جست‌وجوی استاد و پژوهشگر

Paul Ruvoloمشاهده پروفایل

استاد

• Machine Learning
• Robotics
• Computer Vision
• +۳ مورد دیگر

Dr. Paul Ruvolo is a Professor of Computer Science at Olin College in Needham, MA. His research focuses on developing assistive technologies for people with sensory and motor impairments, leveraging machine learning, robotics, and computer vision. He holds a Ph.D. and M.S. in Computer Science and Engineering from the University of California San Diego, and a B.S. in Computer Science from Harvey Mudd College. Key research areas include creating systems that learn through imitation and experience, such as navigation aids for the visually impaired and educational tools for orientation and mobility. He leads projects like Co-Designing Assistive Apps with Students Who Are Blind, emphasizing participatory design. His work integrates Bayesian statistics, numerical optimization, and linear algebra to solve complex sensorimotor tasks. Education: Ph.D., Computer Science and Engineering, UC San Diego M.S., Computer Science and Engineering, UC San Diego B.S., Computer Science, Harvey Mudd College Awards: NSF IGERT Fellowship for 'Learning and Vision in Humans and Machines' Recent publications highlight innovations in AR navigation systems, smartphone-based SLAM for indoor environments, and educational tools for blind users. His work bridges computational methods with real-world accessibility challenges, emphasizing interdisciplinary collaboration and user-centric design. Dr. Ruvolo’s lab, linked at occam.olin.edu , focuses on assistive technologies. He actively contributes to Teach Access and other initiatives promoting inclusive technology education. His research has applications in robotics, healthcare, and educational technology.

• French Music
• Opera Studies
• Musicology
• +۳ مورد دیگر

Professor Richard Langham Smith is a distinguished academic at the Royal College of Music (RCM), holding the title of Professor in Academic Programmes and serving as a Doctoral Supervisor. He specializes in French music, with a focus on 19th- and early 20th-century composers such as Bizet, Debussy, and Poulenc. His research explores opera, musical analysis, and cultural history, culminating in notable works like Bizet's Carmen Uncovered (2021) and co-editing Carmen Abroad (2020), which won an award for outstanding edited collection. Education: Shene Grammar School, University of York, and Amsterdam Conservatoire. Awards include the Chevalier de l'ordre des arts et des lettres (1994) and the RMA/Cambridge Book Prize (2021). He supervises doctoral students researching topics such as masculinity in Belle Époque opera, Fauré's violin works, and Sarasate's legacy. His work bridges historical analysis with performance practice, often engaging interdisciplinary methods. Publications span monographs, edited volumes, and articles in journals like Cambridge Opera Journal and Nineteenth-Century Music Review . He contributes actively to the RCM's research initiatives, fostering academic and creative excellence in musicology.

Ernesto Jiménez-Ruizمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Knowledge Graphs
• Semantic Web Technologies
• +۵ مورد دیگر

Dr. Ernesto Jiménez-Ruiz is a Senior Lecturer in Artificial Intelligence and Director of Research at City, University of London. He holds a PhD from Jaume I University, Spain (2010), and has held academic positions since 2010. His research focuses on knowledge graphs, ontology alignment, semantic web technologies, and neuro-symbolic AI. Currently, he teaches modules on semantic web technologies and research methods. He leads the Research Center affiliated with City St George's, University of London. Administrative Roles: Director of Research (2024–present), Senior Tutor for Research (2023–2024) Research Interests: AI, knowledge representation, ontology alignment, semantic integration, and biomedical informatics. His work bridges machine learning and symbolic reasoning, with contributions to ontology matching and knowledge graph embeddings. He supervises PhD students in areas like knowledge graph alignment and neuro-symbolic systems. Awards: SWSA Ten-Year Award (2021) for influential ontology alignment work. He is a Fellow of AdvanceHE (FHEA). Grants & Collaborations: Leads projects on semantic industrial data modeling and collaborates with Samsung Research UK, Bosch, and Statoil. Active in initiatives like the Turing Institute's Knowledge Graph Interest Group.

Gianluca LIGIمشاهده پروفایل

دانشیار

• Anthropology
• Scandinavian Ethnography
• Risk Perception
• +۳ مورد دیگر

Gianluca LIGI is an Associate Professor at the Department of Humanities at Ca' Foscari University of Venice, specializing in Cultural Anthropology. His research focuses on Scandinavian ethnography, risk perception, and landscape anthropology. He has authored numerous books and articles on topics such as Sami culture, disaster anthropology, and cultural vulnerability. His academic career includes significant contributions to understanding the cultural dimensions of risk, particularly in Arctic regions. Key projects include studies on Sami shamanism, Lapponian domestic architecture, and the symbolic systems of indigenous communities. His work bridges anthropology with environmental studies, emphasizing socio-cultural aspects of natural phenomena. Recent publications include Spazio Scienze umane 2 (2024) and Il tramonto più lungo di un giorno (2022), exploring cultural narratives and Scandinavian anthropology. He has also curated volumes on interdisciplinary research and edited collections on Sami cultural practices. Research grants include a MIUR-funded project on territorial identity in Anatolia and the Transcaucasus. His work is published in journals like La Ricerca Folklorica and RISKELABORATION , and he participates in editorial boards for anthropological series such as 'Lo Scudo di Achille.'

• Business Process Management
• Process Mining
• Process Analytics
• +۴ مورد دیگر

Hajo A. Reijers is a Professor at the University of Utrecht, Netherlands, with a former affiliation at Vrije Universiteit Amsterdam. His research focuses on Business Process Management (BPM), Process Mining, and Robotic Process Automation (RPA), emphasizing practical applications in healthcare, organizational processes, and human-computer interaction. He contributes to developing tools like SWORD for detecting workarounds and DEUCE for auditing electronic health records. His work spans algorithm development for process discovery, predictive analytics, and optimization techniques. Key areas include analyzing event logs, modeling workplace behavior, and enhancing process transparency. Reijers collaborates extensively with industry partners, addressing challenges in process automation, employee acceptance of AI, and ethical monitoring. His contributions to conferences like BPM, CAiSE, and ICIS highlight interdisciplinary approaches, combining computer science with organizational studies. Notable projects include frameworks for task mining, reinforcement learning in care processes, and pattern recognition in government transparency assessments. Research initiatives often involve cross-disciplinary teams, exploring topics like workplace well-being through process mining, decision-making support systems, and overcoming barriers to BPM adoption. His work bridges theoretical advancements with real-world impact, influencing both academic discourse and practical business solutions.

Hailey Austinمشاهده پروفایل

مدرس

• Comics Studies
• Video Game Design
• Creative Industries
• +۴ مورد دیگر

Dr. Hailey Austin is a Lecturer in Visual Media and Culture at Abertay University's Department of Games and Arts, part of the Faculty of Design, Informatics and Business. Her research focuses on comics, video games, and transnational creative industries, with particular emphasis on gender representation and cultural exchange between China and the UK. She holds a PhD in English from the University of Dundee (2021) and has conducted extensive research through projects like the InGAME International initiative. Education: B.A. English & Spanish (Creighton University, 2016); M.Litt Comics & Graphic Novels (University of Dundee, 2017); PhD English (University of Dundee, 2021). Research Interests: Comics studies, feminist media analysis, transmedia storytelling, digital humanities, and the global game development industry. She has authored over 30 publications including peer-reviewed articles, conference proceedings, and creative works like comic-based research outputs. Awards: 2022 Scottish Funding Council People's Choice Award for Public Engagement; 2017 Grant Morrison Prize for Comics Studies. Grants: Secured £10k+ in funding from AHRC, SGSAH, SFC, and other bodies. Current roles include Co-Investigator on InGAME International (until Jan 2024) and editorial work for journals like Journal of Gaming & Virtual Worlds . Creative Work: Author of educational comics for film noir courses, public information campaigns, and scripts for DC Thomson titles (e.g., Commando ). Her PhD research produced a series of comics analyzing anthropomorphic bodies in genre works.

Laura M Westhoffمشاهده پروفایل

استاد

• History of Post-Civil War American Women
• American History
• Education Curriculum Design
• +۸ مورد دیگر

Laura M Westhoff is a Professor of History and Education at the University of Missouri–St. Louis (UMSL), holding a joint appointment in the College of Education and the Department of History. She specializes in Gilded Age/Progressive Era history, democratic education, and the Scholarship of Teaching and Learning (SoTL). Her work bridges historical scholarship with pedagogical innovation, emphasizing how historical knowledge shapes democratic practices and education systems. Westhoff earned her Ph.D. in U.S. History from Washington University in St. Louis. Her research focuses on social movements, education reform, and the intersection of expertise and democracy. Notable works include her book *A Fatal Drifting Apart: Democratic Social Knowledge and Chicago Reform* (2007) and her current project on mid-20th century democratic practices. Research Interests: Post-Civil War American women’s history Curriculum design for history education Social justice and political culture Teaching American History methodologies Westhoff has led five major grants, including projects funded by the U.S. Department of Education and the National Endowment for the Humanities. Her work emphasizes teacher training, social studies certification, and innovative programs like the Student Teaching in China initiative. She regularly presents at national workshops and co-authored several Teaching American History grants. Key Projects: Historical Perspectives on American Democracy (2005–2008) St. Louis In-Gear for Success (2005–2011) Virtual City Project (2001–2004) Her research output spans articles in journals like *The Journal of American History* and books exploring historical pedagogy. Westhoff is a vocal advocate for integrating historical thinking into K-12 education and advancing democratic citizenship through curriculum innovation.

Yasmeen Georgeمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Medical Image Analysis
• +۶ مورد دیگر

Yasmeen George is a Senior Lecturer in the Department of Data Science & AI at Monash University's Faculty of Information Technology. She holds a PhD in Medical Image Processing from the University of Melbourne (2018) and a Master's in Computer Science from the University of Ain Shams (2013). Her research focuses on AI applications in healthcare, particularly medical image analysis for conditions like cancer, glaucoma, and psoriasis. She co-founded the AIM for Health Lab at Monash IT and is a research affiliate at the Victorian Institute of Forensic Medicine. Education: PhD (Medical Image Processing), University of Melbourne (2018); Master of Computer Science (Medical Image Analytics), University of Ain Shams (2013). Research interests include AI-driven medical image analysis, machine learning, and cross-domain healthcare analytics in radiology, dermatology, and ophthalmology. Her work addresses challenges in automated disease detection, lesion segmentation, and severity assessment across modalities like 2D/3D imaging and text data. Recent articles focus on kidney segmentation, glaucoma detection, federated learning for breast cancer, and AI frameworks for hazardous waste policy. Her research has led to patents with IBM and grants from MRFF and NHMRC. Awards: Recipient of the 2023 Heidelberg Laureate Foundation Alumni Award. Collaborations include projects on clean energy sustainability and hazardous waste management through advanced AI techniques. She actively advises PhD students and engages in interdisciplinary research teams across Monash and industry partners. Labs/Teams: Co-founder of the AIM for Health Lab, affiliated with the Victorian Institute of Forensic Medicine.

• Security of Deep Learning Systems
• Side-Channel Attacks
• Privacy-Preserving Machine Learning
• +۳ مورد دیگر

Dr. Yuanyuan Yuan is a Researcher at the Department of Computer Science, ETH Zurich, Switzerland, based at CNB H 104.1, Universitätstrasse 6, 8092 Zurich. Her work bridges computer security and machine learning with a focus on practical vulnerabilities in deployed AI systems. Her research centers on exposing and mitigating security flaws in deep learning deployments, particularly targeting trusted execution environments (TEEs) and on-device inference systems. Key contributions include pioneering side-channel attacks against TEE-shielded neural networks (CipherSteal, HyperTheft), bit-flip attack surfaces in DNN executables (BitShield), and novel testing methodologies for neural network robustness. She investigates cache/timing side channels, ciphertext analysis, privacy leakage in partitioned ML, and concept-based explainability. Analysis of her 2023-2025 publications reveals a cohesive focus on offensive security research for AI infrastructures, with consistent contributions to top venues in security and machine learning. Her work demonstrates expertise in low-level system interactions (memory, cryptography) applied to ML security, spanning attack vectors, defensive mechanisms, and validation frameworks. The research trajectory shows increasing sophistication in exploiting hardware-software interfaces while developing practical hardening techniques for real-world deployments.

• Computer Vision in Medical Imaging
• Machine Learning
• Medical Imaging Segmentation
• +۳ مورد دیگر

Dr. Antonio Ortiz is a Researcher at the University of Bonn, affiliated with the Life and Medical Sciences Institute (LIMES) and the IRU Mathematics and Life Sciences group. He works under the supervision of Professors Alexander Effland and Jan Hasenauer. His research focuses on Computer Vision in Medical Imaging and Machine Learning applications. He holds a Ph.D. in Electric and Electronics Engineering from Cinvestav, Mexico (2023), a Master's in Computer Science from Cicese, Mexico (2019), and a Bachelor's in Mechatronic Engineering (2017). His research integrates Bayesian methods, deep learning, and optical flow techniques for cardiac MRI segmentation, visual-inertial SLAM systems, and 3D shape measurement. Recent work emphasizes adaptive algorithms for medical imaging and robotics applications. Publications span medical imaging, robotics, and materials science, with a focus on algorithmic innovation and interdisciplinary applications. No scientific awards are explicitly mentioned, but his work demonstrates strong academic contributions. His advising activities and grants are not detailed in the provided text. He collaborates within the Effland Lab and IRT Mathematics and Life Sciences team.

• Directed Algebraic Topology
• Algebraic Topology
• Applied Mathematics
• +۳ مورد دیگر

Sanjeevi Krishnan is an Associate Professor in the Department of Mathematics at The Ohio State University (OSU). He specializes in directed algebraic topology, focusing on spaces with time-like structures. His research bridges theoretical mathematics and applications in computer science and robotics. He currently teaches undergraduate Linear Algebra (Math 2568/4568) and has developed software tools like dat.py , cubcat.app , and practice: synthetic homotopy theory for topological computations. Key research interests include model structures, cubical approximations, and homotopy invariants in directed topology. His work has been published in journals like Algebraic & Geometric Topology , Journal of Pure and Applied Algebra , and Applied Categorical Structures . Notable contributions include foundational papers on covering spaces in directed topology and applications of topological duality in pursuit-evasion games. He collaborates with institutions globally, including work with Robert Ghrist on topological max-flow min-cut theorems and with Philippe North on dihomotopy type theory. His teaching and research emphasize practical implementations through computational tools and spectral sequence visualization.

Antoine Miechمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Antoine Miech is a Researcher at DeepMind's Vision Group , with prior affiliations at Inria and Ecole Normale Supérieure where he completed his computer vision Ph.D. under Ivan Laptev and Josef Sivic . He has collaborated with researchers from Facebook AI and Google during his academic career. Research Interests span video understanding, weakly-supervised machine learning, and multimodal analysis. His work focuses on: Text-video embedding Self-supervised video representation Action localization Anticipatory video modeling Scalable multimodal learning Scientific Contributions include: HowTo100M - A massive dataset of narrated instructional videos MIL-NCE - A novel loss function for video-text alignment MEE - A model for handling heterogeneous data Context Gating - Learnable pooling architecture Awards & Recognition : Google Ph.D. Fellowship (2018) Technical Leadership : Created the LOUPE TensorFlow toolbox for feature pooling and maintained annotated video dataset catalogs. Organized the Data Science Game competition (2016-2017).

• Neurosciences
• Cognitive and computational psychology
• Biological psychology
• +۳ مورد دیگر

Roni Maimon Mor is a Research Fellow at the Institute of Ophthalmology, University College London. Their work bridges neuroscience, cognitive psychology, and biomedical engineering, focusing on vision science, neural plasticity, and human-technology interaction. They investigate how sensory deprivation (e.g., congenital sight impairment) and interventions (e.g., gene therapy) reshape neural processes and perceptual abilities. Research interests include developmental vision, robotic prosthetics, and the cognitive embodiment of artificial limbs. Their studies explore how early life experiences influence motor learning and how neural systems adapt to sensory loss or technological augmentation. Mor’s interdisciplinary approach integrates neuroimaging (e.g., fMRI, EEG), behavioral experiments, and engineering solutions like gaze-tracking systems for pediatric diagnostics. Publications highlight advancements in gene therapy outcomes for retinal dystrophies, cortical plasticity in sensory-deprived populations, and neural correlates of prosthetic limb use. Their work contributes to clinical tools for vision assessment and theoretical models of body representation. No scientific awards explicitly listed. Research is supported by collaborations in ophthalmology, robotics, and cognitive science. Mor’s lab at UCL focuses on translating neural findings into therapeutic and assistive technologies.

Sonit Singhمشاهده پروفایل

مدرس

• Artificial Intelligence
• Computer Vision
• Natural Language Processing
• +۷ مورد دیگر

Dr. Sonit Singh is a Lecturer at the School of Computer Science and Engineering at the University of New South Wales (UNSW), Sydney, Australia. Prior to this role, he served as a Postdoctoral Research Fellow at the same institution. He holds a PhD from Macquarie University, completed in collaboration with Macquarie. His research focuses on artificial intelligence, computer vision, natural language processing, and their applications in healthcare, particularly in medical imaging and diagnostic systems. Dr. Singh's academic background includes a strong emphasis on biomedical imaging, intelligent robotics, and computing education. His work bridges machine learning advancements with real-world clinical challenges, such as tumor segmentation, radiology report generation, and disease detection through imaging modalities like CT scans and ultrasound. His recent publications highlight innovations in 3D medical image localization, robust tumor segmentation networks, and clinical context-aware radiology report systems. These contributions underscore his expertise in integrating deep learning techniques with healthcare workflows. Dr. Singh collaborates with multidisciplinary teams, including medical professionals, to develop solutions for challenges like placenta segmentation and dietary intake monitoring using AI. While no specific awards or grants are explicitly listed, his extensive publication record reflects sustained academic engagement in high-impact areas. His research often addresses practical clinical needs, such as improving diagnostic accuracy and patient care through advanced computational methods.

Ariel Genadtمشاهده پروفایل

مدرس

• Modern and Contemporary Architecture
• Japanese Architecture
• Architectural Resilience
• +۳ مورد دیگر

Ariel Genadt is a Lecturer in Architecture at the Stuart Weitzman School of Design, University of Pennsylvania. His work bridges research, teaching, and practice, focusing on modern and contemporary Japanese architecture, architectural resilience, and the intersection of technology, sustainability, and cultural expression. He holds a PhD in Architecture from the University of Pennsylvania (2016), with certificates in Ecological Architecture and University Teaching, alongside degrees from the Architectural Association (London) and Technion (Israel). Education: PhD in Architecture, University of Pennsylvania (2016) Master of Arts in Histories and Theories, Architectural Association, London (2004) Bachelor of Architecture, Technion, Israel (1997, cum laude) Research Interests: Japanese architectural history and practice Sustainable and resilient design Material innovation and tectonic expression Cultural preservation and reinterpretation Genadt's publications and exhibitions explore themes like architectural resilience in Japan, material assemblies, and cultural narratives in urban spaces. His curatorial work includes the Critical Abstractions: Modern Architecture in Japan exhibition (2018) and the 50 Years in Books by Penn Architecture PhDs database (2016). He has practiced globally, collaborating on projects in France, Israel, China, and beyond, and has taught at institutions including Swarthmore College and the Technion. His teaching spans courses on architectural theory, climate-responsive design, and Japanese modern architecture. Notable courses include ARCH 7120: Architectural Envelopes and ARCH 7110: Modern Architecture in Japan . He has advised the Master of Architecture thesis program and led design-build workshops at Tokyo University. Genadt’s professional affiliations include roles as a Fellow Researcher at the Japan Society for the Promotion of Science (Kengo Kuma Lab, 2012) and a visiting scholar at Fondazione Renzo Piano (2013). His work emphasizes cross-cultural dialogue and the role of architecture in addressing environmental and social challenges.