Francesco Pilati is an Associate Professor at the Department of Industrial Engineering, University of Trento, where he serves as local coordinator for the scientific field ING-IND/17 (Industrial Plants and Logistic Systems). He chairs the research group on Industrial Plants, Production Systems, and Logistics, and teaches courses in Industrial Plants and Design of Digital Production and Assembly Systems. As coordinator of the Master's program in Management and Industrial Systems Engineering and University Coordinator for the EIT double degree in Zero-Defect Manufacture, Pilati bridges academic leadership with advanced manufacturing research. He has also served as Invited Lecturer at universities in Vienna and Göttingen. His research focuses on integrating environmental sustainability with technical-economic criteria through multi-objective optimization and impact assessment. Key areas include: Distribution networks and warehousing systems Manufacturing and assembly line design Hybrid energy production systems Digitization of manual production processes using depth cameras Recent publications highlight applications of Industry 4.0 technologies to pandemic safety, logistics optimization, and smart manufacturing. Pilati has received significant recognition including the Philip Morris Italia Empowering Research Award (2016) and Autostrade per l'Italia academic recognition. His editorial contributions include guest editing special issues on Digital Twins and Smart Factories in Q1 journals.
Giuseppe Carlo Marano is a Full Professor at the Department of Structural, Building and Geotechnical Engineering at Politecnico di Torino. He is also a component of the SISCON Interdepartmental Center for Infrastructure Safety. With expertise in civil and structural engineering, his work focuses on machine learning applications, seismic risk reduction, and sustainable structural optimization. Education Graduated cum laude in Structural Engineering from Polytechnic University of Bari PhD in Structural Engineering from University of Florence (2000) Research Interests Marano's research spans structural optimization, seismic engineering, and machine learning applications in civil infrastructure. He develops advanced computational models for: Seismic retrofitting of existing structures Optimization of steel and masonry structures Recycled materials in concrete production AI-driven structural health monitoring Multiobjective design methodologies Publication Trends His recent work emphasizes: Machine learning for concrete mix design and damage assessment Optimization of gridshells and arch structures Seismic isolation systems and vibration control Sustainable construction practices with recycled materials Multiobjective genetic algorithms for structural design Scientific Recognitions National Scientific Qualification - First Band (2013, MIUR Italy) Certificate of Appreciation for Outstanding Lecture (2012, China) Academic Contributions As an educator, he teaches: Consolidamento Strutturale (Structural Consolidation) Dinamica delle Vibrazioni Random (Random Vibration Dynamics) Progettazione Generativa (Generative Design) He also leads Challenge@PoliTo initiatives and contributes to national infrastructure safety regulations. Research Projects ADAPT4CE - Adaptive Digital Systems for Circular Economy (2025-2028) AI-ENVISERS - AI for Seismic Retrofit Environmental Impact (2023-2025) ADDOPTML - Additive Manufacturing Optimization (2021-2025)
Gian Antonio Susto is an Associate Professor at the Department of Information Engineering , University of Padova . With a Ph.D. in Information Technology and post-doctoral experience at National University of Ireland, Maynooth, he leads research in Machine Learning , Semiconductor Manufacturing , and Industrial IoT . His work bridges Anomaly Detection , Continual Learning , and Algorithmic Fairness with applications in Hydroelectric Power Plants , Particle Accelerators , and Smart Mobility . B.Sc. and M.Sc. in Controls Engineering, University of Padova (cum laude) Ph.D. in Information Technology, University of Padova (2013) Post-Doc at National University of Ireland, Maynooth (2012-2013) Assistant Professor at University of Padova (2013-2021) His research focuses on Explainable AI , Virtual Metrology , and Deep Learning for manufacturing and infrastructure monitoring. Recent projects include the AIMS5.0 (AI for Manufacturing Sustainability) and MICS (Circular Economy in Italy) initiatives. His publications span Engineering Applications of Artificial Intelligence , IEEE Transactions , and Information Processing & Management , with 15+ recent papers on topics like Fault Diagnosis , Continual Learning , and Fair Ranking . Key scientific awards include: IEEE CCTA Best Student Paper Award (2021) IP&M 2020 Ph.D Paper Award Best Industry Paper Award, European Workshop on Advanced Control and Diagnosis (ACD 2019) He has supervised Ph.D. students on projects involving Particle Accelerators , Plant Behavior Modeling , and Explainable AI , with alumni now at institutions like Max Planck Institute , IBM , and Scripps Research . Current teaching includes Reinforcement Learning and Explainable Machine Learning at graduate and Ph.D. levels.
Marcus Herrmann is a Professor of Aerospace and Mechanical Engineering at Arizona State University's School for Engineering of Matter, Transport and Energy. He is also affiliated with the Center for Negative Carbon Emissions. His research focuses on fluid mechanics, multiphase flows, atomization processes, and numerical methods for discontinuous interfaces. Herrmann holds a PhD in Mechanical Engineering from RWTH Aachen University (2001) and a Diplom (1995). His career includes a postdoctoral fellowship at Stanford University's Center for Turbulence Research (CTR) and a visiting scientist position at the University of Technology Eindhoven, Netherlands. He has secured major grants from NASA, NSF, and industry partners like Honeywell, focusing on atomization modeling, supersonic crossflows, and turbulence simulations. Research interests span computational fluid dynamics, multiphase flow simulation, and LES/DNS methodologies. His recent work emphasizes high-fidelity numerical techniques for particle-resolved simulations and phase interface dynamics. Teaching includes courses like MAE 561 (Computational Fluid Dynamics) and MAE 384 (Advanced Math Methods for Engineers). He actively advises students through research and dissertation roles. Notable projects include modeling wax deposition in pipelines and developing novel approaches for interface dynamics in turbulent flows. His work bridges fundamental fluid mechanics with industrial applications like combustion systems and porous media modeling.
Sara Vinco is an Associate Professor at the Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Italy. She specializes in battery simulation, digital twins, and energy-efficient design automation for heterogeneous embedded systems, aligning with Industrial and Information Engineering (Area 0009) and ERC sectors including Computer Architecture and Machine Learning . Her research focuses on advancing cyber-physical systems through simulation frameworks like SystemC-AMS, enabling holistic modeling of analog, digital, and thermal domains. Key projects include data-driven digital twins for EV batteries and low-area digital circuits in industrial/medical applications, supported by commercial contracts such as C-based virtual prototyping. Her recent publications (2022-2023) emphasize machine learning for battery SOH/SOC estimation , energy monitoring in production lines , and multi-domain fault modeling . These works span journals like IEEE Transactions and conferences including DATE and ISLPED. Awarded the FFABR 2017 grant and IEEE FDL Best Paper Award 2011 , she also chairs editorial boards for IEEE Transactions on CAD and DATE Conference. She supervises PhD students Giovanni Pollo (Digital Circuits) and Khaled Alamin (EV Battery Twins), reflecting her leadership in smart systems design.
Matteo Nardello is a researcher affiliated with the Department of Industrial Engineering at the University of Trento. His work focuses on embedded systems, IoT, and energy harvesting technologies for sustainable applications. Current academic affiliation: Department of Industrial Engineering, University of Trento Research interests: IoT, embedded systems, energy harvesting, machine learning, cyber-physical systems Contact: matteo.nardello@unitn.it His research integrates hardware-software co-design for batteryless IoT systems, with applications in smart agriculture, industrial monitoring, and autonomous vehicles. Recent work explores deep learning at the edge, energy-efficient sensor networks, and microbial fuel cells for self-powered devices. Key article trends highlight a focus on sustainable power solutions, wireless sensor networks, and machine learning optimization for constrained environments. He contributes to courses on embedded systems, IoT, and AI-powered industrial applications at the University of Trento.
Stefano Grivet-Talocia is a Full Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin, where he also serves as Director of the Doctoral School and President of the Doctoral School Council. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, the University Committee for Research, Technology Transfer and Services to the Territory, and the Commission for the Promotion of Library, Archive and Museum Heritage. His academic career spans over two decades at Politecnico di Torino, where he has established himself as a leading researcher in electromagnetic modeling and signal integrity. Grivet-Talocia earned his Laurea degree (summa cum laude) in Electronic Engineering in 1994 and his Ph.D. in Electronic and Communication Engineering in 1998, both from the Polytechnic University of Turin. Between 1994 and 1996, he conducted research at NASA/Goddard Space Flight Center in Greenbelt, Maryland. His educational background laid the foundation for his expertise in electromagnetic modeling, wavelet analysis, and signal processing. His research focuses on behavioral modeling, electromagnetic compatibility, macromodeling, model order reduction, numerical modeling, passivity, power integrity, signal integrity, transmission lines, and wavelets . Grivet-Talocia is particularly renowned for his work on passive macromodeling of interconnect structures, development of the TOPLine technique for transmission line simulation, and pioneering contributions to passivity enforcement algorithms. He has co-authored the first book entirely dedicated to Macromodeling (2016) and developed innovative approaches to waveform relaxation and wavelet-based signal processing. His recent publications (2024-2025) demonstrate continued leadership in model order reduction, with significant contributions to data-driven modeling of linear and nonlinear systems, power integrity analysis, and electromagnetic compatibility. His work spans both theoretical advances in numerical methods and practical applications in circuit design, with strong industry relevance particularly for semiconductor and electronic design automation companies. IEEE Fellow (2018-present) Three Intel SRS Grants (2022-2024) Three IBM SUR Grant Awards (2007-2009) Best Associate Editor Award - IEEE Transactions on Components, Packaging and Manufacturing Technology (2020) Multiple Best Conference Paper Awards (2006-2020) URSI Young Scientist Awards (1999) Ranked among the "top 2% worldwide researchers" (Stanford) since 2019 Grivet-Talocia actively supervises doctoral students including Michele Cusano, Sara Paknezhad Panahi, Antonio Carlucci, and Kun Zhao. He has secured numerous research grants from competitive national calls (PRIN) and commercial contracts with industry partners including Intel, IBM, Nokia, Hitachi, Infineon, and Cadence. His technology transfer activities include co-founding the spin-off IdemWorks (2007-2016), which was acquired by CST in 2016. He also developed the autoCircuits web service for automated circuit problem generation, widely used in electrical engineering education. He leads the EMC Group (Electromagnetic Compatibility) at DET and has been instrumental in establishing the Compact Dynamical Modeling research area. His work has practical applications in high-speed electronics design, with algorithms embedded in commercial tools like IBM PowerSPICE. Grivet-Talocia maintains strong industry connections through his research projects and serves as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technology.
Giuseppe Vecchi is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , Italy. He leads the Applied Electromagnetics research group and contributes to projects in computational electromagnetics, metamaterials, and biomedical applications of electromagnetic fields. He has been a IEEE Fellow since 2010 and serves on PhD college committees for Electrical, Electronic, and Communications Engineering. Research Interests : Antennas, Applied and Computational Electromagnetics, Metamaterials, Microwave Imaging for medical applications, Nuclear Fusion Reactor Physics. Scientific Leadership : Principal Investigator for projects like METEOR, MTSA, and RESOLVED-K, focusing on terahertz generation, metasurface antennas, and real-time temperature mapping in hyperthermia. Awards : IEEE Fellow (2010), recognizing his contributions to electromagnetic simulations and antenna design. Students : Supervises PhD candidates in advanced antenna engineering, computational electromagnetics, and biomedical applications, including Owais Khan, Francesco Lattanzio, and Sara Paknezhad Panahi. Patents : Holds multiple patents in antenna diagnostics, encrypted metasurface antennas, and microwave soil disinfection systems.
Gabriella Casalino is an Assistant Professor at the University of Bari Aldo Moro, Department of Computer Science, and a key researcher at CILAB - Computational Intelligence Lab. Her work focuses on Computational Intelligence methods for interpretable data analysis, particularly in eHealth, Data Stream Mining, and eXplainable Artificial Intelligence (XAI) within medical and educational domains. She has contributed to innovative approaches in smartphone-based health monitoring, fuzzy logic applications, and remote vital sign detection via photoplethysmography. Education : Ph.D. in Computer Science, with advanced training at institutions like Universitat de Girona and Université de Mons. Research Trends : Recent publications highlight applications of evolving granular computing, neuro-fuzzy systems, and explainable AI in hypertension prediction, bipolar disorder monitoring, and educational data analysis. Key subfields include remote health monitoring, medical data streams, and hybrid AI models. Grants : Research funded by AIRC (Italian Cancer Research Foundation), focusing on computational methods for healthcare challenges. Labs & Collaborations : Active in CILAB, collaborating on projects involving mHealth solutions, cardiovascular risk assessment, and intelligent educational systems.
Luigi Bruno is an Associate Professor of Machine Design at the Department of Mechanical, Energy and Management Engineering (DIMEG), University of Calabria. He has held this position since 2014, following 12 years as an Assistant Professor at the same institution and Visiting Professorships at IIT Gandhinagar (2012), University of Alabama at Birmingham (2013-2017), and Free University of Bozen-Bolzano (2021). 1999 : Master's in Mechanical Engineering, University of Calabria (110/110 cum laude) 2003 : PhD in Mechanical Engineering, University of Pisa His research interests span: Experimental Mechanics : Pioneering speckle interferometry for micro-displacement measurement and residual stress analysis. Materials Science : Elastic characterization of anisotropic materials, biomedical applications of soft substrates, and 3D-printed composites. Biomedical Engineering : Mechanical behavior of biological tissues, ocular biomechanics, and dental implant material testing. Recent research trends focus on: Integrating artificial muscles into rehabilitation devices Advancing full-field optical measurement via microCT/DVC Optimizing 3D printed polymer adhesion for industrial components Exploring neuronal biomechanics on soft surfaces Scientific contributions include: CS2007A00010 patent for dual-focus speckle interferometers Deputy Editor of Optics and Lasers in Engineering (2019-present) Guest Editor for special issues on optical methods in experimental mechanics and nanobiotechnology Academic leadership extends to coordinating Mechanical Engineering committees (2021-present), serving on editorial boards, and organizing international conferences like AIAS National Conference (2018). He has secured multiple MIUR research grants and industry collaborations with Alfagomma, 3DNA, and Ferrovie della Calabria. His laboratory, Mechanics of Materials and Structures , supports both research and teaching activities with advanced optical measurement systems and computational tools for mechanical design.
Daily Rodríguez-Padrón is a Research Fellow at Ca' Foscari University of Venice, affiliated with the Department of Molecular Sciences and Nanosystems and the Research Institute for Green and Blue Growth. She holds a BSc from the University of Havana (2013) and a PhD from the University of Córdoba, Spain (2020). Her research focuses on sustainable catalytic processes, nanomaterials, and biomass valorization. Key areas include the development of bio-based catalysts, green chemistry methodologies, and applications of chitin and other natural resources in catalysis. She has contributed to over 70 peer-reviewed articles, emphasizing eco-friendly synthesis and energy-related materials. Her work spans collaborations with institutions like KelAda Pharmachem Ltd (Ireland) and participation in EU-funded projects such as GreenX4Drug (Marie Skłodowska-Curie RISE). Rodríguez-Padrón’s research integrates mechanochemistry, continuous-flow systems, and waste-derived materials to advance sustainable industrial processes.
Prof. Michele Germani is a Full Professor at the Polytechnic University of Marche, Department of Industrial Engineering and Mathematical Sciences. His research focuses on ergonomics, sustainability, and human-centered design, with particular emphasis on industrial automation, wearable technologies, and circular economy principles. He leads projects on ergonomic risk assessment, environmental impact modeling, and smart manufacturing systems. Academic Background: Holds a position in the Faculty of Engineering, contributing to both teaching and research. His work integrates machine learning, sensor-based systems, and virtual reality to address challenges in manufacturing, healthcare, and sustainable design. Research Interests: Prof. Germani explores topics such as design for disassembly, eco-design tools, and the application of advanced technologies (e.g., exoskeletons, cobots) to enhance workplace safety and efficiency. His studies often bridge engineering and environmental science, aiming to reduce carbon footprints through innovative design methodologies. Key Projects: Development of decision support systems for fall risk detection, sensor-based ergonomic evaluation tools, and frameworks for circular economy implementation. He also investigates the impact of Industry 4.0 technologies on workforce dynamics and operator training via mixed reality simulations. Grants & Collaborations: Engaged in interdisciplinary collaborations focusing on sustainable manufacturing, healthcare technology, and smart systems. His research has led to tools like Durabot for durability analysis and Greenbuild for green building design. Labs & Teams: Oversees labs developing eco-design strategies, human-robot collaboration systems, and ergonomic assessment protocols, with a focus on real-world industrial applications.
Tania Cerquitelli is a Full Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where she leads research in data science, concept-drift management, and inclusive AI technologies. She is a member of SmartData@PoliTO, the GEDI Observatory for Gender Equality, and serves in leadership roles related to social affairs and community policies at the university level. She also acts as a scientific advisor for the partnership with Accenture. Her research interests span Data Science , Concept-Drift Management , Database Systems , Conversational Data Science , and Industry 4.0 . She applies AI and machine learning to industrial, societal, and ethical challenges, particularly in promoting inclusive communication and gender equality in research. The most recent publications highlight her work in explainable AI, concept drift detection, multimodal diagnostics, and AI for social good. Her research integrates machine learning, natural language processing, and computer vision to address real-world problems in manufacturing, healthcare, agriculture, and education. She is an Associate Editor for several prestigious journals including Expert Systems with Applications , Computer Networks , Future Generation Computer Systems , and Knowledge and Information Systems . She has served on the program committees of major conferences such as ECML PKDD, EDBT/ICDT, and ACM KDD, and has been a reviewer and selection committee member for ETH Zurich and EMPA. She actively supervises PhD students and teaches a wide range of courses including Data Science and Database Technologies, Business Intelligence for Big Data, and Gender and Diversity in Research. She is involved in multiple national and international research projects such as E-MIMIC, WEBFARE, and EnABLES, focusing on inclusive AI, smart data, and industrial applications. Her lab affiliations include the DBDM - Database and Data Mining Group (DAUIN) and the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory , where she contributes to advancing data science methodologies and their societal impact.
Michele Gattullo serves as an Assistant Professor within the Department of Mechanics, Mathematics & Management at the Polytechnic University of Bari, Italy, specializing in design methods for industrial engineering (ING-IND/15). His research bridges cutting-edge extended reality technologies with practical industrial applications, focusing on human-centered solutions for manufacturing, maintenance, and workplace design. Dr. Gattullo's research portfolio centers on Augmented Reality, Virtual Reality, and Biophilic Design, with significant contributions to Human-Computer Interaction in industrial contexts. He investigates how nature-inspired elements in virtual workspaces enhance employee well-being and productivity, while simultaneously developing practical AR tools for assembly guidance, technical documentation, and maintenance support. His work uniquely integrates ergonomics, cognitive psychology, and industrial engineering to optimize human-technology interaction in complex production environments. Analysis of his 15 most recent publications reveals two dominant research trajectories: biophilic design frameworks for virtual/metaverse workspaces (2023-2025) and industrial AR authoring methodologies. The biophilic stream establishes evidence-based guidelines for digital nature integration, while the AR stream delivers validated tools like ADAM and minimal AR approaches that streamline technical documentation creation. Both trajectories emphasize user experience validation through rigorous industrial studies, demonstrating strong interdisciplinary impact across computer science, industrial engineering, and environmental psychology. Scientific Awards: No awards or honors were documented in the available sources. Advising and Grants: The provided materials contain no information regarding graduate student supervision, research grants, or funding sources. His academic profile emphasizes publication output over mentoring activities or project financing details. Laboratories and Teams: While Dr. Gattullo's research involves advanced XR technologies, the source text does not specify laboratory facilities, research groups, or collaborative teams associated with his work at Politecnico di Bari.
Sergio Cavalieri is currently Rector of the University of Bergamo and a Full Professor of Operations Management within the Department of Management, Information and Production Engineering. His academic career focuses on innovation in management processes across industrial and service companies, with emphasis on digital transformation and sustainable business models. His research interests span Operations Management, Industrial Systems, and Servitization, with particular expertise in Product-Service Systems, Maintenance Management, and Digital Manufacturing. Cavalieri has pioneered work in Industrial Agile Working, 5G applications in manufacturing, and sustainability-oriented business models, especially within the steel sector. His research bridges theoretical frameworks with practical applications, addressing real-world challenges in manufacturing transformation. His publication record demonstrates consistent output in high-impact journals, with a clear trend toward integrating digital technologies with sustainable business practices. Recent work focuses on leveraging NLP for maintenance optimization, developing maturity models for agile working environments, and creating assessment tools for sustainable servitization in heavy industries. Cavalieri holds significant leadership roles including President of the U4I Foundation (University for Innovation), past President of AIDI (Association of Professors of Industrial Mechanical Plants), and Coordinator of the innovation table for the manufacturing industry of the 2021-2027 National Research Plan. He also directs the MeGMI Master's Program (Master in Industrial Asset and Maintenance Management). As an academic leader, Cavalieri serves on international scientific associations including IFAC-TC 5.1 on Advanced Manufacturing Technology and IFIP WG 5.7 on Advances in Production Management Systems. His work bridges academic research with industrial application through numerous collaborative projects focusing on digital transformation in manufacturing. His research activities are organized around several key initiatives including the MeGMI Master's Program and collaborations with industrial partners focused on implementing digital technologies in production environments. Cavalieri's work emphasizes the human-technology integration necessary for successful Industry 4.0 adoption.
