جستجوی استاد راهنمای دانشگاهی

• Behavioral modeling
• Electromagnetic compatibility
• Macromodeling
• +۷ مورد دیگر

Stefano Grivet-Talocia is a Full Professor at the Department of Electronics and Telecommunications at the Polytechnic University of Turin, where he also serves as Director of the Doctoral School and President of the Doctoral School Council. He is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, the University Committee for Research, Technology Transfer and Services to the Territory, and the Commission for the Promotion of Library, Archive and Museum Heritage. His academic career spans over two decades at Politecnico di Torino, where he has established himself as a leading researcher in electromagnetic modeling and signal integrity. Grivet-Talocia earned his Laurea degree (summa cum laude) in Electronic Engineering in 1994 and his Ph.D. in Electronic and Communication Engineering in 1998, both from the Polytechnic University of Turin. Between 1994 and 1996, he conducted research at NASA/Goddard Space Flight Center in Greenbelt, Maryland. His educational background laid the foundation for his expertise in electromagnetic modeling, wavelet analysis, and signal processing. His research focuses on behavioral modeling, electromagnetic compatibility, macromodeling, model order reduction, numerical modeling, passivity, power integrity, signal integrity, transmission lines, and wavelets . Grivet-Talocia is particularly renowned for his work on passive macromodeling of interconnect structures, development of the TOPLine technique for transmission line simulation, and pioneering contributions to passivity enforcement algorithms. He has co-authored the first book entirely dedicated to Macromodeling (2016) and developed innovative approaches to waveform relaxation and wavelet-based signal processing. His recent publications (2024-2025) demonstrate continued leadership in model order reduction, with significant contributions to data-driven modeling of linear and nonlinear systems, power integrity analysis, and electromagnetic compatibility. His work spans both theoretical advances in numerical methods and practical applications in circuit design, with strong industry relevance particularly for semiconductor and electronic design automation companies. IEEE Fellow (2018-present) Three Intel SRS Grants (2022-2024) Three IBM SUR Grant Awards (2007-2009) Best Associate Editor Award - IEEE Transactions on Components, Packaging and Manufacturing Technology (2020) Multiple Best Conference Paper Awards (2006-2020) URSI Young Scientist Awards (1999) Ranked among the "top 2% worldwide researchers" (Stanford) since 2019 Grivet-Talocia actively supervises doctoral students including Michele Cusano, Sara Paknezhad Panahi, Antonio Carlucci, and Kun Zhao. He has secured numerous research grants from competitive national calls (PRIN) and commercial contracts with industry partners including Intel, IBM, Nokia, Hitachi, Infineon, and Cadence. His technology transfer activities include co-founding the spin-off IdemWorks (2007-2016), which was acquired by CST in 2016. He also developed the autoCircuits web service for automated circuit problem generation, widely used in electrical engineering education. He leads the EMC Group (Electromagnetic Compatibility) at DET and has been instrumental in establishing the Compact Dynamical Modeling research area. His work has practical applications in high-speed electronics design, with algorithms embedded in commercial tools like IBM PowerSPICE. Grivet-Talocia maintains strong industry connections through his research projects and serves as Associate Editor for IEEE Transactions on Components, Packaging and Manufacturing Technology.

Andrea Santilliمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Representation Learning
• Machine Intelligence
• +۱۰ مورد دیگر

Andrea Santilli is a Research Scientist at Nous Research and holds a PhD in Computer Science from GLADIA at Sapienza University of Rome. His research focuses on large language models (LLMs), robustness, reliability, and multimodal learning. He previously worked at Apple MLR, Hugging Face’s BigScience, and Pi School. He earned his MSc and BSc in Computer Science from Tor Vergata University and Sapienza. Education: PhD in Computer Science, Sapienza University of Rome (2024) MSc in Computer Science, University of Roma Tor Vergata (2020) BSc in Computer Science, University of Roma Tor Vergata (2018) Research Interests: Santilli’s work spans LLM robustness , mechanistic interpretability , multimodal neural databases , and instruction-tuning . He introduced Parallel Jacobi Decoding and contributed to projects like BLOOM, Camoscio, and Fauno. His research bridges syntax-aware NLP, privacy-preserving LLMs, and cross-modal alignment. Publications: His work includes advancements in 3D-text latent space alignment (CVPR 2025), evolutionary merging (ICML 2025), and efficient decoding (ACL 2023). Over 15+ peer-reviewed papers span venues like ACL, CVPR, and ICLR. Awards: Received the Emanuele Pianta Award for his MSc thesis on continual language learning with syntax-based episodic memory. Grants & Projects: Winner of ‘Machine Learning Algorithms for Translation’ grant (2022), developing Parallel Decoding Co-PI for ‘Multimodal AI for 3D Analysis’ (2021) with Ecole Polytechnique Labs & Teams: Active in GLADIA (Sapienza), Apple MLR, and Hugging Face’s BigScience initiative. Core contributor to open-source projects like PromptSource and BLOOM.

• Geometric Measure Theory
• Optimal Transport
• Calculus of Variations
• +۳ مورد دیگر

Luigi Ambrosio is a Full Professor at the Scuola Normale Superiore di Pisa (SNS), specializing in geometric measure theory, optimal transport, and partial differential equations. His research focuses on the interplay between geometric analysis, functional analysis, and calculus of variations, with applications to metric measure spaces and stochastic processes. He has organized numerous conferences and schools on optimal transport and geometric analysis, including the 2025 'XXXV Convegno Nazionale di Calcolo delle Variazioni.' Key research interests include the theory of currents, regularity of flows, and the application of optimal transport to problems in probability and geometry. Notable contributions include foundational work on metric Sobolev spaces, RCD spaces, and the analysis of geometric flows. Ambrosio frequently collaborates with leading institutions and has supervised numerous seminars on topics ranging from gradient flows to non-smooth geometric structures. His publications span over 150 papers, addressing topics such as the regularity of vector fields, entropy flows in Carnot groups, and the stability of action functionals. Recent works (2021–2025) explore superposition principles for currents, sharp PDE estimates for random matching, and embedding theorems for metric spaces. Ambrosio is also active in academic leadership, contributing to editorial boards and international research networks.

• Optimal Transport
• Geometric Analysis
• Ricci Curvature
• +۳ مورد دیگر

Fabio Cavalletti is a Full Professor at the University of Milan, specializing in geometric analysis, optimal transport theory, and synthetic curvature bounds. His work bridges differential geometry, mathematical physics, and functional inequalities, with particular focus on Lorentzian spaces and Ricci curvature. He has organized international workshops and conferences on optimal transport and geometric analysis. Research interests include optimal transport in Lorentzian and Riemannian settings, synthetic Ricci curvature conditions, isoperimetric inequalities, and geometric flows. Recent work explores timelike Ricci curvature bounds, null hypersurfaces in general relativity, and applications to quantum information geometry. Key contributions include foundational results on displacement convexity, quantitative Obata's theorem, and optimal transport in singular spaces. He has collaborated extensively with researchers like Andrea Mondino and Nicola Gigli, producing over 35 peer-reviewed publications. Notable activities include organizing the 2024 School and Conference on Metric Measure Spaces, 2025 Workshop on Optimal Transport and Metric Geometry, and mentoring junior researchers in geometric analysis. Current projects address synthetic timelike curvature in Lorentzian spaces and applications to general relativity.

• Electrical Engineering
• Modeling and Simulation
• Machine Learning
• +۵ مورد دیگر

Igor Simone Stievano is a Full Professor at the Polytechnic University of Turin , affiliated with the Department of Electronics and Telecommunications (DET) and the Interdepartmental Center Ec-L - Energy Center Lab . He holds a PhD in Electrical Engineering and has supervised numerous students in disciplines spanning electromagnetic compatibility, machine learning, and multi-energy networks. His research interests include: Modeling and simulation of integrated circuits Machine learning for signal integrity Multi-energy network resilience Stochastic analysis of electrical systems Electromagnetic compatibility Key projects include the EU-funded SHIMMER initiative on hydrogen injection in gas networks and commercial contracts for high-speed I/O macromodeling. He serves as a chair and committee member at major conferences like the IEEE Workshop on Signal and Power Integrity. Scientific recognitions : IEEE Senior Member Recipient of the 2013 Futuro in Ricerca grant Editorial Board member of ENERGIES (2020-) Stievano actively participates in PhD college evaluations for Mathematical Sciences and Metrology programs at Politecnico di Torino, while teaching courses in Electrical Engineering and Digital Technologies across biomedical, computer, and media engineering curricula.

Hugo Georges Victor Lavenantمشاهده پروفایل

استادیار

• Optimal Transport
• Calculus of Variations
• Convex Analysis
• +۳ مورد دیگر

Hugo Georges Victor Lavenant serves as Assistant Professor in the Department of Decision Sciences at Bocconi University, Milan, where he has held a faculty position since 2020. Previously, he completed a postdoctoral fellowship at the University of British Columbia (2019-2020) under the Pacific Institute of Mathematical Sciences and earned his PhD in Mathematics from Université Paris-Sud (2016-2019) under Filippo Santambrogio's supervision. His academic foundation includes: PhD in Mathematics, Université Paris-Sud (2016-2019) Studies at École Normale Supérieure (2012-2016) covering mathematics, physics, history, and philosophy of science Classes préparatoires in mathematics and physics (2010-2012) Lavenant's research centers on optimal transport theory and its applications across mathematical disciplines. He investigates geometric structures in Wasserstein spaces, develops numerical methods for dynamical optimal transport, and bridges theoretical advances with Bayesian statistics. His work demonstrates particular innovation in trajectory inference for biological data and dependence measures for random measures, connecting pure mathematics with computational statistics. Recent publications reveal accelerating interdisciplinary impact, with 2024-2025 works extending optimal transport to machine learning (kernel methods, variational inference) and data science (opinion dynamics, single-cell analysis). This trajectory shows increasing methodological sophistication in handling measure-valued mappings and non-smooth geometries while maintaining computational tractability. Award recognition includes: Pacific Institute of Mathematical Sciences Postdoctoral Fellowship Lavenant actively mentors early-career researchers through formal advising relationships and collaborative projects. He currently supervises two PhD candidates (George Kanchaveli and Francesco Mascari, co-advised with Marta Catalano) and has guided Master's students including Mathis Hardion and Niccolò Bargellini. His teaching portfolio spans advanced analysis, optimization, and real analysis courses at Bocconi, reflecting his commitment to mathematical rigor in education. He operates within Bocconi's Decision Sciences ecosystem while maintaining international collaborations with researchers at UBC, Université Paris-Sud, and statistical groups worldwide. Current projects focus on entropy-based transport methods and geometric approaches to nonparametric statistics, positioning his work at the intersection of theoretical mathematics and data-driven applications.

Federico Reghenzaniمشاهده پروفایل

استادیار

• Computer Science
• Embedded Systems
• Fault Tolerance
• +۳ مورد دیگر

Federico Reghenzani is an Assistant Professor at Politecnico di Milano in the Department of Electronics, Information and Bioengineering. His research focuses on computer science, embedded systems, fault tolerance, high-performance computing, real-time systems, and compiler technology. He leads the HEAP Lab where his team investigates reliability engineering and hardware-software co-design for safety-critical applications. Reghenzani's research examines software-based approaches to hardware fault tolerance, compiler technologies for reliability enhancement, and resource management in high-performance computing environments. His work has significant applications in aerospace systems, real-time embedded platforms, and next-generation computing architectures. His publications demonstrate a consistent focus on improving system reliability through compiler techniques, fault injection methodologies, and hardware-software co-design. The research spans theoretical frameworks, practical implementations, and experimental validation across diverse computing environments.

• Cognitive Neuroscience
• Human Physiology
• Sensorimotor Integration
• +۳ مورد دیگر

Luciano Simone is an Associate Professor at the Department of Medicine and Surgery, University of Parma, Italy. He teaches Human Physiology and Research Methods in Cognitive Neuroscience across multiple degree programs, including Biomedical Laboratory Techniques, Medicine and Surgery (6-year program), and Translational Biomedical Sciences.

Andrea Vinciمشاهده پروفایل

پژوهشگر

• Quantum Computing
• Edge-Cloud Computing
• Internet of Things (IoT)
• +۵ مورد دیگر

Andrea Vinci is an accomplished researcher with 66 publications and 1,261 citations, specializing in the intersection of quantum computing, edge-cloud architectures, and Internet of Things (IoT) systems. His work demonstrates significant contributions to solving complex computational problems through innovative approaches that bridge theoretical quantum algorithms with practical distributed computing applications. His research interests span quantum computing applications for resource management, multi-density clustering techniques for urban analytics, and platform-independent IoT application development. Vinci has pioneered work in variational quantum algorithms for cloud/edge resource allocation, quantum kernels for IoT data classification, and distributed AI for cognitive building systems. His research demonstrates a consistent focus on addressing NP-hard problems through quantum-classical hybrid approaches. Analysis of Vinci's publication trends reveals a strategic research trajectory moving from foundational work in smart city analytics and crime prediction toward cutting-edge quantum computing applications for IoT and edge-cloud systems. His recent publications (2023-2025) show increasing focus on quantum machine learning techniques specifically tailored for IoT data processing, with significant attention to practical implementation challenges. Vinci maintains an extensive collaborative network, frequently publishing with researchers including Fabrizio Marozzo, C. Mastroianni, J. Settino, and Antonio Guerrieri across multiple high-impact venues including IEEE Transactions, ACM conferences, and specialized journals in quantum computing and distributed systems. His technical contributions include the development of the COGITO platform for cognitive buildings, novel approaches to multi-density crime prediction, and significant advancements in quantum kernel methods for IoT data analysis. Vinci's tutorial publications indicate his role in educating the broader research community about emerging quantum computing applications for distributed systems.

• Quantum Computing
• Quantum Machine Learning
• Quantum Simulations
• +۳ مورد دیگر

Marco Russo is a PhD Student in Computer and Systems Engineering (38th cycle, 2022-2025) at the Department of Automatic Control and Computer Science (DAUIN) of the Polytechnic University of Turin. He serves as an external teacher/teaching assistant in DAUIN and holds a Contract Professor position at the Center for Autonomous Management of the Interfaculty University School of Strategic Sciences (SUISS) from November 2023 to October 2024. His research focuses on Quantum Computing, Quantum Machine Learning, and Quantum Simulations, with ERC sectors emphasizing machine learning and quantum computing formal methods. He teaches Computer Architecture courses for Computer Engineering Master's students. Russo's recent publications explore cutting-edge applications in quantum control, embedded systems integration with quantum algorithms, quantum security protocols, and neural-symbolic AI for puzzles. His work bridges theoretical advancements in quantum computing with practical implementations across gaming, communications, and aerospace domains. His academic roles include collaboration with PhD guardians Bartholomew Montrucchio and Olivier the Third. While no formal awards are listed, his contributions span interdisciplinary research areas at the intersection of quantum technologies and classical engineering systems.

Salvatore Ivan Trapassoمشاهده پروفایل

استادیار

• Applied harmonic analysis
• Fourier analysis
• Machine learning
• +۵ مورد دیگر

Salvatore Ivan Trapasso is a Fixed-term Assistant Professor at the Department of Mathematical Sciences "GL Lagrange" (DISMA) , Polytechnic University of Turin , and a member of the SmartData@PoliTO - Big Data and Data Science Laboratory . His research focuses on Applied Harmonic Analysis , Fourier Analysis , Machine Learning , and Quantum Theory , with expertise in Mathematical Analysis (MATH-03/A) and Theoretical PDEs (PE1_11). Education : Implied PhD in Mathematics. Research Areas : Phase Space Analysis, Time-Frequency Methods, and Applications to Quantum Mechanics. His recent publications investigate phase space techniques for Feynman Path Integrals , Twisted Laplacian , Compressed Sensing , and Stability of Scattering Transforms . His work bridges Harmonic Analysis with Machine Learning and Quantum Dynamics . Notable scientific awards include the Axioms Young Investigator Award (2022) , Best Paper Award (ICGF 2020) , and the Quality Award 2019 from Polytechnic University of Turin. He serves on the Editorial Board of Advances in Operator Theory and as Associate Editor for University Texts in the Mathematical Sciences . Teaching roles include Lecturer for Mathematical Principles in the College of Architecture and Design , Collaborator for Mathematical Analysis I/II in Biomedical and Aerospace Engineering, and Contributor to advanced mathematical methods in Computer Science Engineering.

Marc Mezardمشاهده پروفایل

استاد

• Statistical Physics
• Machine Learning
• Information Theory
• +۵ مورد دیگر

Marc Mezard is a Professor of Theoretical Physics at Bocconi University, where he leads the newly established Department of Computational Sciences. Previously, he served as Research Director at CNRS in Paris and held roles at Université Paris Sud. He earned his PhD in Physics from École Normale Supérieure in Paris in 1984. His research focuses on statistical physics of disordered systems, with applications to machine learning, information theory, computer science, and biophysics. His work bridges theoretical physics and interdisciplinary fields, including neural networks and deep learning, where he explores the impact of data structure on learning strategies. He teaches undergraduate courses in statistical and quantum physics and a doctoral course on complex systems. Key research themes include emergent phenomena in complex systems, with contributions to spin glass theory, compressed sensing, and algorithmic solutions for random satisfiability problems. His publications span foundational topics in statistical mechanics and modern applications in data science. Marc Mezard has collaborated extensively with institutions and researchers globally, contributing to the theoretical foundations of computational and physical sciences. His academic leadership includes directing École Normale Supérieure from 2012 to 2022, fostering interdisciplinary research initiatives.

• Computational electromagnetics
• Electromagnetic propagation
• Wave propagation
• +۷ مورد دیگر

Guido Lombardi is a Full Professor in the Department of Electronics and Telecommunications at Polytechnic University of Turin, where he serves as a member of the Interdepartmental Center CARS@PoliTO - Center for Automotive Research and Sustainable Mobility. His academic career spans over two decades with significant contributions to computational electromagnetics and related fields. Dr. Lombardi's research focuses on computational electromagnetics, particularly analytical and numerical methods, electromagnetic propagation (scattering and diffraction), metamaterials, wave propagation, and the Wiener-Hopf technique. His work extends to practical applications including microgrid/technological modernization of eco-districts, triboelectricity in industrial applications, and security and science for peace initiatives. His research aligns with several Sustainable Development Goals, particularly those related to affordable and clean energy, industry innovation, and sustainable cities. His publication record demonstrates a strong focus on electromagnetic theory, with numerous papers in IEEE Transactions on Antennas and Propagation and other prestigious journals. The research trajectory shows consistent development in solving complex electromagnetic problems using advanced analytical and numerical techniques, particularly the Wiener-Hopf method applied to wedge diffraction problems, waveguide analysis, and metamaterial applications. Notable scientific awards and recognitions include: Raj Mittra Junior Researcher Award from IEEE Antennas and Propagation Society (2003) Executive Committee member of IEEE Antennas and Propagation Society (2016-2021) Honorary member of URSI (2018-) Honorary member of IEEE (2011-) Dr. Lombardi has served as a mentor to PhD students including Matteo Perrone (working on multiphysics acoustic-electromagnetic metasurfaces) and Sergio Cannata (focusing on biological image analysis through deep learning techniques). He has secured significant research funding through competitive calls including the PNRR Mission 4 HPC Spoke 6 project (2022-2025) and the GREEN TAGS project (2020-2024). His editorial service includes roles on IEEE Transactions on Antennas and Propagation, Electronics Letters, and IEEE Access. He has been actively involved in organizing major international conferences, serving as program chair for multiple IEEE-APS Topical Conferences on Antennas and Propagation in Wireless Communications and the International Conference on Electromagnetics in Advanced Applications (ICEAA) from 2001 to present. His research group, Electromagnetic Modeling and Applications, focuses on advanced numerical methods for electromagnetic problems.

• Circuit modeling
• Electronic circuit simulation
• Machine learning
• +۷ مورد دیگر

Riccardo Trinchero is an Associate Professor at the Department of Electronics and Telecommunications (DET) within Politecnico di Torino. He actively contributes to the College of Electronic, Telecommunications and Physics Engineering as a course instructor and to the College of Computer, Film and Mechatronics Engineering as a member. His research focuses on circuit modeling, electronic simulation, and machine learning applications. Academic Appointments 2025/26: Spectral and machine learning methods for uncertainty quantification (Main Teacher) 2023/24: Electronic Circuit Modeling (Main Teacher) Research Interests Compact dynamical modeling Stochastic circuit analysis High-speed link optimization via ML Electromagnetic compatibility (EMC) PhD Supervision Marco Atlante (since 2024) Nazanin Soleimani (since 2024) Dilyorjon Yuldashev (since 2024) Minzhou Liu (2020-2024) Yuan Yan (2020-2024) Nastaran Soleimani (2019-2023) Research Projects AI4FREIGHT (2025-2029) - Scientific Manager Physical simulation models for grounding contacts (2020-2021) - Scientific Manager Recent Publications 2025: SPICE modeling with ML kernels 2025: Multi-output active learning for PCB uncertainty 2025: Electromagnetic field analysis for transmission lines 2025: Digital twins in train dynamics 2024: Compressed SPICE-ML IC models

• Computer Graphics
• Geometry Processing
• Computational Topology
• +۴ مورد دیگر

Michela Spagnuolo is a Research Director at the Italian National Research Council’s Institute of Applied Mathematics and Information Technology (CNR-IMATI-GE) since 2001. Her work bridges Computer Graphics , Geometry Processing , and Computational Topology , with applications in 3D Shape Analysis , Cultural Heritage , and Bioinformatics . Co-supervised 6 PhD theses (plus 2 ongoing) Associate Editor for journals like The Visual Computer and Computers&Graphics Chair of conferences including Shape Modeling International and EG Workshops on 3D Object Retrieval Research Interests : Focus on geometric and semantic modeling of 3D objects , computational topology for shape analysis , and structural/similarity evaluation . Her work enables advanced 3D search engines , semantic annotation , and medical imaging applications . Article Trends : Recent publications emphasize mesh quality indicators for Virtual Element Methods in engineering simulations and semantic-driven 3D model analysis for medical diagnostics and cultural heritage . Key subtopics include topological decomposition , data processing services , and multi-scale modeling . Scientific Awards : Fellow of the Eurographics Association (2014) Notable Contributions : Led projects like IQmulus (geospatial data analytics) and MultiScaleHuman (medical shape modeling). Pioneered CIDOC CRMdig for cultural heritage documentation and developed techniques for kernel computation in polyhedra .