جستجوی استاد راهنمای دانشگاهی

Giorgio Grisetti is a Full Professor at Sapienza University of Rome within the Department of Systems and Computer Science, maintaining active research roles in the RoCoCo lab at Sapienza since November 2010 and the Autonomous Intelligent Systems Lab at Freiburg University where he previously served as a Post Doc under Wolfram Burgard starting in 2006. His educational background includes a M.Sc. in Computer Engineering from the University of Rome (2001) and a Ph.D. from Sapienza University of Rome's Intelligent Systems Lab (2006), supervised by Daniele Nardi. His doctoral thesis focused on SLAM using Rao-Blackwellized particle filters. Dr. Grisetti's research centers on mobile robotics with emphasis on robust solutions for autonomous navigation systems. His work spans theoretical and practical advancements in Simultaneous Localization and Mapping (SLAM), robot localization, path planning, and sensor fusion, particularly leveraging LiDAR and multi-sensor configurations. Recent publications demonstrate strong focus on optimization techniques, sensor calibration, and real-time performance for autonomous systems operating in complex environments. His publication trends reveal deep specialization in LiDAR-based SLAM (7 of 15 recent articles), bundle adjustment methods (4 articles), and sensor calibration/perception (3 articles), with consistent contributions to top robotics venues like IEEE Robotics and Automation Letters and ICRA. Key recognitions include: Nomination for the best IROS paper award (2010) Open Source achievement award from Willow Garage (2010) Best paper award at the International Conference and Exhibition on Unmanned Areal Vehicles (2010) Best Paper award at ICRA 2009 (2009) His research is conducted through the RoCoCo lab at Sapienza University of Rome and the Autonomous Intelligent Systems Lab at Freiburg University, focusing on developing foundational algorithms for mobile robot autonomy. Current projects emphasize robust perception systems, optimization frameworks for sensor fusion, and practical implementations for real-world navigation challenges.

• Mobile Robotics
• SLAM
• Robot Localization
• +۳ مورد دیگر

Valeria Bruschi is a Researcher at the Department of Information Engineering (DII) within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. Her academic profile was last updated on April 13, 2024, and she maintains her office at the Engineering Faculty on via Brecce Bianche, with contact information including phone +39 071-220-4486 and email v.bruschi@staff.univpm.it. Dr. Bruschi's research spans multiple domains within audio and signal processing, with particular expertise in spatial audio systems, automotive human-computer interaction, and biomedical signal applications. Her work bridges theoretical signal processing techniques with practical implementations across diverse fields including automotive safety systems, hearing aid technology, sleep medicine, and agricultural monitoring. She has made significant contributions to head-related transfer function (HRTF) processing, real-time audio enhancement algorithms, and innovative monitoring systems that utilize acoustic signals for various applications. Analysis of Dr. Bruschi's recent publications reveals a strong trajectory in developing practical audio processing solutions with real-world applications. Her work shows increasing integration of machine learning techniques with traditional signal processing approaches, particularly in areas like driver monitoring systems, snoring detection and cancellation, and spatial audio rendering. A notable trend is her focus on creating lightweight, real-time implementations suitable for embedded systems and practical deployment scenarios, while maintaining high performance standards. Her research consistently demonstrates interdisciplinary collaboration, connecting audio engineering with fields as diverse as automotive safety, sleep medicine, and agricultural technology. Dr. Bruschi actively contributes to advancing audio engineering through her research on equalization techniques, noise reduction systems, and immersive audio technologies. Her work on pulse compression techniques for hearing aid distortion measurement represents an important contribution to audiological assessment methodologies. Her publication record demonstrates consistent scholarly output with increasing impact across multiple application domains, reflecting her ability to translate theoretical signal processing concepts into practical engineering solutions.

• Audio Engineering
• Signal Processing
• Spatial Audio
• +۵ مورد دیگر

Simon Masnou is a Full Professor at Université Claude Bernard Lyon 1, affiliated with the Institut Camille Jordan (CNRS UMR 5208). He holds leadership roles as Head of the 'Applied Mathematics, Statistics' Master's degree and Head of the 'M2 Maths in Action' program. Previously, he served as Director of the Camille Jordan Institute (2018-2022). His research focuses on applied mathematics, image processing, shape optimization, and geometric measure theory, with contributions to variational models, geometric flows, and applications in computer vision and materials science. Education: PhD in Mathematics (1998, Paris Dauphine) and HDR (2008, Paris 6). Research projects include ANR STOIQUES (2024-2028), PEPR PDE-AI (2023-2028), and collaborations with industry on topics like defect prediction in aluminum production and high-dimensional data analysis. Teaching includes courses on linear algebra, optimization, and machine learning at undergraduate and graduate levels. Key contributions span phase field models, varifold-based surface approximation, and image inpainting. He supervises PhD students in geometric variational problems and computational methods. His work bridges theoretical mathematics with industrial challenges, addressing issues in materials science, medical imaging, and cultural heritage preservation.

• Applied Mathematics
• Image Processing
• Shape Optimization
• +۵ مورد دیگر

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.

• Structural Health Monitoring
• Machine Learning in Civil Engineering
• Earthquake Engineering
• +۹ مورد دیگر

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.

• Dependability
• Fault Tolerance
• Reliability Analysis
• +۸ مورد دیگر

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.

• Reconfigurable computing
• Computer-aided design algorithms
• Fault tolerance and reliability
• +۷ مورد دیگر

Umberto Desideri is a Full Professor of Thermal Machines at the University of Pisa since November 2014, following his tenure as Full Professor at the University of Perugia from 2004 to 2014. He has held leadership roles, including Head of the Department of Engineering at the University of Perugia (2014) and Head of the Department of Energy, Systems, Territory and Construction Engineering at the University of Pisa (2016–2020). He is actively involved in editorial boards, such as the ASME Journal of Fuel Cell Science and Technology (2005–2017), Journal Applied Energy (since 2007, Associate Editor from 2011, Senior Editor since 2022), and Journal Applied Thermal Engineering (since 2013). Additionally, he co-founded two spin-off companies in 2005: Tecnologie per la riduzione delle emissioni engineering srl and Biomasse e nuove tecnologie srl . Desideri obtained his MSc in Mechanical Engineering from the University of Florence in 1988 and his PhD in Energy Engineering from the same university in 1993. His academic career includes roles as Assistant and Associate Professor at the University of Perugia (1992–2004) before becoming a Full Professor there in 2004. His research focuses on renewable energy systems (geothermal, solar, biomass), hydrogen and fuel cell technologies, carbon capture and storage, and energy-efficient buildings. He explores polygeneration systems, sustainable energy storage, and decarbonization strategies for industries like tissue paper production. Recent work emphasizes the integration of renewables with thermal storage and CO2 utilization in circular energy systems. Awards: Fellow of the American Society of Mechanical Engineers (since 1994) Listed in the Top Italian Scientists in Engineering Recognized as a World Top 2% Cited Scientist In advising and grants, he has supervised over 200 Master’s theses and led EU-funded projects such as: H2020 COMPBAT (2020–2024): Computer-aided design for next-gen flow batteries H2020 Regen-by-2 (2020–2027): Multi-energy systems using two-phase fluids LIFE Augia (2020–2023): Sewage oxy-gasification for chemicals production He directed the Fuel Cell Laboratory (2007–2014) and Wind Tunnel (2010–2014) at the University of Perugia. His current work at the University of Pisa’s DESTEC department addresses hydrogen technologies, energy transition, and sustainable systems.

• Renewable Energy Systems
• Thermal Engineering
• Hydrogen Technology
• +۱۵ مورد دیگر

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.

• Reliable and Fault-Tolerant Computing
• RISC-V Architecture
• FPGA-Based Systems
• +۱۲ مورد دیگر

Dr. Ala Alrababah is an Assistant Professor in the Department of Social and Political Sciences at Bocconi University, with affiliations including the Evidence in Governance and Politics (EGAP) network, Immigration Policy Lab (IPL) at ETH Zurich and Stanford, BAFFI Center on Economics, Finance and Regulation at Bocconi, and the Abdul Latif Jameel Poverty Action Lab (J-PAL). She holds a Ph.D. in Political Science from Stanford University (2021). Her research examines immigration, refugees, and political violence using innovative mixed-methods approaches combining fieldwork with experimental and computational techniques. Primary domains include comparative analysis of migration policies, conflict dynamics in the Middle East, prejudice reduction strategies, and quantitative analysis of political discourse. She maintains active field research programs focused on Syrian refugee communities. Publications demonstrate consistent focus on migration policy impacts, refugee decision-making, and political violence analysis across multiple contexts. Computational methods feature prominently alongside field experiments, with strong methodological contributions to survey research and text analysis. As an active member of international research networks, Dr. Alrababah collaborates on large-scale projects examining refugee integration policies, transitional justice mechanisms, and political behavior in conflict regions. Her work has received international media coverage in outlets including The Economist, Foreign Policy, and BBC Arabic.

• Immigration Studies
• Political Violence
• Refugee Politics
• +۳ مورد دیگر

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)

• Digital Circuits and Systems
• Energy-Efficient Circuits and Systems
• Embedded Systems
• +۷ مورد دیگر

Marco Porta is a Full Professor at the University of Pavia, Department of Electrical, Computer and Biomedical Engineering. He teaches Web and Multimedia Technologies in the Computer Engineering Master's program and Web Design and Technologies in the interdepartmental CIM Bachelor's program. His research focuses on Eye Tracking, Vision-Based Perceptive Interfaces, and Human-Computer Interaction, with recent emphasis on AI applications for human-centered systems. He leads the Computer Vision & Multimedia Lab and chairs teaching councils for CIM and CoD programs. Education: Master's in Electronic Engineering (Polytechnic of Milan) and Ph.D. in Electronic & Computer Engineering (University of Pavia). Professional roles include vice-chair of IEEE's Technical Committee on Factory Automation. Over 118 publications in journals/conferences, with contributions to biometrics, e-learning interfaces, and industrial automation. Research highlights include gaze-based authentication systems, interactive museum interfaces, and ergonomic in-vehicle infotainment evaluations. Current projects explore gaze-driven intelligent tutoring systems and public space interaction frameworks.

• Computer Vision
• Human-Computer Interaction
• Eye Tracking
• +۴ مورد دیگر

Luigi De Napoli is an Assistant Professor in the Department of Mechanical, Energy and Management Engineering at the University of Calabria's Engineering Faculty. He has been serving in this position since March 1, 2006, and achieved National Scientific qualification as associate in the Italian higher education system for the disciplinary field of 09/A3 - Industrial design, machine construction, and metallurgy, starting from December 20, 2019. His educational background includes a Bachelor Degree in Mechanical Engineering from the University of Calabria in 1993, followed by qualification as an Engineer in 1994. He completed his Ph.D. degree in Design and Methods in Industrial Engineering at the University of Bologna in 2003, with a thesis focused on the reconstruction of archaeological artifacts using CAD systems. High school: Liceo Scientifico Statale E. Fermi di Cosenza (1986) Bachelor Degree: Mechanical Engineering, University of Calabria (1993) Engineer Qualification (1994) Scholarship: ITIA-CNR in Milan on advanced FEM and BEM systems (1995/96) Ph.D.: Design and Methods in Industrial Engineering, University of Bologna (2003) Dr. De Napoli's research primarily focuses on Reverse Engineering applications in Mechanical Engineering, Product Design and Development, and Virtual Prototyping. His work spans various applications including the reconstruction of archaeological artifacts, geometry inspection, hull and prosthesis reconstruction, and sustainable product design methodologies. His recent publications demonstrate a strong emphasis on biomedical applications, particularly in cranial prosthetics, tissue engineering, and ovarian tissue culture systems. His teaching portfolio is extensive, covering courses such as Computer-Aided Design, Sustainable Product Design, Engineering Drawing/CAD, and Modeling and Prototyping for Bioengineering across both Mechanical and Management Engineering programs. He has been teaching CAD courses since 2010 and Sustainable Product Design since 2011 at the University of Calabria. Dr. De Napoli is actively involved in the Research Group for Industrial Engineering Design and Methods (ING-IND/15), which focuses on methodologies and tools for product development processes, industrial product design and development (with particular attention to parametric and sustainable aspects), prototyping (virtual and mixed), and manufacturing using 3D printers. His work also encompasses Reverse Engineering techniques, User Centered Design methodologies for ergonomic analysis, and Virtual and Augmented Reality applications for industrial product design.

• Reverse Engineering
• Product Design and Development
• Virtual Prototyping
• +۳ مورد دیگر

Alessandro Evangelista is an Assistant Professor at the Polytechnic University of Bari, Italy, within the Department of Mechanics, Mathematics & Management. His scientific-disciplinary sector is ING-IND/15, focusing on Design methods for industrial engineering. His research integrates Virtual, Augmented and Mixed Reality technologies into industrial and training contexts, with strong attention to ergonomics, safety, and human factors. Research Interests Virtual Reality (VR) and immersive simulation for industrial training and safety Augmented Reality (AR) interface design and ergonomic assessment Mixed Reality (MR) applications in product lifecycle and medical prosthesis design Human-computer interaction, cognitive workload, and age-related performance in XR systems Industry 4.0 smart maintenance and real-time data visualization Recent works repeatedly explore how immersive technologies can enhance learning outcomes, safety behaviors, and user experience across manufacturing, retail, maritime navigation and healthcare domains. Studies often adopt comparative user evaluations, ergonomic assessment protocols (e.g., RULA), and multidimensional performance metrics. Publications Trend From 2020 to 2025 Evangelista authored numerous peer-reviewed articles concentrated on immersive technologies. Major themes include: (1) VR training effectiveness for confined spaces and industrial tasks, (2) AR visualization for maintenance and navigation, (3) ergonomic and age-related factors in XR, and (4) application of cinematic VR for safety attitude change and mental-health rehabilitation. His output evidences systematic review work, empirical user studies, and tool prototyping, positioning him at the intersection of design engineering and interactive technologies. Scientific Awards & Grants No specific awards or funded projects are mentioned in the supplied material. Advising & Labs No explicit list of students or research group descriptions are provided; therefore advising activity and laboratory affiliations cannot be detailed at present.

• Virtual Reality
• Augmented Reality
• Mixed Reality
• +۵ مورد دیگر

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 Vision
• Image Processing
• Artificial Intelligence
• +۵ مورد دیگر

Roberto Menichetti is a theoretical physicist at the University of Trento , affiliated with the Department of Physics and the VARIAMOLS research group . His work integrates computational physics, statistical mechanics, and machine learning to model biomolecules and soft matter systems. Prior roles include postdoctoral research at the Max Planck Institute for Polymer Research (2016-2018) and academic training at the University of Rome 'La Sapienza'. PhD in Physics (La Sapienza, 2016) BSc/MSc in Physics (La Sapienza, 2012) His research spans: Coarse-Graining Methods for polymers, colloids, and biomolecules High-throughput Molecular Dynamics Simulations in drug-membrane permeability studies Integration of Machine Learning with physical models for multi-scale analysis Applications in Biophysics (e.g., chromatin condensates, protein dynamics) Article trends highlight his focus on computational frameworks like EXCOGITO and theoretical investigations of non-equilibrium systems and allosteric regulation . He actively develops tools for systematic model reduction and conformational sampling in biomolecular systems. Contact: roberto.menichetti@unitn.it

• Theoretical Physics
• Computational Physics
• Statistical Mechanics
• +۷ مورد دیگر