جستجوی استاد راهنمای دانشگاهی

• Communication Design
• Systemic Design
• Sustainable Design
• +۵ مورد دیگر

Paolo Marco Tamborrini serves as an External Lecturer and Education & Public Awareness Area Coordinator at the Department of Architecture and Design (DAD) of the Polytechnic University of Turin, while holding the position of Full Professor at another university. His academic work spans systemic design, communication design, and sustainable design, with significant contributions to design education and research. Dr. Tamborrini's research focuses on innovation as a dynamic force that responds to specific needs while reinterpreting relationships between people and their context. His work emphasizes quantitative and qualitative context analysis encompassing cultural, social, and economic aspects. He investigates sustainable design from the perspective of product design and systemic design in relation to complexity management, focusing on open, autopoietic systems that transform production outputs into sustainable resources. His communication research shifts from simple graphic design to visual narration of qualitative values and data, ultimately constructing interactive virtual realities that enhance understanding of complex phenomena. His research trends demonstrate a consistent focus on integrating communication, sustainability, and systemic design approaches. Recent publications reveal growing emphasis on data-driven design, territorial analysis, and creative contexts within sustainable innovation frameworks. His work increasingly explores how design can serve as both a sustainability tool and innovative product development methodology, with particular attention to open design networking dynamics. Lucky Strike Talented Design Award (2012) from Raymond Loewy Foundation Italy Premio Selezione ADI Design Index (2011) for Theoretical, Historical, Critical Research Publication Award for Intervention in favor of young researchers (2011) from Polytechnic of Turin Director of GRAPHICUS journal (2013-present) Dr. Tamborrini actively supervises PhD students including Sergio Degiacomi Garbero, Sofia Cretaio, Leonardo Moiso, and Cristina Marino, whose research spans data-driven design for sustainable fashion, gamified educational innovation, and data visualization for corporate resources. His substantial grant portfolio includes current projects through 2026, such as the Implementation Agreement with the Municipality of Turin (2024-2026), the "Pallett 4.0" logistics tracking system (2020-2021), and InnovaEcoFood (2020), reflecting his strong industry connections and applied research approach. His work demonstrates consistent integration of academic research with practical applications across multiple sectors.

Lenny Smithمشاهده پروفایل

استاد

• Climate Science
• Statistical Modeling
• Chaos Theory
• +۲ مورد دیگر

Lenny Smith is a distinguished Professor of Statistics at the London School of Economics and Political Science (LSE) , where he also directs the Centre for the Analysis of Time Series (CATS) . Additionally, he serves as a Senior Research Fellow at Pembroke College, Oxford . With a PhD in Physics from Columbia University (1987), his career spans prestigious institutions including École Normale Supérieure, Warwick, and Potsdam University. Academic Roles: LSE Professor of Statistics, CATS Director, Pembroke College Senior Research Fellow Education: PhD in Physics (Columbia University, 1987); Undergraduate in Physics, Mathematics, and Computer Science (University of Florida) Research Focus: Climate modeling, ensemble forecasting, uncertainty quantification, chaos theory, and applications to disaster risk reduction Grants: Funded by ONR, NOAA, EPSRC, NERC, European Commission, and UK Research Councils Key Projects: NAPSTER (NERC), DIME and REMIND (EPSRC), THORPEX strategic planning Scientific Recognition: Royal Meteorological Society Fitzroy Prize (2003), Selby Fellowship (Australian Academy of Sciences) Students Supervised: Roman Frigg, David Stainforth, Emma Suckling, Falk Niehörster, H. Du, T. Maynard, S. Higgins, A. Jarman Media Presence: Quoted in Nature, New Scientist, BBC, Financial Times, and The Daily Telegraph Smith's work bridges rigorous mathematical analysis with practical applications, notably in climate change economics and weather risk management . His research on ensemble forecasting and probabilistic skill has shaped methodologies for evaluating climate models. He actively contributes to public science through his book A Very Short Introduction to Chaos and media appearances, emphasizing the importance of scientific uncertainty in policy decisions. His publications reveal a consistent focus on dynamical coherence , model error analysis , and weather derivatives , with recent work exploring multi-model cross-pollination and predictability limits . Smith's interdisciplinary approach combines nonlinear dynamics , statistical physics , and hydrological modeling to address real-world climate challenges.

• Artificial Intelligence for Science
• Explainable AI
• Trustworthy AI
• +۷ مورد دیگر

Wei (Celia) Xu serves as Research Professor in the Computer Science Department at Stony Brook University and Computational Scientist/Trustworthy AI (TAI) Group Lead at Brookhaven National Laboratory's Computational Science Initiative, driving innovation in AI for scientific discovery across multiple domains. Her educational foundation includes a Ph.D. in Computer Science from Stony Brook University and dual M.S. degrees in Computer Science from Zhejiang University, establishing expertise in computational methods and visualization. Dr. Xu's research centers on developing explainable and trustworthy AI frameworks for scientific applications, with notable contributions in digital twins for simulation workflows, performance evaluation of quantum/classical computing systems, and visual analytics for X-ray imaging and climate science. Her work integrates GPU acceleration and virtual reality to enhance scientific data interpretation, emphasizing model interpretability and reliability in high-stakes domains. Analysis of her 15 most recent publications (2019-2025) reveals a strategic evolution toward trustworthy AI systems, with increasing focus on counterfactual explanations for medical diagnostics, digital twin implementations for ensemble simulations, and quantum state visualization—demonstrating cross-disciplinary impact in materials science, climate modeling, and high-energy physics. Her exceptional contributions have been recognized with prestigious awards: Best Paper Award, PacificVis (2025) Best Paper Award, IEEE SC/ISAV (2020) Honorable Mention Award, IEEE VIS (2018) Women@Energy Recognition (2014) Best Paper Award, Fully3D/HPIR (2009) Dr. Xu actively mentors through her TAI research group while securing sustained funding from DOE's Biological and Environmental Research (BER) program and SciDAC initiatives, complemented by Brookhaven National Laboratory internal projects (LDRD and NSLSII DSSI). She serves on program committees for SC, VIS, and AAAI conferences and has organized workshops including NYSDS and Fully3D, demonstrating leadership in advancing trustworthy AI methodologies for scientific communities.

• Quantum Key Distribution
• Neuroscience
• Machine Learning
• +۳ مورد دیگر

Dr. Yijun Wang is a researcher affiliated with the Chinese Academy of Sciences, State Key Laboratory on Integrated Optoelectronics, and Institute of Semiconductors in Beijing, China. His work spans multiple disciplines including quantum key distribution, brain-computer interfaces, and machine learning applications in cybersecurity and biomedical imaging. Key Research Areas: Quantum cryptography, Neural signal processing, Transformer-based models, Network security, and Digital health systems. Recent publications highlight advancements in EEG authentication systems 2026 , radar-based activity recognition 2025 , and quantum communication security 2025 . His work demonstrates interdisciplinary expertise bridging theoretical algorithms and practical engineering solutions. Scientific contributions include: Developing attention mechanisms for image restoration 2025 Creating reliability-enhanced BCIs via graph-driven fusion 2025 Designing semi-supervised solvers for CAPTCHA breaking 2021 Dr. Wang's collaborations appear across journals like Pattern Recognition , IEEE Transactions , and conferences including AAAI 2025 , ICLR 2025 , and EMBC 2023 . Current projects integrate LLMs with digital phenotyping for hypertension management 2025 and explore self-taught reasoning mechanisms 2025 .

Meysam Goodarziمشاهده پروفایل

مدرس

• Artificial Intelligence
• Data Science
• Economics
• +۷ مورد دیگر

Meysam Goodarzi is a Lecturer at the Hertie School in Berlin, Germany, specializing in Data Structures & Algorithms within the Master of Data Science for Public Policy program. His research bridges computer science, economics, and probabilistic modeling, focusing on Bayesian inference, probabilistic graphical models, and optimization techniques. PhD in Computer Science (Humboldt University of Berlin) M.Sc. in Economics (Panthéon-Sorbonne University) His work emphasizes applications in data science and economics, particularly within AI-driven network optimization and 5G technology. He has contributed to EU Horizon 2020 projects, advancing synchronization, localization, and machine learning algorithms in telecommunications. Recent publications highlight his expertise in 5G networks , autonomous systems , and probabilistic modeling , with a focus on synchronization, localization, and communication-sensing integration. Articles span from 2024 to 2019, reflecting sustained contributions to 5G/6G research and AI applications. At Hertie School, he contributes to the Data Science Lab , integrating advanced computational techniques into public policy education. His interdisciplinary approach connects technical advancements in telecommunications with economic analysis and public sector applications.

Mark Grechanikمشاهده پروفایل

دانشیار

• Software Systems
• Software Testing
• Cloud Computing
• +۴ مورد دیگر

Mark Grechanik is an Associate Professor in the Department of Computer Science at the University of Illinois Chicago, affiliated with the College of Engineering. With a Ph.D. in Computer Science from the University of Texas at Austin (2006), he has over 30 years of experience as a software consultant for startups and Fortune 500 companies. His research focuses on software systems, security, and quality assurance, with a strong emphasis on automated testing, cloud computing, and data privacy. Ph.D., The University of Texas at Austin, 2006 His work addresses critical challenges in software testing, including integration testing automation (ASSIST project), database deadlock prevention, GUI test script analysis, and cloud elasticity optimization. He has developed techniques leveraging static/dynamic analysis, machine learning, and accessibility technologies to improve test efficiency and fault detection. Grechanik’s research has been recognized with best paper awards at SEKE 2019 and ICST 2009. He has secured funding from the NSF and Microsoft, and his innovations are commercialized through 37 patents. His publications span top venues like ICSE, ICST, ASE, and journals such as Empirical Software Engineering and IEEE Transactions on Software Engineering. He has served as General Chair of ICST 2016, member-at-large of the ACM SigSoft committee for nine years, and on editorial boards including Springer’s Empirical Software Engineering Journal. Grechanik is a senior member of ACM and IEEE.

Pablo Antolin Sanchezمشاهده پروفایل

پژوهشگر

• Numerical Methods
• Computational Mechanics
• Isogeometric Analysis
• +۶ مورد دیگر

Pablo Antolin Sanchez is a Researcher and Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences (SB) and the Department of Mathematics . He leads research at the Numerical Modelling and Simulation chair and contributes to teaching in mathematics and computational methods. Research interests include Isogeometric Analysis Computational Mechanics Numerical Methods for Structural Dynamics High-Performance Computing Machine Learning in Multiscale Modeling Recent publications focus on advanced isogeometric methods for shell structures reduced-order modeling for lattice systems machine learning integration in mechanics geometric modeling and mesh intersection Teaching roles encompass courses such as Numerical Approximation of PDEs and Parallel & High-Performance Computing . He has advised PhD student Ondine Gabrielle Chanon at EPFL.

Domenico Gattiمشاهده پروفایل

دانشیار

• Computational Biology
• Scientific Computing
• Matlab Programming
• +۷ مورد دیگر

Domenico Gatti is an Associate Professor at Wayne State University School of Medicine, affiliated with the Department of Microbiology, Immunology and Biochemistry. He is also an investigator at the Cardiovascular Research Institute, NanoBioScience Institute, and Molecular Medicine Institute. His research spans computational biology, structural biology, and biomedical imaging, with a focus on enzyme mechanisms, protein coevolution, and artificial intelligence applications. M.D., Catholic University of Rome (1982) Ph.D., University of Bari (1987) Dr. Gatti develops computational tools like MSAVOLVE for protein coevolution analysis and neural networks (e.g., Res-CR-Net, CXR-Net, Cardio-Net) for biomedical image segmentation. His work includes QM/MM simulations, X-ray crystallography of metabolic enzymes, and Flux Balance Analysis of cell metabolism. Recent publications highlight AI-driven pandemic diagnostics and protein structure-function relationships. Current teaching includes graduate courses in machine learning, bioinformatics, and data science. He accepts new students in Biochemistry and Molecular Biology (BMB) for both MS and PhD programs. His laboratory is located in Scott Hall, Detroit, and collaborates on interdisciplinary projects integrating computational and experimental approaches.

• Computational Engineering
• Geometric Modeling
• Sensor Technology
• +۳ مورد دیگر

Aleksander Pedersen is an Associate Professor at the Department of Computer Science and Computational Engineering , UiT The Arctic University of Norway. His research focuses on Computational Engineering , Geometric Modeling , and Sensor Technology , with applications in Augmented Reality in Healthcare , Additive Manufacturing , and Winter Road Assessment . Fields of Interest Computational Engineering Geometric Modeling Sensor Technology Augmented Reality in Healthcare Additive Manufacturing Simulation-based Education Pedersen's recent work includes 2024 studies on AR projections for medical simulations and optimization in additive manufacturing , while earlier studies (2020–2015) explore spline-based modeling , sensor fusion for winter roads , and subsurface visualization . He collaborates with researchers like Tanita Fossli Brustad, Rune Dalmo, and Børre Bang, and is affiliated with the Simuleringer research group at UiT. His contact email is aleksander.pedersen@uit.no .

Gabriele Moserمشاهده پروفایل

استاد

• Remote Sensing
• Signal Processing
• Machine Learning
• +۳ مورد دیگر

Gabriele Moser is a Full Professor (Professore ordinario) at the University of Genoa's Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN), affiliated with the Polytechnic School. He serves as Coordinator of the Engineering for Natural Risk Management program, sits on the Departmental Board, and contributes to the School Council. His teaching portfolio spans telecommunications, signal processing, remote sensing, and machine learning courses for energy engineering and natural risk management programs. Professor Moser's research integrates remote sensing , machine learning , and signal processing to address environmental and infrastructural challenges. Key focus areas include: Multisensor data fusion for natural disaster monitoring Deep learning architectures for satellite/UAV image analysis Probabilistic graphical models for classification Lightning nowcasting using meteorological data Hyperspectral image unmixing and reconstruction His recent publications demonstrate a strong emphasis on AI-driven methodologies for remote sensing applications. Dominant themes include deep learning frameworks (CNNs, CRFs, diffusion models) for image segmentation, multiresolution fusion techniques, and heterogeneous change detection, frequently applied to disaster management scenarios like flooding and weather prediction.

Lisa Waananen Jonesمشاهده پروفایل

استادیار بالینی

• Visual Communication
• Data Journalism
• Narrative Storytelling
• +۳ مورد دیگر

Lisa Waananen Jones is a Clinical Assistant Professor in the Edward R. Murrow College of Communication at Washington State University, specializing in Multimedia Content Creation, Data Visualization, and Narrative Storytelling. She teaches courses such as Reporting Across Platforms and Professional Multimedia Content Creation , with a focus on making data and analytics accessible to students. Education: Undergraduate degrees in Communication (Journalism) and Political Science from Washington State University; Graduate studies at Columbia School of Journalism. Professional Experience: Former reporter for The Spokesman Review and teaching assistant at Columbia, followed by two years as an intern at The New York Times graphics desk where she earned multiple awards for collaborative projects. Research Focus: Visual communication and data-driven storytelling as tools for civic journalism, emphasizing simplification of complex topics for public understanding. Awards: Recognized for group projects at The New York Times graphics desk.

Claus-Eberhard Liedtkeمشاهده پروفایل

استاد

• Image Analysis
• Remote Sensing
• Industrial Automation
• +۳ مورد دیگر

Claus-Eberhard Liedtke is a Professor of Digital Signal Processing at the Department of Electrical Engineering, Leibniz University Hannover. He has held academic positions at the University of Minnesota (Assistant Professor, 1973–1976) and lectured as a Visiting Professor at Zhejiang University, China (1985). His work focuses on knowledge-based image analysis, 3D scene modeling, and remote sensing applications in industrial automation. Education: Diplom (1968) and Dr.-Ing. (1972) in Electrical Engineering from TU Berlin. Research Interests include automated knowledge acquisition for image systems, semantic networks in remote sensing interpretation, and multisensor fusion for 3D geometry reconstruction. His publications span hierarchical pose estimation, GIS-data integration, and Bayesian reasoning in vision systems. Publications Trends highlight expertise in remote sensing (7/15), 3D modeling (5/15), knowledge-based systems (6/15), and sensor fusion (3/15). Key subfields include topographic dataset verification, multitemporal analysis, and lifelike 3D human modeling. Professional Affiliations include EURASIP, EUROGRAPHICS, GI, ITG, and DAGM. He chairs the ITG working group on Pattern Recognition and serves on the Signal Processing journal’s editorial board, with over 90 publications and 30 grants from DFG, EU, and industry.

• Educational Technology
• Free and Open Source Software
• 3D Virtual Environments
• +۵ مورد دیگر

Nelson Alexandre Fernandes Gonçalves is an Invited Assistant at the School of Education of the Polytechnic Institute of Viseu, Portugal, a position he has held since 2018. Previously, he served as an Assistant at the same institution from 2003 to 2018 and at the Polytechnic Institute of Leiria from 1998 to 2003, establishing a 25+ year career in Portuguese higher education focused on digital pedagogy and libre culture. His educational background includes: Bachelor's Degree in History (Educational Branch) from the University of Évora (1990-1995) Master's Degree in Educational Technology from the University of Minho (1999-2003), with thesis on virtual environments in primary education Specialized training in Blender and 3D modeling (2008-2017) from institutions including University of Burgos and InterSpace Gonçalves champions Free/Libre Open Source Software (FLOSS) in educational and cultural contexts, developing open workflows for 3D heritage reconstruction, digital animation, and web mapping. His research integrates libre culture with teacher training and K-12 education, emphasizing student creativity and critical digital literacy through cocreation methodologies that bridge humanities with computational practices. Analysis of his 15 most recent publications reveals a strategic pivot toward practical FOSS toolkits for cultural heritage documentation and community engagement. Key trends include democratization of 3D heritage workflows through photogrammetry guides, expansion into alternative geography mapping (e.g., "If Portugal was in Asia"), and development of social movement cartography. His output prioritizes accessibility, with 80% of 2023-2024 works as open-access web resources or multilingual manuals. Gonçalves has co-supervised over 50 undergraduate theses in Arts and Multimedia since 2000, with recent projects spanning virtual museums, 3D animation pipelines, and digital storytelling. His grant portfolio includes: European Projects: Researcher in 7+ Erasmus+/Comenius initiatives (2001-2025) including Digital Era (2019-2022) and WBEE (2010-2012) Local Innovation: Principal investigator for IPV Inova e Inclui (2022-2023) focusing on metaverse-based cocreation He founded OpenLab ESEV (2009-2018), Portugal's pioneering libre software laboratory in higher education, and NERDLab (2020-2022) for digital archaeology. These spaces foster community-driven development of open animation tools and 3D heritage models through cocreation workshops, engaging students, educators, and cultural institutions in libre culture practices.

• Digital Typography
• Graphic Design
• Web Design
• +۴ مورد دیگر

Daniel Rodríguez Valero (Granada, 1973) is a full-time Lecturer at the University of Alicante, affiliated with the Department of Communication and Social Psychology under the College of Social Sciences. His academic career spans teaching and research in digital typography, graphic design, and corporate communication. Education: PhD in Fine Arts, University of Barcelona (2006) Second-Cycle Degree in Fine Arts, University of Barcelona (1996) His research focuses on digital typography , web conversion optimization , branding , and design for entrepreneurship . Recent publications analyze corporate naming strategies, hotel branding, and the intersection of typography with digital communication. Scientific Awards: ADI Medal in Industrial Design Accesit Ensayo Award (Fundación Everis) Juan de Yciar Award for Editorial Quality 2015 Clap Awards First Prize for Text Typography

Rémi Monassonمشاهده پروفایل

پژوهشگر

• Statistical Physics
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

Rémi Monasson is a Researcher at the Laboratoire de physique de l’ENS (LPENS) within the Department of Physics at École normale supérieure (ENS-PSL) in Paris, France. His work bridges Statistical Physics , Machine Learning , Biophysics , and Computational Biology . Active in interdisciplinary research, he contributes to understanding complex systems through theoretical modeling and data-driven approaches. University: École normale supérieure (ENS-PSL) Department: Department of Physics Research Interests: Statistical Physics, Machine Learning, Biophysics, Computational Biology, Neural Networks, Protein Structure Prediction Email: remi.monasson@phys.ens.fr Rémi Monasson's recent publications focus on leveraging Restricted Boltzmann Machines for molecular design, protein sequence modeling , and neural network dynamics . His work spans applications in evolutionary biology , immunology , and biological sequence analysis , often integrating statistical mechanics with machine learning methodologies.