جستجوی استاد راهنمای دانشگاهی

Flaminia Luccioمشاهده پروفایل

دانشیار

• Computer Security
• Cryptography
• Distributed Systems
• +۳ مورد دیگر

Flaminia Luccio is an Associate Professor at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. Her research focuses on computer security, cryptography, distributed systems, and usability engineering. She has contributed to projects like the SAFE PLACE IoT security initiative and the FWS firewall analysis tool. Luccio teaches courses such as Cryptography and Advanced Algorithms at both undergraduate and graduate levels. Research: Her work spans formal verification of cryptographic protocols, secure IoT implementations, and usable security solutions for QR codes and biometric authentication. She has led projects involving secure hardware configuration for cloud environments and resilient firewall management systems. Recent contributions address side-channel vulnerabilities and malware detection through machine learning. Teaching: Courses include Cryptography (Master's), Algorithms and Data Structures (Bachelor's), and Web Technologies for Tourism (Master's). Teaching materials are accessible via her departmental website and personal profile. Collaborations: Collaborates with researchers like Riccardo Focardi on cybersecurity frameworks. Engages in interdisciplinary projects combining accessibility with technology, such as improving tourism websites for users with disabilities.

• Computer Science
• Programming Languages
• Blockchain Technology
• +۳ مورد دیگر

Alvise SPANO' is a Researcher at Ca' Foscari University of Venice, affiliated with the Department of Environmental Sciences, Computer Science and Statistics. He is also part of the Research Institute for Complexity. His academic focus includes Blockchain Programming Languages, Programming Languages, and Information Systems. Research projects include ALGOMOVE for Algorand and the RINmaker bioinformatics tool. He has taught courses like Object-Oriented Programming and Introduction to Programming at both undergraduate and doctoral levels. Research interests span smart contract analysis, type systems, and cybersecurity in distributed systems. He contributed to projects like secure RPL for mobile networks and Android-LEGO interoperability. Funding includes the CEVID 2016 project (Role: LD), collaboratively managed with researchers like Agostino Cortesi and Salvatore Orlando. His work bridges theoretical foundations (e.g., COBOL code typing) with practical applications in wearable systems and bioinformatics. Collaborations include the Blockchain Programming Languages research group with Lorenzo Benetollo and Sabina Rossi.

Stefano Melacciمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +۱۴ مورد دیگر

Stefano Melacci is an Associate Professor in the Department of Information Engineering and Mathematics (DIISM) at the University of Siena, Italy. He is a core member of the Siena Artificial Intelligence Laboratory (SAILab), where his research centers on Machine Learning and Artificial Intelligence, particularly in foundational and applied aspects of Computer Vision and Natural Language Processing. Department: Department of Information Engineering and Mathematics (DIISM) Institution: University of Siena Research Group: Siena Artificial Intelligence Laboratory (SAILab) He holds a PhD in Machine Learning from the University of Siena (2010), with prior research experience at Ohio State University. His career includes academic positions and industrial research at QuestIT, where he led NLP and conversational AI initiatives. His research interests lie at the intersection of deep learning and symbolic reasoning, particularly through the framework of Learning from Constraints . He investigates Kernel Machines, Regularization Theory, and cognitive models such as Developmental Visual Agents (DVA) and Cognitive Action Laws (CALs) . His work emphasizes motion invariance, visual attention, and continual learning. The recent publications highlight a strong trend in neurosymbolic AI, constraint-based learning, and biologically inspired neural computation. Key themes include explainability, adversarial robustness, graph neural networks, and efficient temporal modeling. His collaborative work with Marco Gori, Andrea Betti, and others demonstrates sustained innovation in hybrid AI systems. Scientific Contributions and Recognition: Author of foundational work on Laplacian SVMs trained in the primal (JMLR 2011) Co-author of the book Machine Learning: A Constraint-Based Approach (Elsevier, 2nd ed. 2024) Developer of PyTorch and MATLAB libraries for LapSVMs and cognitive vision models Active contributor to top-tier venues: NeurIPS, ICML, AAAI, IJCAI, IEEE TPAMI Stefano Melacci has advised numerous students in deep learning, continual learning, and neurosymbolic AI. His research is supported by sustained publication output and integration of theoretical and applied work. He teaches courses such as Neural Networks and Fondamenti di Programmazione at the University of Siena. He leads research within SAILab, focusing on cognitive vision, constraint propagation, and hybrid learning systems. His lab develops models that combine data-driven learning with symbolic knowledge, aiming to create more robust, interpretable, and human-like AI systems.

• Geomechanics
• Energy Geostructures
• Underground Gas Storage
• +۷ مورد دیگر

Chiara Deangeli is an Associate Professor in the Department of Environmental, Land and Infrastructure Engineering (DIATI) at the Polytechnic University of Turin. She is a member of the College of Environmental and Land Engineering and serves as the Course Coordinator for the Master's Degree in GEORESOURCES AND GEOENERGY ENGINEERING. She is also affiliated with the FULL Interdepartmental Center - Future Urban Legacy Lab, contributing to interdisciplinary research in sustainable urban development. Her research focuses on geomechanics , energy geostructures , and infrastructure resilience under climate change . Key areas include underground gas storage, reservoir geomechanics, and debris flow hazard mitigation. She applies numerical modeling and data science techniques to analyze geostructure stability and risk in changing environmental conditions. The recent publications highlight a strong trend in reservoir and geomechanical modeling , particularly in shale formations and CO2 storage systems. Her work integrates engineering mechanics with environmental sustainability, addressing challenges in energy infrastructure and geohazard resilience. Topics span from wellbore stability to caprock failure and landslide protection systems. She has served on the editorial board of Frontiers in Earth Science since 2021 and was a guest editor from 2014 to 2016. She also contributes to Applied Sciences as an editorial member since 2020. Dr. Deangeli has supervised doctoral students in the Doctoral College of Civil and Environmental Engineering at Politecnico di Torino across multiple cycles (2010–2025). She leads research projects funded by national grants (PRIN) and industrial contracts, including a major agreement with RFI SPA on railway risk analysis. Her work aligns with UN Sustainable Development Goals 7 (Affordable and Clean Energy), 9 (Industry, Innovation, Infrastructure), 13 (Climate Action), and 15 (Life on Land). She is actively involved in teaching graduate courses such as Reservoir Geomechanics , Geostructures under Climate Change , and Landslides and Slope Engineering , reflecting her expertise in both theoretical and applied geotechnics.

• Applied Geophysics
• Seismic Monitoring
• Machine Learning in Geoscience
• +۷ مورد دیگر

Farbod Khosro Anjom is a fixed-term Assistant Professor and researcher in the Department of Environmental, Land, and Infrastructure Engineering (DIATI) at Politecnico di Torino, Italy. He is affiliated with the College of Environmental and Land Engineering and specializes in Applied Geophysics (GEOS-04/B). He actively contributes to research, teaching, and academic service, including serving as an Associate Editor for the journal Geophysical Prospecting since 2024. His research focuses on applied geophysics with applications in environmental and mining engineering. Key areas include seismic monitoring of landslides and periglacial bodies, machine learning for event classification in passive seismic data, and geophysical characterization of deep and near-surface mines. He employs techniques such as ambient noise tomography, surface wave analysis, and well logging to study geological discontinuities and subsurface structures. His recent publications (2024–2025) highlight a strong trend in integrating machine learning with geophysical data for hazard detection and resource exploration. The works span journal articles and conference proceedings, emphasizing practical applications in mining, landslide early warning, and glacier monitoring. These reflect a multidisciplinary approach combining geophysics, environmental engineering, and data science. He is actively involved in teaching at both PhD and Master’s levels. He is the main teacher for the PhD course Deep Learning Applications in Environmental Engineering and Geoscience (2024/25 and 2025/26) and a course collaborator for Geophysical Exploration and Monitoring and Well Logging and Well Testing in the Master’s program in Georesources and Geoenergy Engineering. Scientific Editorial Role: Associate Editor, Geophysical Prospecting (2024–present) Farbod Khosro Anjom supervises PhD students, notably Valeria Strallo in the Civil and Environmental Engineering PhD program (39th cycle, 2023–ongoing). While specific grants are not mentioned in the text, his active research output and editorial role suggest ongoing research funding and academic leadership. He is part of a research team within DIATI focused on Applied Geophysics, collaborating closely with researchers such as Chiara Colombero, M. Manzi, and V. Socco.

• Aerospace Engineering
• Aircraft
• Composites
• +۸ مورد دیگر

Alfonso Pagani is an Associate Professor at the Department of Mechanical and Aerospace Engineering, Polytechnic of Turin. He holds a Ph.D. in Aerospace Engineering (City University of London, 2016) and a Ph.D. in Fluid-dynamics (Politecnico di Torino). His work focuses on aerospace structures, composites, computational mechanics, and multiscale modeling. Research Interests: Aerospace engineering, composite materials, deployable structures, nonlinear dynamics, and spacecraft design. He leads the MUL2 research group and has secured major grants including an ERC Starting Grant (2019) for variable stiffness composites and PNRR projects on additive manufacturing and renewable composites. Recent publications analyze thermal stresses in 3D printed composites, variable stiffness optimization, and deployable space structures. His work integrates Carrera Unified Formulation (CUF) with machine learning for structural analysis. ERC Starting Grant (2019) ACAM8 Best Paper Award (2014) Ian Marshall Best Student Paper (2013) Ernesto and Ben Omega Petrazzini Scholarship (2012) Aldo Muggia Award (2012) He teaches courses such as Asymptotic Methods in Structural Mechanics and Peridynamics, and supervises Ph.D. students in mechanical and aerospace engineering. He collaborates with institutions including Caltech, Purdue, and RMIT, and co-organizes international conferences on advanced materials.

• Digital Twin
• Aerospace Systems Prognostics
• Embedded Sensors
• +۶ مورد دیگر

Paul Major is a Full Professor in the Department of Mechanical and Aerospace Engineering at the Polytechnic University of Turin, where he has established himself as a leading researcher in aerospace systems. He serves as a member of the PhotoNext Interdepartmental Center for Applied Photonics and the University Internship Commission, demonstrating his commitment to interdisciplinary research and student development across multiple domains of engineering. Professor Major's research focuses on digital twin technology, prognostics and diagnostics of aerospace systems, and embedded sensor systems. His work bridges theoretical modeling with practical applications, particularly in the areas of augmented reality for aircraft monitoring, optical fiber sensors for structural health monitoring, and machine learning applications for predictive maintenance of electromechanical systems. His research has significant implications for improving aircraft safety, efficiency, and sustainability, with applications extending to lunar exploration technologies and space habitat design. His recent publications reveal a strong trend toward integrating advanced computational methods with physical systems, particularly in the domains of lunar exploration technology, additive manufacturing for aerospace applications, and sustainable aviation solutions. The interdisciplinary nature of his work spans aerospace engineering, computer science, materials science, and control systems, reflecting the increasingly interconnected nature of modern engineering research. His team has made significant contributions to optical sensor integration, AR visualization for maintenance, and prognostic frameworks for electromechanical systems. Professor Major actively mentors doctoral students, with current advisees including Matteo Bertone, Pierluigi Vergari, Armando Vittorio Atzori, and several others working on cutting-edge aerospace projects including lunar drones, aircraft anti-icing systems, and electromechanical actuator diagnostics. He has secured numerous research grants from both competitive funding bodies and commercial contracts, including projects like ASTRA (Advanced Space Tethers for Remote-sensing Applications), SmartCore, and FreME (Freno Multidisco Ad Attuazione Elettromeccanica Smart). He leads the ASTRA research group focused on Additive manufacturing for Systems and sTRuctures in Aerospace and is actively involved with the student team ICARUS. His work has practical applications in both terrestrial and space environments, with recent projects addressing lunar exploration technologies, sustainable aviation solutions, and advanced monitoring systems for aerospace applications.

• Systems and Control Engineering
• Control Theory
• System Identification
• +۴ مورد دیگر

Michele Taragna is a Tenured Associate Professor in the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, actively teaching across degree programs: Experimental Modeling for PhD students in Electrical, Electronic and Communications Engineering (2019-2025), Estimation and System Identification for Mechatronic Engineering Master's program (2019-2026), and Automatic Control for Computer Engineering Bachelor's program (2019-2026) as course holder or collaborator. His research centers on Systems and Control Engineering , with primary interests in data-driven control for autonomous vehicles and fleets, direct virtual sensors, and machine learning-enhanced system identification. Key areas include Set Membership methods for robustness under bounded noise, computational complexity reduction in Nonlinear Model Predictive Control (NMPC), sensor fusion for robotics, and applications in automotive suspensions. This work aligns with ERC sectors PE7_1 (Control engineering), PE1_20 (Control theory), and PE6_12 (Scientific computing). Trends in his publications (2024-2004) reveal sustained innovation in applying Set Membership identification to NMPC for autonomous vehicles, achieving real-time feasibility through search domain reduction. Sensor fusion techniques using Kalman filters for mobile manipulators and data-driven filter design for uncertain LTI systems with bounded noise are recurring themes, emphasizing practical implementation and computational efficiency. Scientific awards: None documented in provided materials. Advising and research funding: Supervised PhD student Mattia Boggio (2020-2024) in Electrical, Electronic and Communications Engineering; thesis on Real-time Nonlinear Model Predictive Control with domain reduction. Led the nationally funded PRIN project Controllo ad alte prestazioni a partire dai dati sperimentali (2007-2009) as Scientific Responsible. He is a core member of the Automatica research group within DET, focusing on system identification, control design, and validation for dynamic systems with applications in automotive and robotics domains.

Alessandro Checcoمشاهده پروفایل

استادیار

• Crowdsourcing
• Human Computation
• Distributed Systems
• +۷ مورد دیگر

Alessandro Checco is an Assistant Professor in the Computer Science Department at University of Rome La Sapienza. His research focuses on crowdsourcing, distributed systems, and privacy-preserving technologies, bridging theoretical computer science with practical applications that consider human factors in technological systems. He has established himself as a significant contributor to the field of human computation and privacy-aware systems. His educational background includes: 2020: Fellowship of Higher Education from The University of Sheffield, Higher Education Academy 2015: Ph.D. in Mathematics from Hamilton Institute (Design of decentralised algorithms applied to channel/code selection and convex optimisation for throughput fairness of 802.11 networks) 2010: M.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) 2009: Erasmus Scholarship at Universiteit Gent, Department of Telecommunications 2007: B.Sc. in Mathematical Engineering from University of Roma "Tor Vergata" (110/110 with great distinction) Checco's research spans multiple areas at the intersection of computer science and social implications of technology. He is particularly interested in Crowdsourcing for Human Computation, Distributed Private Recommender Systems, Information Retrieval, Data Privacy, Distributed Systems, User Data Obfuscation in Web Systems, Societal and Economic Analysis of Online Work, Crowd Workers Unionisation, and Algorithmic Bias. His work often examines how technological systems can be designed to respect user privacy while maintaining functionality, and how crowd work can be structured to be more equitable for workers. His recent publications demonstrate a clear evolution in research focus, beginning with foundational work in wireless networks and distributed algorithms, then shifting toward human computation and privacy-preserving systems. His most recent work increasingly addresses the societal implications of crowd work, including investigations into crowd worker unionization and cooperative models. Several publications examine gender bias in algorithmic systems, reflecting growing attention to fairness and ethical considerations in his field. Among his notable achievements: All That Glitters is Gold-An Attack Scheme on Gold Questions in Crowdsourcing (Best Paper Award) Checco has secured significant research funding and led important projects including the H2020-funded FashionBrain project as Research Director and the EPSRC-funded BetterCrowd project as Research Associate. His work on the FashionBrain project demonstrates his ability to lead large-scale, interdisciplinary research initiatives. He has also received the Technology Innovation Development Award (TIDA) from Science Foundation Ireland. His research has practical applications across multiple domains including recommendation systems (BLC: Private Matrix Factorization Recommenders), peer review assistance using AI, smart farming technologies, and cooperative models for crowd workers (CrowdCO-OP). He has developed frameworks for understanding worker behavior in crowdsourcing platforms and created methods for improving quality control in human computation systems.

• Additive Manufacturing
• 3D Printing
• Soft Robotics
• +۳ مورد دیگر

Gianluca Percoco is a Full Professor at the Department of Mechanics, Mathematics & Management, Politecnico di Bari (Poliba), specializing in manufacturing technologies and systems. His research focuses on advancing 3D printing methodologies for soft robotics, sensors, and biomedical applications. Department: Mechanics, Mathematics & Management Research Themes: Additive manufacturing, material extrusion, bioinspired structures His recent work explores ironing process optimization for improved sensor sensitivity, electromagnetic assistance in silicone-based soft robotics, and machine learning for predicting interlayer adhesion in multi-material printing. Publications from 2023-2025 highlight innovations in 3D printed sensors , self-healing polymers , and microfluidic devices . Contact: gianluca.percoco@poliba.it | Tel: +39 080 596 3267

• Applied Mechanics
• Structural Dynamics
• Vehicle Dynamics
• +۵ مورد دیگر

Leonardo Soria is an Associate Professor at the Department of Mechanics, Mathematics & Management at the Polytechnic University of Bari. His research focuses on applied mechanics, structural dynamics, and vehicle vibrations, with a strong emphasis on computational modeling and experimental validation. Department: Mechanics, Mathematics & Management Email: leonardo.soria@poliba.it Contact: +39 080 596 3484 His work spans topics such as viscoelastic foundations, flutter analysis, road roughness identification, and structural health monitoring. He employs advanced methodologies like the unsteady compressible source and doublet panel method, operational modal analysis, and machine learning techniques for diagnostics. Recent publications highlight his contributions to vibro-acoustical analysis of microsystems, robustness of measurement probes, and shock response synthesis in aerospace. His research also explores fluid-structure interactions in nanoscale systems and energy harvesting from vibrating polymers. Professor Soria actively investigates the dynamics of sharp-edged beams, helicopter cabin vibrations, and vehicle suspension performance assessment. His studies often bridge theoretical models with experimental validation, particularly in scenarios involving Brownian excitation, hydrodynamic coupling, and seismic loading.

• Additive Manufacturing
• 3D Printing
• Soft Robotics
• +۵ مورد دیگر

Gianni Stano is an Assistant Professor at the Department of Mechanics, Mathematics & Management, Politecnico di Bari (Bari Polytechnic University), Italy. His research focuses on advanced additive manufacturing techniques and their applications in soft robotics, sensors, and multi-material systems. Academic Rank: Assistant Professor Department: Mechanics, Mathematics & Management Field: Manufacturing Technology and Systems (ING-IND/16) Email: gianni.stano@poliba.it Research Interests Stano's research explores the intersection of additive manufacturing , soft robotics , and smart materials . Key areas include: Multi-material 3D printing and interfacial adhesion optimization Biomimetic and MRI-guided fabrication of anatomical structures Development of silicone-based electromagnetic actuators and grippers Embedded sensor and actuator integration in soft robotics Process parameter modeling for polymer-based additive manufacturing Self-healing materials and assembly-free smart structures Article Trends Stano's recent publications (2023-2025) emphasize multi-material extrusion printing , bioinspired design , and machine learning applications in manufacturing. His work addresses challenges in: Void reduction and layer adhesion in polymers Electromagnetic actuation for untethered soft robots Piezoresistive sensor optimization through process parameters Self-healing polymer fabrication via Diels-Alder chemistry Embedded electronics and copper feature integration Lithium-ion battery manufacturing using material extrusion

Stefano Guizzardiمشاهده پروفایل

دانشیار

• Connective Tissues
• Biocompatible Materials
• Osteoinductive Properties
• +۳ مورد دیگر

Stefano Guizzardi is an Associate Professor at the University of Parma , affiliated with the Department of Medicine and Surgery . His career spans decades of teaching and research in histology, embryology, and biomedical technologies. Education: University of Bologna (MD, 1983) PhD in Biomedical Technologies (1989) Research Interests: Guziardi's work focuses on connective tissues and biocompatible materials , particularly their osteoinductive and osteostimulatory properties. He explores endosseous implant surfaces , synthetic apatites , and platelet gel for bone repair, alongside nucleotides/nucleosides in cellular biology. His recent publications highlight advancements in histology education using AI and digital tools. Notable Trends in Publications: His 2025 articles emphasize natural language processing , large language models , and technology-driven pedagogy in biomedical education. Topics include literature screening efficiency , prompt engineering , and automated journal recommendation systems . Scientific Awards: Venosmine Award (1984) for innovative phlebology research Teaching Roles: Guizzardi has taught Histology and Embryology at multiple levels since 1990, including for Dentistry , Physiotherapy , and Neuropsychomotor Therapy programs. He collaborates with the Institute of Science and Technology for Ceramics (ISTEC-CNR) and institutions in Bologna and Varese. Contact: Office at the Integrated Biotechnology Complex, University of Parma .

Aldo Geunaمشاهده پروفایل

استاد

• Economics of Science
• Economics of Innovation
• Science and Technology Policy
• +۷ مورد دیگر

Aldo Geuna is a Full Professor at the Department of Cultures, Politics and Society at the University of Torino and a Fellow of the Collegio Carlo Alberto. He previously served as Full Professor at the Department of Economics and Statistics Cognetti de Martiis (2008-2020) and has held academic positions at SPRU, University of Sussex (1998-2008), where he advanced from Lecturer to Senior Lecturer. His international experience includes Senior Research Fellowships at RSCAS-European University Institute and research positions at BETA-Strasbourg and MERIT-Maastricht. His educational background includes a PhD in Economics from Maastricht University (1993-1998), following Master's degrees in Technology Policy and Innovation Management from MERIT (1992-1993), Economics from University of Torino (1991-1992), and Management Engineering from Politecnico di Milano (1984-1991). Geuna's research focuses on: Economics of Science Economics of Innovation Science and Technology Policy Political Economy of Science and Technology ICT and Internet Economics Economic Growth and Development Economics His work centers on the socio-economic analysis of university research behavior and its links to innovation and economic growth. His recent publications reveal a strong emphasis on university-industry collaboration, research assessment methodologies, academic mobility, and the economic impact of technological advancements across multiple disciplines. Key recognitions include: Included in the list of Top Italian Scientists of VIA-Academy CIFAR Fellow Member of Editorial Boards for Research Policy, Journal of Technology Transfer, Italian Economic Journal, and others Geuna has coordinated numerous research projects funded by the European Commission, UK Research Councils, and Italian Ministry, including the current HPC/AI Transformative Impact on Science project. He has supervised PhD students and served on defense committees at institutions worldwide, while also advising governmental bodies and non-profit organizations across multiple countries including the OECD, National Academies (US), and EU.

• Mechanical Systems Dynamics
• Modal Analysis
• Nonlinear Dynamics
• +۷ مورد دیگر

Alessandro Fasana is a Full Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Polytechnic University of Turin, where he serves as Deputy Coordinator of the College of Mechanical, Aerospace and Automotive Engineering. His academic career spans multiple decades with continuous involvement in doctoral education as Course Coordinator in Mechanical Engineering from 2018-2024 and consistent participation in doctoral colleges since the 27th cycle (2011/2012). Professor Fasana's research focuses on Mechanical Systems Dynamics, Modal Analysis, Nonlinear Dynamics, Rotating Machinery Diagnosis, Structural Health Monitoring, Viscoelastic Materials, Prognostics and Health Management, and Signal Processing. His work bridges fundamental mechanical principles with practical industrial applications, particularly in vibration analysis, structural dynamics, and condition monitoring systems. His research lines specifically include modal analysis and identification of linear dynamic systems, characterization of viscoelastic materials, dynamics of nonlinear systems, and evaluation of defects and residual life of structures. Analysis of his recent publications reveals a strong emphasis on pyroshock testing for aerospace qualification, structural health monitoring, vibration control, and advanced signal processing techniques. His work spans both theoretical developments and practical applications across aerospace, mechanical engineering, and industrial sectors, with particular attention to vibration analysis, structural dynamics, and condition monitoring systems. The research demonstrates increasing integration of computational methods, machine learning, and experimental validation. Professor Fasana has supervised PhD student Luca Viale, whose thesis focused on Pyroshock Testing for aerospace qualification. His research portfolio includes numerous commercial research projects spanning from 2007 to 2023, primarily focused on vibration testing, characterization of damping materials, and structural analysis for diverse industrial applications including aerospace, dental equipment, and power generation systems. He leads the research group 'Dinamica dei sistemi meccanici e identificazione (DIMEAS)' and has been Principal Investigator on multiple commercial research projects related to vibration analysis, structural dynamics, and material characterization. His work connects mechanical engineering fundamentals with practical industrial solutions across multiple sectors including aerospace, automotive, and energy.