Find Academic Supervisors

• Structural Health Monitoring
• Machine Learning in Civil Engineering
• Earthquake Engineering
• +9 more

Marco Martino Rosso is a Research Fellow at the Department of Structural, Building and Geotechnical Engineering (DISEG) at the Polytechnic University of Turin, where he also serves as an external lecturer and teaching assistant in both DISEG and the Department of Mathematical Sciences (DISMA). He is affiliated with the Doctoral School (SCDOTT) and completed his PhD under the supervision of Professor Giuseppe Carlo Marano. His academic work bridges civil engineering with advanced computational methods, focusing on structural health monitoring, optimization, and machine learning applications. His research interests center on Structural Health Monitoring , Machine Learning in Civil Engineering , Earthquake Engineering , Structural Optimization , Operational Modal Analysis , and AI-driven diagnostics for infrastructure. He applies deep learning, neural networks, and hybrid modeling techniques to problems such as damage detection, post-earthquake assessment, tunnel and bridge monitoring, and dynamic analysis of timber and concrete structures. His recent publications, spanning from 2023 to 2025, demonstrate a strong trend toward integrating artificial intelligence with structural engineering, particularly in automating modal analysis, optimizing structural forms, and enhancing seismic resilience. These works appear in journals like Mechanical Systems and Signal Processing , Computers & Structures , and Bulletin of Earthquake Engineering , as well as in proceedings of international conferences such as IOMAC and EWSHM. Marco Rosso has not received any explicitly mentioned scientific awards in the provided text. However, his extensive publication record and active role in research projects indicate strong recognition in his field. He has contributed to teaching as a course collaborator in subjects including Dynamic Identification of Structures , Statistics , Construction Techniques , and Safety Assessment and Retrofitting of Structures . He has also been involved in the ARTISTE 2025 Summer School, indicating engagement in advanced training programs. While no formal lab or team name is specified, his frequent collaborations with researchers such as Angelo Aloisio, Giuseppe Carlo Marano, and Jonathan Melchiorre suggest he is part of a vibrant research group focused on intelligent structural systems and data-driven engineering at Politecnico di Torino.

Cristiana BolchiniView profile

Professor

• Dependability
• Fault Tolerance
• Reliability Analysis
• +8 more

Cristiana Bolchini is a Professor at the Department of Electronics, Information and Bioengineering (DEIB) at Politecnico di Milano. She holds a PhD in Automation and Computer Science Engineering (1997) and a Laurea in Electronic Engineering (1993), both from Politecnico di Milano. Her research focuses on dependable systems, fault tolerance, and embedded systems design, with recent work on ICT solutions for smart buildings and energy efficiency. She coordinates projects such as the FP7 SAVE initiative and serves on technical committees for conferences like DATE and DAC. Education: PhD in Automation & Computer Science (1997), Laurea in Electronic Engineering (1993), both from Politecnico di Milano. Research interests span dependability (fault modeling, diagnosis), heterogeneous architectures, and sustainable smart environments. She collaborates with Prof. Giuliana Iannaccone on foresight for sustainable built environments and has led EU-funded projects like the SAVE initiative. Publications include over 150 refereed papers on dependability and context-awareness. She holds editorial roles for journals such as IEEE Transactions on Computer-Aided Design and ACM Transactions on Embedded Computing Systems. Awards include IEEE Senior Member status and two Cisco University Research Program Fund gifts (2012, 2014). Academic roles include Rector’s delegate for Southeast Asia relations and leadership of Technology Foresight workgroups. She teaches courses on computer science fundamentals and dependable systems, emphasizing problem-solving and programming in Python and C.

Luca SterponeView profile

Professor

• Reconfigurable computing
• Computer-aided design algorithms
• Fault tolerance and reliability
• +7 more

Luca Sterpone is a Full Professor at the Department of Control and Computer Science (DAUIN), Politecnico di Torino. He serves as Head of the Control and Computer Engineering Department (2023-2027), coordinates the Aerospace and Safety Computing Lab, and is a member of the Academic Senate and Power Electronics Innovation Center (PEIC). His research spans reconfigurable computing, fault tolerance, and radiation effects analysis in electronic systems. Professor since 2021 Department Head (DAUIN) since 2023 Coordinates international collaborations with ESA, AMD Xilinx, NVIDIA, and Thales Alenia Space Develops radiation-hardened FPGA tools (SETA, VERI-Place, PyXEL) 2007 EDAA Outstanding Dissertation Award and 2005 IEEE Best Paper Award Research Focus : Designing radiation-tolerant systems for aerospace, including fault-tolerant AI accelerators, FPGA reliability, and software-based error mitigation. He investigates soft error propagation in nanoscale circuits and develops tools for radiation sensitivity analysis in VLSI. His work integrates hardware-software co-design for mission-critical applications. Awards : EDAA Outstanding Dissertation Award (2007) IEEE European Test Symposium Best Paper (2005) SMACD Best EDA Tool Award (2018) ARC Best Paper candidate (2018) Teaching : He leads courses in Reconfigurable Computing (PhD level), GPU Programming , and Operating Systems . He has formal responsibility for teaching roles across 9 bachelor's and 7 master's years, and mentors multiple PhD students. Collaborations : Coordinates with the European Space Agency (ESA), University of Bielefeld, Universidad de Sevilla, and industrial partners like AMD Xilinx, NVIDIA, and General Motors. He leads projects such as RESCHIP4EU, VEGAS, and TERRAC for radiation-hardened computing solutions.

• Reliable and Fault-Tolerant Computing
• RISC-V Architecture
• FPGA-Based Systems
• +12 more

Sarah Azimi is a fixed-term researcher at the Department of Control and Computer Science (DAUIN) within the College of Computer, Film and Mechatronics Engineering at Politecnico di Torino. She actively contributes to research and teaching in the domains of reliable computing, reconfigurable systems, and AI applications for space and smart city security. Research Interests: Reliability and fault tolerance in safety-critical and space systems RISC-V and FPGA-based architectures High-performance computing (HPC) and reconfigurable computing AI resilience and real-time gesture recognition for public safety Radiation effects and hardening techniques for aerospace applications Publication Trends: Her recent publications focus on RISC-V reliability, radiation effects in space missions, AI resilience in reconfigurable platforms, and smart city security through gesture recognition. Her work spans both journal and conference venues, emphasizing practical and mission-tailored solutions in embedded and aerospace computing. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: Sarah Azimi supervises multiple PhD students including Federico Buccellato, Aobo Cui, and Giorgio Cora. She leads the competitive research project Safe Smart City: Detecting Violence and Requests for Help in Real Time Through Video Surveillance Devices (2024). She is also a member of the RAMSES CubeSat-1 Development project (2025–2026) and led the commercial research project on the Rempro fault-tolerant processor (2022–2023). Labs and Teams: She is a key member of the CAD - Electronic CAD & Reliability Group (DAUIN) at Politecnico di Torino, contributing to cutting-edge research in electronic design automation and system reliability for aerospace and terrestrial applications.

• Digital Circuits and Systems
• Energy-Efficient Circuits and Systems
• Embedded Systems
• +7 more

Massimo Poncino is a Full Professor at the Department of Control and Computer Science (DAUIN) within the Faculty of Engineering at Politecnico di Torino. He serves as Scientific Advisor for the STMicroelectronics partnership and coordinates basic engineering subjects. A Senior Member of IEEE since 2012 and Fellow since 2012, he has served on editorial boards for IEEE Transactions on Computer-Aided Design, IEEE Design & Test of Computers, and ACM Transactions on Design Automation. Education: Laurea in Electronic Engineering (1989) and PhD in Computer and Systems Engineering (1993) from Politecnico di Torino Academic Career: Visiting Scientist University of Colorado (1993-1994), Researcher at Politecnico di Torino (1995-2001), Associate Professor at University of Verona (2001-2004), Full Professor at Politecnico di Torino (2006-present) His research focuses on energy-efficient digital systems , including design automation of SoCs, hardware-aware AI, battery management, cyber-physical systems, and embedded systems. Recent publications highlight advancements in digital twins for batteries , low-power neural network deployment , and IoT privacy . Scientific Awards: Recognition of Service Award - ACM (2013) Certificate of Appreciation - IEEE Circuits and Systems Society (2006, 2008, 2009) IEEE Fellow (2012-) Research Involvement: EU H2020, VI/VII Framework Programs evaluator Scientific Director for projects: Approxim@ction, EMBAI, DISLO-MAN, DAMASCO Member of EDA research group Teaching: Course director for Energy Management for IoT (2019-2025) Lecturer for Computer Science courses (2003-2025)

Marco GrangettoView profile

Professor

• Computer Vision
• Image Processing
• Artificial Intelligence
• +5 more

Marco Grangetto serves as Full Professor in the Department of Computer Science at the University of Turin, coordinating research in image processing and computer vision. His expertise spans wavelets, image/video coding, data compression, error resilient video coding, and biomedical image processing, with significant contributions to ISO JPEG2000 standardization and editorial roles in IEEE Transactions on Multimedia. His educational background includes a PhD in Electrical and Communications Engineering (2003) and MSc in Telecommunications Engineering (1999), both from Politecnico di Torino. His research integrates Artificial Intelligence and Deep Learning with medical imaging and fundamental compression theory , producing innovations in neural network pruning, capsule networks, and entropy-based models. Recent work focuses on Covid-19 diagnosis from chest X-rays and efficient 3D scene modeling. His publication trends reveal dual trajectories: applied medical AI (Covid-19 diagnostics, lung cancer segmentation) and theoretical advances (learned compression, contrastive learning, bias mitigation). This bridges clinical validation with information-theoretic foundations, particularly in resource-constrained environments. Scientific recognition includes: Premio Optime by Unione Industriale di Torino (2000) Fulbright Grant for research at UC San Diego (2001) He maintains leadership through IEEE editorial positions, ISO standardization participation, and MPAI membership. His research group develops medical datasets (UniToChest, UniToPatho) while advancing neural network efficiency for clinical deployment. Current projects focus on entropy minimization techniques and unbiased representation learning for healthcare applications.

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +6 more

Francesco Strada is a Fixed-term Assistant Professor at the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino. He serves as a Course Lecturer for Virtual Reality and Technical Art for Cinema and Video Games, and as a Course Collaborator for multiple courses across Computer Engineering, Film and Media Engineering, and Architecture programs. He is an active member of the College of Computer, Film and Mechatronics Engineering and the College of Architecture and Design teaching committees. Dr. Strada's research focuses on Computer Graphics, Virtual Reality, Augmented Reality, and Human-Computer Interaction with particular emphasis on Embodied Conversational Agents, emotion recognition, and serious games applications. His work bridges technical computer science with psychological and human factors considerations to create more believable and effective virtual experiences. His research spans applications in education, healthcare, automotive interfaces, cultural heritage, and emergency response training. His recent publications demonstrate a strong trend toward emotionally intelligent virtual agents, VR/AR applications in specialized domains, and technical innovations in latency management and digital human representation. His work often combines psychological principles with technical implementations to enhance user experience and system effectiveness. Dr. Strada actively supervises PhD students including Alessandro Emmanuel Pecora, Stefano Calzolari, and Leonardo Vezzani, whose research focuses on Emotionally Aware Embodied Conversational Agents (E2CA) and Car AR-HUD design. He leads significant research projects including Holo-BLSD (2024-2025), a Mixed Reality tool for first aid emergency response training, and '50 shadows of AI' (2025), focusing on personalized education in corporate settings. He is a member of the CGVG - Computer Graphics and Vision Group at DAUIN, where his team develops cutting-edge applications in AR/VR, Human-Computer Interaction, User Experience, Computer Vision, Machine Learning, and Artificial Intelligence. His research has practical applications in education, training, healthcare, automotive interfaces, and cultural heritage preservation.

• Architecture
• Art and architecture
• Building information modeling (BIM)
• +11 more

Giovanna Massari is an Associate Professor at the Department of Civil, Environmental and Mechanical Engineering, University of Trento. She serves as Rector's Delegate for Open Science and President of the Open Science Commission. Specializes in architectural design, digital modeling, and BIM/HBIM technologies Teaches courses on Civil Design + CAD, Digital models for the project, and Architectural survey with Design Laboratory Expertise includes geometric modeling, photogrammetry, and spatial representation Her research focuses on integrating digital technologies with architectural surveying and civil engineering design. She emphasizes interdisciplinary approaches and digital interoperability in construction projects. Teaching activities include training students in visual analysis, 3D digital modeling, and technical communication standards for civil engineering applications.

Giovanni MichettiView profile

Associate Professor

• Archival Science
• Digital Archives
• Document Management
• +5 more

Giovanni Michetti serves as Associate Professor in the Department of Modern Literature and Culture at Sapienza University of Rome. His academic career focuses on archival science with particular expertise in digital archives, document management systems, and technological applications for archival practices. Currently teaching multiple courses including Document Management, Digital Preservation, Archival Organization and Description, and Computer Science for Archives and Libraries for the 2024/2025 academic year, he maintains an active role in the university's archival science programs within the Historical Sciences and Archival and Library Science degree courses. Michetti's research centers on contemporary archives with special emphasis on digital transformation in archival practices. His work spans digital archives management, document management systems, descriptive models, classification plans, and technology integration in archival contexts. He investigates blockchain applications for enhancing trust in digital archives, develops data architectures for cultural heritage, and examines the economic value of archival resources. His scholarly contributions bridge traditional archival science with modern information technologies, addressing critical challenges in preserving digital records while maintaining intellectual control over archival materials. His recent publications reveal a clear trajectory toward technological solutions for archival challenges, spanning theoretical aspects of archival science, practical applications of new technologies, and professional standards development. Key recurring themes include digital preservation techniques, blockchain applications for record authentication, data architectures for cultural heritage, and the evolving role of archivists in the digital age. This research reflects the field's transition from traditional archival methods to innovative digital approaches that address contemporary challenges in recordkeeping. Michetti leads the research project ADA (Advanced Digital Archive), which develops systems for online access to digital collections of humanities at Sapienza University. While specific student advising details aren't provided in the available materials, his extensive publication record and active research projects suggest significant mentorship activities within the archival science community.

• Functional Safety
• Functional Testing
• Microprocessor Testing
• +9 more

Riccardo Cantoro is an Associate Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he is a member of the College of Computer, Film and Mechatronics Engineering and the College of Mechanical, Aerospace and Automotive Engineering. He is affiliated with the CAD - Electronic CAD & Reliability Group and the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His work bridges academic research and industrial applications through multiple commercially funded projects. Scientific Disciplinary Sector: IINF-05/A - Information Processing Systems ERC Sectors: PE7_4, PE6_2, PE6_11, PE6_12 His research focuses on functional safety, functional testing, and microprocessor testing, with a strong emphasis on embedded systems and reliability. He applies machine learning and formal methods to enhance test efficiency and system robustness, particularly in automotive and safety-critical domains. His work integrates computer-aided design, fault modeling, and resilience assessment in both hardware and AI systems. The recent publications highlight a trend toward data-efficient and intelligent testing methodologies, combining machine learning (e.g., TabPFN, active learning) with traditional electronic design automation. Topics include microcontroller performance screening, CNN resiliency, FeFET device testing, and system-level test optimization, reflecting a cohesive research agenda in trustworthy computing and hardware reliability. Scientific Awards: No awards explicitly mentioned in the provided texts. Advising and Grants: Dr. Cantoro supervises numerous PhD students in Computer and Systems Engineering, focusing on functional safety, test methodologies, and AI for CAD. He leads multiple industry-funded research projects, including collaborations with Infineon Technologies and Dana-TM4 Italia, on topics such as ATPG tools, speed monitor modeling, and power module reliability. His role as Scientific Manager/Head underscores his leadership in applied research and technology transfer. Labs and Teams: He is a core member of the CAD - Electronic CAD & Reliability Group (DAUIN) and contributes to the CARS@PoliTO center, fostering interdisciplinary research in automotive systems and sustainable mobility.

• Nanoelectronics
• Heterogeneous Systems
• Computing Architectures
• +3 more

Ian O'Connor is a Professor of Heterogeneous and Nanoelectronics Systems Design at Ecole Centrale de Lyon , affiliated with the Lyon Institute of Nanotechnology (INL) . He serves as joint head of the Electronics group at INL and Director of the SoC² research network . Since 2008, he has held an Adjunct Professor position at Ecole Polytechnique de Montréal , Canada. Research focuses on novel computing architectures leveraging emerging technologies and design exploration methodologies Active in European/National research projects as workpackage leader and scientific coordinator Key roles: IEEE Council for Electronic Design Automation (Vice-President), EDAA Main Board member, IFIP WG10.5 participant Editorial leadership: Associate Editor for IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems Expert evaluator for France 2030 Council and IRDS Systems and Architectures IFT

• Architecture
• Urban Design
• Computational Design
• +4 more

Rossella Gugliotta is a Research Fellow at the Department of Architecture and Design (DAD) , Politecnico di Torino. She serves as an external lecturer and teaching collaborator, contributing to courses such as Architecture and Urban Economics , Computational Design , and Reuse of Built Structures . Email: rossella.gugliotta@polito.it Research Focus: Her work centers on urban morphology, computational design practices, and transitional processes in architecture. She develops diagrammatic tools for analyzing urban forms and explores intersections between digital technologies and contemporary city design. Publications include studies on morphological paradigms, counter-computational methodologies, and educational strategies for architectural representation. Her recent outputs address transitional urban processes, digital tools in morphology, and pedagogical innovations. Teaching Portfolio: She collaborates in both undergraduate and graduate courses, including Design Theory Laboratory A , Architecture Design Studio , and Project and Modeling Workshop modules spanning 2019–2025 academic years.

Mihai Teodor LazarescuView profile

Associate Professor

• Artificial intelligence
• Capacitive sensors
• Embedded software
• +10 more

Dr. Mihai Teodor Lazarescu is an Associate Professor at the Department of Electronics and Telecommunications (DET), Politecnico di Torino , where he contributes to research and teaching activities. He is also a member of the PolitoBIOMed Lab (Biomedical Engineering Lab) and the Ambient Sensing and Processing research group. Scientific Affiliation: IEEE Member (2019-present) Editorial Roles: Guest Editor for SENSORS, ELECTRONICS, and ACM Transactions on Embedded Computing Systems His research interests focus on hardware acceleration for machine learning algorithms, particularly using FPGAs for data center and embedded applications. He works on high-level synthesis optimization flows, capacitive sensor design for indoor monitoring, and low-power embedded systems . His work intersects Internet of Things , Wireless Sensor Networks , and Machine Learning with applications in human localization, environmental monitoring, and industrial automation. Recent publications demonstrate expertise in neural network optimization , DSP resource sharing , and multi-FPGA allocation . His teaching spans Applied Electronics , Digital Electronic Design , and Embedded Systems Optimization across bachelor's and master's programs in Electronic Engineering and Computer Engineering . Patents: Noise cancellation for single-plate capacitive sensors Capacitive sensor for space change detection Projects: Scientific Manager for Horizon 2020-S2RJU project (2018)

• Electronics
• Nanocomputing
• Quantum Technologies
• +12 more

Fabrizio Riente is a Fixed-term Researcher at the Department of Electronics and Telecommunications (DET) , Politecnico di Torino. He holds academic responsibilities in multiple programs and contributes to editorial and conference committees. Member of College of Electronic, Telecommunications and Physics Engineering Invited Member of College of Computer, Film, and Mechatronics Engineering His research spans Nanocomputing , Quantum Technologies , and Machine Learning for environmental and healthcare applications, with a focus on: Qubit Control & Readout Systems IoT for Bee Health Monitoring 3D Audio-Visual Reproduction for Hearing Research Hybrid Simulation and Emerging Nanotechnologies Low-Power Electronic Systems His recent publications demonstrate interdisciplinary work bridging Quantum Electronics and Acoustic Ecology , particularly in developing VLSI architectures for novel applications. Notable scientific awards include Associate Editorship at Frontiers in Electronics and program committee roles at international conferences. He supervises PhD students in Quantum Engineering and Electronic Engineering , directing research projects funded by commercial contracts on quantum architectures and automotive technologies. His teaching portfolio includes courses on Microelectronic Systems and Low-Power Electronics .

• Artificial intelligence
• Energy efficiency
• Smart cities
• +7 more

Massimo Ruo Roch serves as an Associate Professor in the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin, Italy. His academic appointment falls under the scientific disciplinary sector IINF-01/A - Electronics within Area 0009 - Industrial and Information Engineering. His research spans multiple cutting-edge domains including Artificial Intelligence, Internet of Things, Energy Efficiency, Smart Cities, Logic in Memory, and Nanomagnetics . His work aligns with several European Research Council sectors including Micro- and nano-systems engineering, Artificial intelligence, Computer architecture, and Distributed systems. Ruo Roch leads the VLSILAB research group and has developed significant expertise in smart embedded systems for lighting and IoT applications, as well as agritech with autonomous robot systems for grape harvesting. His publication record demonstrates consistent contributions to low-power computing, magnetic logic circuits, and error correction techniques dating back to the late 1990s. Among his notable recognitions are the National Innovation Award (2013) and the prestigious Prize of Prizes (2014) conferred by the President of the Italian Republic through the National Foundation for Technological Innovation COTEC. He actively supervises doctoral candidates including Fabrizio Mo (working on Molecular Sensors at the Nanoscale) and Andrea Mongardi (researching Bio-inspired sEMG-based embedded systems). His research portfolio includes multiple commercial contracts and patents related to test systems, data-driven architectures, and intelligent lighting devices.