جستجوی استاد راهنمای دانشگاهی

Marta Kryven is an Assistant Professor in the Faculty of Computer Science at Dalhousie University. Her research integrates artificial intelligence, cognitive science, and experimental psychology to develop computational models of human cognition, focusing on planning, perception, and behavior. She is actively engaged in interdisciplinary research and is accepting graduate students. Research Interests: Computational models of cognition and behavior Large Language Models and their alignment with human thought Spatial navigation and environmental interaction Program synthesis and induction Representation learning and cognitive modeling Human-AI alignment and interpretability Her recent publications demonstrate a strong trend in combining symbolic AI with neural models to simulate human-like reasoning, particularly in spatial and social contexts. She frequently collaborates with leading researchers at MIT, especially Joshua Tenenbaum. Her work appears in top-tier venues such as NeurIPS, Cognitive Science, and Nature Computational Science. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: Marta Kryven is currently accepting applications from graduate students and has several projects available for both undergraduate and graduate researchers. While specific grants are not listed, her active publication record in high-impact journals suggests ongoing funded research. She also offers consulting in AI system design, behavioral modeling, and data science for businesses. Labs and Teams: She is part of the Big Data Analytics, AI & Machine Learning research cluster at Dalhousie University. Her work is closely affiliated with cognitive science and AI research groups, likely involving collaboration with MIT’s Center for Brains, Minds and Machines. She leads a research group focused on human-like AI and computational cognitive modeling.

• Computational Cognitive Science
• Artificial Intelligence
• Cognitive Psychology
• +۷ مورد دیگر

Pierre-Yves Lajoie is an Assistant Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, a leading engineering school affiliated with Université de Montréal. His research focuses on robotics and artificial intelligence, with specialization in robotic perception for single and multi-agent systems. He has held research positions at prestigious institutions including the Massachusetts Institute of Technology (2019), Samsung AI Center (2023), and University of Oxford (2024). Education: Ph.D. in Computer Engineering, Polytechnique Montréal Dr. Lajoie's research interests span across robotics, computer vision, and distributed systems. He specializes in developing algorithms for robotic perception in challenging environments, with applications in aerial, underground, indoor, and space robotics. His work focuses on enabling robots to understand their surroundings through visual and sensor data, particularly in collaborative multi-robot scenarios where communication may be limited or unreliable. His primary research center of excellence is the Industry of the Future and Digital Society, with secondary centers in Modeling and Artificial Intelligence and New Frontiers in Information and Communication Technologies. His publication record demonstrates a strong focus on collaborative SLAM (Simultaneous Localization and Mapping) systems, with recent work addressing challenges in planetary exploration, swarm robotics, and pedestrian positioning. His research combines computer vision, machine learning, and distributed systems to create robust solutions for real-world robotic applications, particularly in environments with communication constraints. Scientific Awards: Vanier Canada Scholarship Best Paper Award at IEEE ICC 2024 Dr. Lajoie is actively recruiting graduate students for PhD and Master's programs, with openings for Fall 2025 and Spring 2026. He encourages students to apply for various scholarship opportunities including NSERC, FRQ, and IVADO scholarships at multiple academic levels. His research is supported by collaborations with academic and industrial partners, focusing on applications in space robotics, automated manufacturing, and service robotics. He has supervised research projects in areas such as search and rescue with sparsely connected swarms and distributed risk-aware exploration systems.

• Robotics
• Computer Vision
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Christopher Collins is a Professor of Computer Science at Ontario Tech University, leading the Visualization for Information Analysis Lab (vialab). He holds a PhD from the University of Toronto (2010) and focuses on interdisciplinary research in information visualization, human-computer interaction, and natural language processing. His work addresses challenges in information overload, text analytics, and novel interfaces such as touch, pen, VR/AR. Collins' research has been featured in top-tier venues like ACM CHI and IEEE Transactions on Visualization and Computer Graphics, earning honorable mentions and over $3M in funding as sole PI. He serves on the IEEE VIS Executive Committee and Board of Governors at Ontario Tech University. Education: PhD in Computer Science, University of Toronto (2010) MSc in Computer Science, University of Toronto (2004) BSc (Hons) in Computer Science, Memorial University (2001) Research Interests: Collins' work spans information visualization , pen+touch interfaces , visual analytics , and text-driven systems . He explores how interactive technologies can democratize complex data analysis, particularly in education, healthcare, and creative domains. Recent projects include gaze-driven learning tools, context-aware camera interfaces, and bias-mitigating product review analysis. Awards: ACM CHI Honorable Mention Award IEEE VIS Honorable Mention Award Grants & Impact: Secured $3M+ in research funding. Media coverage includes New York Times and CBS Sunday Morning for innovations in visualization and text analytics. Teaches courses in human-computer interaction, computer graphics, and information visualization. Labs & Collaborations: vialab develops tools like Lexichrome , ConToVi , and NeuroSight . Active in IEEE Visualization and ACM Interactive Media communities. Collaborates with academia and industry globally.

• Information Visualization
• Human-Computer Interaction
• Pen+Touch Interface Design
• +۷ مورد دیگر

Steven Ding is an Adjunct Assistant Professor and Lab Director at the School of Computing, Queen's University , leading the L1NNA Artificial Intelligence and Security Lab. His research focuses on the intersection of machine learning, data mining, and cybersecurity with applications in malware analysis, reverse engineering, and authorship attribution. Education: PhD in Information Studies (McGill University, 2019), M.A.Sc. in Information Systems Security (Concordia University), B.S. in Information Systems (University of the Fraser Valley), B.S. in Computer Science (University of Shanghai for Science & Technology) Research Interests: His work integrates artificial intelligence and security systems to develop solutions for malware phenotype decomposition, neural malware analysis, binary provenance, and explainable AI in cybersecurity. He explores data analytics for assembly code evolution and authorship analysis using machine learning and differential privacy . Publication Trends: His peer-reviewed work (IEEE Transactions, ACM conferences) emphasizes binary code analysis , neural networks , and cybersecurity , with a focus on static malware characterization , authorship attribution , and cross-architecture code similarity . Scientific Awards: FRQNT Doctoral Research Scholarship (2017-2018) Dean’s Graduate Award at McGill University (4 years, 2014-2018) NSERC Alliance Grant (2021-2024) Best Poster Award, SERENE-RISC Research Showcase (2016) Second Prize, Hex-Rays Software Plug-in Contest (2015) ACM SIGKDD Student Travel Award (2016) Advising & Grants: Dr. Ding has supervised numerous Ph.D. and Master’s students (e.g., Li Tao Li, Mark M. Adams) and secured significant funding from BlackBerry Cylance , DRDC , and NSERC , including a 1.24M CAD NSERC Alliance Grant (50%) and 1.5M CAD DRDC Contract (50%). Labs & Teams: The L1NNA lab collaborates with DRDC Canada, NVIDIA, and IEEE Security & Privacy, focusing on AI-driven security tools (e.g., Kam1n0 assembly clone search engine) and neural malware analysis . The lab is located in Goodwin Hall, Queen's University, and emphasizes practical software development and industrial partnerships .

• Artificial Intelligence
• Data Analytics
• Security
• +۴ مورد دیگر

Dima Damen is a Professor of Computer Vision at the School of Computer Science, University of Bristol , and leads the Machine Learning and Computer Vision Group . She also holds a position as Senior Research Scientist at Google DeepMind. Her research focuses on egocentric vision , video understanding , and action recognition , with significant contributions to human routine modeling , hand-object interaction analysis, and multimodal learning from real-world environments. EPSRC Early Career Fellow (2020-2025) ELLIS Society Member Active in organizing workshops and challenges (e.g., EPIC, Ego4D, EgoVis) Her recent work explores temporal discrimination in video captioning ( It's Just Another Day ), active memory representations for long egocentric videos ( AMEGO ), and hand-object interaction referral ( HOI-Ref ). She has co-authored 15+ articles in top venues like CVPR, ICCV, NeurIPS, and IJCV, with a focus on egocentric scene modeling , audio-visual binding , and cross-scenario generalization . Awards include the Best Paper at ACCV 2024 and recognition as an Outstanding Reviewer at CVPR 2020 . She has supervised numerous PhD students and postdocs , including Adriano Fragomeni, Jacob Chalk, Alexandros Stergiou, and others who now hold academic or industry roles. Her funded projects include VISUAL AI (EPSRC Programme Grant) and UMPIRE (EPSRC Early Career Fellowship), supporting innovations in egocentric dataset creation , real-time tracking , and industrial workflow assistance .

• Computer Vision
• Egocentric Vision
• Video Understanding
• +۳ مورد دیگر

Donald R. Sheehy is an Associate Professor of Computer Science in the College of Engineering at North Carolina State University. His research focuses on the intersection of geometric algorithms and topological data analysis, with significant contributions to computational geometry and persistent homology. Sheehy's research interests span geometric algorithms, topological data analysis, computational geometry, persistent homology, metric spaces, Voronoi diagrams, and Delaunay triangulations. His work bridges theoretical computer science with practical applications in data analysis, where he develops algorithms that extract meaningful topological information from complex datasets. His research has particular relevance for understanding the structure of high-dimensional data through geometric and topological lenses. Analysis of his recent publications reveals a strong focus on developing efficient algorithms for topological data analysis. His work on sparse filtrations, greedy permutations, and metric properties of persistence diagrams has advanced the field by providing computationally tractable methods for analyzing large datasets. Sheehy frequently explores how geometric structures like Voronoi diagrams and Delaunay triangulations can be adapted to topological contexts, creating bridges between classical computational geometry and modern data analysis techniques. Sheehy actively collaborates with researchers across multiple institutions, as evidenced by his extensive publication record in top venues like SOCG (Symposium on Computational Geometry) and SODA (Symposium on Discrete Algorithms). His work demonstrates a consistent trajectory of advancing both theoretical foundations and practical applications of geometric and topological methods in computer science.

• Geometric Algorithms
• Topological Data Analysis
• Computational Geometry
• +۴ مورد دیگر

Jim Clark is a Senior Lecturer at the University of Lethbridge's Dhillon School of Business, specializing in E-commerce and Information Systems. He has been teaching at the institution since 1990 and maintains an active presence through his course instruction and professional blog. His educational background includes degrees from BYU and Ivey School of Business. Clark's professional experience extends beyond academia, with previous positions at Revenue Canada, Shell Canada, and Drowland Technologies, along with numerous small business consulting projects. Clark's research and teaching interests focus on E-commerce, Information Systems, Data Analytics, and Data Visualization, with particular emphasis on financing, organizational design, and entrepreneurship within E-commerce organizations. His work explores the application of technology in business contexts and classroom pedagogy. His recent publications and blog posts demonstrate consistent engagement with current technology trends affecting business, including digital advertising evolution, AI in finance, e-commerce strategies, and ethical considerations in technology adoption. These works reflect his commitment to connecting academic concepts with real-world business applications. Clark teaches Management of Information Systems (MGT 3061) and maintains an active online presence through his blog 'Info Systems in Practice' where he discusses relevant technology topics for business students and professionals. He has developed extensive teaching materials including video lectures, chapter projects, and discussion questions that integrate current business technology examples with core information systems concepts. His teaching approach emphasizes practical application of information systems knowledge in business decision-making contexts.

• E-commerce
• Information Systems
• Data Analytics
• +۲ مورد دیگر

Sabine MAS is a Full Professor at the School of Library and Information Studies, Faculty of Arts and Sciences at the University of Montreal. Her research focuses on classification systems for digital archives, typology of contemporary archives, and user-centric information management. She has supervised 5 major theses and leads/co-leads 9 research projects including the Centre de recherche interuniversitaire sur les humanités numériques (CRIHN). Teaches courses like Introduction à l'archivistique and Diplomatique contemporaine Active in digital humanities and legal documentation fields Recipient of multiple grants from CRSH and FRQSC Research highlights include development of faceted indexing models for legal documents and studies on emotion-driven archival description. She co-edited Typologie des documents des organisations (2019) and modernized the Portail International Archivistique Francophone (PIAF). Grants include a 2024-2028 strategic research grant (FQRSC) and 2023 CRSH exploration grant for studying archival practices. Her work bridges archival theory with practical applications in digital environments.

• Archival Science
• Digital Documentation
• Classification Systems
• +۶ مورد دیگر

Jenna Hartel is an Associate Professor at the Faculty of Information, University of Toronto, where she has been a faculty member since 2008. Her work bridges Library and Information Science (LIS) with interdisciplinary social science, focusing on information in the context of leisure, creativity, and well-being. She is affiliated with the Faculty of Information and teaches in the Master of Information program, particularly within the Library and Information Science concentration. PhD in Information Studies, University of California, Los Angeles BA in American Studies, Colby College Her research centers on the nature of information in pleasurable and profound life experiences, especially serious leisure activities like hobbies. She employs innovative visual and arts-informed methodologies and leads the iSQUARE Research Program. Her teaching includes courses such as The Information Experience and Information Ethnography , and she advises both master’s and doctoral students on information behavior in everyday life. Her recent publications reflect a trajectory toward positive information science, contemplative practices, multispecies perspectives, and storytelling in research. Themes across her work include happiness, care, creativity, and holistic visions of information science. She uses multimedia platforms, notably her YouTube channel INFIDEOS, to disseminate knowledge and innovate in LIS education. Scientific Awards ASIS&T Distinguished Member, 2023 ASIS&T Outstanding Information Science Teacher Award, 2023 ASIS&T/SI-USE Outstanding Information Behaviour Research Award, 2022 ALISE Pratt-Severn Faculty Innovation Award, 2022 Community of Champions (Teaching Award) Nominee, University of Toronto, 2016 Excellence in Teaching Award, Library Journal/ALISE, 2016 Innovation Award, ASIS&T/SIG-USE, 2013 Highly Cited Paper Award, Journal of Documentation, 2010 Dialog/ALISE Methodology Paper Award, 2006 Hartel has secured multiple research grants, including projects on Information and Contemplation and A Theory of Information in the Hobby of Gourmet Cooking . She mentors graduate students and promotes compassionate, inclusive academic supervision. She is actively involved in leadership roles, such as serving on the Masters of Information Recruiting and Admissions Committee and the Life and Times Committee. Her work with the INFIDEOS YouTube channel exemplifies her commitment to public engagement and creative pedagogy. She is also associated with research teams and initiatives like the iSQUARE Research Program and has collaborated widely across the LIS field. Her future work continues to explore contemplative, positive, and multispecies dimensions of information science.

• Information Behaviour
• Serious Leisure
• Visual Research Methods
• +۷ مورد دیگر

Dirk Arnold is a Professor in the Faculty of Computer Science at Dalhousie University, Halifax, Canada. His research focuses on evolutionary computation, optimization, and surrogate modeling, with applications in machine learning and digital media. He is actively involved in teaching and research, contributing to major conferences and journals. PhD, University of Dortmund (2001) MSc, Simon Fraser University (1997) Diplom, University of Dortmund (1995) His research interests lie in evolutionary algorithms, particularly evolution strategies, and their application to noisy and constrained optimization. He investigates constraint handling, surrogate modeling, and parameter adaptation mechanisms. His work bridges theoretical analysis and practical applications in image processing, tone mapping, and robotics. Recent publications show a strong trend toward surrogate-assisted optimization, constrained evolutionary algorithms, and applications in computer vision and graphics. His work is consistently published in top venues such as GECCO, PPSN, and IEEE Transactions on Evolutionary Computation. Scientific Awards: Best Paper Award, Continuous Optimization Track, GECCO 2015 Best Paper Award, ES/EP Track, GECCO 2013 Best Paper Award, PPSN XII 2012 Best Paper Award, ES/EP Track, GECCO 2010 Best Paper Award, PPSN IX 2006 Best Student Paper Award, ACM Symposium on Document Engineering 2014 Arnold has advised numerous students, many of whom are co-authors on his publications. He has received research grants supporting work in evolutionary computation and optimization, though specific grant details are not listed. He is a key member of research clusters in Human-Computer Interaction, Visualization & Graphics, and Algorithms & Bioinformatics. He leads a research group focused on evolutionary algorithms and optimization, collaborating with researchers such as H.-G. Beyer, N. Hansen, and S. Brooks. Future work includes advancing constrained and mixed-integer evolutionary optimization, improving surrogate models, and expanding applications in computer vision and HCI.

• Evolutionary Computation
• Optimization
• Constraint Handling
• +۱۲ مورد دیگر

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.

• Visual Text Analytics
• Modelling and Mining of Networked Information Spaces
• Text Mining
• +۸ مورد دیگر

Dr. Orland Hoeber is a Professor and Head of the Department of Computer Science at the University of Regina. He holds a Ph.D. in Computer Science from the University of Regina, and his research focuses on developing visual and interactive tools for information exploration in digital libraries and mobile search environments. His work bridges information retrieval, human-computer interaction, and data visualization to support complex search tasks. Education: Ph.D. Computer Science, University of Regina (2007) M.Sc. Computer Science, University of Saskatchewan B.Sc. Mathematics, University of Saskatchewan Dr. Hoeber's research examines how people interact with information systems, with particular emphasis on visual interfaces that support exploratory search behaviors. His lab investigates novel approaches to representing search results, understanding mobile search interruptions, and analyzing social media data for sport analytics. Recent work explores cross-device search patterns in academic contexts and interface designs that facilitate serendipitous discovery. His publications demonstrate a consistent focus on human-centered approaches to information system design, with recent work examining multimodal evaluation techniques and search behavior in digital humanities. Article keywords frequently include information retrieval, visualization, and interactive systems, reflecting his interdisciplinary approach. Dr. Hoeber actively mentors graduate students and postdoctoral fellows in his research group, supervising projects on exploratory search behavior, information visualization, and user interface evaluation. He has served as Associate Head (Graduate) and currently leads the Department of Computer Science.

• Interactive Information Retrieval
• Information Visualization
• Human-Computer Interaction
• +۳ مورد دیگر

Dr. Enayat Rajabi is an Associate Professor of Business Analytics at the Shannon School of Business, Cape Breton University. Holding a PhD in Information and Knowledge Engineering from the University of Alcala (Spain) and a postdoctoral fellowship from Dalhousie University, his research focuses on the intersection of Machine Learning, Knowledge Graphs, and Data Analytics. He actively applies these technologies in healthcare, smart cities, and social media crisis response contexts. Education PhD in Information and Knowledge Engineering, University of Alcala (Spain) Postdoctoral Fellowship, Dalhousie University Research Interests His work bridges Knowledge Graphs with Machine Learning, emphasizing explainability and practical applications. Key areas include: Explainable AI for clinical decision-making Knowledge Graph applications in healthcare systems Social media analytics for emergency response Smart city data integration Generative modeling for tabular data Recent Publications Trends Recent articles highlight: Explainable AI in healthcare settings Industrial breakdown prediction systems Social media influencer detection Smart city infrastructure modeling Advanced data synthesis techniques Continued focus on Knowledge Graph applications

• Machine Learning
• Knowledge Graphs
• Data Analytics
• +۳ مورد دیگر

John K. Tsotsos is a Distinguished Research Professor at York University's Lassonde School of Engineering, holding positions in both the Department of Electrical Engineering & Computer Science and the Centre for Vision Research (CVR). His work bridges computer science, cognitive science, and neuroscience with a focus on visual attention and active vision systems. Dr. Tsotsos's research interests center on visual attention mechanisms, active visual search, and visuospatial reasoning. His work explores how humans and machines process visual information, with applications in autonomous driving, robotics, and human-computer interaction. He investigates the computational principles underlying visual attention, comparing biological systems with artificial implementations. His research has significant implications for developing more human-like computer vision systems that can effectively navigate and interpret complex visual environments. Analysis of his recent publications reveals a strong focus on active vision systems where observers dynamically control their viewpoints during visual search tasks. His work spans both theoretical foundations of visual attention and practical applications in autonomous vehicles. A significant portion of his recent research addresses driver attention modeling, gaze prediction, and the challenges of real-world visual processing where traditional computer vision approaches often fail. His work consistently bridges cognitive theory with practical engineering applications. Dr. Tsotsos has made substantial contributions to the field of computational vision through his theoretical work on attentional mechanisms and their implementation in artificial systems. His research has influenced both academic understanding of visual processing and practical applications in autonomous systems and human-machine interfaces. As a faculty member at York University, Dr. Tsotsos contributes to the vibrant research ecosystem of the Centre for Vision Research, where interdisciplinary teams work on cutting-edge problems in visual perception, cognitive modeling, and machine vision. His work exemplifies the integration of cognitive science principles with advanced computational techniques to solve complex visual processing challenges.

• Computer Vision
• Visual Attention
• Active Visual Search
• +۵ مورد دیگر

Dr. Shepherd Steiner is an Associate Professor at the School of Art, University of Manitoba . His research spans literary theory, philosophical aesthetics, and the intersection of modernism with contemporary art practices, focusing on projection, identity, and ethics in artistic works. Education: PhD and MA from the University of British Columbia; BA (Specialization) from the University of Alberta. His scholarship explores how micro-level artistic interpretations are shaped by broader political dynamics, particularly through the concept of teleopoiesis . He is authoring The Outsides of Photography , analyzing contemporary photographic practices, and has published extensively on figures like Rodney Graham, Frank Stella, and Helen Frankenthaler. His publications (2013–2009) reveal a focus on formalism, political art, and photographic theory, with notable contributions to debates around modernism’s legacy and socially engaged art. Awards include SSHRC grants , Mondrian Fonds support, and Premiers Research Excellence Awards . Advisory Roles: Van Abbe Museum (2006–present), Rijksakademie (2007–present). Lectures: Delivered at institutions like UC Berkeley, University of London, and MIT Press events.

• Literary Theory
• Philosophical Aesthetics
• Modernist Art
• +۷ مورد دیگر