جستجوی استاد راهنمای دانشگاهی

Alessia Ferrari is a fixed-term researcher in the Department of Engineering and Architecture at the University of Parma, Italy. She lectures on Hydrology within the Bachelor’s degree programme in Civil and Environmental Engineering and serves as the reference teacher for the same programme across multiple academic years (2020/2021 – 2025/2026). Research Focus Ferrari’s research integrates advanced numerical modelling with real-world flood-risk management. Key themes include: High-resolution 2-D shallow-water simulations using GPU-parallel codes. Porosity-based approaches for large-scale urban flood modelling. Levee-breach hydraulics and emergency-action planning. Calibration of hydraulic models using tools such as PEST. Integration of machine-learning techniques with physics-based flood forecasting. Publication Trends Across more than 25 peer-reviewed works (2015-2025), Ferrari has concentrated on computational hydraulics applied to extreme flood events in Northern Italy (e.g., Parma 2014, Lamone 2024). Her papers consistently advance numerical schemes (ADER, HLLEM Riemann solvers) and GPU acceleration while validating models against field data, thereby bridging theoretical development and practical flood-mitigation strategies. Contact & Office E-mail: alessia.ferrari@unipr.it Office: Science and Technology Campus – Pavilion 10, Engineering Scientific Headquarters, Parco Area delle Scienze 181/A, 43124 Parma, Italy.

• Hydraulic Engineering
• Hydrology
• Computational Hydraulics
• +۶ مورد دیگر

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.

• Integrated Circuits
• Pervasive Computing
• Electronics
• +۱۴ مورد دیگر

Eleonora Vacca is a PhD student and Research Fellow in the Department of Automatic Control and Computer Science (DAUIN) at the Polytechnic University of Turin. She holds a B.S. in Electronic Engineering from the University of Palermo (2018) and an M.S. in Electronic Engineering-Embedded Systems from Politecnico di Torino (2021). Her research focuses on digital hardware design, reliability engineering, reconfigurable devices, and AI applications in aerospace and safety-critical systems. She is a member of the Aerospace and Safety Computing Lab and the CAD - Electronic CAD & Reliability Group (DAUIN). Her work addresses challenges such as radiation effects mitigation in space missions, fault-tolerant AI accelerators, and real-time anomaly detection in satellite telemetry. She has contributed to projects like the RAMSES CubeSat-1 Development (2025-2026), funded by commercial contracts. In 2024, she won the Best Student Paper Award at the NEWCAS Conference for her research on radiation effects in space missions. Vacca collaborates on teaching, including assisting in the course 'Electronic Calculators' for Computer Engineering students. Her recent publications explore AI resilience in RISC-V ecosystems, radiation environment analysis for space missions, and gesture recognition systems for smart cities. She actively contributes to conferences such as the ACM International Conference on Computing Frontiers and the IEEE International Smart Cities Conference.

• Digital Hardware Design
• Reliability Engineering
• Reconfigurable Devices
• +۳ مورد دیگر

Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.

• Telecommunications
• Digital Signal Processing
• Wireless Communications
• +۵ مورد دیگر

Neil Shah is a Lead Research Scientist at Snap Inc., leading initiatives in user modeling, personalization, and trust and safety across Snapchat. His research focuses on advancing machine learning algorithms for large-scale structured data, including graph and sequential representations, with applications to recommendation systems and social platform security. PhD in Computer Science, Carnegie Mellon University (2017), advised by Christos Faloutsos B.S. in Computer Science, North Carolina State University Current research interests span: Graph Neural Networks (GNNs) for real-time inference and scalable training Cross-domain recommendation systems and generative modeling Test-time augmentation and hyperbolic geometry in representation learning Explainability methods for GNNs and fairness-aware outlier detection Recent publications highlight productionized GNN frameworks (GiGL), multimodal graph benchmarks, and novel approaches to link prediction and collaborative filtering. His work has appeared at top venues like KDD, ICLR, NeurIPS, and WWW. Scientific recognition includes: Outstanding Service Award at WSDM 2022 Best Paper Honorable Mention at CHI 2019

• Graph Neural Networks
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Luigi De Russis is an Associate Professor at the Department of Control and Computer Engineering (DAUIN) within Politecnico di Torino . He serves as Deputy Director of DAUIN and is a member of the PIC4SeR (PoliTO Interdepartmental Centre for Service Robotics). His academic roles focus on Human-Computer Interaction , Digital Wellbeing , and Artificial Intelligence applications. Research interests: Accessibility, Conversational agents, Developers tools, Digital wellbeing, Intelligent user interfaces, Internet of Things Teaching: Courses in Human-AI Interaction, Web Applications, and Computer Vision at undergraduate and graduate levels Leadership: Vice-President of ACM SIGCHI (2024-), Executive Committee member (2021-2024) His research explores: Digital wellbeing education for teens through gamified systems AI-assisted UI design tools Smart home interaction via multimodal commands End-user development for self-control technologies Integration of accessibility guidelines in AI systems Recent article trends show a focus on generative AI for interface design, attention-capturing heuristics, and educational systems for step-by-step learning. He has received the Most Influential Paper Award (2024) and Best Late Breaking Results Award (2025) from ACM SIGCHI. Scientific awards: Award of Scientific Excellence, University of Salamanca (2011) Most Influential Paper Award, International Conference on Intelligent Environments (2024) Best Late Breaking Results Paper Award, ACM SIGCHI Symposium (2025) As advisor, he supervises PhD students in Artificial Intelligence and Computer Engineering , focusing on topics like user-centered AI, generative models, and digital self-control interfaces. He leads the ELITE research group and contributes to commercial projects including TEIA (AI tourism) and MAPP (interactive museums).

• Accessibility
• Conversational agents
• Developers tools
• +۱۱ مورد دیگر

Seth Frey is an Associate Professor in the Department of Communication at the University of California, Davis, with affiliate status at Indiana University's Ostrom Workshop and as Research Director at Metagov. His research focuses on computational social science approaches to understanding self-governance in complex social systems, particularly through the lens of online communities as model institutions. Education: Ph.D. in Cognitive Science and Informatics (complex systems), Indiana University, 2013 B.A. in Cognitive Science, UC Berkeley, 2004 Research Interests: Frey specializes in computational approaches to institutional analysis and the cognitive science of strategic behavior . His work examines how communities design governance systems to overcome collective action problems, with emphasis on: Emergent institutional structures in digital commons Policy-as-data through NLP and institutional grammar frameworks Cognitive mechanisms underlying cooperative behavior Design principles for participatory change in online platforms His methodology integrates large-scale data analysis, web-based experiments, and computational modeling across diverse contexts including Minecraft, Reddit, and professional sports ecosystems. Publication Trends: Recent publications (2023-2025) demonstrate a cohesive trajectory toward computational institutional analysis, with increasing focus on NLP-driven policy analysis (e.g., NLP4Gov), decentralized governance architectures (DAOs, multi-level platform governance), and the cognitive foundations of collective action. His work consistently bridges theoretical institutional analysis with practical applications in digital community design, showing particular growth in translating Ostrom's design principles into computational frameworks. Awards: Honorable Mention Award for Best Paper at ACM CSCW 2019 Advising and Grants: Frey mentors students interested in data science applications at the intersection of communication, cognition, and complex systems, emphasizing resourcefulness and intellectual curiosity. His research has secured substantial funding from: National Science Foundation (NSF) NASA Ford Foundation Google Open Source Foundation He actively encourages aspiring graduate students with strong self-directed research skills to explore computational approaches to social phenomena. Labs and Teams: He leads the Computational Communication Lab at UC Davis and co-directs the Institutional Grammar Research Initiative. Through Metagov, he develops the 'Governance API' framework for modular community governance. His past affiliations include Disney Research (Walt Disney Imagineering) where he applied complexity science to theme park systems, and the New England Complex Systems Institute (NECSI). Current collaborations span Ethereum governance, Minecraft server ecosystems, and Colorado's cannabis monitoring infrastructure.

• Computational Social Science
• Governance of Commons
• Complex Systems
• +۵ مورد دیگر

Pietro Liò is a Full Professor in the Department of Computer Science and Technology at the University of Cambridge, where he is also a member of the Artificial Intelligence group. His work bridges computer science and biomedical applications, with a strong focus on advancing AI methods for healthcare. Research Interests: His research is centered on developing Artificial Intelligence and Computational Biology models to unravel the complexity of diseases and support personalized and precision medicine. A current emphasis is on Graph Neural Network modeling, leveraging topological data structures to represent biological and medical systems. His interdisciplinary background enables innovative approaches at the intersection of machine learning and life sciences. The trends in his research, though no specific articles are listed, indicate a strong focus on AI-driven biomedical discovery, particularly using deep learning on structured data for health applications. This includes modeling biological networks, disease mechanisms, and patient-specific conditions through advanced neural architectures. Scientific Awards: As a principal investigator and academic leader, Pietro Liò likely supervises PhD and postdoctoral researchers and secures research grants in AI for health, though specific advisees and funding details are not mentioned in the text. His dual PhD background and affiliation with a leading AI group suggest a robust research program with significant grant involvement. He is associated with AI research activities at Cambridge, including seminars and software development, possibly contributing to or leading a research lab or initiative focused on AI applications in biology and medicine, though no formal lab name is provided beyond the general AI group membership.

• Artificial Intelligence
• Computational Biology
• Graph Neural Networks
• +۵ مورد دیگر

Ursula Zich is an Associate Professor at the Polytechnic of Turin's Department of Architecture and Design (DAD), where she serves as a member of the Student Discipline Commission. Born in Turin on July 16, 1969, she holds a Doctor of Architecture degree with highest honors from the Polytechnic of Turin (1994) and a Doctor of Research in Surveying and Representation of Architecture and the Environment from the University of Genoa. Her research interests focus on critical reading of drawing, descriptive geometry, history of representation, and physical models. She leads the MAG.IA (Mathematics, Architecture, Geometry. Application Interconnections) research line and the POLIMADE project exploring scientific applications of origami. Her work spans multiple ERC sectors including application of mathematics in sciences, computational modeling in cultural spheres, cultural studies, history of art and architecture, and museum studies. Zich has published extensively on architectural representation, with recent publications examining tangible geometries for inclusive game design, architectural heritage accessibility, and interdisciplinary approaches to architectural representation. Her research demonstrates consistent integration of mathematical principles with architectural representation techniques. Effective member of Study Group on Environmental Color Design (ECD) of the International Color Association (AIC), United States (2021-) Effective member of Italian Design Union (UID), Italy (2001-) She has served on the Program Committee for multiple Italian Conferences on Origami, Educational Dynamics and Teaching since 2014. Zich also co-invented a patent for a foldable aluminum foil food tray, demonstrating practical applications of her origami research. At the Polytechnic of Turin, she teaches architectural drawing, surveying, and geometric modeling courses across multiple academic years, maintaining an active teaching schedule through the 2025/26 academic year.

• Critical reading of drawing
• Descriptive geometry
• History of representation
• +۵ مورد دیگر

Carlo Baldassi is an Associate Professor at Bocconi University, where he has served as Director of the BSc in Mathematical and Computing Sciences for Artificial Intelligence (BAI) since 2023/24. He holds a background in Theoretical Physics from the University of Trieste and a PhD in Computational Neuroscience from the University of Turin. His research focuses on applying Statistical Mechanics to Machine Learning and Neural Networks, particularly studying loss landscapes, optimization problems, and the role of quantum annealing in nonconvex learning. He teaches courses in Machine Learning, Artificial Intelligence, and Computer Science, emphasizing Python and Julia programming. His work bridges theoretical physics and AI, exploring topics like synaptic stochasticity in low-precision neural networks and the efficiency of quantum vs. classical annealing. He has published extensively in top journals such as Physical Review Letters and Proceedings of the National Academy of Sciences , contributing to foundational understanding of neural network dynamics and optimization techniques. Teaching includes Machine Learning and Artificial Intelligence Computer Science I Machine Learning II Machine Learning and Artificial Intelligence Lab Research emphasizes large-scale inference problems, with a focus on the interplay between statistical mechanics and modern AI architectures.

• Machine Learning
• Computational Neuroscience
• Statistical Mechanics
• +۴ مورد دیگر

Gaetano Miraglia is a Fixed-term Assistant Professor in the Department of Structural, Building and Geotechnical Engineering (DISEG) at Politecnico di Torino, where he conducts research in structural health monitoring, seismic analysis, and computational modeling. He is a member of the Interdepartmental Center R3C – Responsible Risk Resilience Centre, contributing to interdisciplinary efforts in risk mitigation and infrastructure resilience. His work spans both theoretical and applied domains, with strong emphasis on heritage preservation and sustainable urban development. His research interests include Bayesian calibration of nonlinear models, hybrid simulation, peridynamics, masonry structures, and the integration of satellite interferometric (InSAR) data with in-situ measurements for structural monitoring. He applies advanced computational and machine learning techniques to improve the accuracy and reliability of structural assessments, particularly in historical and monumental buildings. His work supports UN Sustainable Development Goals 9, 11, and 13. His recent publications demonstrate a consistent focus on data fusion, digital twinning, domain adaptation, and real-time damage detection. He frequently collaborates with researchers such as Rosario Ceravolo and Erica Lenticchia, publishing in high-impact journals like Computer-Aided Civil and Infrastructure Engineering , Structures , and Scientific Reports , as well as at major conferences including EWSHM, SAHC, and EVACES. His research is applied in projects such as the monitoring of the Vicoforte Sanctuary and the development of the CAMELOT and HY-LEARN toolboxes. Research Projects: MONITORAGGIO VICOFORTE (2024–2026) – Member of Research Group CAMELOT – PoC Transition (2023–2024) – Member of Research Group HY-LEARN – Model Calibration via Hybrid Simulation and ML (2022–2024) – Scientific Manager (PNRR Mission 4) He teaches in various programs, including as a course collaborator in PhD, Master’s, and Bachelor’s level courses such as Earthquake Engineering , Structural Consolidation , and Seismic Risk of Cultural Heritage . He is also an inventor on national and international patents and software related to the CAMELOT toolbox, highlighting the translational impact of his research. He has no listed scientific awards or formal advisees in the provided text.

• Structural Health Monitoring
• Seismic Analysis
• Bayesian Calibration
• +۱۴ مورد دیگر

Emanuele Naboni is an Associate Professor in the Department of Engineering and Architecture at the University of Parma, Italy. He teaches in the Second Cycle Degree program in Architecture and City Sustainability, offering courses such as Architectural Technologies for the Built Environment , Environmental and Outdoor Comfort Assessment , and Innovative Technologies for Sustainable Design from academic year 2019/2020 through 2025/2026. His research focuses on sustainable and climate-responsive architecture, with particular emphasis on urban microclimates, passive design strategies, and building performance optimization in Mediterranean environments. Key areas include facade engineering, thermal comfort, and computational simulation of localized climate impacts. The recent publications (2024–2025) highlight a strong trend in climate change adaptation through architectural and urban interventions. Topics span from simulating hyperlocal temperature variations to optimizing courtyard microclimates using evaporative cooling and adaptive shading, as well as retrofitting modernist urban forms for improved climate resilience. These works reflect interdisciplinary engagement with urban climatology, building physics, and environmental design. Scientific Awards: No awards mentioned in the provided text. Prof. Naboni is actively engaged in teaching and research. There is no mention of formal advising roles, grants, or leadership in labs or research teams within the available information. His scholarly output demonstrates consistent collaboration with researchers such as Marcello Turrini, Barbara Gherri, Carlos Alberto Rivera Gómez, and Carmen Galán-Marín. He contributes to advancing sustainable design practices through empirical and simulation-based studies, particularly focused on urban and architectural responses to climate change in Southern Europe.

• Sustainable Architecture
• Climate Change Adaptation
• Urban Microclimate
• +۷ مورد دیگر

Massimo Canale is a Tenured Associate Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino , and a member of the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His academic career spans over two decades, focusing on control systems engineering with applications in automotive technology. Scientific Branch: Systems and Control Engineering (IINF-04/A) ERC Sectors: Automotive Engineering, Control Engineering, Control Theory Dr. Canale's research bridges theoretical advancements in Model Predictive Control (MPC) with practical applications in autonomous vehicles , hybrid/electric propulsion , and active suspension systems . His work integrates reinforcement learning and dynamic programming for optimizing vehicle performance and energy efficiency. Recent publications demonstrate trends in autonomous driving architectures (2024), sliding mode control for highway scenarios (2024), and energy management for sustainable mobility (2023-2024). He has developed patented solutions for semi-active suspension control and autonomous vehicle guidance. Award: IEEE Transactions on Control Systems Technology Outstanding Paper Award (2011) Editorial Roles: Associate Editor, IEEE Open Journal of Control Systems (2022–present) Dr. Canale supervises PhD students like Francesco Cerrito and teaches courses on digital control technologies , automatic control , and reinforcement learning at Politecnico di Torino. His research is funded through competitive grants (e.g., MPC4AVP 2021-2022) and commercial contracts (AD Shuttle 2024).

• Control and Systems Engineering
• Automotive Engineering
• Model Predictive Control
• +۱۰ مورد دیگر

Luciano Lavagno is a Full Professor at the Department of Electronics and Telecommunications, Polytechnic University of Turin, with over two decades of academic and research contributions. His work bridges hardware acceleration, low-power electronics, and intelligent system design. Research Focus: Hardware-accelerated machine learning, high-level synthesis (HLS) for FPGA/ASIC, heterogeneous CPU/GPU/FPGA platforms Key Projects: SPACE (predictable acceleration), REBECCA (secure AI acceleration), HPC-National Center (quantum computing), and oral history preservation via "Ti racconto una storia" initiative His recent publications analyze CNN inference optimization, subgraph isomorphism, and superword-level parallelism exploitation. Lavagno supervises multiple PhD students working on FPGA acceleration, neural network hardware, and embedded systems. As Principal Investigator for national and EU-funded projects (PRIN, JTI-ECSEL, PNRR), he drives advancements in sustainable computing infrastructure. His patented technologies include MIx&Latch timing methodology, capacitive sensing innovations, and 5G acceleration frameworks.

• Field Programmable Gate Arrays (FPGA)
• High-Level Synthesis
• Indoor Positioning
• +۱۰ مورد دیگر

Maurizio MUZZUPAPPA is a Full Professor at the Department of Mechanical, Energy and Management Engineering (University of Calabria) since 2018. His roles include Rector's Delegate for Technology Transfer, Academic Delegate for Education at DIMEG, and Head of the Physical Prototyping Laboratory at the MaTeRiA Center (UNICAL-CNISM collaboration). He supervises the Unical Racing Team in Formula SAE competitions and co-founded three university spin-offs: 3DResearch, Tech4Sea, and Q-BOT. As Scientific Director of projects like TECH4YOU (climate change adaptation technologies) and GROWN IN THE BLUE (Mediterranean reef conservation), he integrates research in industrial design, augmented reality, and underwater cultural heritage. He has authored over 200 publications (h-index 27) and holds 10 patents. His teaching includes Tools and Methods for Industrial Design and Formula SAE LAB . His research focuses on: Industrial design methodologies with parametric and sustainable approaches 3D prototyping and additive manufacturing User-Centered Design for product ergonomics Virtual/Augmented Reality applications in engineering and cultural heritage Underwater robotics and artifact restoration Recent publications highlight trends in AR for industrial maintenance, generative design tools, and mechatronic solutions for underwater heritage. He has supervised over 300 theses and 10 Ph.D. students while leading technology transfer initiatives.

• Industrial Engineering Design
• Augmented Reality (AR) Applications
• Product Development Methodologies
• +۵ مورد دیگر