2MTC (2020), and EnvImeko (2019, 2017). His work is supported by grants like the Ministry of Health's GR-2016-02361306 and Guangdong Province's 2019B010150002.

Carolina Vittoria BeccariView profile

Associate Professor

• Geometric modeling
• Numerical methods for curves and surfaces
• Interpolation
• +4 more

Carolina Vittoria Beccari is an Associate Professor in the Department of Mathematics at the University of Bologna, Italy, a position she has held since October 2021. Previously, she served as Senior Assistant Professor (2018-2021) and Junior Assistant Professor (2014-2018) at the same institution. Her academic career includes several postdoctoral research fellowships at the University of Bologna in Mathematics, Physics and Astronomy, and the CIRAM (Interdepartmental Research Center for Applied Mathematics). Her educational background includes: Ph.D. in Computational Mathematics from the University of Padova, Italy (2007) M.Sc. in Mathematics from the University of Bologna, Italy (2003) Dr. Beccari's research focuses on geometric modeling, numerical methods for curves and surfaces, interpolation, subdivision schemes, splines, and computer-aided design. She has made significant contributions to the theory and application of Chebyshevian splines, multi-degree B-splines, and rational geometric splines. Her work bridges theoretical mathematics with practical applications in engineering and design, particularly in developing numerical methods that can automatically generate smooth boundary surfaces from tessellations produced by topological optimization. Her research interests also extend to approximation theory and the integration of advanced mathematical techniques into CAD systems. Analysis of her recent publications reveals a clear progression from foundational work on subdivision schemes to more sophisticated applications in topological optimization and industrial design problems. Her work demonstrates increasing sophistication in handling multi-degree splines and Chebyshevian spaces, with growing emphasis on practical applications in manufacturing and engineering design processes. Dr. Beccari has secured multiple research grants including the Alma Idea research grant (2022/23) for mathematical methods to enhance structural optimization of environmentally friendly transport vehicles, the Eurostars Project NIIT4CAD (2010/12), and the University of Bologna Strategic Project IT4CAD (2007/09). She has also participated in numerous research projects funded by INdAM-GNCS on spline regression, data processing, and approximation methods. She teaches multiple courses at the University of Bologna including Introduction to Numerical Methods, Numerical Methods M, and Analisi Numerica e Modellazione Geometrica across various engineering and design programs. Her teaching spans both undergraduate and graduate levels with courses offered in both Italian and English, reflecting her international academic engagement.

• Industrial Engineering
• Mechanical Design
• Computer-Aided Design (CAD)
• +7 more

Alberto Vergnano is an Associate Professor at the Department of Engineering 'Enzo Ferrari' at the University of Modena and Reggio Emilia. His academic roles include teaching courses such as Design and Modelling of Electronic Systems , Industrial Technical Design , and Design Methods for Vehicle Engineering . His research focuses on advanced manufacturing processes, occupant safety systems, and simulation-based design optimization. Education: Doctorate in Industrial Engineering (not explicitly stated, inferred from academic rank). Affiliations: Member of LaPIS Lab and contributor to the MASA (Modena Automotive Smart Area) project. Research Interests: Thermal management in additive manufacturing, occupant position detection for vehicle safety, casting process optimization, and reconfigurable manufacturing systems. Recent projects include lattice structure design for shock absorption, sensorized vehicle seats, and heat transfer modeling in sand casting. Publications: Over 30 peer-reviewed articles and conference papers since 2019, emphasizing simulation-driven design and safety engineering. Key themes include occupant safety systems, die casting optimization, and smart manufacturing. Labs/Teams: Active in the LaPIS Lab, focusing on design tools and methods. Collaborates with industry partners on automotive and aerospace projects.

• Additive Manufacturing
• Automotive Engineering
• Design Optimization
• +3 more

Francesco LEALI is a Full Professor at the Department of Engineering 'Enzo Ferrari' of the University of Modena and Reggio Emilia. His research focuses on Additive Manufacturing, Automotive Engineering, and Design Optimization, with applications in materials science and industrial processes. He teaches courses such as "Total Quality Management Oriented Design" and "Vehicle Conceptual Design" in the Master's programs of Mechanical Engineering and Advanced Automotive Engineering. Research Interests: Professor LEALI's work emphasizes sustainable design methodologies, advanced manufacturing processes (e.g., die casting, powder bed fusion), and the integration of sensor technologies in automotive safety systems. He has pioneered studies on multifunctional lattice structures for thermal management and shock absorption, as well as tolerance allocation and process simulation for automotive components. Publications: His recent articles address topics like additive manufacturing optimization, robust die casting processes, and sensorized seat systems for occupant safety. These contributions highlight advancements in manufacturing efficiency, material performance, and human-centric automotive design. Labs/Teams: His research is conducted within the Department of Engineering's facilities, collaborating with industry partners to bridge academic innovation with real-world applications in automotive and sustainable mobility sectors.

• Machine Learning
• Artificial Intelligence
• Medical Image Analysis
• +7 more

Francesco Ponzio is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, where he contributes to teaching and research in information processing systems. He is actively involved in multiple engineering programs, including Computer, Aerospace, and Management Engineering. University: Politecnico di Torino Department: Department of Control and Computer Engineering (DAUIN) Role: Fixed-term Assistant Professor Scientific Sector: IINF-05/A - Information Processing Systems Francesco Ponzio's research spans artificial intelligence and machine learning with applications in medical imaging, industrial automation, and smart manufacturing. His work integrates advanced computational models into real-world systems, particularly in healthcare and advanced manufacturing. His recent publications reveal a strong trend toward interdisciplinary research, combining deep learning, radiomics, and physics-informed neural networks to address challenges in biomedical diagnostics and industrial process optimization. Notably, his work in histopathological image analysis, tumor classification, and real-time anomaly detection highlights his expertise in both algorithmic development and practical deployment. Francesco Ponzio has contributed to high-impact journals and top-tier conferences such as IEEE ETFA, DAC, DATE, and Frontiers in Oncology. His recent work includes journal articles in Journal of Intelligent Manufacturing and Scientific Reports , as well as conference papers in ACM/IEEE Design Automation Conference and IEEE ICIT. He has served as a course collaborator for Machine Learning in Applications and as a lecturer and collaborator in foundational computer science courses across various engineering disciplines. He is also an invited member of two degree program councils, reflecting his institutional engagement. francesco.ponzio@polito.it

Primo ZingarettiView profile

Professor

• Artificial Intelligence
• Computer Vision
• Neural Rendering
• +5 more

Primo Zingaretti serves as a Full Professor in the Department of Information Engineering at Marche Polytechnic University's School of Engineering. His academic position focuses on information processing systems within the IINF-05/A scientific sector, maintaining an active research profile with publications extending into 2025. Contact information shows his office is located at via Brecce Bianche in Ancona, Italy, with professional correspondence handled through p.zingaretti@univpm.it. Zingaretti's research spans multiple cutting-edge domains where artificial intelligence intersects with practical applications. His primary focus areas include neural rendering for cultural heritage preservation and fashion technology, augmented reality systems development, and computer vision applications in retail environments. His work demonstrates strong interdisciplinary connections between engineering, cultural studies, and commercial applications. The research portfolio shows particular emphasis on ethical considerations in AI deployment, especially for heritage preservation and creative industries. Analysis of his recent publications reveals a clear trajectory toward practical AI implementations. His 2024-2025 work shows increasing focus on real-time rendering efficiency, ethical frameworks for extended AI, and specialized applications in retail monitoring and cultural heritage protection. The publications demonstrate consistent methodological rigor with strong emphasis on neural network optimization and practical system deployment, particularly in the Italian context including Marche region heritage sites. Zingaretti has developed significant research infrastructure including the open-source DeepReality framework for AI-based AR applications and the SIGNIFICANCE platform for combating cultural heritage trafficking. His work bridges academic research with commercial applications, particularly in retail technology where his shelf monitoring systems and shopper behavior analysis tools show direct industry relevance. Current projects indicate active development in neural rendering systems for fashion design and context-aware generative AI for XR environments.

• Multimedia Data Management
• Collaborative Filtering
• Similarity Search
• +5 more

Ilaria Bartolini is a Full Professor at the University of Bologna's Department of Computer Science and Engineering, specializing in multimedia data management and preference learning. She coordinates the MultiMedia Database Group and leads the PhD Programme in Computer Science and Engineering. Her research focuses on similarity search, collaborative filtering, and applications in cultural heritage and health domains. Education: Laurea in Computer Science (1997), University of Bologna PhD in Electronic and Computer Science Engineering (2002), University of Bologna Research Interests: Her work spans multimedia systems, data curation, and AI-driven solutions for healthcare and cultural heritage. She collaborates with institutions like HKUST, NJIT, and the European Processor Initiative, leading projects such as DETECt (EU H2020) and S-PIC4CHU (PRIN 2022). Grants & Projects: EU H2020 DETECt (2018–present): Transcultural crime narrative analysis PRIN 2022 S-PIC4CHU (2024–present): Data science integrity GenData 2020, WISDOM, COOPERARE (Italian national projects) Teaching: Leads courses on web applications, multimedia data management, and digital humanities at the undergraduate and graduate levels. Her educational framework emphasizes active e-learning through tools like ALDO. Labs & Teams: Directs the MultiMedia Database Group, fostering interdisciplinary research in data science and AI applications.

• Advanced Manufacturing
• Sustainable Manufacturing
• Industry 5.0
• +3 more

Alessandro Simeone is an Associate Professor at Politecnico di Torino, affiliated with the Department of Management and Production Engineering (DIGEP) and College of Management and Production Engineering. His research focuses on advanced and sustainable manufacturing with particular emphasis on Industry 5.0, human-centric approaches, and AI integration. Faculty member since 2021 Researcher in Manufacturing Technologies and Systems Teaching roles across Biomedical Engineering and Management Engineering programs Key research areas include sustainable manufacturing systems, inclusive production strategies, and AI-driven process optimization, with specific attention to SDG goals 3 (Health), 8 (Decent Work), 10 (Equality), and 13 (Climate Action). His recent publications demonstrate strong focus on AI applications for manufacturing inclusivity, particularly for neurodiverse operators, and sustainable production optimization. Notable works include AI-based assistance systems for assembly and smart approaches to waste reduction. Teaching activities span multiple courses across academic years 2021-2025, including: Sustainable Manufacturing (2024-2025) Manufacturing Technologies and Processes (Biomedical Engineering) Analysis and Management of Production Systems Designing Diversity PhD course collaboration As thesis supervisor for Yuchen Fan's PhD in Management and Production Engineering (39th cycle, 2023-ongoing), he continues to shape next-generation manufacturing research.