جستجوی استاد راهنمای دانشگاهی

Ting Sunمشاهده پروفایل

دانشیار

• Urban climate modelling
• Climate change impacts and adaptation
• Extreme weather events in cities
• +۵ مورد دیگر

Dr Ting Sun is an Associate Professor in Climate & Meteorological Hazard Risks at University College London , Department of Risk and Disaster Reduction. He earned his BEng (2009) and PhD in Hydrology (2013) from Tsinghua University , followed by a visiting period at Princeton University (2011–2012). After postdoctoral appointments at Tsinghua and the University of Reading , he held a NERC Independent Research Fellowship at Reading (2017–2022) before joining UCL in May 2022. Education PhD in Hydrology, Tsinghua University, 2013 BEng in Hydraulic Engineering, Tsinghua University, 2009 Visiting PhD Student, Princeton University, 2011–2012 Research Interests Dr Sun’s work converges on urban climate modelling across scales —from neighbourhood blocks to global grids—focusing on the impacts of weather and climate extremes such as heat waves and extreme rainfall in cities. He is the lead developer of the Surface Urban Energy and Water balance Scheme (SUEWS) and its Python wrapper SuPy , developed in collaboration with Prof Sue Grimmond’s micromet group. He also contributes as a core member of the Urban Multi-scale Environmental Predictor (UMEP) development team. His multidisciplinary expertise integrates hydro-climate dynamics, computational modelling, machine learning, built-environment processes, and public-health linkages . Research Trends from Recent Publications Across the 15 most recent articles, a clear trajectory emerges from high-resolution urban-process modelling toward integrated socio-environmental assessments . Studies published in 2024–2025 couple atmospheric models (WRF-SUEWS) with global building-morphology datasets (GLAMOUR) to quantify how cities alter rainfall patterns, temperature sensitivity, and heat-related mortality. Earlier works progressively refined SUEWS’s physical parameterisations and Python accessibility, while recent outputs leverage deep-learning remote-sensing tools (SHAFTS) and hybrid hydrological-neural architectures to deliver actionable insights for urban planning and climate adaptation. Scientific Awards & Fellowships NERC Independent Research Fellowship , University of Reading, 2017–2022 HEA Fellowship , University College London, 2023 Professional Service & Editorial Roles Topic Editor , Geoscientific Model Development (from 2025) Editorial Board Member , Scientific Data (from 2024) Peer review and consultancy for journals, conferences, and policy bodies Supervision of taught-course projects and research degrees External examining and mentoring Labs, Teams & Collaborations Dr Sun leads and collaborates within the UCL Department of Risk and Disaster Reduction , working closely with the micromet group at the University of Reading (Prof Sue Grimmond) on SUEWS/SuPy development. He is an active member of the UMEP consortium and maintains extensive international collaborations spanning Tsinghua University, Princeton, and numerous European research centres, underpinning a vibrant, interdisciplinary research network focused on urban climate resilience.

Leonardo Lanariمشاهده پروفایل

دانشیار

• Robotics
• Humanoid Locomotion
• Model Predictive Control (MPC)
• +۴ مورد دیگر

Leonardo Lanari is an Associate Professor at the Department of Computer, Control and Management Engineering (DIAG) of Sapienza University of Rome. His research focuses on robotics, particularly humanoid motion generation, model predictive control, and nonlinear control systems. He has contributed to advancements in gait stability, underactuated robotics, and remote robotic experiments through the REAL Lab. PhD in Systems Engineering from Sapienza University Visiting Scholar at Rensselaer Polytechnic Institute Research Interests Robotics (humanoid locomotion, flexible manipulators, underactuated systems), control theory (MPC, robust control), and large-scale system control. His work integrates geometric approaches with practical robotic implementations. Recent Article Trends Focus on model predictive control for humanoid stability, stair navigation, and cooperative transportation systems. 2025 studies emphasize feasibility-driven motion planning in complex environments. Scientific Awards 2020 IEEE Robotics and Automation Magazine Best Paper Award Teaching & Grants Teaches Control Systems and Multivariable Feedback Control at Sapienza. Has developed courses on underactuated robots and control problems in robotics. Involved in grants for healthcare AI platforms like CADUCEO and humanoid applications in aircraft manufacturing. Labs & Teams Membro del Robotics Lab at DIAG. Collaborates with international institutions including MIT, Rensselaer Polytechnic Institute, and Airbus on humanoid robotic projects.

• Artificial Intelligence
• Machine Learning
• Internet of Things
• +۱۳ مورد دیگر

Edoardo Patti is an Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Politecnico di Torino, Italy. He is actively involved in research and teaching, focusing on artificial intelligence, machine learning, IoT, smart grids, energy communities, co-simulation, and digital twin technologies. He is a member of the EDA (Electronic Design Automation) research group and the Interdepartmental Center IAM@PoliTo for Integrated Additive Manufacturing. His research interests span Artificial Intelligence, Machine Learning, Internet of Things, Smart Grids, Energy Communities, Co-simulation, Distributed Software Infrastructure, Digital Twin, Physics-Informed Neural Networks, and Reinforcement Learning . His work is closely aligned with Sustainable Development Goals such as Affordable and Clean Energy (Goal 7), Sustainable Cities (Goal 11), and Climate Action (Goal 13). The latest publications reveal a strong trend in AI-driven modeling for energy systems, including digital twins for wave energy converters, urban electric mobility simulation, real-time battery health estimation, and co-simulation platforms for integrated energy systems. His work combines machine learning with physical models and large-scale distributed systems to address sustainability challenges. He supervises several PhD students, including Maria Adelaide Loffa, Matia Torlini, Rafael Natalio Fontana Crespo, Pietro Rando Mazzarino, Claudia De Vizia, and Marco Massano. He has led numerous research projects funded by EU (H2020), PNRR, regional initiatives, and corporate contracts, particularly in additive manufacturing, smart grids, and IoT platforms. He is involved in multiple research groups and centers: EDA - Electronic Design Automation (DAUIN) Interdepartmental Center IAM@PoliTo - Integrated Additive Manufacturing

Lucia Seminaraمشاهده پروفایل

دانشیار

• Tactile Sensing
• Electronic Skin
• Haptic Robotics
• +۵ مورد دیگر

Lucia Seminara serves as an Associate Professor in the Department of Naval, Electrical, Electronic, and Telecommunications Engineering (DITEN) at the University of Genoa's Polytechnic School. She teaches Electronic Devices, Sensors, and Sensing Systems for Master's programs in Electronic Engineering and Engineering for Natural Risk Management, while also contributing to Philosophy of Medicine for Philosophical Methodologies. As a member of the Joint Teacher-Student Commission, she bridges academic governance with pedagogical innovation in engineering education. Her research pioneers tactile sensing systems using piezoelectric polymers (PVDF) and electronic skin for robotics and prosthetics. She investigates indentation mechanics on soft electronic skin, grasping speed sensitivity, and hierarchical sensorimotor control frameworks for human-in-the-loop robotic hands. Key innovations include machine learning-based contact force estimation and electrotactile feedback systems that restore natural touch perception in prosthetic devices, addressing critical gaps in sensory substitution technology. Analysis of her 2021-2025 publications reveals escalating integration of machine learning with tactile sensing, particularly in symmetry detection for efficient haptic exploration and transdisciplinary human-in-the-loop applications. Recent work emphasizes real-world implementations like post-stroke rehabilitation systems and high-bandwidth human-machine interfaces, demonstrating a strategic shift from foundational sensor development toward clinically viable solutions with measurable user impact. Dr. Seminara's research lineage includes significant contributions to the Roboskin project (2013), which established large-area tactile sensor arrays for robotics. Her current work extends this foundation through investigations into viscoelastic properties, stress transmission modeling, and AI-driven tactile perception, positioning her at the forefront of intelligent electronic skin development with active collaborations across engineering, neuroscience, and clinical rehabilitation domains.

• Air pollution meteorology
• Atmospheric physics
• Climate
• +۱۲ مورد دیگر

Lorenzo Giovannini is an Associate Professor at the University of Trento, affiliated with the Department of Civil, Environmental and Mechanical Engineering. His expertise spans air pollution meteorology, atmospheric physics, climate change, renewable energy, and urban meteorology, with a focus on numerical weather modeling and pollutant dispersion studies. His research interests include: Atmospheric boundary layer dynamics and turbulence Numerical weather prediction and dispersion modeling Renewable energy resource assessment Climate change impacts on Alpine and urban environments Mountain meteorology and thermally-driven flows His recent publications highlight interdisciplinary approaches combining field measurements, numerical simulations, and data analysis across atmospheric physics, environmental engineering, and climate science. Key article trends involve: Advancing WRF-HAILCAST for severe weather simulations Quantifying snowfall and climate variability in Alpine regions Developing machine learning tools for environmental sensitivity analysis Studying turbulence in complex terrain and urban settings Investigating CO2/H2O fluxes in vineyard ecosystems Applying nature-based solutions to urban heat islands

• Cybersecurity
• Critical Infrastructure Protection
• Industrial Control Systems
• +۳ مورد دیگر

Chiara Foglietta is a Lecturer associated with the Department of Civil, Computer and Aeronautical Engineering at Roma Tre University. Her research focuses on cybersecurity for critical infrastructure and industrial systems. She specializes in developing advanced security solutions using machine learning, anomaly detection (particularly Kalman Filter variants), and simulation modeling (CISIApro framework). Her work addresses protection strategies for Industrial Control Systems (ICS), Cyber-Physical Systems (CPS), and interdependent critical infrastructure networks. Recent publications demonstrate a consistent theme of enhancing infrastructure security through innovative algorithms and modeling techniques. Key contributions include anomaly detection frameworks for testbeds like Hydra, security extensions for industrial systems, and uncertainty management methods within simulation environments.

Riccardo Patriarcaمشاهده پروفایل

استادیار

• Resilience Engineering
• Risk Management
• Industrial Systems Engineering
• +۴ مورد دیگر

Riccardo Patriarca is an Assistant Professor in Industrial Systems Engineering at Sapienza University of Rome's Department of Mechanical and Aerospace Engineering, part of the Faculty of Civil and Industrial Engineering. He holds adjunct professor and lecturer roles in courses such as Operations Management and Risk Management. His research focuses on resilience engineering, risk assessment, and safety management in complex socio-technical systems, including aviation, industrial plants, and critical infrastructures. He co-founded aiComply, a Sapienza spin-off addressing risk and compliance challenges. His work combines theoretical frameworks (e.g., STAMP, FRAM) with practical applications in cyber-physical systems and emergency response. Education: BSc and MSc in Aerospace/Aeronautical Engineering (Sapienza), PhD in Industrial and Management Engineering (2017). Postdoctoral research at Sapienza (2018–2021) and collaborations with Lund University and Eurocontrol. He has authored over 100 peer-reviewed papers, edited journals including Safety Science and Reliability Engineering , and serves as a guest editor for Sustainability . Research highlights include systemic safety analysis for advanced air mobility (eVTOLs), Bayesian methods for hydrogen safety, and resilience metrics for healthcare systems. Awards include the Royal Aeronautical Society Young Person Award (2017), Forbes 30 Under 30 (2019), and National Academic Qualification as Associate Professor (2018). His work bridges academia and industry, emphasizing human factors and digital transformation.

• Antenna Theory and Design
• Electromagnetic Fields
• Quantum Electromagnetics
• +۷ مورد دیگر

Nicola Anselmi is a Researcher (RTD-A) at the University of Trento, affiliated with the Department of Civil, Environmental and Mechanical Engineering. He also contributes to the Department of Physics through teaching and research. His work focuses on advanced antenna array design, quantum computing applications in electromagnetics, and modular phased array architectures. Key research areas include tolerance analysis of reconfigurable systems, compressive sensing techniques for antenna characterization, and optimization strategies for next-generation wireless communication systems. He teaches courses such as Antenna Theory and Synthesis Methods (Civil Engineering) and Quantum Electromagnetics (Physics), emphasizing theoretical foundations and practical software applications. His research leverages quantum computing for solving complex electromagnetic problems and explores novel array configurations for low Earth orbit (LEO) satellite communications and urban wireless networks. Anselmi’s recent work highlights advancements in interval arithmetic for robust array tolerance analysis, Bayesian compressive sensing for microwave imaging, and self-replicating tiling techniques for modular array design. His publications span IEEE journals and conferences, addressing topics like electromagnetic environment optimization, sparse array synthesis, and AI-driven antenna optimization. Though no scientific awards are explicitly mentioned, his contributions reflect cutting-edge innovations in electromagnetics and quantum engineering. His research also involves collaborations with the ELEDIA Research Center, focusing on task-oriented reflectarrays and system-by-design methodologies for multi-scale applications. Current interests include overcoming electromagnetic challenges in smart cities and next-generation radar systems.

• Machine learning
• Numerical analysis
• Numerical methods
• +۱۰ مورد دیگر

Sandra Pieraccini is a Full Professor in the Department of Mathematical Sciences "GL Lagrange" (DISMA) at the Politecnico di Torino, where she also serves as Deputy Director of the department, Contact Person for student orientation, and Coordinator of the basic subjects for first-year engineering programs. She is a member of the University Open Access Commission and actively contributes to academic governance. Her research interests include machine learning, numerical analysis, scientific computing, uncertainty quantification, and numerical optimization . She is a key member of the research group Numerical Analysis and Scientific Computing and leads the national research project FaReX (2023–2025) on reduced-order modeling and automatic learning. Her work integrates advanced numerical methods with AI techniques, particularly in modeling discrete fracture networks and fluid dynamics. The most recent publications reflect a strong trend in combining graph-informed neural networks , explainable AI , and meshless computational methods to solve complex problems in geophysics, fluid mechanics, and data science. Her research bridges applied mathematics with real-world engineering and environmental challenges. She is an active member of the scientific community, serving on the editorial boards of Journal of Machine Learning for Modeling and Computing and GEM , and participating in steering committees of UMI groups on AI and machine learning. She has also contributed to organizing major workshops and conferences. Sandra Pieraccini teaches across multiple programs, including doctoral courses in Mathematical Sciences and Aerospace Engineering, master’s courses in Mathematical Engineering and Data Science, and bachelor’s courses such as Linear Algebra and Problem Solving Lab. She is deeply involved in curriculum development and academic leadership.

• Deep Learning
• Uncertainty Quantification for Physically-Based Simulations
• Numerical Optimization
• +۱ مورد دیگر

Francesco Della Santa is a Fixed-term Assistant Professor at the Department of Mathematical Sciences (DISMA) of Politecnico di Torino, where he contributes to teaching and research in deep learning, numerical analysis, and optimization. Master Degree in Mathematics, University of Florence (2017) Ph.D. in Pure and Applied Mathematics, Politecnico di Torino (2021) His research focuses on Deep Learning and its applications to Numerical Optimization and Physically-Based Simulations , with a particular emphasis on uncertainty quantification and graph-informed neural networks. Recent publications explore discontinuous neural networks for kernel learning, edge-wise graph modeling, and multi-start optimization techniques. Francesco collaborates on courses like Numerical Optimization for Large Scale Problems and Mathematics for Artificial Intelligence across Mathematical Engineering and Data Science programs. He supervises Ph.D. student Filippo Aglietti in the Energetics program (38th cycle, ongoing since 2022). Research groups: Numerical Analysis and Scientific Computing (DISMA)

• Systems Engineering
• Sustainable Manufacturing
• Cyber-Physical Systems
• +۵ مورد دیگر

Dr. Ali Asghar Bataleblu is a Senior Research Fellow at the Sustainable Manufacturing Laboratory within the Faculty of Engineering at the Free University of Bozen-Bolzano . His work focuses on transdisciplinary systems engineering for resilience, sustainability, and circular economy , with over a decade of experience in uncertainty-based Multidisciplinary Design Optimization (MDO) . He was previously the director of an MDO research center for nearly ten years. Academic Rank: Research Fellow Key Research Areas: Systems Engineering, Cyber-Physical Systems, Resilience Engineering, Sustainable Manufacturing Dr. Bataleblu’s research bridges model-based systems engineering (MBSE) , digital twins , and surrogate-assisted optimization to address sustainability challenges in manufacturing and mobility. He employs multi-agent systems and system-of-systems frameworks to analyze complex interactions in industrial and environmental contexts. His work includes requirements management and axiomatic design for holistic system decomposition. The 15 most recent articles highlight his focus on resilient cyber-physical production systems , sustainable mobility , AI-integrated MBSE , and multi-agent optimization for wildfire management. These works span disciplines like industrial engineering , computational intelligence , and urban planning , with subfields covering digital twins , dynamic system modeling , and automated routing . Scientific Awards: TOWARDS South Tyrol International Postdoctoral Fellowship (2023) Young Scientist Award at ICQIS-2024 (2024) He leads the Sustainable Factory Design Decomposition (SFDD) project funded by the Autonomous Province of Bolzano , collaborating with Purdue University Fort Wayne . His research integrates graph database visualization for supply chain resilience and life cycle assessment (LCA) automation in fast-moving consumer goods. He also explores reinforcement learning for aerial vehicle design and robust control systems for drones.

Marco Ricottiمشاهده پروفایل

استاد

• Thermal Fluid Dynamics
• Passive Safety Systems
• Economics of Nuclear Energy
• +۶ مورد دیگر

Prof. Marco Ricotti is a Professor at Politecnico di Milano specializing in nuclear engineering with core expertise in Thermal Fluid Dynamics (modelling & experimental), Passive Safety Systems, and Economics of Nuclear Energy. His research directly impacts Small Modular Reactor (SMR) development, nuclear safety validation, and decommissioning technologies. As a key contributor to the Consorzio Interuniversitario per la Ricerca TEcnologica Nucleare (CIRTEN), he supports the Italian National Repository of radioactive waste and participates in European initiatives like the TANDEM Euratom project. Ricotti's research program bridges fundamental thermal-hydraulic phenomena with practical nuclear applications. His work on passive safety systems includes experimental validation of decay heat removal mechanisms and two-phase flow behavior in compact heat exchangers. Economic analyses of SMRs, lead fast reactors, and hybrid energy systems form another critical pillar, addressing cost competitiveness and grid integration challenges. Recent efforts increasingly focus on nuclear decommissioning techniques for graphite-moderated reactors and space nuclear applications. Analysis of Ricotti's 2024-2025 publications reveals concentrated SMR research across three interconnected domains: thermal-hydraulic safety validation (35% of output), economic viability studies (30%), and innovative applications like space reactors and decommissioning technologies (35%). His work consistently emphasizes experimental verification of passive safety systems while exploring synergies between nuclear and renewable energy in multipurpose systems for decarbonization. No scientific awards were documented in the source material. Information regarding student advising or specific research grants was not provided in available records. Ricotti actively contributes to CIRTEN's mission supporting Italy's radioactive waste repository Technology Park, with emphasis on graphite decommissioning and thermal-hydraulic testing. His leadership in the TANDEM Euratom project shapes European SMR licensing frameworks, while collaborations with SIET laboratory advance suppression pool safety validation. Current efforts also integrate nuclear systems with phase-change materials for district heating and seawater desalination applications.

Emanuele Borgonovoمشاهده پروفایل

استاد

• Sensitivity Analysis
• Decision Analysis
• Risk Assessment
• +۶ مورد دیگر

Emanuele Borgonovo is a Full Professor and Director of the Department of Decision Sciences at Bocconi University. He holds a PhD from MIT and an MSc in Nuclear Engineering from Politecnico di Milano. As a Research Affiliate at MIT's Department of Nuclear Science and Engineering, he contributes to interdisciplinary research. His roles include Co-editor-in-Chief of the European Journal of Operational Research and former President of the Decision Analysis Society of INFORMS. His research focuses on sensitivity analysis methodologies, including the development of Differential Importance Measures adopted by NASA. Applications span risk assessment (e.g., space systems, climate models), machine learning, and optimal transport theory. Key contributions include methods for feature importance, interaction quantification, and probabilistic sensitivity measures. Education: PhD, Massachusetts Institute of Technology, 2001 MSc in Nuclear Engineering (Mathematics/Physics focus), Politecnico di Milano Recipient of the 2020 Bocconi Teaching Innovation Award, Borgonovo teaches courses in quantitative methods, analytics, and computer experiments across undergraduate, graduate, and PhD programs. He pioneered the Bachelor in Economics, Management, and Computer Science at Bocconi. His work bridges theoretical advancements with practical applications in sustainability, business analytics, and policy, leveraging collaborations with institutions like NASA and the Silvio Tronchetti Provera Foundation.

• Numerical Analysis
• Computational Mathematics
• Isogeometric Analysis
• +۳ مورد دیگر

Giancarlo Sangalli is a Professor in the Department of Mathematics at the University of Pavia. His research focuses on Scientific Computing, particularly Numerical Methods and Applications, with a strong emphasis on Isogeometric Analysis (IGA) for solving Partial Differential Equations (PDEs). He leads the Scientific Computing group and contributes to interdisciplinary fields such as computational mechanics, biomedical engineering, and environmental modeling. His work integrates advanced numerical techniques, including high-order finite element methods, space-time formulations, and matrix-free solvers, to address challenges in computational efficiency and accuracy. Key areas of application include cardiac electrophysiology, wave propagation, and groundwater flow modeling. Sangalli has pioneered low-rank solvers, Tucker tensor-based methods, and immersed boundary techniques to enhance computational scalability. He actively publishes in top journals and conferences, with a focus on advancing IGA theory and its applications to real-world problems. His research also explores uncertainty quantification, Bayesian calibration, and nonlinear dynamics. Despite no explicitly listed awards, his extensive publication record reflects recognition in computational mathematics and engineering. Sangalli collaborates internationally and maintains a research website at https://mate.unipv.it/sangalli . His group's work is supported by projects in computational electromagnetics, structural mechanics, and fluid-structure interaction, demonstrating a commitment to bridging theoretical advancements with practical engineering solutions.

• Fluid Dynamics
• Combustion Engineering
• Turbomachinery
• +۳ مورد دیگر

Pietro De Palma serves as a Full Professor in the Department of Mechanics, Mathematics & Management at the Polytechnic University of Bari, Italy. His research focuses on fluid machinery systems with applications spanning hydrogen propulsion, renewable energy conversion, and fundamental fluid dynamics. Contact details include email pietro.depalma@poliba.it and office phone +39 080 596 3226 at Via Orabona 4, Bari. His primary research domains encompass Fluid Dynamics , Combustion Engineering , and Turbomachinery , with specialized expertise in hydrogen engine combustion phenomena, wind turbine aerodynamics, and thermal management systems. Recent work investigates lubricant oil interactions in hydrogen engines, Coriolis effects on wind turbine wakes, and stability mechanisms in transitional channel flows. He employs advanced computational methods including Large Eddy Simulation (LES), Reynolds-Averaged Navier-Stokes (RANS), and Dynamic Mode Decomposition (DMD) for complex fluid-structure interactions. Analysis of his 15 most recent publications (2024-2026) reveals three dominant research thrusts: (1) Hydrogen propulsion systems addressing pre-ignition mechanisms and combustion characterization, (2) Wind energy optimization focusing on wake dynamics and floating platform simulations, and (3) Fundamental fluid mechanics exploring coherent structures in turbulent flows. His work consistently bridges theoretical fluid dynamics with practical energy system challenges, particularly in decarbonization technologies. No scientific awards were documented in the provided sources. While student advising details are unavailable in the scraped materials, his extensive publication record indicates active mentorship in mechanical engineering research. No specific grant information appears in the sources, though his involvement in projects like PONa3_00372 'Innovative Processes for Energy Conversion–PrInCE' suggests competitive funding acquisition. Research activities appear centered within the university's Department of Mechanics, Mathematics & Management, with collaborations evident in wind energy and combustion studies through co-authored publications. His work connects with international initiatives like the IEA Wind Task 32 on wind turbine wake behavior.