جست‌وجوی استاد و پژوهشگر

Leah Macfadyenمشاهده پروفایل

عضو هیئت علمی

• Critical Intercultural Studies
• Digital Literacies
• Digital Research Methods
• +۶ مورد دیگر

Leah Macfadyen is an Associate Professor of Teaching in the Department of Language & Literacy Education at the University of British Columbia (UBC), Faculty of Education. She serves as Coordinator for Curriculum & Instruction in the Master of Educational Technology (MET) program. With interdisciplinary training in experimental sciences and humanities, she bridges analytical rigor with cultural theory in her research on digital education and learning analytics. Her research spans learning analytics , digital literacies , and critical intercultural communication . Key projects include developing UBC’s Introduction to Global Citizenship online course (2005) and co-authoring MET program courses like ETEC 542. She explores ethical dimensions of ‘big data’ in education and data literacy challenges. Recent publications (2020–2023) focus on institutional learning analytics frameworks, curriculum NLP analysis, and ethical codes for practitioners. Collaborative work with Shane Dawson and others has been published in journals like Journal of Learning Analytics , Computers & Education , and Journal of Genetic Counselling . Key Themes : Intercultural communication in digital spaces, systems thinking for educational analytics, ethical implications of data-driven learning Courses Developed : ETEC 500, 520, 542, 543, 581, and 590

Lianne Lefsrudمشاهده پروفایل

دانشیار

• Risk Management
• Sustainability
• Organizational Theory
• +۵ مورد دیگر

Lianne Lefsrud serves as Associate Professor and Risk, Innovation, and Sustainability Chair (RISC) in the Department of Chemical and Materials Engineering at the University of Alberta's Faculty of Engineering. Her interdisciplinary research bridges engineering, social sciences, and policy to transform risk management practices across energy, mining, construction, and railroading industries, directly influencing regulations, building codes, and industry operations for sustainable development. Her academic credentials include: BSc in Civil Engineering (Cooperative Program), University of Alberta (1994) MSc in Interdisciplinary Civil & Environmental Engineering and Sociology, University of Alberta (1996) PhD in Strategic Management and Organization, Alberta School of Business (2014) Dr. Lefsrud's research centers on risk management frameworks for sustainability challenges. She examines hazard identification, social license to operate, and technology adoption drivers in high-hazard industries, with emphasis on prospective risk assessment (e.g., hydrogen infrastructure design) and retrospective analysis (e.g., microplastic pollution impacts). Her work integrates circular economy principles into energy systems while addressing unintended consequences across UN Sustainable Development Goals. Recent publications (2024-2025) demonstrate heavy focus on machine learning applications for rail and construction safety, hydrogen infrastructure risk analysis, and science denial mitigation. Key patterns show cross-industry adaptation of AI for incident prediction, regulatory gap analysis for emerging energy systems, and socio-technical approaches to reconcile sustainability goals with operational realities. Scientific recognition includes: Erb Post-Doctoral Fellowship (University of Michigan) Dow Sustainability Research Fellowship (Ross School of Business) Dr. Lefsrud mentors graduate students through industry-integrated projects like her Sustainable Design course where teams generated patents and city solutions. Her research secures Alberta Innovates funding with 1:4 industrial-to-federal matching, collaborating with Suncor, Transport Canada, and Canadian Standards Association. Grants target practical implementations including railcar inspection systems and hydrogen safety protocols. She co-founded Insight Risk Systems and leads the Lefsrud Lab, prioritizing inclusive teams with under-represented groups (women, Indigenous, LGBTQ2S+, neurodiverse) to tackle 'wicked problems' in sustainability. The lab leverages interdisciplinary partnerships across engineering, computer science, psychology, and environmental sociology for real-world risk management solutions.

Yang Wangمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Domain Adaptation
• +۳ مورد دیگر

Dr. Yang Wang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on computer vision and machine learning, with a particular emphasis on domain adaptation, meta-learning, and privacy-preserving techniques. He actively advises prospective graduate students through a dedicated webpage outlining application procedures. Research interests include few-shot learning, test-time adaptation, and cross-modal applications such as handwritten text recognition and gaze estimation. His work explores how models can adapt dynamically to new domains using limited labeled data, with applications in crowd counting, medical data analysis, and cybersecurity. He also investigates privacy-preserving methods for deep learning models to protect user attributes and sensitive information. Recent publications highlight advancements in meta-auxiliary learning frameworks and efficient user adaptation techniques. His contributions span journals and conferences, showcasing innovations in both foundational machine learning methodologies and real-world applications.

Snigdha Chaturvediمشاهده پروفایل

دانشیار

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۸ مورد دیگر

Snigdha Chaturvedi is an Associate Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. She previously held faculty positions at the University of California, Santa Cruz, and has conducted postdoctoral research at the University of Pennsylvania and University of Illinois, Urbana-Champaign. PhD in Computer Science from University of Maryland, College Park Bachelor's degree in Computer Science and Engineering from Indian Institute of Technology (IIT) Kanpur Her research spans Natural Language Processing with emphasis on Narrative Understanding , Text Summarization , and Socially Aware Language Generation . She advances Fairness in AI through ethical NLP applications in Mental Health and Educational Technology . Recent work focuses on 2025 publications in ACL and NAACL journals, alongside 2024 contributions to EMNLP Findings and ICLR . Earlier projects include the NarraSum dataset (2022) and MOOC forum analysis (2020). Scientific recognitions include: ACM Student Research Competition First Place (2014) IBM PhD Fellowship (2014-2015, renewed in 2015) Kulkarni Summer Research Fellowship (2015) WPI STEM Faculty Launch Program Participant (2015) Her team has advised 13 PhD and Master's students with notable placements at Bloomberg, AI2, and University of Southern California. Research integrates Accessibility challenges through collaborations with Google and IBM labs.

James Chlupمشاهده پروفایل

دانشیار

• Roman History
• Greek and Latin Historiography
• Ancient Military Manuals
• +۲ مورد دیگر

James Chlup is an Associate Professor at the University of Manitoba , where he teaches in the Department of Classics within the Faculty of Arts . His academic career spans multiple institutions, having earned a PhD in Latin from Durham University, an MA in Ancient History from Dalhousie University, and a BA (Honours) in Classics from the University of New Brunswick. Specializes in Roman history (Middle to Late Republic, 250-30 BCE) Research focuses on Greek/Latin historiography, military manuals, and biographical traditions Currently working on a commentary of Plutarch's Life of Crassus and related articles on Frontinus, Appian, and Roman decapitation practices Chlup's publications reveal particular interest in ancient military theory, exempla tradition, and intertextual relationships between Plutarch's Lives. He has co-edited volumes on Greek and Roman military manuals while maintaining active research into Roman imperialism and its literary representations. His work frequently bridges classical texts with contemporary political theory frameworks. As a member of the Department of Classics, Chlup teaches diverse courses spanning: Greek and Roman mythology Ancient history surveys Latin language instruction (beginner to advanced) Specialized seminars on Roman Republic topics

Rohan Alexanderمشاهده پروفایل

استادیار

• Quantitative Social Science
• Bayesian Methods
• Text as Data
• +۴ مورد دیگر

Rohan Alexander is an Assistant Professor jointly appointed in the Faculty of Information and the Department of Statistical Sciences at the University of Toronto. His research focuses on improving the trustworthiness of data science through rigorous workflows, including reproducibility and bias mitigation. He co-founded The Data Workshop, a platform for data science best practices, and authored Telling Stories With Data , a book emphasizing reproducible methods. Rohan holds a PhD in Economics from the Australian National University, specializing in economic history. Rohan’s academic roles include Assistant Director of CANSSI Ontario and Senior Fellow at Massey College. His teaching includes courses like Experimental Design for Data Science and Worlds Become Data . He actively contributes to interdisciplinary initiatives like the Schwartz Reisman Institute for Technology and Society. His research interests span quantitative social science, Bayesian methods, text analysis, and computational reproducibility. He emphasizes code transparency and testing in data science projects. Rohan’s work addresses challenges in data measurement, such as systematic missingness, and explores AI’s societal impacts through collaborative projects with academia and industry. Rohan is affiliated with the Data Sciences Institute and leads initiatives on reproducibility. His current supervision includes PhD student Ciara Zogheib. His institutional roles extend to strategic projects like the Climate Positive Energy initiative and School of Cities.

• Nanotechnology
• Microfluidics
• Biosensors
• +۶ مورد دیگر

Sushanta Mitra is a Professor in the Department of Mechanical and Mechatronics Engineering and the Executive Director of the Waterloo Institute of Nanotechnology at the University of Waterloo. He holds cross-appointments in multiple research groups and leads the Micro-Nano Scale Transport Lab. His research focuses on nanotechnology, microfluidics, biosensors, and fluid dynamics, with applications in energy systems, biomedical engineering, and soft matter physics. Key research interests include liquid-liquid encapsulation, droplet dynamics, and advanced material characterization. His work spans interdisciplinary areas such as graphene physics, catalysis for fuel cells, and sensor development for medical diagnostics. He has pioneered techniques like magnetic manipulation of hydrogels and multilayer liquid encapsulation, with applications in drug delivery and environmental monitoring. Recent publications highlight innovations in biosensing platforms, including SERS-based systems for tuberculosis and glioma detection. His studies on soft interfaces, droplet adhesion, and magnetic actuation contribute to advancements in soft robotics and biomedical devices. Mitra’s lab emphasizes practical applications of nanotechnology to address global challenges in health, energy, and sustainability. No scientific awards are explicitly mentioned in the provided texts. His advising and grants involve collaborations in interdisciplinary projects, though specific details on grants or student advisement are not documented here. The Micro-Nano Scale Transport Lab serves as a hub for cutting-edge research in nanoscale transport phenomena and material science.

Malcolm Heywoodمشاهده پروفایل

استاد

• Genetic Programming
• Coevolution
• Reinforcement Learning
• +۱۲ مورد دیگر

Dr. Malcolm Heywood is a Professor in the Faculty of Computer Science at Dalhousie University, Halifax, Canada. He leads the Network Information Management and Security (NIMS) Lab and is actively involved in research on genetic programming, coevolution, reinforcement learning, and big data analytics. His research interests span: Genetic Programming and Evolutionary Computation Coevolution and Competitive Learning Problem Decomposition and Hierarchical Models Streaming Data Analysis and Anomaly Detection Network Security and Insider Threat Detection Reinforcement Learning in Games (Atari, ViZDoom, Dota 2) Dr. Heywood's recent publications focus on emergent behaviors in reinforcement learning using Tangled Program Graphs (TPG), benchmarking genetic programming for streaming data, and applications in cybersecurity and computational finance. His work demonstrates a strong trend toward scalable, efficient evolutionary models for complex, real-world problems. His scientific awards include: Silver placed at Human-Competitive (Humies) Competition (2018) Best Paper at EuroGP (2017) Best Paper at DETA track, ACM GECCO (2017) Best Paper at RWA track, ACM GECCO (2018) Nomination for Best Paper at DETA track, ACM GECCO (2019) He has supervised numerous graduate students, including PhD and Master's candidates, many of whom have continued research in evolutionary computation. His lab has developed open-source code distributions for Tangled Program Graphs and Symbiotic Bid-Based GP. Dr. Heywood teaches courses in Computer Organization, Introduction to AI with Gaming Applications, and Genetic Algorithms and Programming.

Marta Kryvenمشاهده پروفایل

استادیار

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

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.

Daniel Baumمشاهده پروفایل

استاد پژوهشی

• Scientific Visualization
• Computational Biology
• Image Analysis
• +۶ مورد دیگر

Daniel Baum is a Research Professor and Head of the Visual Data Analysis research group at the Zuse Institute Berlin (ZIB), which is affiliated with Freie Universität Berlin. His work spans across scientific visualization, computational biology, and image analysis, with a particular focus on developing methods for analyzing complex biological structures and neural circuits. He is actively involved in multiple interdisciplinary research projects including HFSP Chitons, Geometric Learning for Single-Cell RNA Velocity Modeling, and RobustCircuit. Dr. Baum's research interests center on visual and data-centric computing approaches to solve complex problems in biology and medicine. His work bridges the gap between computational methods and biological applications, with significant contributions to cryo-electron tomography analysis, neural circuit mapping, and geometric morphometrics. He develops innovative algorithms for 3D reconstruction, image segmentation, and visualization of biological structures, from molecular to organismal scales. His publication record demonstrates consistent contributions to visualization techniques applied to biological problems, with recent work focusing on neural circuit analysis in zebrafish and Drosophila, biomechanical studies of animal structures, and advanced methods for analyzing ancient artifacts. The research shows a clear trajectory toward increasingly sophisticated multimodal data integration and machine learning approaches. Dr. Baum leads a productive research group with several key collaborators who frequently appear as co-authors on his publications, indicating a strong mentoring relationship. His projects involve substantial funding from various sources supporting interdisciplinary collaborations across biology, computer science, and engineering. His laboratory at ZIB focuses on visual data analysis for complex biological systems, with particular strength in developing computational methods for neuroscience applications and biomaterial analysis. The group maintains strong collaborations with multiple institutions working on cutting-edge imaging technologies and biological model systems.

Matthew Brehmerمشاهده پروفایل

استادیار

• Human-Computer Interaction (HCI)
• Data Visualization
• Ubiquitous Information Experiences
• +۵ مورد دیگر

Matthew Brehmer is an Assistant Professor at the University of Waterloo, specializing in Human-Computer Interaction (HCI) and data visualization. His research focuses on ubiquitous information experiences, exploring innovative ways to communicate and collaborate around data through multimodal interfaces and interactive visualizations. He holds a PhD from the University of British Columbia (2016), an MSc (2011), and a BComp from Queen's University (2009). His research interests emphasize multimodal communication , data storytelling , and collaboration platforms . Notable themes include gesture-aware augmented reality video presentations, semantic alignment of text and visual data, and adaptive visualization systems for enterprise environments. He leads efforts in designing tools like RemixTape and VisConductor to enhance data-driven narratives and remote collaboration. Recent work trends highlight advancements in dynamic data presentation , context-aware visualization , and cross-platform integration . His projects address challenges in making data accessible and interactive across diverse user contexts, from mobile devices to enterprise systems. Matthew’s contributions span over 50 peer-reviewed articles, with a focus on IEEE VIS workshops and ACM venues. He actively engages with industry through collaborations on tools like QualDash for healthcare and Charticulator for bespoke chart design.

Vincent Wadeمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۸ مورد دیگر

Professor Vincent Wade is a prominent academic and co-founder of the ADAPT SFI Research Centre, holding the Professorial Chair of Computer Science (established 1990) and a Personal Chair in Artificial Intelligence at Trinity College Dublin's School of Computer Science and Statistics. He co-directs the DREAL Centre for Research Training and leads ADAPT, a globally recognized centre for digital media technology and AI research. His work spans intelligent systems, personalisation, machine learning, and ethical AI applications in healthcare and education. Research interests include AI-driven personalisation, multimodal interaction, knowledge graphs, and ethical considerations in digital technologies. He has published over 350 peer-reviewed papers, earned the prestigious Provost Innovation Award (2018), and holds patents in personalisation technologies. He co-founded EmpowerTheUser, a TCD spin-out focused on simulation-based learning analytics. Major Achievements: 2018 Provost Innovation Award (Trinity College Dublin) 2010 European Language Label Award Fellow of Trinity College Dublin Over 350 scientific publications Key Contributions: Developed the ADELE corpus for social conversation analysis Pioneered cross-site personalisation frameworks Advanced adaptive e-learning systems through platforms like Slicepedia and AMASE His research bridges technical innovation with societal impact, addressing challenges in healthcare, education, and digital ethics.

Christopher Collinsمشاهده پروفایل

استاد

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

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Masoud Makrehchi is an Associate Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University, part of the Faculty of Engineering and Applied Science. His research focuses on Natural Language Processing, Artificial Intelligence, Machine Learning, and Social Computing, with a strong emphasis on applications in network science and moral AI. He holds a PhD from the University of Waterloo (2007), along with earlier degrees from Shiraz University and Iran University of Science and Technology. Prior to academia, he worked as a Senior Research Scientist at Thomson Reuters (2008–2012) and completed a postdoctoral fellowship at the University of Waterloo (2007–2008). His research expertise includes text mining, social network analysis, and network science, addressing challenges such as signed social network analysis, document classification, and crime trend prediction using social media data. He has received several awards, including the NSERC Postgraduate Scholarship and the SBP Challenge Award (2012). His work spans over 50 peer-reviewed publications in journals like Expert Systems with Applications, Social Network Analysis and Mining, and Web Intelligence, with contributions to conferences such as GECCO and IEEE/ACM. Dr. Makrehchi’s publications highlight innovations in feature selection, text segmentation, and AI-driven frameworks for requirements elicitation. His recent work explores coherence graphs for text segmentation, generative AI in education, and bias detection in medical datasets. He has also contributed to patent applications related to sentiment analysis and text extraction systems.

Stan Matwinمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Stan Matwin is a Professor and Director of the Institute for Big Data Analytics at the Faculty of Computer Science, Dalhousie University. He is also affiliated with the Institute for Computer Science of the Polish Academy of Sciences. Previously, he was a Distinguished University Professor at the University of Ottawa and has held academic positions at Warsaw University, University of Guelph, Acadia University, and visiting roles across the U.S., Europe, and Latin America. His educational background includes a Ph.D. from Warsaw University (1977) and a D.Sc. (habilitation) from the Polish Academy of Sciences (2010). Stan Matwin's research focuses on Artificial Intelligence , Machine Learning , Data Mining , Text Mining and Analytics , Big Data , and Data Privacy . He is internationally recognized for pioneering work in visual text analytics and the application of machine learning to real-world data challenges. His work bridges academic research and industrial innovation, particularly in technology transfer and data-driven applications. The publications linked from his profile are inaccessible due to a server restriction (403 Forbidden), but he is known to have authored or co-authored over 250 research papers in top-tier venues. Scientific Awards and Honors: Canada Research Chair (Tier 1) in Visual Text Analytics Fellow of the European Coordinating Committee on Artificial Intelligence (ECCAI) Fellow of the Canadian Artificial Intelligence Association (CAIAC) Ontario Champion of Innovation Stan Matwin has secured significant research funding from organizations including the Canada Research Chairs program, Canada Foundation for Innovation (CFI) , NSERC , Ontario Centres of Excellence , and the Canadian Bureau for International Education . He has supervised numerous graduate students and led major research initiatives. He was former president of the Canadian Artificial Intelligence Association (CAIAC) and IFIP Working Group 12.2 on Machine Learning. He is also an active innovator, co-founding technology companies such as Distil Interactive Inc. and Devera Logic Inc. He leads the Big Data Analytics, AI & Machine Learning research cluster at Dalhousie and continues to be a key figure in advancing data science research and training through the Institute for Big Data Analytics.