جست‌وجوی استاد و پژوهشگر

Federico ZANETTINمشاهده پروفایل

استاد

• Corpus Linguistics
• Translation Studies
• Graphic Narrative Translation
• +۵ مورد دیگر

Federico ZANETTIN is a Full Professor in the Department of Comparative Linguistic and Cultural Studies at Ca' Foscari University of Venice. His research focuses on translation studies with particular emphasis on corpus linguistics, graphic narrative translation, and journalistic translation. He maintains an active presence in the academic community through editorial work and research collaborations. Professor ZANETTIN's research interests span multiple areas of translation studies. He is particularly known for his work on corpus linguistics and its applications to translation analysis, with a focus on creating and using linguistic databases. His research on the translation of graphic narratives examines the verbal and visual aspects of translating comics and graphic novels across cultures. Additionally, he investigates journalistic translation , analyzing how information is translated and disseminated across media platforms. His scholarly work demonstrates consistent productivity, with numerous publications that explore the intersection of translation, culture, and media. Professor ZANETTIN's research shows particular strength in analyzing adaptation processes across linguistic, cultural, and modal boundaries, both synchronically and diachronically. Professor ZANETTIN serves on several important editorial boards: Co-editor of inTRAlinea Member of the international advisory board for The Translator Member of the international advisory board for Translang Member of the international advisory board for Entreculturas Member of the publications committee for Transletters. International Journal of Translators and Interpreters Member of the scientific committee for the Book series Interactio He is also frequently called upon as a referee for prestigious research projects, including those funded by The British Academy (UK), MIUR (Ministry of Education, University and Research), Italy, CSIC (Consejo Superior de Investigaciones Científicas), Spain, NRC (National Research Council), Canada, National and Kapodistrian University of Athens, Greece, and SNSF (Swiss National Science Foundation). Professor ZANETTIN teaches courses in English language and translation at both undergraduate and graduate levels, focusing on European, American, and postcolonial languages and literatures. His teaching reflects his research expertise in translation studies and cross-cultural communication.

Anna Gottardمشاهده پروفایل

دانشیار

• Multivariate Statistical Models
• Graphical Models
• Statistical Machine Learning
• +۵ مورد دیگر

Anna Gottard is an Associate Professor of Statistics at the University of Florence, where she leads the Department of Statistics, Computer Science, and Applications. She directs the Florence Center for Data Science (FDS) and participates in the Technical Scientific Committee of the Tuscan Center for Big Data, Data Science, and AI (CBDAI). Her research focuses on multivariate statistical models, particularly graphical models, and extends to statistical machine learning, fair models, and directional data analysis. She is an Associate Editor for the Journal of the Royal Statistical Society Series A (JRSSA) and Statistical Methods & Applications (SMA). Her recent work includes Bayesian approaches for mixed graphical models, uncertainty-aware classification trees, and methodological advancements in latent uncertainty models. Her contributions span theoretical developments and applied research in interdisciplinary areas like biostatistics and sustainability. Her research interests emphasize bridging statistical theory with practical applications, including fairness in machine learning, interpretable models, and tree-based methodologies. She has actively contributed to open-source software, notably the Mix3Trees R package for mixed-effect tree models. Her work addresses challenges in variable selection, graphical model inference, and ethical AI practices. Current projects explore Bayesian frameworks for complex data structures and methodological improvements in graphical model interpretability. Anna has advised on interdisciplinary collaborations, such as studies on GDPR compliance in biobanking and epidemiological modeling of the SARS-CoV-2 pandemic in Tuscany. She collaborates with institutions like the CBDAI to advance data science applications in regional policy and healthcare. Her research trajectory reflects a commitment to both foundational statistical theory and real-world problem-solving across diverse domains.

Giorgio Grisettiمشاهده پروفایل

استاد

• Mobile Robotics
• SLAM
• Robot Localization
• +۳ مورد دیگر

Giorgio Grisetti is a Full Professor at Sapienza University of Rome within the Department of Systems and Computer Science, maintaining active research roles in the RoCoCo lab at Sapienza since November 2010 and the Autonomous Intelligent Systems Lab at Freiburg University where he previously served as a Post Doc under Wolfram Burgard starting in 2006. His educational background includes a M.Sc. in Computer Engineering from the University of Rome (2001) and a Ph.D. from Sapienza University of Rome's Intelligent Systems Lab (2006), supervised by Daniele Nardi. His doctoral thesis focused on SLAM using Rao-Blackwellized particle filters. Dr. Grisetti's research centers on mobile robotics with emphasis on robust solutions for autonomous navigation systems. His work spans theoretical and practical advancements in Simultaneous Localization and Mapping (SLAM), robot localization, path planning, and sensor fusion, particularly leveraging LiDAR and multi-sensor configurations. Recent publications demonstrate strong focus on optimization techniques, sensor calibration, and real-time performance for autonomous systems operating in complex environments. His publication trends reveal deep specialization in LiDAR-based SLAM (7 of 15 recent articles), bundle adjustment methods (4 articles), and sensor calibration/perception (3 articles), with consistent contributions to top robotics venues like IEEE Robotics and Automation Letters and ICRA. Key recognitions include: Nomination for the best IROS paper award (2010) Open Source achievement award from Willow Garage (2010) Best paper award at the International Conference and Exhibition on Unmanned Areal Vehicles (2010) Best Paper award at ICRA 2009 (2009) His research is conducted through the RoCoCo lab at Sapienza University of Rome and the Autonomous Intelligent Systems Lab at Freiburg University, focusing on developing foundational algorithms for mobile robot autonomy. Current projects emphasize robust perception systems, optimization frameworks for sensor fusion, and practical implementations for real-world navigation challenges.

• Quantitative Finance
• Risk Management
• Operational Research
• +۶ مورد دیگر

Sandra Paterlini is a Full Professor in the Department of Economics and Management at the University of Trento, Italy. She holds academic roles including Co-Chair of the ERCIM Working Group on Optimization Heuristics and Vice-Chair of the IEEE Task Force on Portfolio Optimization. Her career includes visiting positions at institutions such as the University of Minnesota and Ludwig-Maximilians-Universität München. She earned a PhD in Computational Methods for Financial and Economic Decisions from the University of Bergamo, an MSc in Financial Mathematics from the University of Warwick, and a Laurea in Economics from the University of Modena and Reggio E. Her research focuses on quantitative finance, risk management, portfolio optimization, and network analysis, with applications to ESG, systemic risk, and financial stability. Key research contributions include methodologies for sparse graphical modeling, systemic risk analysis, and ESG scoring frameworks. She has received multiple awards for research excellence and serves on editorial boards of journals like Computational Statistics & Data Analysis and Frontiers in Applied Mathematics and Statistics . Her work bridges academia and policy, with contributions to the European Central Bank’s Financial Stability Directorate and involvement in global conferences on computational finance and econometrics.

Daniele Loiaconoمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۶ مورد دیگر

Daniele Loiacono is an Associate Professor at Politecnico di Milano's Department of Electronics, Information, and Bioengineering (DEIB), affiliated with the Artificial Intelligence and Robotics Lab (AIRLab). His research focuses on interdisciplinary applications of Artificial Intelligence, Machine Learning, and Deep Learning in medical imaging, radiation therapy, and procedural content generation for games. He leads projects in synthetic image generation for radiotherapy quality assurance, automated treatment planning, and bias analysis in medical AI systems. Key research areas include medical image synthesis using GANs, radiation therapy optimization, and algorithmic game design. His contributions span clinical applications such as total marrow irradiation (TMI) planning and lymph-node segmentation, alongside innovations in shader generation and interactive evolutionary tools for game development. Loiacono collaborates on multi-center studies to validate AI-driven workflows in healthcare and has pioneered methods combining lean Six Sigma with machine learning for treatment process improvement. His work bridges clinical medicine and computer science, addressing challenges in radiation oncology, anatomical imaging, and procedural content automation. The AIRLab serves as a hub for his research, integrating AI advancements into real-world medical and engineering solutions.

Vincent Lepetitمشاهده پروفایل

استاد پژوهشی

• Computer Vision
• 3D Computer Vision
• Machine Learning
• +۳ مورد دیگر

Vincent Lepetit currently serves as a Director of Research at École des Ponts ParisTech since 2019. His prior academic appointments include: Full Professor at the Institute for Computer Graphics and Vision, Graz University of Technology, Austria Senior Researcher at the Computer Vision Laboratory (CVLab) of École Polytechnique Fédérale de Lausanne (EPFL), Switzerland His research resides at the critical intersection of Machine Learning and 3D Computer Vision, with concentrated efforts on advancing 3D scene understanding from images. This work integrates deep learning methodologies with geometric computer vision to solve complex perception challenges, driving innovations in computational intelligence and visual recognition systems. His expertise spans both theoretical foundations and practical implementations across computer vision subdomains. Prof. Lepetit maintains significant leadership roles within the computer vision community, consistently serving as area chair for premier conferences including CVPR, ICCV, and ECCV. He further contributes through editorial positions as associate editor for top-tier journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), International Journal of Computer Vision (IJCV), and Computer Vision and Image Understanding (CVIU), shaping research standards across the field. No scientific awards or honors were explicitly documented in the provided source material. While the text confirms his past affiliation with EPFL's Computer Vision Laboratory (CVLab), current laboratory or team leadership details remain unspecified. Information regarding doctoral advisees, research grants, or funding mechanisms was not included in the available documentation, though his editorial and conference leadership roles indicate substantial research influence.

• Critical reading of drawing
• Descriptive geometry
• History of representation
• +۵ مورد دیگر

Ursula Zich is an Associate Professor at the Polytechnic of Turin's Department of Architecture and Design (DAD), where she serves as a member of the Student Discipline Commission. Born in Turin on July 16, 1969, she holds a Doctor of Architecture degree with highest honors from the Polytechnic of Turin (1994) and a Doctor of Research in Surveying and Representation of Architecture and the Environment from the University of Genoa. Her research interests focus on critical reading of drawing, descriptive geometry, history of representation, and physical models. She leads the MAG.IA (Mathematics, Architecture, Geometry. Application Interconnections) research line and the POLIMADE project exploring scientific applications of origami. Her work spans multiple ERC sectors including application of mathematics in sciences, computational modeling in cultural spheres, cultural studies, history of art and architecture, and museum studies. Zich has published extensively on architectural representation, with recent publications examining tangible geometries for inclusive game design, architectural heritage accessibility, and interdisciplinary approaches to architectural representation. Her research demonstrates consistent integration of mathematical principles with architectural representation techniques. Effective member of Study Group on Environmental Color Design (ECD) of the International Color Association (AIC), United States (2021-) Effective member of Italian Design Union (UID), Italy (2001-) She has served on the Program Committee for multiple Italian Conferences on Origami, Educational Dynamics and Teaching since 2014. Zich also co-invented a patent for a foldable aluminum foil food tray, demonstrating practical applications of her origami research. At the Polytechnic of Turin, she teaches architectural drawing, surveying, and geometric modeling courses across multiple academic years, maintaining an active teaching schedule through the 2025/26 academic year.

Valeria Bruschiمشاهده پروفایل

پژوهشگر

• Audio Engineering
• Signal Processing
• Spatial Audio
• +۵ مورد دیگر

Valeria Bruschi is a Researcher at the Department of Information Engineering (DII) within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. Her academic profile was last updated on April 13, 2024, and she maintains her office at the Engineering Faculty on via Brecce Bianche, with contact information including phone +39 071-220-4486 and email v.bruschi@staff.univpm.it. Dr. Bruschi's research spans multiple domains within audio and signal processing, with particular expertise in spatial audio systems, automotive human-computer interaction, and biomedical signal applications. Her work bridges theoretical signal processing techniques with practical implementations across diverse fields including automotive safety systems, hearing aid technology, sleep medicine, and agricultural monitoring. She has made significant contributions to head-related transfer function (HRTF) processing, real-time audio enhancement algorithms, and innovative monitoring systems that utilize acoustic signals for various applications. Analysis of Dr. Bruschi's recent publications reveals a strong trajectory in developing practical audio processing solutions with real-world applications. Her work shows increasing integration of machine learning techniques with traditional signal processing approaches, particularly in areas like driver monitoring systems, snoring detection and cancellation, and spatial audio rendering. A notable trend is her focus on creating lightweight, real-time implementations suitable for embedded systems and practical deployment scenarios, while maintaining high performance standards. Her research consistently demonstrates interdisciplinary collaboration, connecting audio engineering with fields as diverse as automotive safety, sleep medicine, and agricultural technology. Dr. Bruschi actively contributes to advancing audio engineering through her research on equalization techniques, noise reduction systems, and immersive audio technologies. Her work on pulse compression techniques for hearing aid distortion measurement represents an important contribution to audiological assessment methodologies. Her publication record demonstrates consistent scholarly output with increasing impact across multiple application domains, reflecting her ability to translate theoretical signal processing concepts into practical engineering solutions.

Simon Masnouمشاهده پروفایل

استاد

• Applied Mathematics
• Image Processing
• Shape Optimization
• +۵ مورد دیگر

Simon Masnou is a Full Professor at Université Claude Bernard Lyon 1, affiliated with the Institut Camille Jordan (CNRS UMR 5208). He holds leadership roles as Head of the 'Applied Mathematics, Statistics' Master's degree and Head of the 'M2 Maths in Action' program. Previously, he served as Director of the Camille Jordan Institute (2018-2022). His research focuses on applied mathematics, image processing, shape optimization, and geometric measure theory, with contributions to variational models, geometric flows, and applications in computer vision and materials science. Education: PhD in Mathematics (1998, Paris Dauphine) and HDR (2008, Paris 6). Research projects include ANR STOIQUES (2024-2028), PEPR PDE-AI (2023-2028), and collaborations with industry on topics like defect prediction in aluminum production and high-dimensional data analysis. Teaching includes courses on linear algebra, optimization, and machine learning at undergraduate and graduate levels. Key contributions span phase field models, varifold-based surface approximation, and image inpainting. He supervises PhD students in geometric variational problems and computational methods. His work bridges theoretical mathematics with industrial challenges, addressing issues in materials science, medical imaging, and cultural heritage preservation.

• 3D modeling
• Reconstructive modeling
• Augmented Reality (AR)
• +۱۲ مورد دیگر

Roberta Spallone is a Full Professor in the Department of Architecture and Design (DAD) at Politecnico di Torino, where she conducts research and teaches in architectural representation, digital modeling, and cultural heritage. Her work bridges historical architectural theory with cutting-edge digital technologies like AR, VR, and AI. Research Interests: Her research focuses on 3D and reconstructive modeling, augmented and virtual reality (AR/VR) for cultural heritage, descriptive geometry, history of architectural representation, and the study of architectural treatises—especially those on military engineering. She explores digital technologies for the survey, representation, and communication of cultural heritage, with a strong emphasis on geometric analysis and historical accuracy. The trends in her recent publications reflect a consistent focus on the digital interpretation of early modern military architecture, particularly through parametric modeling and geometric analysis of treatises by figures like Guarini. She applies AR and VR to enhance accessibility and storytelling in museum and urban heritage contexts, emphasizing inclusive and sustainable cultural tourism. Scientific Awards: Best paper award, Italian Union for Drawing - UID (2021) Best Paper, 40th International Conference of Teachers of Representation Disciplines UID (2018) Best paper, FORTMED Conference 2015 (Historical Research) UID Silver Plaque (1997) PhD 1st prize ex aequo, Italian Design Union (1997) Advising and Grants: She supervises PhD students including Enrico Pupi and Fabrizio Natta. She leads the national PRIN research project INFORTREAT and multiple applied research contracts involving AR/VR for heritage sites like Palazzo Carignano and Mirafiori Castle. She is the Scientific Responsible for collaborative agreements with Fondazione Torino Musei and the Regional Directorate of Museums in Piedmont. Labs, Teams, and Collaborations: She is a key member of the scientific committees of FORTMED, UID, and Nexus Architecture and Mathematics. She serves on editorial boards for journals such as Nexus Network Journal and Diseñar Con... , and has guest-edited special issues. She frequently collaborates with researchers across Europe on projects linking architecture, mathematics, and digital heritage.

• Artificial intelligence
• Data compression
• Deep learning
• +۱۵ مورد دیگر

Enrico Magli is a Full Professor at the Department of Electronics and Telecommunications (DET) at Polytechnic University of Turin, Italy. He serves as Director of the Image Processing and Learning group and Coordinator of the 'ICT for Smart Societies' M.Sc. degree program. Additionally, he is a committee member of the PhD program in Electrical, Electronic and Communications Engineering and a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. Professor Magli's research focuses on applying machine learning and deep learning methods to satellite imaging, with applications to onboard processing and image analysis on the ground. His work spans deep learning for image and video analysis, image and video compression, compressive sensing, satellite imaging, and graph signal processing. He has published over 90 journal papers with 5900+ citations and an h-index of 40 on Google Scholar. His recent publications demonstrate a strong focus on developing deep learning architectures for satellite image processing, particularly for onboard applications. His research addresses challenges in hyperspectral image compression, super-resolution, change detection, and efficient neural network architectures suitable for resource-constrained satellite environments. There's also significant work on secure authentication systems using deep learning techniques and neural network optimization for edge devices. Elevated to IEEE Fellow (2017) 'for contributions to compression and communication of remotely sensed imagery' IEEE Geoscience and Remote Sensing Society 2011 Transactions Prize Paper Award IEEE Multimedia 2019 Best Paper Award Best Paper Awards at IEEE ICIP (2015, 2019) ERC Starting grant (consolidator type) and ERC Proof-of-Concept Grant recipient Multiple Best Paper Awards Francesco Carassa (2011, 2013, 2014) Professor Magli actively supervises numerous PhD students working on cutting-edge topics in deep learning for satellite imaging, image processing, and secure authentication systems. His research is supported by significant grants including ERC projects and multiple commercial contracts with space agencies and technology companies. He leads the Image Processing and Learning (IPL) Group at Politecnico di Torino, which focuses on developing innovative solutions for satellite image analysis and compression.

• Machine Learning
• Data Mining
• Bioinformatics
• +۱۱ مورد دیگر

Andrea Passerini is a Full Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy, where he also serves as Coordinator of the PhD programme in Information Engineering and Computer Science (Ministerial Decree 45/2013). His academic footprint spans multiple departments including Mathematics, Sociology, Cellular Biology, and Industrial Engineering, reflecting deep interdisciplinary engagement across computational sciences and life sciences. His research centers on Machine Learning and Data Mining with specialized expertise in Neuro-Symbolic AI , Probabilistic Reasoning , and Statistical Relational Learning . He pioneers methods for graph-based learning, medical AI applications, and explainable systems, with significant contributions to bioinformatics (particularly RNA-protein interactions) and healthcare diagnostics. His work bridges theoretical rigor with practical implementations in critical domains. Analysis of his 2025 publications reveals dominant trends in neuro-symbolic integration for graph data, human-AI collaboration in medical decision-making, and robust recommender systems. His research increasingly focuses on interpretable AI for high-stakes applications like surgical planning and physician support, while advancing foundational techniques in graph neural networks and concept-based modeling. As PhD programme Coordinator, Professor Passerini mentors doctoral candidates across AI and computer science disciplines. His collaborative network extends to medical researchers at CIBIO (Cellular, Computational and Integrative Biology department) and industrial partners, though specific lab structures aren't documented in available materials. Current projects emphasize medical AI validation, temporal network modeling, and LLM integration with structured reasoning frameworks.

• Human-Centered Systems
• Human-Computer Interaction
• Artificial Intelligence
• +۹ مورد دیگر

Alessio Malizia is a Professor of User Experience Design at the University of Hertfordshire, UK, and concurrently holds a full Professorship at the Computer Science Department of the University of Pisa, Italy. His research focuses on Human-Centered Systems, Human-Centered AI, and Design Fictions, emphasizing ethical AI, user participation, and the integration of visual programming languages. He has held roles at institutions including Sapienza University of Rome, IBM, Silicon Graphics, and Xerox PARC, where he researched neural networks and gestural interfaces. His work bridges academia and industry, addressing challenges in healthcare, agriculture, and education. Malizia’s career includes visiting research at Xerox PARC, associate professorship at the University Carlos III of Madrid, and senior lecturer roles at Brunel University London. He is an ACM Distinguished Speaker and actively promotes democratizing AI through tools like BlocklyBias and PyFlowML. His research spans touchless interfaces, collaborative design methodologies, and AI explainability. Key contributions include frameworks for socio-technical process modeling in agriculture, tools for bias detection in AI data, and visual languages fostering user participation in ML systems. His work on telemedicine and healthcare AI emphasizes co-design and trusted AI systems. Recent studies explore end-user development for smart environments, digital agriculture, and computational thinking education through tools like TAPASPlay. Awards: ACM Distinguished Speaker Key Interests: Human-AI Interaction, UX Design, AI Ethics, IoT Ecosystems, and Co-Creation Methodologies Notable Projects: Figmant, ModeLLer, and the Chatbot Usability Scale validation His grants and collaborations focus on improving AI transparency, user-centered design processes, and participatory innovation in technology adoption across sectors.

• Artificial Intelligence
• Extended Reality
• Computer Science
• +۳ مورد دیگر

Pasquale Cascarano is a fixed-term Assistant Professor at the University of Bologna , affiliated with the Department of the Arts . His research bridges computer science with creative industries (cinema, art, fashion) and biomedical applications, focusing on Artificial Intelligence and Extended Reality paradigms. He collaborates with national and international institutions on interdisciplinary projects. Institutional Affiliation: University of Bologna Academic Role: Assistant Professor (fixed-term) Research Interests center on integrating AI and XR into creative sectors and healthcare, with emphasis on: Generative AI for immersive environments Medical imaging and diagnostics Digital heritage preservation XR-based educational tools 3D visualization techniques Creative technology applications Recent Publications highlight trends in: Medical XR for surgical training AI-driven image restoration LLM integration with AR/VR Privacy in collaborative AR Fashion and cultural heritage digitization Deep learning for video enhancement

Simone Paolo Ponzettoمشاهده پروفایل

استادیار

• Knowledge acquisition
• Natural Language Processing
• Semantic Web technologies
• +۵ مورد دیگر

Simone Paolo Ponzetto is an Assistant Professor (Juniorprofessor) at the University of Mannheim since 2013, affiliated with the Research Group Data and Web Science. His research focuses on Semantic Web technologies, Natural Language Processing (NLP), and knowledge acquisition, particularly leveraging collaboratively built resources like Wikipedia. Prior to Mannheim, he held postdoctoral roles at Sapienza University of Rome and research positions at the University of Heidelberg and Stuttgart. His work includes pioneering projects like BabelNet, a multilingual semantic network. Ponzetto earned his PhD in Computational Linguistics from the University of Stuttgart, with interdisciplinary contributions to coreference resolution, semantic relatedness, and ontology learning. Research Interests: Unsupervised/weakly-supervised knowledge extraction Multilingual ontology learning and semantic networks Lexical semantics (word sense disambiguation, semantic similarity) Discourse semantics (coreference resolution, coherence modeling) Professional Contributions: Guest editor for a Artificial Intelligence Journal special issue on AI and Wikipedia Area chair for EMNLP-CoNLL 2012 and EACL 2014 Program committee member for ACL, AAAI, and other top conferences Lab/Team: Active in the Research Group Data and Web Science at Mannheim, advancing AI and NLP applications in collaborative knowledge systems.