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Valery VishnevskiyView profile

Lecturer

• Biomedical Imaging
• Magnetic Resonance Imaging (MRI)
• Ultrasound Imaging
• +3 more

Dr. Valery Vishnevskiy is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich , affiliated with the Biomedical Imaging Group . His research focuses on advanced medical imaging techniques, particularly in cardiac MRI , ultrasound , and machine learning applications . He contributes to projects involving 4D flow MRI reconstruction , speed-of-sound imaging , and motion-corrected diffusion tensor analysis . Primary Affiliation : ETH Zürich, Department of Information Technology and Electrical Engineering Research Interests : Biomedical Imaging, MRI Reconstruction, Ultrasound Physics, Cardiac Imaging, Deep Learning His recent work emphasizes self-supervised learning for medical imaging, including the development of FlowMRI-Net for accelerated 4D flow MRI and Speed-of-Sound Imaging using diverging waves. Publications span hyperpolarized 13C metabolic imaging , viscoelasticity reconstruction , and probabilistic sampling optimization . Dr. Vishnevskiy's contributions to deformable image registration include methods for handling sliding interfaces in abdominal and cardiac imaging, with applications in respiratory motion compensation and tissue ablation monitoring . He also explores mathematical models for enzyme activity analysis and behavioral pattern detection.

• Neuroinformatics
• Animal Behavior
• Machine Learning
• +3 more

Dr. Anja Zai is a Researcher affiliated with the Department of Neuroinformatics at ETH Zürich. Her work focuses on interdisciplinary investigations of vocal motor control, neuroethology, and computational methods in animal behavior. She specializes in studying songbirds as model systems to explore sensory-motor integration, reinforcement learning, and acoustic communication. Her research integrates advanced imaging techniques (e.g., synchrotron X-ray CT), machine learning, and experimental setups like the RecOOrder modular recording environment. Key research themes include vocal learning mechanisms in zebra finches, environmental influences on vocal behavior, and neuroprosthetic applications through sensory substitution. Her studies address fundamental questions about how organisms adapt vocalizations under sensory deprivation, optimize motor exploration, and encode complex vocal repertoires. Recent work emphasizes multimodal sound source separation (Vib2Sound) and algorithmic modeling of vocal planning processes. Dr. Zai’s methodological contributions include benchmarking datasets for vocalization analysis and tools for non-invasive welfare monitoring in isolated animals. While no scientific awards are explicitly listed, her frequent publication in high-impact journals since 2015 indicates sustained research excellence. Her work bridges computational neuroscience, behavioral ecology, and engineering through cross-disciplinary approaches.

• Semantic Web
• Knowledge Graphs
• Linked Data
• +3 more

Mohamed Ahmed Sherif is an academic affiliated with Paderborn University's Department of Computer Science and the University of Leipzig's Institute of Computer Science. His primary research focuses on semantic web technologies, knowledge graph integration, and machine learning applications in data integration. Key affiliations: Paderborn University, University of Leipzig Specialization: Link discovery, knowledge graph construction, semantic web standards His work emphasizes scalable methods for linking heterogeneous data sources, explainable AI techniques for knowledge integration, and geospatial semantic technologies. Recent contributions include the ANTS system for entity summarization in knowledge graphs and the NELLIE framework for continuous linked data integration. Notable projects include LIMES - a widely-used link discovery framework - and contributions to the HOBBIT benchmarking platform. His research has been applied in disaster management (I-AID system), Quran semantification, and global health data integration.

• Augmented reality
• Computer graphics
• Extended reality
• +4 more

Davide Calandra is a Fixed-term Researcher at the Department of Control and Computer Science (DAUIN) within the College of Computer, Film, and Mechatronics Engineering at Politecnico di Torino. He holds expertise in Information Processing Systems (IINF-05/A) and focuses on computer graphics, human-computer interaction, and virtual reality applications. His research spans augmented reality, extended reality, mixed reality, and virtual reality with applications in healthcare, education, emergency response, and cultural heritage preservation. Calandra's work addresses fundamental challenges in human-robot interaction, social VR experiences, and XR-based training systems. His research contributes to multiple UN Sustainable Development Goals including Good Health and Well-being, Quality Education, Industry Innovation and Infrastructure, Sustainable Cities and Communities, and Life on Land. Analysis of his recent publications reveals a consistent focus on practical applications of VR/AR technologies, particularly in social interaction enhancement, emergency response training, cultural heritage preservation, and rehabilitation. His work demonstrates a strong interdisciplinary approach, bridging computer science with practical applications in diverse fields. Calandra actively contributes to the GRAINS - GRAphics and INtelligent Systems research group and the VR@POLITO laboratory, where he develops cutting-edge XR technologies and applications. As an educator, he teaches across multiple programs including PhD courses in Information Visualization and Visual Analytics, Master's courses in Generative Artificial Intelligence for Graphics and Multimedia, and various undergraduate courses in databases and information systems. His teaching spans multiple engineering disciplines including Computer Engineering, Aerospace Engineering, and Engineering and Management. His notable project includes the Augmented Sand Table for Forest Firefighting, which demonstrates his commitment to applying XR technologies to real-world emergency response scenarios.

• Enterprise Modeling
• Cybersecurity
• Multi-Level Modeling
• +5 more

Manfred Jeusfeld is a Professor of Information Technology at the University of Skövde's School of Informatics, Department of Information Technology. He specializes in enterprise modeling, cybersecurity, multi-level modeling, and critical infrastructure protection. His research integrates formal methodologies with practical applications in domains like product lifecycle management and data warehouse architecture. Research Interests: Multi-Level Modeling (formal semantics, tool implementation) Cybersecurity in Critical Infrastructures (model-based analysis, vulnerability assessment) Conceptual Modeling Methodologies (enterprise architecture, ontological frameworks) Product Lifecycle Management (virtual factories, extended PLM systems) Key Projects: Leading the Virtual Factories of the Future (VF-KDO) research profile (2018–2026) ELVIRA project (EU ISF-funded cybersecurity analysis for smart grids) OMI project (teaching enterprise modeling tools for European education) Publications: Recent work emphasizes systematic literature reviews in cybersecurity modeling, formal verification of multi-level systems, and tool contributions like DeepTelos for ConceptBase. His work bridges theoretical model development with real-world applications in critical infrastructure protection.

Lena LiepeView profile

Professor

• Medieval Art History
• Nordic Visual Culture
• Relics and Reliquaries
• +4 more

Lena Liepe is a Professor of Art and Visual Studies at Linnaeus University, affiliated with the Faculty of Arts and Humanities and the Department of Music and Art. She specializes in Nordic medieval art, visual culture, and the historiography of medieval art history. Her research focuses on methodological approaches to medieval artifacts, the public display of ecclesiastical heritage, and the role of relics in medieval Nordic spirituality. Key projects include the six-year research program 'At the End of the World' (2023–2028), exploring apocalyptic imagery, and a digital humanities project mapping medieval saints’ cults. She is also involved in the Centre for Applied Heritage and Medeltidsforum Linné. Her work bridges art history with material culture, emphasizing interdisciplinary and transdisciplinary methods. Liepe has authored monographs on topics such as medieval wood sculpture, stone churches, and relic use. Her awards include the Wallquistpriset (2020) and Gad Rausings pris (2019). She actively contributes to academic networks like ICMA and serves on editorial boards, including the journal Iconographisk Post . Her teaching includes Western art history courses and supervision of student projects. Current research interests include spatiality of sacred spaces and renewing art historical methodologies through world art history paradigms.

• Computational Biology
• Structural Biology
• Protein Structure Prediction
• +3 more

Andrej Sali, PhD, is a Professor of Bioengineering at the University of California, San Francisco (UCSF), affiliated with the School of Pharmacy. His research focuses on computational methods to study protein structure and function, including predicting protein structures, analyzing macromolecular assemblies, and annotating protein functions using structural data. This work bridges genomics and medicine, enhancing the impact of structural and functional genomics. Research Interests: Dr. Sali integrates physics-based computational models and evolutionary principles to address fundamental questions in structural biology. His lab develops methods for protein structure prediction, structural genomics, and modeling dynamic biological processes. Key areas include nuclear pore complex assembly, molecular mechanisms of transporters, and integrative modeling platforms like the Integrative Modeling Platform (IMP). Grants & Funding: He has led/co-investigated numerous NIH-funded projects, including: NIH S10OD021596 (2016-2017) for high-performance computing infrastructure NIH P01GM111126 (2015-2020) on transmembrane transporter conformational cycles NIH P41RR001081 (1976-2012) for Biocomputing resources Awards & Honors: Recognized with prestigious awards such as the Zois Award (2000-2003), Irma T. Hirschl Career Award (1998-2000), and election to the National Academy of Sciences (2018). His work has been supported by grants from the Jane Coffin Childs Memorial Fund and Merck Sharp & Dohm. Labs & Teams: Leads the Sali Lab at UCSF, collaborating on cutting-edge projects such as nuclear pore complex dynamics, drug resistance mechanisms, and structural modeling of biomolecular systems.

Guy De TréView profile

Associate Professor

• Computational Intelligence
• Data Quality
• Decision Support Systems
• +7 more

Guy De Tré is an Associate Professor at the Department of Telecommunications and Information Processing within Ghent University's Faculty of Engineering and Architecture. He leads the Database, Document and Content Management (DDCM) research group and focuses on computational intelligence in information systems, with expertise in bi-polarity handling, uncertainty modeling, and multi-valued logic systems. Primary Affiliation: Ghent University Research Focus: Data quality, fuzzy querying, spatio-temporal modeling Key Contributions: Foundational work in possibilistic databases and explainable AI His research combines theoretical and applied approaches to information management systems. Theoretical work includes: Bipolarity and uncertainty handling in databases Multi-valued logic frameworks Interval B-tree indexing for possibilistic data Applied research spans: NoSQL database optimization Decision support systems Contextualized machine learning 3D/4D modeling for geological resources Recent publications show increasing focus on explainable AI, with multiple works on contextualized support vector machine classification and orthographic similarity measures for graph-based data representations. His work bridges database theory with practical applications in data quality assessment, medical informatics, and cultural heritage projects like the Byzantine Book Epigrams database. Research Group: Leads the DDCM group at Ghent University, specializing in: Database management innovation Content modeling techniques Fuzzy logic implementations Temporal data indexing Intelligent information systems

Laura Sánchez GómezView profile

Associate Professor

• Literary Education
• Children's and Young Adult Literature
• Electronic Literature in Spanish
• +2 more

Laura Sánchez Gómez is an Associate Professor in the Department of Language and Arts Didactics at the Faculty of Education of Complutense University of Madrid. She combines academic roles with cultural management, focusing on Digital Humanities, Electronic Literature, and Literary Education. Her research explores digital transformations in literature and culture, particularly through the LEETHI research group. She holds a PhD Cum Laude in Literary Studies and has received a 2021-2022 Research Fellowship from the Electronic Literature Organization. Education: PhD in Literary Studies (Cum Laude), specialized in Electronic Literature in Spanish. Research Projects (Last 10 Years): 2021-present: Member of the Sciences + Letters = CLAP project (FCT-20-15816). 2021: Collaborator on Mnemosine: Digital History of the Other Silver Age (RTI2018-095522-B-I00). 2016-19: Support for eLITE-CM, Electronic Literary Edition (H2015/HUM-3426). Teaching: Teaches Language and Literature Didactics, Electronic Literature in the UCM Master's program, and Digital Humanities at Nebrija University. Cultural Management: Curated exhibitions like Lorem BITsum: Electronic Literature (2018) and collaborated on projects at the Instituto Cervantes. Co-founder of the Ciberia Project, a digital literature platform. Awards: Electronic Literature Organization Research Fellowship (2021-2022). EmprendeLibro Scholarship (Factoría Cultural, Matadero Madrid). Labs/Teams: Active in LEETHI (Spanish and European Literatures from Text to Hypermedia) and Ciberia Project.

• Contemporary Theatre
• Digital Humanities
• International Cultural Policy
• +4 more

Assoc. Professor Margaret Hamilton is an Associate Professor and Discipline Leader in Performance and Theatre at the School of the Arts, English and Media, University of Wollongong. She holds leadership roles including Head of Postgraduate Studies (2023–present) and has extensive experience in arts policy development and cultural diplomacy. Her research focuses on contemporary theatre in Australia and Europe, particularly exploring neoliberalism’s impact on artistic critique. Hamilton’s work includes contributions to the UNESCO-recognized AusStage database and authorship of Transfigured Stages (2011). She has held roles at the Australian Embassy in Berlin, managing arts diplomacy programs, and collaborated with major European institutions like the Hebbel Theater and Berliner Festspiele. Education: PhD (2006) from the University of New South Wales under Prof. Hans-Thies Lehmann, renowned for her thesis on postdramatic theatre in Australia. Research interests span digital humanities, international cultural policy, and postdramatic theatre aesthetics. She has secured ARC grants for AusStage development and led projects on Robert Wilson’s aesthetic innovations. Awards include the Marlis Thiersch Prize (2019) and UNESCO recognition for AusStage (2021). Her teaching focuses on contemporary theatre theory and practice, with courses like Contemporary Theatre & Text and Theatre, Politics & Spectatorship . Hamilton supervises PhD students in topics ranging from AI ethics in performance to meat culture critiques. Key grants include ARC Linkage Infrastructure grants for AusStage phases 5–7 (2014–2023) and a Small Grant on Robert Wilson’s Watermill Centre (2007). Labs/Teams: AusStage Management Committee member, contributing to live performance data infrastructure. Active in international theatre networks including the International Federation of Theatre Research.

Bernard Dionysius GeogheganView profile

Associate Professor

• History and theory of digital media
• Cybernetics and its influence on humanities
• German media theory
• +6 more

Bernard Dionysius Geoghegan serves as a Reader in the History and Theory of Digital Media within the Department of Digital Humanities at King's College London's Faculty of Arts & Humanities. He earned a binational Ph.D. from Northwestern University and Bauhaus University Weimar, with academic qualifications in Medienwissenschaft and Screen Cultures. His research portfolio spans several prestigious institutions where he has taught, including Yale University, Coventry University, Humboldt University of Berlin, and the American University of Paris. Geoghegan's research interests form a rich tapestry exploring how digital technologies shape science, culture, and environment. His work investigates the historical intersections between cybernetics and humanities, German media theory, critical histories of media interactivity, ethnicity in AI histories, and the complex relationship between new media and occult practices. He examines how anxiety and vigilance shape networked communications, the political origins of interactive digital interfaces, and how cybernetics influenced fields like French theory and family therapy. His publications reveal a consistent focus on the material and historical dimensions of digital media, with recent works exploring statistical discourse ordering, orientalism in informatics, and the ecological operations behind computer screen development. Geoghegan's scholarship bridges theoretical frameworks from media studies, history of science, and critical theory, revealing how information technologies encode cultural, political, and social structures. Forestscapes: cocreating immersive soundscapes for more diverse, interdisciplinary and participatory environmental research and interventions (2023) Organising participation with air pollution data (2019) As an educator, Geoghegan teaches courses in the history and theory of digital media, science and technology studies (STS), and critical media practice. His expertise extends to media curation, particularly through his role as Co-Curator of the Technosphere Project at Haus der Kulturen der Welt, where he develops educational programming around the Anthropocene and screen cultures. His approach integrates theoretical scholarship with practical engagement in digital environments and media arts.

• Structural Biology
• Membrane Proteins
• Computational Biology
• +3 more

Judith Klein-Seetharaman is a Professor at Arizona State University (ASU), jointly appointed in the School of Molecular Sciences and the College of Health Solutions. Her research integrates computational and experimental approaches to study protein structure, dynamics, and function, with a focus on membrane proteins and their roles in health and disease. Education: PhD from MIT, advised by Nobel Laureate Har Gobind Khorana, studying rhodopsin conformational changes. Undergraduate degrees in Biology and Chemistry from the University of Cologne, Germany. Research Interests: Her work spans structural biology, computational modeling, and systems biology. Key areas include: Membrane protein dynamics, particularly GPCRs and insulin receptors. Environmental and biomedical applications, such as coral microbiome resilience and asphalt toxicity. Protein interactions and drug discovery, including SARS-CoV-2 human interactome studies. Articles Trends: Recent work highlights interdisciplinary projects, such as coral signaling pathways, neurotoxic effects of asphalt emissions, and ferroptosis suppression mechanisms. These studies leverage structural biology, bioinformatics, and systems-level analyses to address complex biological questions. Awards: NSF CAREER Award for integrating teaching and research on membrane receptor evolution. Margaret Oakley Dayhoff Award for computational biology contributions. Bill and Melinda Gates Foundation Grant for HIV drug target discovery. Advising & Grants: Mentored over 20 graduate students, including interdisciplinary projects in computational biology and biophysics. Active in industry collaborations, including CEO roles in Sarkar-Klein-Labs LLC and Neosensations LLC. Labs/Teams: Leads research groups in structural discovery and health solutions, collaborating with institutions like the Biodesign Center for Applied Structural Discovery and the Arizona Alzheimer's Consortium.

• Neurodevelopmental Disorders
• Synaptic Plasticity
• Neurodegenerative Diseases
• +3 more

Marcelo Pablo Coba, PhD, is an Associate Professor in the Department of Psychiatry and the Behavioral Sciences at the University of Southern California. His research employs systems biology to investigate neurodevelopmental and neurodegenerative disorders, focusing on synaptic protein networks and signaling pathways. He integrates proteomics, CRISPR, hiPSC-derived models, and computational approaches to dissect mechanisms underlying schizophrenia, autism, and Alzheimer's disease. Research Interests: Dr. Coba's work centers on: Synaptic plasticity and post-synaptic density complexes Functional genomics of neurodevelopmental disorders Multi-omics profiling of synaptic dysfunction Protein interaction networks in psychiatric diseases hiPSC and organoid models of brain disorders His recent publications (2017–2025) emphasize synaptic biology, neurogenomics, and the development of experimental models. A consistent theme is the integration of proteomic data with genetic and functional analyses to map disease pathways in disorders like schizophrenia and autism. Key methodological advances include organoid technology, phosphoproteomics, and CRISPR-based functional screens. Dr. Coba leads a laboratory specializing in proteomic assays, mouse genetics, and hiPSC technology. The team focuses on defining spatiotemporal protein networks to stratify brain disorders by molecular signatures and genotype-phenotype relationships.

Åsmund FlobakView profile

Associate Professor

• Systems Medicine
• Drug Synergy Prediction
• Cancer Research
• +3 more

Åsmund Flobak is an Associate Professor at the Norwegian University of Science and Technology, where he leads the FlobakLab and serves as Principal Investigator for the IMPRESS-Norway clinical trial. His research integrates wet-lab experiments and computational modeling to predict drug responses in cancer. Education includes: Medical Doctor (2005) MSc Nanotechnology (2013) PhD in Systems Medicine (2016) His research focuses on systems medicine approaches to cancer treatment, developing the DrugLogics pipeline for drug synergy prediction. Work combines logical modeling of signaling networks with high-throughput drug screening in patient-derived cells. Publications demonstrate consistent focus on computational oncology, with themes including: Boolean network modeling of drug interactions High-throughput combination screening platforms Nanotechnology applications in drug delivery Awards and Honors: Medical Teaching Award, Norwegian Medical Association (2024) Lecturer of the Year, NTNU Medical Students (2019, 2023) Current projects include: PRESORT (RCN-funded drug response prediction) OncoLogics (EU PerMed consortium) COLOGIC (3D patient-derived tumor models) Lab comprises 5 PhD candidates and postdoctoral researchers investigating precision oncology approaches.

• Pattern Recognition
• Applied Machine Learning
• Document Analysis
• +7 more

Fischer Andreas is a Professor at HES-SO (University of Applied Sciences and Arts Western Switzerland) , specifically affiliated with the School of Engineering and Architecture of Fribourg (HEIA-FR) . His research spans Pattern Recognition , Applied Machine Learning , Handwriting Recognition , and Graph-based Methods . He has secured significant grants from TAINA Technology , Swisscom , and the Hasler Foundation for projects including automatic handwriting recognition for tax forms , Swiss German translation , and graph-based keyword spotting in Vietnamese steles . Education : BSc in Computer Science from HEIA-FR. Research Highlights : Graph Neural Networks for Büchi automata classification Annotation-free alignment in historical documents Graph edit distance optimization for keyword spotting Hybrid deep learning for Vietnamese stele analysis Graph-based tumor budding analysis in digital pathology Collaborative Impact : Fischer's work bridges historical document analysis and medical imaging , demonstrated through frameworks like DIVA-DAF and tools like GammaFocus for histopathology. His 2024 conferences suggest ongoing exploration of LLM integration in document processing and OCR-free models for information extraction.