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نمایش ۷۲۱-۷۳۵ از ۳٬۰۴۷ استاد راهنما
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مدرس ارشد
Peter Passmore is a Senior Lecturer in the Department of Computing Science at Middlesex University. His research focuses on Virtual Reality, Human-Computer Interaction, and Visual Analytics, with applications in gaming, intelligence analysis, and immersive media. Research Interests: Virtua... (truncated for brevity)
Evangelos E. Milios is a Professor in the Faculty of Computer Science at Dalhousie University , Halifax, Nova Scotia. He has been a faculty member since 1998 and leads the MALNIS (Machine Learning and Networked Information Spaces) research group. He is affiliated with the Institute of Big Data Analytics and served as Scientific Director of DeepSense , an innovation hub for ocean data analytics. Education: PhD in Electrical Engineering and Computer Science, MIT (1986) SM & EE, MIT (1983) Dipl. Eng. in Electrical Engineering, NTUA, Greece (1980) His research focuses on visual text analytics, text mining, graph mining, social network analysis, and machine learning . He has made significant contributions to modeling and mining of networked information spaces, with applications in data science and AI. The recent publications reflect a strong trend in data mining, robotics, pattern recognition, and semantic analysis , particularly in log analysis, pose estimation, and information retrieval. His work bridges theoretical algorithms with practical applications in robotics and web technologies. Scientific Awards and Honors: Distinguished Research Professor (2017–2022) Killam Chair in Computer Science (2006–2011) Senior Member, IEEE Professional Engineer, Ontario (1998–2024) He has served in key administrative roles including Associate Dean, Research (2008–2017) and Director of the Graduate Program (1999–2002) . He has supervised numerous graduate students and taught a wide range of courses in AI, machine learning, data science, and networking. His research is supported by major grants and collaborations, including NSERC and industry partnerships. Research Labs and Teams: MALNIS – Focuses on machine learning and networked information spaces. DeepSense – Ocean data analytics and AI innovation. Institute of Big Data Analytics – Cross-disciplinary big data research.
Tian Heong Chan is an Associate Professor at Emory University's Goizueta Business School in the Information Systems & Operations Management department. His research and teaching focus on new product/service development, team collaboration, and technology operations. Education: PhD in Technology and Operations Management, INSEAD MS in Management Science and Engineering, Stanford University BS in Mechanical Engineering, UC Berkeley His work investigates: Collaboration dynamics in diverse settings (product design, problem-solving, customer-supplier co-production) Novelty emergence in design processes (exaptation, computer vision similarity metrics) Team composition effects on invention value (expertise similarity, gender diversity, cohesion) Recent publications analyze: Exaptation in IKEA hacks Voting protocols in FDA advisory committees Style evolution in product design Free-rider problems in medical equipment maintenance
Professor Richard Blythe is Pro Vice-Chancellor of the Faculty of Humanities at Curtin University. He is a member of the Curtin Senior Executive Team, Chair of the Respect at Curtin sub-committee, and PVC representative on the Curtin Digital Steering Committee. Previously, he served as Professor in Architecture and Dean of the College of Architecture and Urban Studies at Virginia Tech, Dean of the School of Architecture + Design at RMIT University, and Head of the School of Architecture + Design at RMIT, among other leadership roles. Pro Vice-Chancellor, Humanities Faculty, Curtin University Dean, College of Architecture and Urban Studies, Virginia Tech Dean, School of Architecture + Design, RMIT University Head, School of Architecture + Design, RMIT University Deputy Head, School of Architecture, University of Tasmania Richard’s research focuses on creative practice, practice-based research, and architectural theory. He has secured over $6.8 million in research funding and developed frameworks for validating creative outputs. His work spans architectural history, design pedagogy, and the intersection of practice and academia. His recent publications examine reflective practices in design, PhD training models for creative practitioners, and methodologies for evaluating artistic research. These works highlight his commitment to advancing interdisciplinary research and institutional leadership in creative disciplines. Richard has held leadership roles in national and international architectural organizations, including President of the Society of Architectural Historians Australia and New Zealand and Chair of the Australian Institute of Architects National Education Committee. He was a founding director of the architectural practice Terroir, blending academic and professional expertise. He has contributed extensively to research funding and accreditation panels, emphasizing strategic leadership in creative practice. His work bridges European and Australian research frameworks, fostering collaboration between academia and industry.
استاد مدعو
Olivier Verscheure serves as the Executive Director of the Swiss Data Science Center (SDSC), a national R&D center organizationally hosted by both École Polytechnique Fédérale de Lausanne (EPFL) and ETH Zurich. He also holds multiple Adjunct Professor appointments at EPFL, specifically within the School of Computer and Communication Sciences (SIN and SSC) and the School of Engineering (SEL). His educational background includes: Ph.D. in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), June 1999 Verscheure's research focuses on the intersection of data science and real-world applications. His work centers on stream and big data mining, geospatial analysis, and large-scale data management. These technical capabilities are applied across diverse domains including personalized health and medicine, Intelligent Transportation Systems, telecommunications, smart building technologies, Smart Grid infrastructure, healthcare analytics, and waste water management systems. His approach emphasizes creating practical data science solutions that address complex challenges in these sectors while considering the constraints of real-world deployment. An analysis of his recent publication record reveals a strong focus on real-time data processing and analytics, particularly for transportation and urban systems. His work frequently addresses challenges in handling massive time series data, developing efficient architectures for low-latency analytics, and creating practical applications for smart city infrastructure. There's a clear progression from theoretical data science contributions to production-ready systems that can process billions of data points daily, demonstrating his ability to bridge research and practical implementation. His notable achievements include: Two IBM Outstanding Technical Achievement Awards Best Paper Award for his research Student Best Paper Award Verscheure has substantial experience in research leadership and mentoring. During his tenure at IBM, he managed the Exploratory Stream Analytics research group and led a technical and management team of approximately 40 people at the IBM Research lab in Ireland. He has served on PhD committees at major universities and published nearly 100 research papers that have garnered over 2,400 citations. His work has resulted in more than 40 US and international patents, demonstrating both academic and practical impact. As Executive Director of the Swiss Data Science Center, Verscheure oversees a distributed multi-disciplinary team working across domains including personalized health, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and computer scientists, and subject-matter experts around a cutting-edge analytics platform while addressing security and privacy issues. Under his leadership, the SDSC develops embedded data science support, offers end-to-end data science services, and fosters a community to share tools and knowledge in data science.
Christopher McCarthy is an Associate Professor in the Department of Computing Technologies within the School of Science, Computing and Emerging Technologies at Swinburne University of Technology. His research focuses on computer vision algorithms applied to robotics, intelligent transport systems, and assistive technologies, particularly for people with low vision. He serves as Stream Leader in Swinburne’s Innovative Planet Research Institute, leading the Intelligent Transport stream, and is a Chief Investigator in the Australian Cobotics Centre funded by the ARC. He has held research roles at CSIRO Data61, the Bionics Institute, and the University of Melbourne, contributing to bionic eye technology under the Bionic Vision Australia consortium. His research interests include: Computer Vision and AI for real-time systems Robot perception and navigation Assistive technologies for low-vision and blind users Intelligent transport systems and video analytics Human-machine interaction and cyber-human teams His recent publications reflect strong trends in deep learning, continual learning, and real-world deployment of vision systems in transport and healthcare. He has led numerous field trials and evaluations to assess system performance in real-world contexts. His work is highly interdisciplinary, combining computer science with engineering, medicine, and urban planning. Christopher McCarthy has received multiple awards, including: FSET Research Collaboration Award Excellence in Industry Engagement Special Commendation – VC Research Impact Finalist – National Disability Award in Technology Best Paper Award (IEEE) Excellence in Teaching (University of Melbourne) He has supervised over 20 HDR students in areas including robotics, AI, assistive tech, and transport analytics. He has led major research grants from ARC, Defence, SmartCrete CRC, iMOVE, and city councils. He also served as Academic Director for Work-Integrated Learning (2016–2023) and coordinated professional placements. His teaching includes core computer science units such as Computer Systems and Object-Oriented Programming. He maintains ongoing affiliations with: Bionics Institute (Honorary Member) Bionic Vision Australia (Affiliate) Data61 (Honorary Member) Royal Children's Hospital, Melbourne International Task Force for Vision Restoration Outcomes (Chair)
Laurent Charlin is an Associate Professor at HEC Montréal and holds an adjunct appointment in Computer Science at Université de Montréal. His research focuses on machine learning for decision-making with applications in recommender systems, reinforcement learning, and optimization.
Professor Doris Tophinke is affiliated with the University of Paderborn, where she serves in the Faculty of Cultural Studies within the Institute of German Studies and Comparative Literature, specifically in the Department of German and General Linguistics. She maintains her office in room H3.134 at Warburger Str. 100, 33098 Paderborn and serves as the project leader for the Paderborn location of the Dialect Atlas of Central West Germany (DMW). Professor Tophinke's research spans multiple interconnected areas within linguistics, with a primary focus on literacy and writing practices across historical and contemporary contexts. Her work uniquely bridges contemporary graffiti studies with medieval linguistic research, examining how written forms carry grammatical significance. She investigates 'small forms' of writing like graffiti through the lens of multimodal grammar and cognitive linguistics, while simultaneously documenting language change through her extensive work on Low German dialects and the Dialect Atlas of Central West Germany. Her research demonstrates how seemingly marginal linguistic phenomena provide profound insights into grammatical structures and language evolution. The patterns in her recent publications reveal consistent engagement with informal language in everyday contexts - from street graffiti to digital communication. Her scholarly output shows increasing interdisciplinary collaboration, particularly with computational linguists on projects analyzing grammatical change. Her work on political graffiti and linguistic expressions demonstrates how language functions as political commentary and social identity marker in public spaces. Since 2008: Member of the editorial board of Praxis Deutsch (Friedrich Verlag) Since 2008: Member of the editorial board of Zeitschrift für Germanistische Linguistik (de Gruyter) December 2011-February 2016: Member of the DFG Subject Committee 'Sprachwissenschaften' October 2011-September 2015: Service in DAAD selection committees Since March 2019: Member of the review board of 'Niederdeutsches Wort' journal Since June 2019: Member of the advisory board for Low German language at the Ministry of Home Affairs of North Rhine-Westphalia September 2011-May 2019: Deputy Ombudsperson for Good Scientific Practice at University of Paderborn June 2019-March 2022: Ombudsperson for Good Scientific Practice at University of Paderborn Professor Tophinke actively supervises doctoral students through the DMW project and related research initiatives, providing opportunities for students to work with research data in their theses. She teaches courses including 'Zeichensetzung und (komplexe) Sätze' (Punctuation and Complex Sentences), 'Wörter: Semantik und Funktionen im Wandel' (Words: Semantics and Functional Change), and 'Der Wortschatz der Mode' (Vocabulary of Fashion), integrating her research interests across German teacher training programs and Linguistics degree programs. She leads the Paderborn team for the Dialect Atlas of Central West Germany (DMW), which involves systematic fieldwork collecting dialect data throughout North Rhine-Westphalia and neighboring states. The project team includes scientific associates, research assistants, and student collaborators who conduct interviews in participants' homes across the survey region, documenting linguistic variations with particular attention to Low German where it is still spoken. The team also works on the Informationssystem Graffiti in Deutschland (INGRID) project, which catalogs and analyzes graffiti as a linguistic phenomenon.
Dr. Svetlana V. Poroseva is a Professor at the Department of Mechanical Engineering, University of New Mexico (UNM), with a distinguished career in turbulence physics, uncertainty quantification, and bio-inspired design. Her work bridges computational fluid dynamics (CFD) with applications in renewable energy, power systems survivability, and aerospace engineering. Her educational background includes a Ph.D. in Fluid and Plasma Mechanics (1996) and an M.S. in Physics (1989) from Novosibirsk State University, Russia. She has held faculty positions at UNM since 2010, progressing from Assistant to Professor (2023). Her research focuses on high-order turbulence closures, data-driven modeling, and evidence theory for multi-model predictions, with a strong emphasis on quantifying uncertainty in simulations. Dr. Poroseva’s recent publications highlight advancements in bio-inspired rotor design, DNS analysis of mixing layers, and solar energy accessibility studies. She has developed software tools like FIESTA and Power System Graph Converter, both under open licenses. Her work spans turbulent flow validation, power grid topology optimization, and aerosol transmission modeling, particularly during the pandemic. Scientific Awards UNM School of Engineering Dean’s Excellence Lectureship Award (2022) Harrison Faculty Excellence Award (2021-2022) Rainforest Innovation Award (2022) AIAA Associate Fellow (2013) Fellowships at Stanford, CNRS, and CISM She advises numerous graduate and undergraduate students, leads the UNM AIAA Student Chapter, and collaborates internationally on projects involving NASA, Sandia, and European institutions.
Dr. Maryam Bostanara is a Researcher at the City Futures Research Centre (CFRC) , part of the School of Built Environment at the University of New South Wales (UNSW Sydney). She completed her PhD in 2024 at the Research Centre for Integrated Transport Innovation (rCITI) , School of Civil and Environmental Engineering , UNSW Sydney, with a thesis titled "Urban Dynamics and Household Decisions: Advanced Statistical Methods in Relocation, Land Use, and Transport Planning." She holds a BSc and MSc in Industrial Engineering (Systems Optimization) from Sharif University of Technology, Iran (2016 and 2018). Maryam’s research focuses on the intersection of transport and land-use, emphasizing behavioral models and data-driven approaches to urban sustainability. Her work integrates data visualization , machine learning , and econometric methods to analyze residential relocation, transport planning, and urban dynamics. A notable trend in her publications is the application of advanced statistical frameworks (e.g., DDCM, survival analysis) to study relocation behaviors, cycling infrastructure, and time-use patterns during crises like the COVID-19 pandemic. She has also contributed to interdisciplinary topics, including AI-driven healthcare analytics. Recipient of UNSW Women in Engineering Research Top-Up Scholarship Awarded Best research demonstration at TRANSW 2021 Maryam is supported by the Digital Grid Futures Institute Seed Funding (DGFI) 2024 and is affiliated with the CFRC, a leader in urban futures research. Her expertise spans transport modeling, behavioral economics, and data science, with a growing focus on health-related applications.
استاد پژوهشی
Dr. Emiel Heijnen is a Research Professor in the Arts Education department at Amsterdam University of the Arts (AHK), where he leads the Lectorate of Arts Education. With a doctorate from Radboud University Nijmegen focusing on contemporary visual practices in art education, he has established himself as a leading researcher in authentic art education and curriculum innovation. His research focuses on Arts Education , Contemporary Art Practices , Curriculum Design and Innovation , and the emerging field of ArtsSciences Integration . He has developed the influential concept of Wicked Arts Assignments , which challenges traditional educational approaches by embracing complexity and uncertainty in art education. His work bridges theory and practice, connecting contemporary art practices with educational settings to create more authentic learning experiences. Dr. Heijnen's publications and presentations reveal a consistent focus on interdisciplinary approaches, particularly the integration of arts with science and technology (ArtsSciences). His recent work emphasizes creative citizenship, media literacy, and strategies for implementing authentic art education in diverse educational contexts from primary schools to higher vocational education. As an active researcher and thought leader, he serves on editorial boards, participates in international conferences, and collaborates with educational institutions worldwide. His work has significantly influenced arts education policy and practice in the Netherlands and beyond, particularly through his leadership in developing research agendas and educational frameworks that connect contemporary art practices with educational innovation.
João André Pinto Soares is a Senior Researcher at the Knowledge Engineering and Decision Support Research Group (GECAD) at the Polytechnic Institute of Porto's School of Engineering. He earned his PhD in Electrical and Computer Engineering from UTAD in 2017 and has since secured significant funding through FCT projects, including CENERGETIC as Principal Investigator and BENEFICE as co-PI. Principal Investigator for CENERGETIC project on energy resource management Co-PI for BENEFICE project on smart building optimization Visiting Professor at Centrale Lille since 2019 Co-coordinator of SAtCOMM project for sustainable Atlantic energy communities Dr. Soares has established international collaborations with institutions including Sao Paulo State University (UNESP), Honda Research Institute Europe, and Centrale Lille. His research focuses on energy resource management in smart grids, with particular emphasis on local energy markets and electric vehicles. He has successfully managed a team of 10 researchers over the last 5 years and supervised numerous students at various academic levels. His publication record includes over 200 scientific articles, with 75 in international journals, garnering more than 5500 citations and an h-index of 40. His most recent work demonstrates strong trends in applying advanced optimization techniques, machine learning, and metaheuristics to energy resource management problems, particularly focusing on uncertainty modeling, electric vehicle integration, and local energy markets. Chair of IEEE ISATC Task Force on Computational Intelligence for the Energy Domain Secretary of the IEEE PES Intelligent Systems Subcommittee Launched 16 special issue editions as co-editor in JCR journals Reviewed over 400 scientific papers Dr. Soares has supervised 9 PhD students (7 ongoing), 23 MSc students, and 23 BSc students. His research has been supported by 28 national/international projects (10 as PI, 2 as Co-PI, and 17 as researcher), including Horizon/H2020 projects. He has also been instrumental in organizing over 30 scientific events and has delivered more than 30 invited talks at international conferences.
Robert Bergevin is a Full Professor in the Department of Electrical Engineering and Computer Engineering at Laval University's Faculty of Science and Engineering, where he has been employed since 1990 and achieved full professor status in 2001. He is also a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence) and actively participates in graduate recruitment. Dr. Bergevin's educational background includes: Ph.D. in Electrical Engineering from McGill University (1985-1990), with thesis titled "Primal Access Recognition of Visual Objects" under Professor Martin D. Levine M.Sc.A. in Biomedical Engineering from École Polytechnique de Montréal (1982-1984), with thesis on "Modeling and numerical simulation of a nuclear magnetic resonance imaging system" under Professor Robert Guardo B.Sc.A. in Electrical Engineering (Communications specialty) from École Polytechnique de Montréal (1978-1982) Professor Bergevin's research spans cognitive computer vision, pattern recognition, and information systems design methodologies. His work is guided by a unique methodology that progresses "from the general to the particular" to achieve "simply communicable and universally applicable understanding." He has been a researcher in cognitive computer vision since 1985, with particular focus on ontology, methodology, and categorization. His research interests include Ontology of Cognitive Digital Vision, Cognitive Digital Vision Development Methodology, Categorization in cognitive digital vision, Analysis and understanding of images and videos, and Understandable artificial intelligence. As a generalist, he is also a proponent of the science of global anticipatory design (R. Buckminster Fuller) and general semantics (Alfred Korzybski). Analysis of Professor Bergevin's recent publications reveals a strong focus on video anomaly detection, carried object detection, and human activity recognition. His work consistently applies cognitive principles to computer vision problems, often developing novel methodologies for segmentation, tracking, and recognition. The research shows progression from foundational work on image analysis to more complex spatio-temporal understanding of video content, with increasing integration of deep learning techniques in recent years while maintaining a focus on interpretable and cognitively-inspired approaches. Among his professional recognitions: Teaching Star, Faculty of Science and Engineering (2019, 2012) Professor Bergevin has supervised numerous graduate students throughout his career, including four PhD candidates and four Master's students in recent years. His current research includes the "Cyber-physical systems and materialized machine intelligence" project funded by Université Laval, École de technologie supérieure, and Fonds de recherche du Québec - Nature and technologies, running from 2019 to 2026. He was also the director of the bachelor's program in computer engineering from 2001 to 2010 and served as Area Editor for the journal Computer Vision and Image Understanding from 2002 to 2017. As a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence), Professor Bergevin collaborates with researchers across multiple disciplines to advance the fields of robotics, computer vision, and machine intelligence. His work bridges theoretical foundations with practical applications, particularly in the analysis of human activities and object recognition in complex visual scenes.
Professor Onno Bokhove holds the Chair in Geophysical Fluid Dynamics at the School of Mathematics, Faculty of Engineering and Physical Sciences, University of Leeds. With extensive expertise in applied mathematics of geophysical fluid dynamics, he bridges theoretical mathematical approaches with practical environmental solutions, particularly in flood mitigation and wave dynamics. His research encompasses: Design and testing of laboratory configurations for mathematical model validation Computational techniques for PDEs using discontinuous Galerkin FEM Hamiltonian fluid dynamics frameworks Idealised models for weather prediction Hydraulic solutions of hyperbolic systems Flood mitigation strategies through flood-excess volume analysis Analysis of his recent publications reveals a strategic shift toward practical applications of geophysical fluid dynamics with significant societal impact. Professor Bokhove pioneered the concept of "flood-excess volume" as a communication tool for flood mitigation effectiveness, which evolved from the Wetropolis demonstrator into a REF2021 Impact Case Study. His work increasingly integrates mathematical rigor with policy-relevant applications, particularly through the EU-funded Eagre project on high-seas wave-impact modeling, where he serves as principal investigator collaborating with MARIN (Maritime Research Institute Netherlands). Professor Bokhove has supervised numerous PhD students across diverse fluid dynamics applications: Tom Kent (2014-2016): EPSRC Case Met Office project with Steve Tobias Floriane Gidel (2015-2018): EU project with Mark Kelmanson Tomasz Salwa (2015-2019): EU project with Mark Kelmanson Luca Cantarello: NERC Case with Met Office Current students Yang Lu and Wajiha Rehman working on the EU Eagre project His research has been supported by significant grants including: EU European Industrial Doctorates project "Eagre" (2020-2023, project 859983) NERC-funded projects on flood mitigation EPSRC Case projects with the Met Office REF2021 Impact Case Study funding Professor Bokhove leads research teams within the Leeds Institute for Fluid Dynamics focusing on: The Wetropolis flood demonstrator project, now a policy-relevant analytical framework The Eagre project developing numerical wavetanks for extreme wave modeling Collaborations with MARIN on wave-energy devices and offshore structures
عضو هیئت علمی
Eric Money is an Associate Teaching Professor and serves as the Director of Education at NC State University's Center for Geospatial Analytics, where he has worked since May 2014. He also directs the Master of Geospatial Information Science & Technology and Graduate Certificate in GIS programs. Academic Rank: Associate Teaching Professor Department: Geospatial Information Science & Technology Previous Positions: Environmental Scientist at RTI International, Postdoctoral Researcher at Duke University His research spans geospatial pedagogy, curriculum development, and applied geospatial modeling with public health implications, including: Environmental modeling under uncertainty Spatial-decision support tools Geovisualization of health risks K-12 GIS education initiatives Integration of GIS in STEM education Ecological risk assessment Recent publications focus on modern GIS curriculum development, spatial decision support systems, and geospatial education outreach. His work emphasizes interdisciplinary collaboration and stakeholder engagement through geospatial modeling.
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