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Giuseppe Carlo Marano is a Full Professor at the Department of Structural, Building and Geotechnical Engineering at Politecnico di Torino. He is also a component of the SISCON Interdepartmental Center for Infrastructure Safety. With expertise in civil and structural engineering, his work focuses on machine learning applications, seismic risk reduction, and sustainable structural optimization. Education Graduated cum laude in Structural Engineering from Polytechnic University of Bari PhD in Structural Engineering from University of Florence (2000) Research Interests Marano's research spans structural optimization, seismic engineering, and machine learning applications in civil infrastructure. He develops advanced computational models for: Seismic retrofitting of existing structures Optimization of steel and masonry structures Recycled materials in concrete production AI-driven structural health monitoring Multiobjective design methodologies Publication Trends His recent work emphasizes: Machine learning for concrete mix design and damage assessment Optimization of gridshells and arch structures Seismic isolation systems and vibration control Sustainable construction practices with recycled materials Multiobjective genetic algorithms for structural design Scientific Recognitions National Scientific Qualification - First Band (2013, MIUR Italy) Certificate of Appreciation for Outstanding Lecture (2012, China) Academic Contributions As an educator, he teaches: Consolidamento Strutturale (Structural Consolidation) Dinamica delle Vibrazioni Random (Random Vibration Dynamics) Progettazione Generativa (Generative Design) He also leads Challenge@PoliTo initiatives and contributes to national infrastructure safety regulations. Research Projects ADAPT4CE - Adaptive Digital Systems for Circular Economy (2025-2028) AI-ENVISERS - AI for Seismic Retrofit Environmental Impact (2023-2025) ADDOPTML - Additive Manufacturing Optimization (2021-2025)

• Civil Engineering
• Structural Engineering
• Machine Learning in Structural Engineering
• +4 more

Gaetano Valenza is an Associate Professor of Bioengineering at the University of Pisa, Italy, where he leads the Neuro-Cardiovascular Intelligence Lab at the Enrico Piaggio Research Centre. He holds affiliations with the Neuroscience Statistics Research Laboratory at MIT and has served as a Research Fellow at Harvard Medical School and Massachusetts General Hospital. His academic work spans bioengineering, computational physiology, and affective computing. His research focuses on statistical and nonlinear biomedical signal and image processing , cardiovascular and neural modeling , and physiologically interpretable artificial intelligence . He develops wearable systems for physiological monitoring, with applications in autonomic nervous system assessment, brain-heart interactions, and mental health. His work has led to novel metrics such as the Sympathetic and Parasympathetic activity indices derived from ECG. The 15 most recent publications reflect a consistent trend in brain-heart interplay , complexity analysis of physiological signals , explainable AI in healthcare , and virtual reality applications in mental health . His work integrates advanced signal processing, nonlinear dynamics, and machine learning to decode emotional and cognitive states from physiological data. Dr. Valenza is a Senior Member of IEEE and serves on several technical committees. He is an active editorial leader, currently serving as Associate Editor for IEEE-EMBC , Plos One , Complexity , and Scientific Reports , and has guest-edited special issues in Philosophical Transactions of the Royal Society A and IEEE Journal of Biomedical and Health Informatics . He has led or participated in numerous international research projects, including FP7 and H2020 initiatives such as NEVERMIND and EXPERIENCE. He teaches courses in Biostatistics, Probability & Biostatistics, and Advanced Image Processing at the University of Pisa. As lab head and project coordinator, he leads a multidisciplinary team working on neuro-cardiovascular intelligence, wearable systems, and AI-driven mental health interventions.

• Biomedical Signal and Image Processing
• Cardiovascular and Neural Modeling
• Physiologically-interpretable Artificial Intelligence systems
• +5 more

Giulia Giordano is a Full Professor in the Department of Industrial Engineering at the University of Trento, Italy, where she leads the Dynamical Networks and Systems Biology research group. She also holds a dual appointment as Visiting Professor and Delft Technology Fellow at the Delft Center for Systems and Control, Delft University of Technology, The Netherlands. Her career includes previous positions as Assistant Professor at Delft University of Technology (2017-2019), Postdoctoral Research Fellow at Lund University, Sweden (2016-2017), and Research Fellow at the University of Udine, Italy (2016). Giulia earned her Ph.D. in Industrial and Information Engineering: Automation (Excellent) from the University of Udine with a thesis titled "Structural Analysis and Control of Dynamical Networks." She completed her M.Sc. and B.Sc. in Electrical Engineering (both Summa cum laude) at the same institution. She also undertook research visits at Caltech (2012) as a SURF Fellow and at the University of Stuttgart (2015) as a DAAD Research Scholar. Her primary research focuses on the analysis and control of dynamical networks with applications in systems biology, mathematical ecology, and mathematical epidemiology. She develops mathematical frameworks that bridge control theory, network theory, and dynamical systems to address complex problems in biological systems. Her recent work spans epidemic modeling, opinion dynamics, biochemical networks, and neurological disorders, with a particular emphasis on structural analysis of networked systems. She employs both theoretical and computational approaches to understand system behavior under uncertainty. Giulia's publications reveal a strong interdisciplinary focus, spanning from theoretical control systems to practical applications in epidemiology and biology. Her recent work shows increasing emphasis on epidemic modeling (particularly related to mpox and SARS-CoV-2), network synchronization, and the application of control theory to biological phenomena like fibromyalgia pathogenesis and opinion formation. Many of her papers appear in top-tier control journals including Automatica and IEEE Transactions on Automatic Control. 2024: Outstanding Service as Associate Editor of IEEE Control Systems Letters 2021: SIAM Activity Group on Control and Systems Theory Prize 2020: Outstanding Reviewer, Annals of Internal Medicine 2017: NAHS Best Paper Prize and EECI PhD Award 2016: Outstanding TAC Reviewer, IEEE Transactions on Automatic Control Giulia actively mentors students and postdoctoral researchers, currently supervising five postdoctoral researchers and two Ph.D. students at the University of Trento. She has advised numerous M.Sc. and B.Sc. students on topics ranging from bio-inspired modeling to optimal control of epidemic systems. Her research is supported by competitive grants including the ERC Starting Grant INSPIRE (Integrated Structural and Probabilistic Approaches for Biological and Epidemiological Systems). She serves as Associate Editor for IEEE Control Systems Letters and Automatica, and is a Senior Member of IEEE and the Control Systems Society. Giulia leads the Dynamical Networks and Systems Biology research group at the University of Trento, which maintains strong international collaborations across Europe and North America. The group's work combines theoretical advances in control theory with practical applications to pressing problems in public health and biological systems, demonstrating the power of mathematical approaches to understanding complex phenomena in the life sciences.

• Automatic control
• Complex networks
• Control systems
• +12 more

Maria Elena Valcher is a Professor at the Department of Information Engineering, University of Padova, Italy. She is an IEEE Fellow (since 2012), IFAC Fellow (since 2023), Socio Effettivo of Istituto Veneto di Scienze, Lettere ed Arti (since 2017, previously Socio Corrispondente 2008-2017), and Socio Effettivo of Accademia Galieliana di Scienze, Lettere ed Arti in Padova (since 2022, previously Socio Corrispondente 2017-2022). She currently serves as Administrator of the Istituto Veneto and holds leadership positions including EUCA President (2024-2025) and IEEE Control Systems Society Past President. Her research focuses on control systems, systems theory, optimization, Boolean control networks, multi-agent systems, and consensus problems. She has made significant contributions in distributed control, data-driven methods, and network optimization, with recent work exploring applications in opinion dynamics and social networks. Recent publications demonstrate a strong emphasis on data-driven approaches to control systems, particularly in distributed state estimation, unknown-input observer design, and multi-agent coordination. Her work shows consistent development in theoretical frameworks for networked systems with practical applications. Awards and Honors: IEEE Fellow (2012) IFAC Fellow (2023) Socio Effettivo, Istituto Veneto di Scienze, Lettere ed Arti (2017-present) Socio Effettivo, Accademia Galieliana di Scienze, Lettere ed Arti in Padova (2022-present) She teaches 'Controlli Automatici' (Bachelor in Information Engineering) and 'Systems Theory' (Master in Control Systems Engineering) during the 2024/2025 academic year. She has chaired major conferences including the 61st IEEE Conference on Decision and Control (CDC 2022) and serves as Program Chair for ICSTCC 2025.

• Control Systems
• Systems Theory
• Optimization
• +5 more

Stefano Grivet Talocia is a Full Professor in the Department of Electronics and Telecommunications at Polytechnic University of Turin. He serves as Director of the Doctoral School, is a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, and holds positions on the University Committee for Research and the Commission for the Promotion of Library, Archive and Museum Heritage. He is also President of the Doctoral School Council. His educational background includes a Laurea degree (summa cum laude) in Electronic Engineering (1994) and a Ph.D. in Electronic and Communication Engineering (1998), both from Polytechnic University of Torino. From 1994 to 1996, he worked at NASA/Goddard Space Flight Center in Greenbelt, MD, USA. Professor Grivet Talocia's research focuses on passive macro-modeling of concentrated and distributed interconnect structures for Signal/Power Integrity, order reduction techniques, and modeling and simulation of fields, circuits, and their interactions. His work spans several key areas including fast simulation of transmission lines (TOPLine technique), macromodeling and model order reduction, simulation methods for fields and circuits, passivity enforcement of lumped macromodels, waveform relaxation techniques, and wavelet applications. His research has significant applications in electromagnetic compatibility and signal integrity verification of complex electronic systems. His recent publications demonstrate strong trends in model order reduction techniques applied to power integrity verification, advanced macromodeling for electromagnetic compatibility, nonlinear circuit analysis, uncertainty quantification in PCB design, and power electronics modeling. These works consistently address practical engineering challenges in high-speed electronic design with emphasis on computational efficiency and accuracy. URSI Young Scientist Award (1999) Best symposium paper (2006) Three IBM Shared University Research Awards (2007-2009) IEEE Transactions on Advanced Packaging Best Paper Award (2007) Best EPEP conference paper awards (2007, 2008) Best Associate Editor Award - IEEE Transactions (2020) Best Conference Paper Award (2020) Three Intel SRS Grants (2022-2024) IEEE Fellow (2018) Professor Grivet Talocia actively supervises PhD students working on cutting-edge topics including machine learning applications in signal integrity, model reduction techniques, and electromagnetic compatibility. He has secured significant research funding through competitive grants including PRIN projects and multiple industry-sponsored research contracts with major technology companies such as IBM, Intel, Nokia, Hitachi, and Infineon. His technology transfer activities include co-founding the spin-off IdemWorks (acquired by CST in 2016) and maintaining active collaborations with industry partners. He leads the EMC Group (Electromagnetic Compatibility) within the Department of Electronics and Telecommunications and has developed the autoCircuits web service for automated generation of circuit theory problems. His research has been recognized by inclusion in the top 2% worldwide researcher catalog (Stanford) since 2019.

• Electromagnetic Compatibility
• Signal Integrity
• Power Integrity
• +7 more

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.

• Behavioral modeling
• Electromagnetic compatibility
• Macromodeling
• +7 more

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
• +14 more

Vincenzo Sciacca is a Full Professor in the Department of Mathematics and Computer Science at the University of Palermo, Italy. His academic position is listed under classification code MATH-04/A, which typically refers to Mathematical Analysis in the Italian academic system. He maintains regular office hours on Thursdays from 3:00 PM to 6:00 PM at the Department of Mathematics and Computer Science, Via Archirafi 34, Office No. 216 (2nd floor). Professor Sciacca's research spans several areas of mathematical physics and fluid dynamics. His primary interests include: Fluid dynamics and vortex theory Partial differential equations, particularly Navier-Stokes and Euler equations Singularity formation in boundary layer theory Numerical analysis of complex fluid systems Mathematical modeling in geophysical fluid dynamics Complex singularity analysis for nonlinear systems Analysis of his recent publications reveals a strong focus on the mathematical aspects of fluid dynamics, with particular attention to singularity formation, vortex dynamics, and the behavior of solutions to fundamental equations in fluid mechanics. His work combines rigorous mathematical analysis with computational approaches to understand complex phenomena in fluid systems. Over the years, his research has evolved from fundamental studies of singularity formation to more applied problems in geophysical fluid dynamics and mathematical biology as evidenced by his 2024 paper on Multiple Sclerosis. Professor Sciacca maintains an active research profile with publications spanning from 1994 to the present, demonstrating sustained scholarly contribution to his fields of expertise. His work shows interdisciplinary reach, connecting pure mathematical analysis with applications in physics, geophysics, and biomedical modeling. He can be contacted at vincenzo.sciacca@unipa.it and maintains a personal web page at http://math.unipa.it/~sciacca/ where additional information about his teaching and research is available.

• Fluid Dynamics
• Mathematical Physics
• Partial Differential Equations
• +5 more

Marco Paggi is a Full Professor of Structural Mechanics at the IMT School for Advanced Studies Lucca, Italy, since 2017. He previously held academic roles at Politecnico di Torino (Assistant Professor, 2007-2013) and has been an Alexander von Humboldt Fellow at Leibniz University Hannover. His research focuses on fracture mechanics, contact mechanics, and computational methods applied to renewable energy systems, composite materials, and multi-scale modeling. Key Themes: Fracture propagation, contact interfaces, phase field modeling, photovoltaic durability, and material heterogeneity. Awards: Stanford Top 2% Scientists (2020-2024) Research.com Top Scientists (2022-2024) European Structural Integrity Society Young Scientist Award (2010) Publications: His work spans tribology, computational fracture mechanics, and material degradation, with recent emphasis on phase field modeling for quasi-brittle materials and photovoltaic systems. He has pioneered methods for multi-scale and multi-physics analysis of structural systems. Mentorship: Supervised 17 PhD graduates and 14 postdocs, including award-winning researchers like Pietro Lenarda and Zeng Liu.

• Fracture mechanics
• Contact mechanics
• Computational methods for nonlinear partial differential equations
• +15 more

Giuseppe Mingione is a Full Professor in the Department of Mathematical, Physical and Computer Sciences at the University of Parma, Italy. His research spans Calculus of Variations , Elliptic and Parabolic PDEs , and Nonlinear Potential Theory . He has delivered over 25 lecture series and 180+ invited talks globally. PhD in Mathematics, University of Naples Federico II (1999) Degree in Mathematics, University of Naples Federico II (1994) His work focuses on regularity theory for nonlinear PDEs, nonuniform ellipticity, and geometric analysis. Publications include breakthroughs in Schauder estimates, double phase problems, and nonlocal systems. He has received the Amerio Prize (2016) , Caccioppoli Prize (2010) , and Stampacchia Medal (2006) . Recent articles address nonuniform ellipticity, nonlocal PDEs, and gradient regularity. Awards include the Order of the Merit of the Italian Republic (2017) and Von Staudt Chair (2004) . He serves on editorial boards for international journals.

• Calculus of Variations
• Elliptic Partial Differential Equations
• Parabolic Partial Differential Equations
• +3 more

Cristiana De Filippis serves as Associate Professor in the Department of Mathematical, Physical and Computer Sciences at the University of Parma. Her academic journey includes a Bachelor's degree from the University of Torino (2014), Master's from University of Milano-Bicocca (2016), and PhD from the University of Oxford (2020), followed by a tenure-track position at Parma since 2021 and habilitation to full professorship in 2023. Her research focuses on Mathematical Analysis , particularly Regularity Theory for elliptic and parabolic partial differential equations and the Calculus of Variations . She investigates fundamental properties of solutions to nonlinear PDEs, including sharp growth conditions, nonuniform ellipticity, and double-phase functionals. Her work bridges abstract mathematical theory with applications in physics and engineering through rigorous analysis of solution behavior. Analysis of her 15 most recent publications reveals a concentrated research program in nonuniformly elliptic systems (2022-2025), double-phase variational problems (2023-2024), and gradient regularity under irregular coefficients (2020-2024). Key contributions include establishing sharp growth rates in Schauder theory and developing novel techniques for nearly linear growth conditions. European Mathematical Society Prize 2024 Bartolozzi Prize 2023 (Italian Mathematical Union) Iapichino Prize 2020 (Accademia dei Lincei) Premio per la Cultura Mediterranea 2023 G-Research Prize 2019 Forbes 100 Most Successful Italian Women 2023 European Mathematical Society Young Academy (inaugural cohort) Professor De Filippis has delivered invited lectures at prestigious institutions including Erwin Schrödinger Institute (2025), Charles University Prague (2024), and Accademia Nazionale dei Lincei (2022). She teaches Mathematical Analysis courses for Computer Science, Geological Sciences, and Management Engineering programs at undergraduate level. Her research is supported through multiple international collaborations, particularly with Giuseppe Mingione at Parma and researchers at European institutions.

• Mathematical Analysis
• Partial Differential Equations
• Calculus of Variations
• +3 more

Marco Pirola is a Full Professor at the Department of Electronics and Telecommunications (DET) of the Polytechnic University of Turin, Italy. He is a member of the Interdepartmental Center 'CleanWaterCenter@PoliTo' and actively contributes to research in high-frequency electronics and microwave engineering. His work focuses on power amplifiers, device characterization, and advanced microwave circuit design. Research Interests: Microwave power devices, GaN technology, 5G/mm-Wave applications, space communications, and smart pipeline monitoring systems. Awards: IEEE Fellow (since 2019), IEEE Senior Member. Recent Publications address topics like Ka-band MMIC amplifiers for SAR systems, broadband Doherty amplifiers using GaN, and harmonic analysis of current-mode power stages. His projects include STARGATE (European GaAs power architectures) and Millimetre-Wave GaN Radar for UAV detection. Teaching: He leads courses on 'Radio Frequency Integrated Circuits' and 'Advanced Devices for High Frequency Applications' at the Polytechnic University of Turin. Supervised PhD students include Wenjun Zhang and Abbas Nasri, who worked on III-V HEMT circuits and GaN power amplifiers.

• Microwave Engineering
• Power Amplifiers
• Gallium Nitride (GaN) Technology
• +7 more

Gianluca Setti is a Full Professor at the Department of Electronics and Telecommunications (DET) at Polytechnic University of Turin, where he has been serving since 2017. He previously held positions at the University of Ferrara from 1997 to 2017. His institutional roles include being the Contact Person for the Research Quality Evaluation process, Member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory, and Member of the University Quality Assurance Committee. He serves as Editor-in-Chief of the Proceedings of the IEEE, the first non-US editor to hold this position. Dr. Setti's research spans multiple interdisciplinary fields including machine learning, artificial intelligence, big data analytics, Internet of Things, biomedical signal processing, power electronics, and electromagnetic compatibility. His work bridges theoretical foundations with practical applications, particularly focusing on compressed sensing, neural networks, and circuit design for specialized applications. His research has significant implications for healthcare, sustainable infrastructure, and next-generation electronics. His publication record reveals a consistent trajectory from foundational work in chaotic systems and neural networks to contemporary applications in AI, IoT, and edge computing. The most recent publications demonstrate his focus on anomaly detection at the edge, neural oracles for biosignal processing, and power electronics innovations. His work shows strong integration between theoretical signal processing and practical circuit implementation. 1998 Caianiello prize (best Italian Ph.D. thesis on Neural Networks) IEEE Fellow (2006) IEEE Circuits and Systems Society Distinguished Lecturer (2004, 2015) 2004 IEEE CAS Society Darlington Award 2013 IEEE CAS Society Meritorious Service Award 2013 IEEE CAS Society Guillemin-Cauer Award 2019 IEEE Transactions on Biomedical Circuits and Systems best paper award Multiple best paper awards at major conferences including ECCTD2005, EMCZurich2005, ISCAS2011, PRIME2019, and EMCCOMPO2019 Dr. Setti has supervised numerous PhD students across various research domains including electromagnetic compatibility, signal and power integrity, communication networks, mechatronics and robotics. His research is supported by significant funding including national PRIN projects, EU-funded JTI-ECSEL initiatives, and commercial contracts. He leads the VLSILAB Group at DET, focusing on circuit architectures, embedded systems, and AI applications. His current projects include DECORI (anomaly detection), StorAIge (embedded storage for AI), PROGRESSUS (energy infrastructure), CONNECT (smart grid), and CONVERGENCE (wearable healthcare applications).

• Machine learning
• Artificial intelligence
• Big data analytics
• +8 more

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
• +5 more

Giorgio Fagiolo is a Full Professor of Economics at Sant'Anna School of Advanced Studies. His work spans agent-based computational economics, economic networks, and macroeconomic policy analysis. University: Sant'Anna School of Advanced Studies (Scuola Superiore Sant'Anna) Department: Economics Email: giorgio.fagiolo@sssup.it Research interests focus on agent-based modeling , macroeconomic instability , and climate-economy interactions . He develops computational models to study industrial dynamics, financial integration, and policy design in complex systems. Key themes: Endogenous growth cycles, R&D network stability, and green transition policies. Methodological emphasis: Empirical validation of agent-based models and nonlinear economic dynamics. Scientific awards include collaboration with leading institutions like ETH Zurich, Columbia University, and OFCE Sciences Po. His publications appear in journals such as Journal of Economic Dynamics and Control and Ecological Economics .

• Agent-Based Computational Economics
• Economic Networks
• Macroeconomics
• +3 more