Matteo Davide Lorenzo Dalla Vedova is an Assistant Professor at the Polytechnic of Turin in the Department of Mechanical and Aerospace Engineering (DIMEAS) . He is a member of the ASTRA research group (Additive Manufacturing for Aerospace Systems) and the PhotoNext Interdepartmental Center for Applied Photonics. Research focuses: Aerospace systems engineering , FBG-based optical sensors , prognostic algorithms , and servomechanism analysis . Teaching roles: Main teacher for Advanced Numerical Modeling for Systems Engineering (PhD level) and collaborator for Aerospace Onboard Systems (Master's level). His work includes design of smart structures with multifunctional sensors, numerical simulations of aerospace systems, and development of prognostic algorithms . Publications include studies on FBG sensor integration , machine learning for actuator diagnostics , and fluid dynamics modeling . He collaborates with the ICARUS student team and contributes to regional and commercial research projects like FreME (Electromechanical Brake Systems) and Contactor Box Structural Analysis.
Francesco Di Gregorio is a Professor at the Department of Psychology 'Renzo Canestrari' within the Alma Mater Studiorum - University of Bologna . His research spans neuroscience, cognitive neuroscience, and neurorehabilitation, with a focus on error monitoring, neural oscillations, and brain-body interactions in neurological and psychiatric disorders. Research Highlights : Stroke recovery, EEG-based functional connectivity, transcranial magnetic stimulation (TMS), alpha rhythms in perception, pain diagnostics via wearable sensors, and metacognitive processes. Scientific Award : Royal Netherlands Academy of Arts and Sciences (KNAW) in 2025. Email : francesco.digregori5@unibo.it. His recent publications emphasize applications of TMS/EEG in understanding brain dynamics, biomarker development for disorders of consciousness, and neurophysiological underpinnings of schizotypy and spatial neglect.
Nicola Dilillo is a PhD Student in Computer and Systems Engineering (38th cycle, 2022-2025) at the Department of Control and Computer Science (DAUIN) of Politecnico di Torino. He also serves as an External Collaborator for Internationalization, Cooperation, Alliances and Mobility (INCAM) and as an External lecturer and/or teaching assistant at DAUIN. His educational background includes: Bachelor's degree in Computer Engineering (specializing in Embedded Systems) from Politecnico di Torino Master's degree in Computer Engineering (specializing in Embedded Systems) from Politecnico di Torino His research focuses on Smart Agriculture, integrating advanced technologies to address agri-food sector challenges. He develops AI and computer vision solutions for soil moisture prediction using recurrent neural networks (RNN, GRU, LSTM), multispectral imaging for crop health assessment, and deep learning for weed detection. His work aims to optimize resource use, increase yields, and reduce environmental impact through precision farming. His recent publications (2024-2025) demonstrate a strong trend in applying artificial intelligence to agricultural problems, particularly in soil moisture modeling, crop classification via spectral analysis, and sustainable practices using biofertilizers. The research spans computer vision, machine learning, and environmental science, highlighting interdisciplinary approaches for sustainable farming. No information on student advising or research grants was provided in the available text. He is an active member of the CAD - Electronic CAD & Reliability Group at DAUIN, contributing to research in electronic design and reliability.
Erich Malan is a PhD Student in Computer and Systems Engineering (2022-2025) at the Department of Control and Computer Science (DAUIN), Polytechnic University of Turin, where he also serves as an External Lecturer and Teaching Assistant. He holds an M.Sc. in Data Science and Engineering from the same institution (2021). His research focuses on developing efficient deep learning solutions for IoT networks, with expertise in: Distributed and federated learning optimization Communication efficiency for low-power IoT nodes Privacy-preserving techniques in edge computing Automated data annotation and security His publications concentrate on federated learning optimizations, featuring techniques like layer freezing, homomorphic encryption, and learning rate tuning to address challenges in edge computing environments. Awards include: Speaker recognition at IEEE ICECS 2024 Speaker recognition at IEEE ISLPED 2023 Teaching activities include serving as Course Collaborator for Computer Science courses in Aerospace Engineering and Computer Science Engineering programs. He conducts research with the Electronic Design Automation (EDA) Group at DAUIN.
Lorenzo Martini is a Research Fellow at the Department of Control and Computer Science (DAUIN) at Politecnico di Torino , with teaching roles as an external lecturer and teaching assistant. His research focuses on bioinformatics, computational biology, and machine learning applications in genomics and neuroscience. Research Groups: SMILIES (reSilient computer architectures and LIfE Sciences) Teaching: Courses in Computer Science, Aerospace Engineering, and Visualizing Quantitative Information (2022/23–2024/25). His work emphasizes multi-omic data integration , single-cell sequencing analysis , and neuronal heterogeneity investigation , leveraging genomic annotation databases and machine learning pipelines. Publications include methodological advancements like GAGAM and GRAIGH, alongside computational frameworks for neuronal spike shape analysis. Research Trends: Recent publications highlight applications in transcriptional regulation , cellular heterogeneity , chromatin accessibility , and neuronal subtyping , with tools like GAGAM and GRAIGH improving genomic data interpretation. Labs/Teams: SMILIES research group at DAUIN
Marco Mellia is a Full Professor at the Department of Control and Computer Science (DAUIN) of Politecnico di Torino, Italy, and a member of the Academic Senate. He serves as Coordinator of the Interdepartmental Center SmartData@PoliTO and Scientific Advisor for the Huawei partnership. His research focuses on Internet traffic analysis, cybersecurity, machine learning applications in network security, and data science. Artificial Intelligence Big Data Network Security Machine Learning His recent publications investigate topics like Telegram group dynamics, federated learning for network telescopes, darknet anomaly detection, and AI-driven sound-squatting prevention. These works span applications in cybersecurity, social networks, and network management. Marco Mellia has received numerous accolades including IEEE Fellow (2020), Applied Networking Research Prize (2013), and multiple best paper awards at IEEE ICDCS, ACM CoNEXT, and IEEE P2P. He advises PhD students in cybersecurity and data science, leads large-scale research projects (AI4CTI, XInternet, HPC4AI), and holds 13 patents. He has held visiting researcher positions at Carnegie Mellon University, Sprint AT Labs, Narus, Cisco Systems, and Federal University of Minas Gerais. Marco is Editor-in-Chief of Proceedings of the ACM on Networking and has chaired major conferences including ACM CoNEXT and IEEE TMA.
Alessandro Visconti is a PhD student in Computer and Systems Engineering (38th cycle, 2022-2025) at the Polytechnic University of Turin, affiliated with the Department of Control and Computer Science (DAUIN). He serves as an external lecturer and teaching assistant, actively contributing to academic instruction. BSc & MSc in Cinema and Media Engineering, Polytechnic University of Turin (2019, 2021) PhD candidate researching digital twinning, metaverse social interaction, and virtual presence Member of GRAINS (Graphics and Intelligent Systems) group and VR@POLITO lab His research focuses on advancing the Metaverse through consumer technology integration and AI-driven methods, aiming to enhance user immersion and social engagement in virtual environments. Key themes include real-time application development, facial mimicry synthesis, and social VR dynamics. His publications (2023-2025) demonstrate expertise in Metaverse architecture, VR education, and emotion conveyance through avatars. Awards include the 2024 IEEE ICIR Best Paper Award and top 10 most-cited recognition in 2025. 2024: Best Paper Award, IEEE ICIR 2025: Top 10 Most-Cited Publication, Computer Animation and Virtual Worlds Visconti teaches courses like Innovation Management & ICT Product Development, Object-Oriented Programming, and Data & Algorithms, while collaborating on interdisciplinary projects spanning aerospace and management engineering.
Francesco Manigrasso is a Research Fellow at the Department of Control and Computer Science (DAUIN) within Politecnico di Torino . He contributes to both research and teaching, serving as a course collaborator for multiple degree programs including Computer Engineering, Aerospace Engineering, and Management Engineering. Research Fellow, DAUIN (2020–present) Doctoral School (SCDOTT) affiliation Research Interests: Neuro-Symbolic Integration Machine Learning for Medical Imaging Logical Reasoning in LLMs High-Dimensional Data Interpretation Intelligent Systems Development Deep Learning Architectures Scientific Recognition: Co-inventor of national patent for multi-view mammography classification Academic Contributions: Active in teaching roles since 2020, with a focus on courses like Machine Learning for Vision and Multimedia and Introduction to Databases. His publication record demonstrates expertise in combining symbolic reasoning with deep learning approaches across multiple domains.
Stefano D'Ambrosio serves as a Full Professor in the Department of Energy (DENERG) at Politecnico di Torino, Italy. He is an active member of the Interdepartmental Center CARS@PoliTO (Center for Automotive Research and Sustainable Mobility) and affiliated with the College of Mechanical, Aerospace and Automotive Engineering. His academic career spans research, teaching, and industry collaboration in automotive engineering and energy systems. His primary research interests focus on combustion processes, diesel engines, internal combustion engines, and vehicle emissions. His scientific work falls under disciplinary sector IIND-06/A - Fluid Machinery within Area 0009 - Industrial and Information Engineering, with research lines centered on performance and emissions evaluation of internal combustion engines using conventional and alternative fuels. His expertise aligns with ERC sector PE8_5 covering fluid mechanics and various engine types. Professor D'Ambrosio has consistently contributed to doctoral education, serving on the Collegi of the PhD programme in ENERGETICA from 2019/2020 through 2024/2025. His teaching portfolio includes the Master's course 'Propulsion systems and their applications to vehicles' and the Bachelor's course 'Fundamentals of Fluid Machines' (previously 'Fundamentals of Machines and Hydraulics'). His publication record demonstrates focused research on alternative fuels (particularly HVO), engine emissions, and vehicle efficiency. Learning to Teach (L2T) - Issued by Politecnico di Torino on 09-07-2024 His work contributes to Sustainable Development Goals 4 (Quality education), 9 (Industry, Innovation, and Infrastructure), and 12 (Responsible consumption and production). Professor D'Ambrosio leads research projects including the Advanced Central Tire Inflation System (2016-2018) and holds multiple patents related to tire pressure systems, vehicle mass estimation, and centralized tire inflation technology, demonstrating strong industry connections and practical applications of his research.
Paolo Di Leo is an Associate Professor at the Polytechnic University of Turin within the Department of Energy (DENERG). His research focuses on photovoltaic systems , smart grids, and renewable energy integration, aligning with the IIND-08/B - Electrical Power Systems scientific sector. Research interests include: Photovoltaic Systems Smart Grids Wind Energy Energy Storage Grid Parity Analysis He contributes to the IEEE Transactions on Industry Applications and Solar Energy journals. Recent publications address self-sufficiency in PV systems, voltage control in low-voltage grids, and thermal-electrical modeling of PV modules. Teaching roles: Course Lecturer for Electrical System Design (2019–2025) Course Collaborator for Photovoltaic and Wind Power Generation (2019–2025) Research groups: GUSEE (DENERG) SOLAR (DENERG) Collaboration agreements include a 2017–2020 training initiative with the Order of Engineers of Turin as Scientific Director.
Tao Huang is an Associate Professor at the Department of Energy (DENERG) , Politecnico di Torino , Italy. His research focuses on Agent-based modeling , Complex networks , Energy digitalization , and Power systems economics . He contributes to interdisciplinary projects and teaches Power system economics at the PhD level and Smart grids , Energy networks , and Smart electricity systems at the master's level. Research Interests: Machine learning applications in energy systems, prosumer community modeling, digitalization of power networks, complex system analysis Awards: 2020 MIT A+B Applied Energy Symposium Best Paper Award Teaching: Course instructor for Power system economics (2021-2025), Energy networks (2022-2025), and collaborator in various energy-related courses Research Groups: GUSEE (Energy Systems) and LAME (Applied Mechanics)
Gianmario Pellegrino is a Full Professor at the Department of Energy (DENERG) , Polytechnic of Turin, Italy. He leads the Power Electronics Innovation Center (PEIC) and serves on the PoliTO Spin-Off Evaluation Commission. His research focuses on electric drives, electrical machines, power converters, and sensorless control , with industry collaborations spanning automotive and aerospace sectors. Professor of Power Converters, Electrical Machines, and Drives IEEE Senior Member and Associate Editor for IEEE Transactions on Industry Applications Research Interests include: Finite element analysis for motor design Optimization algorithms in SyR-e open-source platform Thermal management of high-performance motors Sensorless control techniques Recent Publications highlight advancements in: Thermal transient modeling for supercars Data-driven multi-physics simulations Active fault-reaction strategies Scientific Recognition: IEEE Fellow (2022) for Synchronous Reluctance machine contributions Eight Best Paper Awards and ECCE Third Prize (2011) Advising: Supervises 10+ PhD students in electrical engineering, focusing on motor design and control. Labs: Leads PEEMD research group and contributes to PCIM Europe advisory board.
Stefano Paolo Pastorelli is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin. He serves as Operating Project Manager for the Uzbekistan project and is a member of the Interdepartmental Center PIC4SeR (PoliTO Interdepartmental Centre for Service Robotics). His academic career spans over a decade at Politecnico di Torino, where he has been consistently involved in teaching Mechanical Engineering programs since at least the 2010/2011 academic year, and currently participates in doctoral colleges for Robotics and Intelligent Machines at both Politecnico di Torino and the University of Genoa. Professor Pastorelli's research spans multiple interconnected fields focused on human-centered robotics and biomechanics. His primary research interests include biomechanics, human movement analysis, wearable robotics, industrial robotics, human-machine interaction, mechatronics, adaptive sports, wheelchair technology, cobots, and human body modeling. His work bridges engineering with healthcare applications, particularly in developing assistive technologies for people with mobility limitations. He has extensive expertise in motion tracking systems, exoskeleton development, and wheelchair propulsion assistance technologies. His recent publications reveal a strong focus on applying machine learning and sensor technologies to human-robot interaction problems, particularly in the context of assistive devices. A significant portion of his work addresses wheelchair maneuverability and propulsion assistance, with multiple publications on power-assist devices and their control systems. His research also extends to exoskeletons, gesture recognition for human-robot collaboration, and biomechanical analysis of human movement in various contexts including electric scooter riding. Professor Pastorelli has supervised numerous PhD students including Francesco Crivellari, Giovanni Lando, Elena Caselli, Michele Polito, and Valerio Cornagliotto. His research is supported by multiple funded projects including EMPATHY (2024-2026), ADD-MATE 2.0 (2024-2025), HESTER (2023-2026), and ALBA (2021-2023), among others spanning from international collaborations to regional and corporate-funded research. He is actively involved in several research groups, most notably the Mechatronics and Servosystems group within DIMEAS. His work aligns with Sustainable Development Goals 3 (Good Health and Well-being), 9 (Industry, Innovation, and Infrastructure), and 11 (Sustainable Cities and Communities), reflecting the societal impact of his research in healthcare, industrial innovation, and urban mobility solutions.
Giuseppe Quaglia is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin, where he also serves as a Member of the Interdepartmental Center PIC4SeR (PoliTO Interdepartmental Center for Service Robotics). He holds additional roles as the Inclusion and Equal Opportunities Coordinator and Director of the Japan Hub. His academic career spans numerous PhD and Master's programs at both the Polytechnic University of Turin and the University of Genoa. Professor Quaglia's research spans a wide range of topics in applied mechanics, robotics, and sustainable engineering. His primary research interests include service robotics for healthcare, precision agriculture, cultural heritage, and search/rescue operations; assistive devices for disabled individuals; pneumatic actuators and soft robotics; electronic parking brake systems; and human-robot interaction. His work strongly aligns with multiple UN Sustainable Development Goals, particularly in areas of health, clean energy, innovation, and responsible consumption. His recent publications demonstrate a strong focus on practical applications of robotics, particularly in assistive technologies (wheelchairs, rehabilitation devices), agricultural robotics (AGRIMARO.Q), and novel actuator designs (PAL-HAND.Q). The research shows consistent innovation in making robotic systems more accessible, sustainable, and user-friendly. Best Paper Award from IFToMM Italy (2016) First Prize in the Technical Paper Award IHTC 2017 Multiple Best Paper/Research Awards from RAAD, IFToMM, and I4SDG conferences (2018-2022) CERTIFICATE EDITOR'S CHOICE ARTICLES, Machines 2021 Professor Quaglia actively supervises PhD students working on cutting-edge robotics projects, while also leading numerous research projects including PAL-HAND, TWIN-IT-ROMANS, MoviWE.Q, and AGRITECH. His work bridges academic research with real-world applications through collaborations with industry partners and commercial contracts.
Piero Bevilacqua is a Researcher at the Department of Mechanical, Energy and Management Engineering , University of Calabria. His work focuses on energy efficiency in buildings, solar energy systems, and thermal properties of materials. Research areas: Rational energy use, building energetics Applications: Bioclimatic architecture, energy certification, passive solar systems His recent publications highlight innovations in parabolic trough collectors , phase change materials (PCM) for building envelopes, and LNG regasification energy recovery . Projects include solar-assisted heat pumps and thermal storage optimization in Mediterranean climates. He is part of the Environmental Technical Physics research group, working on national and international scales. Collaborators include Prof. Roberto Bruno and Natale Arcuri.
