جست‌وجوی استاد و پژوهشگر

Michele Ruggeriمشاهده پروفایل

استادیار

• Numerical Analysis
• Partial Differential Equations
• Materials Science
• +۶ مورد دیگر

Michele Ruggeri is an Assistant Professor of Numerical Analysis (RTD-B) at the Department of Mathematics, University of Bologna, and an Honorary Lecturer at the University of Strathclyde, UK. His research focuses on numerical analysis of partial differential equations in materials science and engineering, including liquid crystal theory, micromagnetism, nonlinear elasticity, and spintronics. He is also active in developing numerical methods for uncertainty quantification and model order reduction. Education: PhD in Technical Mathematics (TU Wien, Austria), Laurea Magistrale in Mathematics (University of Pavia, Italy), and a Diploma in Science and Technology from Scuola Universitaria Superiore IUSS, Italy. He holds a Fellowship (FHEA) from Advance HE and a PGCert in Learning & Teaching in Higher Education from the University of Strathclyde. His work emphasizes finite element methods and their applications, with contributions to computational micromagnetics and software development (e.g., Commics). He is affiliated with the (AM)² Research Center on Applied Mathematics and ARCES at the University of Bologna. Awards: Fellowship (FHEA), Advance HE, UK. Key Projects: Development of numerical methods for micromagnetic simulations, uncertainty quantification in stochastic models. Contact: m.ruggeri@unibo.it

• Distributed Systems
• Computer Networks
• Middleware
• +۱۳ مورد دیگر

Antonio Corradi is a Full Professor of Computer Networks and Infrastructures supporting Cloud and Big Data at the University of Bologna's School of Engineering, within the Department of Computer Science - Science and Engineering. His roles include President of the regional CLUSTER RER for service innovation, President of the Alma Mater FAM Foundation, and Director of the UNIBO High Studies Center in Buenos Aires. He previously served as Director of the DISI department (2018–2021) and International Delegate for Latin America (2014–2018). His research focuses on distributed systems, middleware for pervasive computing, cloud solutions, mobile systems, smart cities, Industry 4.0/5.0, and 5G communication standards. Education: Laurea cum laude in Electrical Engineering (University of Bologna, 1979) and a Master's in Computer Engineering from Cornell University (1981, supported by a Fulbright-Hayes grant). He joined the University of Bologna as a Researcher in 1983 and became Full Professor in 2000. Research interests span distributed/parallel systems, middleware for mobile agent systems, cloud computing, smart city monitoring, and Industry 4.0 protocols. He emphasizes QoS-aware solutions, edge computing, and IoT integration. His work includes designing frameworks for big geospatial data and novel architectures for serverless and fog computing environments. Selected scientific awards include the 1980 'Cavalieri del Lavoro' prize for his thesis. He actively contributes to institutional duties, including the CCIB (Computer Services Centre of the Engineering School) and CINI Bologna University Section (Italian Interuniversity Consortium). In advising and grants: He coordinates PhD programs and has led projects funded by MIUR, CNR, and European initiatives. Notable collaborations include industry grants with Jakala, OTConsulting, ENAV-Sicta, and the Zefiro Consortium. His projects address challenges in energy efficiency, smart manufacturing, and healthcare management during crises. Labs/Teams: Developed platforms like SOMA and REDMAN middleware. Involved in initiatives such as ParticipAct (mobile crowdsensing), COLOMBO (vehicular traffic monitoring), and the Audit4Cloud platform for cloud performance auditing.

Giovanni Russoمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Numerical Methods for Conservation Laws
• Numerical Methods for Kinetic Equations
• +۵ مورد دیگر

Giovanni Russo is a Full Professor of Numerical Analysis at the Department of Mathematics and Computer Science, University of Catania, Italy . He coordinates the PhD program in Pure and Applied Mathematics and has been a visiting scholar at institutions including Courant Institute, University of California, Los Angeles, University of Michigan, and University of Bordeaux. His career spans over four decades across academia and research institutions. Education: PhD in Physics (1986, University of Catania), Laurea in Nuclear Engineering (1982, Politecnico di Milano). Research Interests: Russo specializes in Computational Fluid Dynamics , Numerical Methods for Conservation Laws , and Kinetic Equations . His work includes asymptotic preserving schemes , IMEX methods , semi-Lagrangian schemes , and high-order numerical techniques for PDEs with applications to fluid dynamics, plasma physics, and multiscale modeling. Scientific Trends: Recent publications focus on modeling epidemic dynamics , kinetic equations for inert mixtures , semi-Lagrangian methods , and uncertainty quantification in quantum systems. These works reflect his expertise in high-order numerical schemes , multiscale analysis , and applied mathematical modeling . Scientific Awards: CNR-NATO Fellowship (1987) Advising and Grants: Russo has supervised nine PhD students and served as Principal Investigator (PI) for major projects including MOSCOVID (modeling COVID-19) and ModCompShock (Horizon 2020 Marie Curie project). He has also organized international conferences like the 18th European Conference on Mathematics for Industry with 370 participants. Labs and Teams: Russo collaborates with research groups at the University of Catania and has been a visiting researcher at Courant Institute, University of Michigan, and GSSI L’Aquila. He contributes to journals as an editor and reviewer, including SIAM Journal of Numerical Analysis and Journal of Computational Physics .

• Machine Learning
• Online Learning
• Algorithmic Game Theory
• +۴ مورد دیگر

Andrea Celli is an Assistant Professor in the Department of Computing Sciences at Bocconi University. He is affiliated with the ELLIS Society and the Bocconi Institute for Data Science and Analytics. Previously, he was a postdoctoral researcher at Meta (formerly Facebook Research) in London. He holds a Ph.D. in Computer Science from Politecnico di Milano and conducted research at Carnegie Mellon University's Electronic Marketplaces Lab. His research focuses on intersections of computer science, machine learning, and economics, particularly in strategic interactions and online learning environments. Notable achievements include a NeurIPS 2020 Best Paper Award and the 2017 Lesmo Prize for his MSc thesis. His research is supported by grants including an ERC Starting Grant (2024) for the PLA-STEER project and an MUR-PRIN grant (2022). He teaches courses such as Deep Learning and Reinforcement Learning, Machine Learning, and Optimization at the Ph.D. level. His work spans topics like equilibrium finding, online learning under constraints, and mechanism design. Key publications include contributions to ICLR, NeurIPS, EC, and other top venues. Celli advises Master’s students including Annalisa Barbara, Emanuele Coccia, Davide Drago, and Antonio Preiti. He collaborates with postdocs like Riccardo Poiani and Martino Bernasconi. He actively organizes academic events, such as the EC 2025 workshop on Online Learning and Economics. His research emphasizes theoretical foundations while addressing practical challenges in algorithmic game theory and data-driven decision-making.

Andrea Tosinمشاهده پروفایل

استاد

• Mathematical Physics
• Kinetic Theory
• Transport and Diffusion Equations
• +۷ مورد دیگر

Andrea Tosin is a Full Professor of Mathematical Physics at the Department of Mathematical Sciences "G. L. Lagrange" (DISMA), Politecnico di Torino. He serves as Coordinator of the Doctoral College of Mathematical Sciences and Deputy Coordinator of the Doctoral College of Pure and Applied Mathematics. His research bridges kinetic theory, transport equations, and applied mathematics with applications in multi-agent systems, traffic, social dynamics, and epidemiology. His research interests focus on: Kinetic theory and its applications to real-world systems Transport and diffusion equations in complex environments Modeling of vehicular traffic, crowd dynamics, and social behavior Epidemiological modeling with a focus on viral load and multi-scale dynamics Mathematical modeling of collective behavior in biological and social systems His recent publications demonstrate a consistent trend in developing and analyzing kinetic models for traffic flow, opinion dynamics, and epidemic spread, often incorporating uncertainty, network structures, and multi-population interactions. These works frequently involve rigorous mathematical derivations from microscopic models to macroscopic equations, with applications in safety, public health, and urban planning. His scientific awards include: SIMAI Biennial Award (2013) INDAM-SIMAI Award (2010) He actively supervises PhD students and postdoctoral researchers, including Martina Fraia, Emanuele Bernardi, Elisa Paparelli, and Mattia Sensi. He has secured significant research grants from national (PRIN, INdAM) and institutional (Politecnico di Torino, Google) sources. His research is supported by projects such as IMASED (Integrated Mathematical Approaches to Socio-Epidemiological Dynamics) and ANATOMY (A Unitary Mathematical Framework for Modelling Muscular Dystrophies). He also leads the "Modelli e Metodi della Fisica Matematica" research group at DISMA.

Diego Regruto Tomalinoمشاهده پروفایل

دانشیار

• System Identification
• Robust Control
• Convex Relaxation Techniques
• +۵ مورد دیگر

Diego Regruto Tomalino is an active Associate Professor in the Department of Control and Computer Engineering (DAUIN) at Polytechnic University of Turin, Italy, with contact details +39 0110907077 and diego.regruto@polito.it. He holds leadership roles in the IEEE Control Systems Society as Scientific Committee member of the Technical Committee on System Identification and Adaptive Control (2008-present) and served as its President (2013-2015). His work spans academic research, teaching, and international collaboration within control engineering. Education : Laurea in Electronic Engineering, Politecnico di Torino (2000) Ph.D. in Systems Engineering, Politecnico di Torino (2004) Research Interests : System Identification : Specializing in set-membership, sparse, and LPV techniques for nonlinear systems with applications in automotive and biomedical domains. Optimization & Control : Developing convex relaxation methods for model predictive control, robust control algorithms, and electrified vehicle propulsion systems. Control Education : Innovating through remote laboratories and industrial platforms to enhance engineering pedagogy globally. Publication Trends : Recent work (2021-2024) focuses on sparse optimization for cyber-physical security and electrified vehicles, extending set-membership identification to continuous-time systems, and educational frameworks. Dominant fields include control theory, optimization, and automotive applications with increasing emphasis on data-driven methods and sparse computing. Scientific Awards : No specific prizes, medals, or fellowships were documented in the provided texts. Advising and Grants : PhD Supervision : Alice Re (2024-present, sparse optimization for identification), Francesco Ripa (2023-present, electric vehicle propulsion management), Simone Pirrera (2021-2025, dynamical systems learning). Research Projects : Principal investigator for OpThermEV (2021-2022) on thermal management of electric vehicles, plus corporate-funded automotive research initiatives. Labs and Teams : Core member of the SIC (System Identification & Control) research group and LAB 11 at DAUIN. Leads international control education collaborations, notably a remote laboratory partnership between Asian and European institutions.

Giorgio Vinciguerraمشاهده پروفایل

پژوهشگر ارشد

• Data Compression
• Algorithm Engineering
• Learned Data Structures
• +۳ مورد دیگر

Giorgio Vinciguerra is a Research Fellow (RTD-A) at the Department of Computer Science of the University of Pisa since January 2023, and a member of the A³ Lab. His research focuses on compact data structures, data compression, and algorithm engineering, with a specialization in learned data structures that leverage machine learning to improve space-time trade-offs. He holds a PhD from the University of Pisa (2022), awarded the Best PhD thesis in Theoretical Computer Science by the Italian Chapter of EATCS. His academic journey includes postdoc research (2022), a visiting researcher role at KTH Royal Institute of Technology (2024), and Harvard University (2020). He has contributed to EU-funded projects like SoBigData.it and owns patents for innovations in data structure design. Key research interests include: Learned compression techniques for time series and string dictionaries Space-efficient indexing for massive datasets Algorithmic integration of machine learning into traditional data structures His work has been published in top venues including ICDE, Inf. Syst., and ACM Trans. Algorithms. Awards include the 2025 WSDM Outstanding Reviewer Award. He has co-supervised multiple theses on topics like adversarial query optimization and compressed indexing. Teaching roles include courses on programming, algorithms, and information retrieval at the University of Pisa. His software libraries (e.g., LeMonHash, PGM-index) are widely used in database systems and bioinformatics.

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.

• Numerical Linear Algebra
• Matrix Theory
• Numerical Analysis
• +۶ مورد دیگر

Davide Palitta is an Assistant Professor (tenure track) at the Department of Mathematics of the University of Bologna. His research focuses on numerical linear algebra, matrix equations, and their applications in fields like data assimilation, deep learning, and parallel computing. He holds a PhD in Mathematics from the University of Bologna (2018) and has held postdoctoral positions at the Max Planck Institute in Magdeburg (2018–2021) and a visiting fellowship at Brown University (2020). His work emphasizes the development of efficient numerical algorithms for large-scale matrix equations, including Sylvester, Lyapunov, and Riccati equations. Key contributions include Krylov subspace methods, randomized techniques, and time-parallel integration strategies. His recent publications span topics such as sketched Krylov methods, tensor-based solvers, and preconditioning strategies for weak-constraint data assimilation. Palitta collaborates actively with international institutions and organizes seminars like the Scube series on numerical linear algebra. He is involved in upcoming conferences on matrix equations, data assimilation, and parallel computing. No scientific awards are explicitly mentioned in the provided materials.

Andrea Maranzoniمشاهده پروفایل

دانشیار

• Hydraulics
• Numerical Modelling of Free Surface Flows
• Flood Hazard Assessment
• +۷ مورد دیگر

Andrea Maranzoni is an Associate Professor of Hydraulics at the Department of Engineering and Architecture, University of Parma, Italy, where he has been serving since February 2019. He previously held assistant professor positions at the University of Parma and the University of Brescia, and has been actively involved in teaching and research in hydraulic and environmental engineering. Education: Ph.D. in Civil Engineering (Hydraulic Engineering), University of Parma, 2004 Degree in Civil Engineering (cum laude), University of Parma, 2000 His research focuses on the numerical and physical modeling of unsteady free surface flows, flood hazard assessment due to dam-breaks and levee breaches, probabilistic flood mapping, shallow water equations, and finite volume methods. He also investigates hydrodynamic actions on structures, mixed flow modeling, and imaging techniques for water surface measurement. His work bridges theoretical hydraulics with practical flood risk mitigation strategies. The recent publications (2023–2024) reflect a strong trend in dam-break modeling, flood hazard quantification, and theoretical advances in fluid mechanics. Key themes include probabilistic risk assessment, extension of classical equations like Bernoulli’s under non-inertial frames, and experimental analysis of hydrophobic sphere impacts. These works demonstrate a consistent focus on improving flood prediction accuracy and safety through advanced numerical and experimental methods. Scientific Awards: None listed in the provided text. Maranzoni has advised one Ph.D. student, Susanna Dazzi, and has supervised approximately 30 Bachelor’s and Master’s theses. He has received research funding from MIUR’s FFABR program (€3,000) and is a participant in the RELAID project (€600,000 total, 2020–2022). He also serves as Vice Coordinator of the Ph.D. Programme in Civil Engineering and Architecture at the University of Parma. He is involved in the research community through editorial roles, notably as Guest Editor for a special issue in Water (MDPI) on dam-break modeling, and as a reviewer for leading journals such as Journal of Hydraulic Engineering (ASCE) and Advances in Water Resources . He is a member of the Italian Hydraulic Group (GII), the Faculty Board of the Ph.D. program, and the CIDEA Interdepartmental Center for Energy and the Environment.

Daniele Cappellettiمشاهده پروفایل

دانشیار

• Stochastic Processes
• Probability Theory
• Mathematical Biology
• +۷ مورد دیگر

Daniele Cappelletti is an Associate Professor in the Department of Mathematical Sciences (DISMA) at the Politecnico di Torino, where he conducts research in stochastic modeling of biochemical reaction networks. He holds a PhD from the University of Copenhagen and has held postdoctoral positions at ETH Zurich, University of Wisconsin-Madison, and the University of Copenhagen. He is affiliated with the 'Probability and Applications' research group and leads the ConStRAINeD project funded by the Italian PRIN program. PhD in Probability, University of Copenhagen (2012–2015) M.S. in Mathematics, Pisa University (2009–2012) B.S. in Mathematics, Pisa University (2005–2009) His research focuses on stochastic processes, probability theory, and mathematical biology, particularly in the modeling and analysis of chemical reaction networks. He investigates the long-term behavior, stability, and model reduction in both deterministic and stochastic frameworks, with applications in systems biology and synthetic biology. His work bridges theoretical mathematics with practical biological systems, especially those exhibiting absolute concentration robustness. The trend in his recent publications shows a strong emphasis on the mathematical foundations of stochastic reaction networks, including tier structures, non-explosivity, and approximation techniques. He has also extended his work into computational applications such as using chemical networks to approximate probability distributions and analyzing security in blockchain protocols, demonstrating interdisciplinary reach across mathematics, biology, and computer science. Daniele Cappelletti currently supervises PhD student Giulio Cuniberti in the Mathematical Sciences program at Politecnico di Torino. He has been involved in competitive research grants, most notably as Scientific Manager of the ConStRAINeD project (2023–2026), which aims to advance the convergence and stability theory of reaction network dynamics. He has not received any explicitly mentioned scientific awards in the provided text. He is actively involved in teaching across multiple programs, including Mathematical Engineering, Data Science and Engineering, and Management Engineering. He teaches courses on stochastic processes, statistics, and time series analysis, both as course instructor and collaborator. He is a member of the Doctoral College in Mathematical Sciences and participates in the College of Management and Production Engineering and the College of Mathematical Engineering.

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.

Francesco Venezianoمشاهده پروفایل

دانشیار

• Geometry
• Number Theory
• Algebra
• +۳ مورد دیگر

Francesco Veneziano serves as an Associate Professor in the Department of Mathematics (DIMA) at the University of Genoa, Italy, holding academic rank MATH-02/B in Geometry. His teaching portfolio spans multiple engineering and mathematics programs, including Geometry for Computer Engineering and Naval Engineering undergraduates, and advanced graduate courses such as Galois Theory and Higher Geometry in Institutions for Mathematics Master's students. Office hours are maintained via the university's Aulaweb platform. His research program centers on pure mathematics with emphases on geometric structures and number-theoretic phenomena. Primary investigations explore continued fractions over algebraic number fields, rational angle classification in lattice geometries, and nonlinear recurrence relations. Recent work demonstrates interdisciplinary expansion into computational mathematics, notably applying reinforcement learning to game theory problems. The geometric perspective permeates all research strands, connecting abstract algebraic frameworks with concrete discrete structures. Analysis of his 2022-2024 publications reveals consistent focus on classical number theory problems with geometric interpretations. Key trends include periodicity properties in continued fraction expansions, Diophantine constraints in lattice configurations, and algorithmic approaches to strategic game analysis. The 2024 publication on 7 Wonders Duel represents a methodological evolution, merging dynamical systems theory with artificial intelligence techniques while maintaining core mathematical rigor. No scientific awards or honors were documented in the source material. No information regarding doctoral advisees, master's students, or externally funded research grants was provided. His academic contributions appear concentrated in theoretical research and advanced mathematical education within the university's mathematics department.

Gianluca Cimaمشاهده پروفایل

استادیار

• Knowledge Representation and Reasoning
• Description Logics and Ontologies
• Database Theory
• +۳ مورد دیگر

Gianluca Cima is an Assistant Professor at the Department of Computer, Control and Management Engineering of Sapienza University of Rome since April 2023, following a postdoctoral position at CNRS's LaBRI laboratory (University of Bordeaux) from February 2021 to March 2023. His educational background includes: PhD in Engineering in Computer Science from Sapienza University of Rome (2020), supervised by Prof. Maurizio Lenzerini, with a six-month visiting period at the University of Oxford Dr. Cima's research centers on Knowledge Representation and Reasoning , Description Logics and Ontologies , and Ontology-Based Data Management , with significant contributions to Controlled Query Evaluation for secure data access. His work bridges theoretical foundations in description logics with practical applications in semantic technologies, as demonstrated by co-chairing the First International Workshop on Logical Foundations of Neuro-Symbolic AI (LNSAI 2024). Analysis of his 2024-2025 publications reveals a concentrated research trajectory in controlled query evaluation mechanisms, entity resolution systems, and ontology-based data integration, increasingly incorporating epistemic reasoning and security policies while maintaining strong ties to database theory fundamentals. His scientific recognition includes: EurAI Doctoral Dissertation Award (2020) for "Abstraction in Ontology-based Data Management" (published in FAIA book series) Distinguished Paper Award at IJCAI 2024 Dr. Cima serves as Guest Editor for the "Knowledge Representation and Ontology-Based Data Management" special issue in Information journal and has held leadership roles including Program/General Co-Chair for LNSAI 2024. His academic service and editorial work indicate active grant involvement and research direction-setting within his field. He is embedded in Sapienza's Data Management and Semantic Technologies research group, contributing to the Artificial Intelligence and Knowledge Representation domain through collaborative projects in semantic web technologies and knowledge-based systems development.

Didier Duboisمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Operations Research
• Decision Sciences
• +۴ مورد دیگر

Didier Dubois is a Research Advisor at IRIT (Institut de Recherche en Informatique de Toulouse), affiliated with the Computer Science Department of Paul Sabatier University in France and the French National Centre for Scientific Research (CNRS). His work spans Artificial Intelligence, Operations Research, and Decision Sciences, focusing on modeling and processing imprecise and uncertain information in reasoning, decision-making, and risk analysis. Co-author (with Henri Prade) of foundational monographs on fuzzy sets and possibility theory. Coordinated the 7-volume HANDBOOK of FUZZY SETS series (1998-2000). Contributed approximately 200 technical journal papers on uncertainty theories and applications. Co-Editor-in-Chief of Fuzzy Sets and Systems and serves on editorial boards of journals in uncertain reasoning. He held leadership roles as former President of the International Fuzzy Systems Association (IFSA, 1995-1997) and received the 2002 IEEE Pioneer Award, while being recognized as an IFSA and ECCAI Fellow.