Marco Toffolon is a Full Professor at the University of Trento's Department of Civil, Environmental and Mechanical Engineering, where he leads the Physical Limnology Laboratory. He serves as Deputy Director for International Relations and previously directed the Environmental Engineering programs. His research spans ecohydraulics, sediment transport, lake hydrodynamics, and environmental modeling. He investigates physical limnology, tidal morphodynamics, and stratified flows using analytical and numerical approaches. His work integrates field measurements with machine learning for water quality prediction and climate impact assessment. His publications focus on lake dynamics, river morphodynamics, and sustainable water management, with recent emphasis on climate-driven changes in alpine systems. Research demonstrates strong interdisciplinary linkages between hydraulics, ecology, and climate science. Awards: 2016 Coastal Engineering Journal Award 2013 Enrico Marchi Lecture invitation He leads international collaborations with institutions like EPFL and Sun Yat-sen University, and organizes conferences including the Physical Processes in Natural Waters workshop series.
Professor Weimin Huang is a full Professor in the Faculty of Engineering and Applied Science at Memorial University of Newfoundland, where he has served since 2010 and became a full professor in 2019. He held the position of Department Deputy Head from 2020 to 2023. Education: BSc in Radio Physics (Radio Wave Propagation and Antennas), Wuhan University, 1995 MSc in Radio Physics (Radio Wave Propagation and Antennas), Wuhan University, 1997 PhD in Space Physics, Wuhan University, 2001 MEng in Electrical and Computer Engineering, Memorial University of Newfoundland, 2004 Postdoctoral Fellowship in Electrical and Computer Engineering, Memorial University of Newfoundland, 2007 Research Focus: Huang specializes in radar-based ocean remote sensing , with core expertise in high-frequency ground wave radar (HF radar) , GNSS Reflectometry , and synthetic aperture radar (SAR) . His work targets ocean surface parameter mapping including wind speed, oil spills, ship detection, and sea ice monitoring through advanced digital image processing and applied electromagnetics . Recent innovations integrate deep learning (CNNs, physics-informed models) with radar data for enhanced environmental monitoring. Publication Trends: His 2025 publications reveal a strong shift toward AI-driven solutions in remote sensing, with 5 high-impact papers in IEEE TGRS and Remote Sensing focusing on wind speed estimation (using GNSS-R and wavelet-CNN hybrids), oil spill mapping via SAR, ship detection with HF radar, and climate change analysis. These works demonstrate cross-disciplinary integration of machine learning with geophysical remote sensing. Scientific Awards: No awards were documented in the source material. Advising & Collaboration: With 358 co-authors including Bahram Salehi and Biyang Wen, Huang maintains a robust global research network. While specific student supervision isn't listed, his leadership role and publication volume indicate active graduate mentoring. The text mentions no grant details. Research Infrastructure: His work operates within Memorial University's engineering faculty, leveraging radar facilities for ocean sensing. Collaborations span institutions including Wuhan University and SUNY, suggesting participation in international radar remote sensing consortia focused on maritime applications.
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.
Sebastiano Vascon is an Associate Professor at Ca' Foscari University of Venice's Department of Environmental Sciences, Computer Science and Statistics (DAIS), and affiliated with the European Center for Living Technology. He earned his PhD in 2016 from the Italian Institute of Technology and University of Genoa, focusing on evolutionary game theory in pattern analysis and computer vision. His postdoctoral work spanned institutions like the Technical University of Munich and ETH Zurich, where he specialized in Active Learning and multi-object tracking. His research merges AI with interdisciplinary challenges, including climate change, environmental science, and cultural heritage preservation. Key areas include graph neural networks, computer vision, and game-theoretic models. He leads projects like RePAIR (AI for cultural heritage reassembly) and EasyWalk (AI-driven mobility solutions), and contributes to initiatives like MEMEX (digital storytelling). Teaching spans courses in Deep Learning, Machine Learning for Environmental Applications, and AI in Cultural Management. Research projects include: RePAIR: AI-driven 3D puzzle solving for artifact reconstruction EasyWalk: Socially-aware navigation systems MEMEX: AI for inclusive digital storytelling Climate modeling with IceBoost framework Publications highlight innovations in trajectory forecasting, environmental risk assessment, and graph-based methods. He actively reviews for top conferences (CVPR, ECCV) and journals.
Professor Paolo Casoli is a Full Professor at the Department of Industrial Systems and Technologies Engineering within the University of Parma . With over 30 years of academic experience since 1990, he specializes in fluid power systems, combustion modeling, and energy efficiency improvements in mobile machinery. Research Interests : Development of advanced combustion models for ICE optimization Hydraulic component simulation and experimental testing Hybrid systems and energy recovery technologies Condition monitoring of fluid power machinery Teaching : Active in second-cycle Mechanical Engineering programs (2013–2026), teaching courses on Fluid Machinery , Oleodynamics Systems , and Advanced Heat Engines . Also involved in first-cycle Management Engineering as a tutor. Scientific Contributions : Co-author of 120+ publications with ORCID 0000-0002-0433-6279, focusing on gear pump optimization, vibration analysis, and CFD applications. Currently active in experimental studies on pumps and motors. Contact : Office hours available by appointment via email at paolo.casoli@unipr.it. Located at Campus Scienze e Tecnologie - Padiglione 10 - Parco Area delle Scienze, 181/A, Parma, Italy.
Andrea Boni is an Associate Professor in the Department of Information Engineering at the Faculty of Engineering, University of Parma, where he has been a faculty member since 1999. He leads the Analog IC Design research group and teaches core electronics courses including Analog Design, Amplifier Design, and Electronics 2 at both undergraduate and graduate levels. His research focuses on analog and mixed-signal integrated circuits, with emphasis on high-speed and ultra-low-power designs in CMOS and BiCMOS technologies. Key areas include Analog-to-Digital Converters (ADCs), low-voltage reference circuits, RF oscillators, frequency synthesizers, and their applications in wireless sensors, UWB radars, and RFID systems. The recent publications highlight a strong trend toward low-power, wireless, and intelligent sensing systems, particularly in structural health monitoring, precision agriculture, and food authenticity. These works reflect a convergence of analog circuit innovation with embedded intelligence and IoT applications. Dr. Boni serves on the technical committee of the Custom Integrated Circuits Conference and is a reviewer for IEEE Journal of Solid-State Circuits and IEEE Transactions on Circuits and Systems – II. He advises no listed students in the provided text and has not been awarded any scientific prizes mentioned. His group receives both public and private funding. He leads the Analog IC Design group, which has been active for over a decade in cutting-edge analog circuit research.
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
Cristiano Varin is a Full Professor in Statistics at the Ca' Foscari University of Venice , affiliated with the Department of Environmental Sciences, Computer Science and Statistics (DAIS). He works at the Scientific Campus in via Torino and maintains the DAIS website for research and teaching updates. His research focuses on: Composite likelihood inference - A key methodological contributor with seminal papers in Biometrika and Statistica Sinica Copula regression - With practical implementations in R software Meta-analysis - Including improved likelihood inference techniques Spatial statistics - With applications to environmental data Paired comparison modeling - Applied to sports analytics and behavioral studies Recent publications demonstrate expertise in crossed random effects models (2025), ridge regression for paired comparisons (2024), and thermal comfort range analysis (2023). Scientific recognition includes: Royal Statistical Society Read Paper (2015) on journal citation modeling Gumbel Lecture (2006) by German Statistical Society Ca' Foscari Teaching Award (2020) He has collaborated with institutions including: Swiss National Science Foundation Natural Sciences and Engineering Research Council of Canada Norwegian Council of Research
Andrea De Martin is a fixed-term researcher at the Polytechnic University of Turin , affiliated with the Department of Mechanical and Aerospace Engineering (DIMEAS) and the Power Electronics Innovation Center (PEIC) . His work focuses on Prognostics and Health Management (PHM) for robotic and aerospace systems, particularly critical components like harmonic drives and flight control actuators. Key research areas: Actuators, Digital Twins, Flight Control Systems, PHM, Robotics He contributes to teaching courses like System Health Management and Servosystems at the PhD and Master’s levels, emphasizing aerospace and automotive applications. Recent publications highlight advancements in real-time electromechanical actuator modeling, fault detection in ball screws, and PHM systems for aircraft brakes. Scientific roles include guest editorships for journals like Aerospace and Actuators . He leads commercial research contracts with industry leaders such as Collins Aerospace and collaborates on national projects including PRIN and hybrid-electric aircraft systems development.
Matteo Bilardo is a Fixed-term Assistant Professor at the Polytechnic University of Turin , affiliated with the Department of Energy (DENERG) . His research focuses on advanced building envelopes , energy design optimization , and urban-scale energy modeling . Bilardo contributes to teaching in programs like Energy Transition and Low-Carbon Architecture, as well as courses on building energy systems. Research Interests : Building energy performance, climate-resilient design, renewable integration in districts, and innovative storage systems. His work aligns with SDG 7 (Affordable Clean Energy) , SDG 11 (Sustainable Cities) , and SDG 13 (Climate Action) . Scientific Awards : Effective communication with businesses (2024) Learning to Teach (L2T) badge (2024) Advising : Supervises PhD student Lorenzo Pellizzon in Energetics (40th cycle, 2024–ongoing).
Luciano Rolando is an Associate Professor at the Department of Energy (DENERG) in Politecnico di Torino. He is a member of the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His academic roles include teaching Hybrid Propulsion Systems at the PhD level and various undergraduate/graduate courses such as Thermal Machines and Structural Mechanics and Fluid Machines across Chemical, Mechanical, and Energy Engineering programs. As Scientific Director and Manager of competitive and commercial research projects like OpThermEV (2021-2022) and Alternative Fuels: Large Bore Ammonia Combustion (2024-2025), he focuses on optimizing thermal management systems, hydrogen combustion, and emission reduction technologies. His research group E3 (DENERG) explores synergies between hybrid propulsion, renewable fuels, and predictive control algorithms. His recent publications highlight advancements in deep reinforcement learning for energy management, hydrogen-fueled powertrains, and dual-diluted combustion systems. Collaborations include industry partnerships and supervision of seven ongoing PhD students. He holds a national patent for predictive thermal control systems in electric vehicles, aligning with SDG goals 7, 12, and 13.
Paolo Manfredi is a Full Professor at the Department of Electronics and Telecommunications (DET) of Politecnico di Torino, Italy. He actively contributes to the EMC Group (Electromagnetic Compatibility) and serves as an Associate Editor for journals including IEEE Journal on Multiscale and Multiphysics Computational Techniques and International Journal of Circuit Theory and Applications. His research focuses on uncertainty quantification in circuits, surrogate modeling , machine learning applications, and signal integrity analysis . He leads projects on compact dynamical modeling of complex systems and stochastic analysis of interconnects. Recent publications highlight advancements in active learning for PCB line uncertainty quantification, connector degradation impacts on microwave signals , and SPICE-compliant IC model compression , reflecting his expertise at the intersection of electrical engineering and data science . Scientific Awards: Best Paper Award EPEPS (2010, 2013) Premio Optime (2010) URSI Young Scientist Award (2011) Honorable Mention - IMS (2011) He supervises PhD students in projects spanning 5G/6G metasurfaces , power cable corrosion assessment , and neural network applications in circuit design.
Chiara Colombero is an Associate Professor at Politecnico di Torino, affiliated with the Department of Environment, Land and Infrastructure Engineering (DIATI) and the Interdepartmental Center Photonext. Her work bridges applied geophysics, natural hazard monitoring, and environmental characterization. Research Interests: Passive seismic monitoring of natural hazards Geophysical characterization of glacial/periglacial environments Integration of seismic, electrical, and EM methods Geoengineering applications for infrastructure and cultural heritage Recent Article Trends: Focus on seismic monitoring of rock glaciers, hydrodynamic modeling using radon tracers, and machine learning applications for landslide early warning systems. Methods include ambient noise tomography, surface wave analysis, and multi-sensor integration. Scientific Awards: Premio AGLC "Licio Cernobori" (2016) Teaching Roles: She teaches courses on Applied Geophysics , Remote Sensing , and Innovation Lab for Climate Change , while supervising Ph.D. candidates Lorena Di Toro and Valeria Strallo in projects related to cryospheric and landslide monitoring.
Daniele Jahier Pagliari is an Associate Professor in the Department of Control and Computer Science (DAUIN) at Politecnico di Torino, where he is also a member of the Interdepartmental Center PEIC - Power Electronics Innovation Center. He is actively involved in teaching and research, focusing on embedded systems, electronic design automation, and machine learning for edge computing. He teaches courses such as Optimized Execution of Neural Networks at the Edge, Machine Learning for IoT, and Hardware/Software Codesign of Flexible Computing Systems for Edge AI across various engineering programs including Computer Science and Systems Engineering, Data Science, and Automotive Engineering. His research interests span electronic design automation, embedded systems, energy-efficient computing, low-power design, and machine learning. He is particularly engaged in applying machine learning techniques to improve the design and performance of digital and analog circuits, with a focus on edge AI applications. His work aligns with key scientific areas including computer architecture, cyber-physical systems, and scientific computing. The recent publications highlight a strong trend in optimizing deep learning models for resource-constrained environments, accelerating neural network inference on ultra-low-power devices, and integrating physics-based models with AI for battery state estimation. There is also significant focus on using machine learning to enhance electronic design automation, particularly for analog and mixed-signal circuits, reflecting a convergence of AI and hardware design. He leads and participates in several high-impact research projects, including EU-funded initiatives like HAL4SDV, ISOLDE, TRISTAN, and AMBEATion, as well as commercial projects such as MASAI and software platform development for production support. He serves as the Scientific Responsible or Director in multiple projects, demonstrating leadership in both academic and industrial research contexts. He supervises multiple PhD students in the Computer and Systems Engineering program, including Luca Benfenati, Mohamed Amine Hamdi, Beatrice Alessandra Motetti, Giovanni Pollo, and Matteo Risso, whose research topics include latency-optimized inference, compiler optimization for edge devices, and hardware-aware deep learning design. He is also involved in patent development, notably for an instrumentation method to dynamically modify circuit precision. He is a member of the College of Computer, Film and Mechatronics Engineering and contributes to various degree programs. His work supports UN Sustainable Development Goals related to good health, affordable and clean energy, industry innovation, and sustainable cities.
Antonio Ancona is a Full Professor in the Department of Physics at the University of Bari, Italy, specializing in laser-based manufacturing and microfluidic systems. His research bridges fundamental physics with industrial applications, particularly in advanced materials processing and biomedical device development. Professor Ancona's primary research domains include: Laser Materials Processing : Pioneering adaptive beam shaping with deformable mirrors for precision welding, gap bridging in autogenous joints, and surface texturing for functional properties. Microfabrication : Developing femtosecond laser techniques for polymeric lab-on-a-chip devices enabling high-throughput cell sorting and liquid biopsy applications. Surface Engineering : Creating superhydrophobic, anti-icing, and friction-reducing surfaces through laser texturing for aerospace and marine industries. Photonics : Innovating in laser-welded optical components, black quartz photodetectors, and micro-resonator fabrication. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) AI-integrated laser welding systems using deep learning for real-time gap classification, (2) Femtosecond laser fabrication of biomedical microdevices focusing on inertial particle sorting, and (3) Laser surface texturing for antimicrobial and acoustic camouflage applications. His work consistently integrates optics, fluid dynamics, and materials science to solve industrial challenges. Scientific Awards: No major scientific awards were documented in the provided materials. Advising and Grants: While specific grant information isn't provided, his extensive publication record (50+ papers 2015-2025) indicates substantial research funding. No doctoral students are listed in available records, though his position suggests graduate student supervision in physics and engineering programs. Labs and Teams: Professor Ancona leads laser processing research within Bari's Department of Physics, collaborating with biomedical engineers on lab-on-a-chip development and industrial partners on advanced manufacturing solutions. His team specializes in femtosecond laser systems, microfluidic prototyping, and surface characterization facilities.
