جست‌وجوی استاد و پژوهشگر

Judith Ellen Fanمشاهده پروفایل

استادیار

• Cognitive Science
• Artificial Intelligence
• Data Visualization
• +۵ مورد دیگر

Judith Ellen Fan is a Courtesy Assistant Professor at Stanford University, holding primary appointment in the Department of Psychology and courtesy appointments in the Graduate School of Education and the Department of Computer Science. She directs the Cognitive Tools Lab, focusing on how humans use physical representations to learn, communicate, and solve problems through interdisciplinary approaches combining cognitive science, computational neuroscience, and AI. Her research interests span cognitive tool development, data visualization literacy, educational technology, and developmental psychology. Key areas include understanding how drawing and sketching shape memory and conceptual representation, evaluating machine comprehension of visual and physical concepts, and designing human-centered AI systems. Recent work emphasizes benchmarking human and machine abilities in physical dynamics understanding (Physion++), evaluating data visualization literacy (CHART-6), and analyzing large-scale drawing datasets (THINGS-drawings). These projects bridge cognitive science with AI to advance both fields through shared benchmarking frameworks. Judith has received funding for projects on cognitive tool development and human-AI collaboration. Her lab collaborates across disciplines, emphasizing empirical studies with human participants and algorithmic benchmarking. Notable datasets include the 1,854-concept THINGS-drawings collection and Physion++ physical prediction benchmarks.

• Data mining
• Reverse engineering
• Machine learning
• +۱ مورد دیگر

Mohammadhossein Amouei is a researcher and lecturer affiliated with McGill University's School of Information Studies. He holds the role of Course Lecturer for INFS 691: Computer Programming for Information Professionals. His primary research interests span data mining, reverse engineering, machine learning, and cybersecurity. He is affiliated with research labs including the Data Mining & Security Lab and the Accessible Computing Technology Research Group Lab. His educational background includes PhD candidacy at McGill University. Recent research focuses on reinforcement learning-driven vulnerability discovery in cybersecurity and natural language generation for assembly code documentation. He has contributed to federated learning security through game-theoretic frameworks. Advising and grants information is not explicitly detailed in available texts. He maintains an active presence on LinkedIn and GitHub, and his work bridges theoretical computer science with practical security applications.

Signy Sheldonمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Behavioural Neuroscience
• Episodic Memory
• +۵ مورد دیگر

Signy Sheldon is an Associate Professor in the Department of Psychology at McGill University, specializing in cognitive and behavioral neuroscience. Her research focuses on understanding the neural mechanisms of episodic memory, including how the hippocampus and related structures support memory retrieval, imagination, and problem-solving. She also explores how aging and individual differences influence memory processes. Sheldon uses behavioral experiments, neuroimaging (fMRI), and patient studies to investigate memory's role in non-mnemonic functions like creativity and decision-making. Her work highlights the interplay between memory and broader cognitive abilities, such as schema formation and context processing. She leads the Sheldon Memory Lab , which employs multidisciplinary approaches to study memory's neural underpinnings. Though no specific awards are listed, her extensive publications reflect her contributions to memory science. No advising or grant details are provided in the text. Research interests span episodic memory, cognitive aging, neuroimaging, and the application of NLP to memory narratives. Her lab's work often addresses translational questions, such as using memory reconstruction to address clinical issues like social anxiety.

Frank Woodمشاهده پروفایل

دانشیار

• Probabilistic Programming
• Deep Generative Models
• Reinforcement Learning
• +۴ مورد دیگر

Frank Wood is an Associate Professor of Computer Science at the University of British Columbia and a Canada CIFAR AI Chair at AMII. He directs the Pacific Laboratory for Artificial Intelligence (PLAI) research group and co-founded Inverted AI, a spin-out focused on advanced simulation for autonomous vehicles. His research focuses on probabilistic programming, deep generative models, and reinforcement learning, with applications in autonomous driving, robotics, and vision. Wood teaches courses such as Machine Learning and Data Mining (CPSC 340) and Topics in Artificial Intelligence (CPSC 532W). He has been on academic leave from January to December 2025. His work integrates theoretical advancements with practical applications, including projects like PLAICraft, a large-scale embodied AI dataset. Key awards include the ICML Best Paper Honourable Mention and contributions to probabilistic programming systems like Anglican. His research group collaborates on tools such as TorchDriveEnv for autonomous driving benchmarking and explores cutting-edge methods in diffusion models and continual learning.

• History of Philosophy
• Logic/Philosophy of Logic
• Philosophy of Religion
• +۳ مورد دیگر

Dr. Anders Kraal is a Lecturer in the Department of Philosophy at the University of British Columbia (UBC), part of the Faculty of Arts. He joined UBC in 2015 and specializes in the history of philosophy, logic/philosophy of logic, and philosophy of religion. His research focuses on figures like David Hume, Søren Kierkegaard, and Bertrand Russell, particularly addressing the Problem of Evil and early modern philosophical writings. His teaching includes courses such as Introduction to Philosophy, Epistemology, Medieval Philosophy, and specialized topics in early modern thought. He maintains an active research profile with publications in prestigious journals and edited volumes, exploring themes ranging from Hume’s religious skepticism to logical formalization in theology. Kraal’s work bridges historical analysis with contemporary philosophical debates, emphasizing textual interpretation and contextual understanding. While no awards are explicitly listed, his scholarly contributions reflect sustained engagement with foundational issues in philosophy of religion and early modern thought.

Juha Joenvääräمشاهده پروفایل

دانشیار

• Finance
• Asset Management
• Hedge Funds
• +۵ مورد دیگر

Juha Joenväärä is an Associate Professor of Finance at Aalto University's School of Business, Department of Finance. His research focuses on hedge fund performance, asset management strategies, and institutional investment dynamics. He has published extensively on topics such as hedge fund allocation, climate-related financial risks, private equity trends, and investor behavior. His work bridges theoretical finance with practical applications in portfolio optimization and risk management. Key research themes include analyzing hedge fund performance persistence, evaluating the impact of regulatory constraints on investment strategies, and exploring behavioral aspects of financial decision-making. He has contributed to debates on the efficacy of socially responsible investments and the evolving landscape of private equity markets. Dr. Joenväärä holds a prominent role in academic discourse through his publications in top-tier journals and presentations at conferences like the Aalto Institutional Investments Conference and Lapland Investment Summit. His work emphasizes data-driven approaches to understanding complex financial systems and investor behaviors.

Julia Cassanitiمشاهده پروفایل

استاد

• Cultural Anthropology
• Religious Studies
• Mind and Culture
• +۴ مورد دیگر

Julia Cassaniti is a Professor in the Department of Religious Studies at the University of Virginia, part of the College of Arts & Sciences. Her research focuses on the intersections of mind, culture, and religion in transnational Asian contexts, particularly Theravāda Buddhist practices in Northern Thailand. She examines how embodiment, gender, sexuality, and cultural ideologies shape health, well-being, and perceptions of reality. Her notable works include Remembering the Present: Mindfulness in Buddhist Asia (2018), Universalism Without Uniformity: Explorations in Mind and Culture (2017), and Living Buddhism: Mind, Self, and Emotion in a Thai Community (2016), which received the Stirling Prize. Current research explores temporality, attention, and perception’s impact on mental health and daily life in Thailand, Japan, and globally. Her publications frequently analyze Buddhist frameworks for understanding social and personal challenges, such as environmental crises, pandemic responses, and economic shifts. She critiques secular mindfulness movements while advocating for culturally grounded interpretations of spiritual practices. Awards: Stirling Prize (2016), Richard G. Condon Prize (2006) Labs/Teams: Active in UVA’s Religious Studies research network and international collaborations on Southeast Asian studies

• Image and Video Processing
• Multimedia Analysis
• Computer Vision
• +۵ مورد دیگر

Prof. Tan Yap Peng is a Professor and Chair of the School of Electrical & Electronic Engineering at Nanyang Technological University (NTU), Singapore. He holds the President's Chair in Electrical and Electronic Engineering and serves as Associate Vice President (Lifelong Learning – Postgraduate Programmes by Coursework). His research focuses on multimedia analysis, computer vision, machine learning, and data analytics. He earned his B.S. from National Taiwan University and M.A./Ph.D. from Princeton University. He has led major initiatives including the INFINITUS Infocomm Research Centre and contributed to IEEE technical committees. His over 200 publications span image/video processing, neural network robustness, and cross-modal systems. Awards include IEEE Fellow status. Education: B.S. Electrical Engineering (NTU), M.A./Ph.D. (Princeton) Research interests emphasize interactive digital media, content-based analysis, and AI-driven solutions for visual and signal processing. His work addresses challenges in adversarial attacks, video generation, and low-light image enhancement. He has held editorial roles at IEEE Transactions and EURASIP journals. Conference leadership includes chairs for ICME and ICIP. His contributions bridge academia and industry through collaborative research networks.

Alec Marantzمشاهده پروفایل

استاد

• Neurolinguistics
• Morphology
• Syntax
• +۳ مورد دیگر

Alec Marantz is a Silver Professor of Linguistics and Psychology at New York University's College of Arts & Science. He joined NYU in 2006 from MIT, where he served as Department Head and Kenan Sahin Distinguished Professor. As Chair of NYU's Linguistics Department (2007–2013), he co-founded the Distributed Morphology theory. His research bridges linguistics, psychology, and neuroscience, focusing on morphology, syntax, and neurolinguistics. His work uses MEG neuroimaging to study how language is processed in the brain, emphasizing cross-linguistic studies (e.g., Arabic, Hindi). He directs the Neuroscience of Language Lab (NeLLab), exploring neural correlates of linguistic structure and computations. Marantz's research highlights language universals and the brain's mechanisms for processing complex linguistic structures. His key contributions include pioneering the 'full decomposition' model of morphological complexity and advancing MEG methods for studying language. NeLLab's Abu Dhabi branch focuses on understudied languages like Arabic, enhancing cross-linguistic understanding. Marantz's work integrates theoretical linguistics with empirical neuroimaging, addressing how syntax and morphology are represented neurally. His research spans topics such as word structure, predictive processing, and the neural basis of language acquisition. Marantz has advised numerous researchers and contributed to interdisciplinary collaborations. His labs investigate language processing across modalities (speech production, listening, reading), emphasizing both cognitive and neural mechanisms. Recent studies explore how the brain predicts linguistic structure and handles ambiguity. While no formal awards are listed, his global influence and foundational work in neurolinguistics are widely recognized. Future directions include expanding cross-linguistic studies and refining MEG techniques to map language-specific neural signatures. His work continues to bridge generative linguistics with empirical neuroscience, offering insights into the biological foundations of language.

Willem Heijltjesمشاهده پروفایل

مدرس ارشد

• Logic
• Proof Theory
• Lambda-Calculus
• +۳ مورد دیگر

Willem Heijltjes is a Senior Lecturer in the Department of Computer Science at the University of Bath. His research focuses on logic and proof theory, particularly on canonical graphical representations of proofs (proof nets) and their applications in lambda-calculus and type systems. He is actively involved in theoretical computer science, exploring foundational aspects of programming languages and computational logic. He leads the project 'Typed Lambda-Calculi with Sharing and Unsharing', funded by the Engineering and Physical Sciences Research Council (EPSRC) from 2019 to 2022. This project investigates advanced type systems and computational models, contributing to the understanding of call-by-value and call-by-name evaluation strategies in the context of linear logic and sequent calculus. His research interests span lambda-calculus, linear logic, proof nets, type systems, and programming language semantics. He has published extensively in top-tier conferences such as CSL, FSCD, and LICS, addressing topics like probabilistic termination, functional machine calculus, and normalization without syntax. He is currently accepting doctoral students in these areas. Heijltjes collaborates internationally on foundational computer science topics, including the development of combinatorial proofs and the exploration of confluence in higher-order rewriting systems.

Rachel Dudleyمشاهده پروفایل

استادیار

• Language Acquisition
• Semantic Development
• Pragmatic Competence
• +۵ مورد دیگر

Rachel Dudley is an Assistant Professor in the Department of Linguistics at the University of California San Diego. She holds a BA in Linguistics from New York University and a PhD from the University of Maryland. Her research focuses on understanding how children develop semantic and pragmatic competence through language acquisition, integrating insights from linguistics, psychology, and philosophy. Education: B.A., Linguistics, New York University Ph.D., Linguistics, University of Maryland Research Interests: Rachel investigates the cognitive mechanisms underlying children's acquisition of complex linguistic concepts such as propositional attitudes, presupposition triggers, and thematic relations. Her work employs diverse methodologies including behavioral experiments with children/adults, infant eye-tracking, and corpus analyses of naturalistic speech. She explores how environmental input interacts with innate linguistic capacities to shape developmental trajectories. Awards: No specific awards listed in provided texts. Advising & Grants: No student advisees or grant information explicitly mentioned. Previously held postdoctoral fellowships at the Cognitive Development Center (Central European University) and the Institut Jean Nicod (Ecole Normale Supérieure). Labs/Teams: Active in UC San Diego's Department of Linguistics research community, though no specific lab affiliation listed.

Ken Barkerمشاهده پروفایل

استاد

• Computer Science
• Data Security
• Distributed Systems
• +۷ مورد دیگر

Ken Barker is a Professor and Director of ISPIA at the University of Calgary's Department of Computer Science within the Faculty of Science. He holds a Ph.D. from the University of Alberta (1990) and has extensive experience in industrial computer systems and database design. His research focuses on distributed systems, data privacy/security, bioinformatics, and heterogeneous systems. He has served as Dean of the Faculty of Science, Department Head of Computer Science, and Past President of the Canadian Association of Computer Science (CACS/AIC). His work emphasizes privacy-preserving technologies, blockchain applications, and event understanding systems. Barker has published over 200 peer-reviewed papers across domains like transaction systems, spatial databases, and astro-informatics. He advocates for balancing data utility with privacy through frameworks like the Privacy Policy Permission Model. His contributions include the CHRONOS event prediction system and blockchain-based platforms for secure data storage.

Breanne Wylieمشاهده پروفایل

استادیار

• Developmental Psychology
• Forensic Psychology
• Child Witness Testimony
• +۳ مورد دیگر

Breanne Wylie is an Assistant Professor in the Department of Psychology at NC State University’s College of Humanities and Social Sciences. Her research focuses on adult-child communication within legal contexts, particularly improving children’s accurate reporting of maltreatment experiences during interviews by legal professionals. She employs multi-method approaches including lab-based tasks to assess linguistic development and field-based analysis of child witness testimonies. Dr. Wylie emphasizes knowledge mobilization, collaborating with practitioners to provide evidence-based training. Her research interests span developmental psychology, forensic psychology, and legal communication. She investigates how children’s cognitive and linguistic abilities influence their interactions with legal systems, aiming to enhance forensic interviewing practices and reduce misunderstandings in judicial contexts. Key areas include the impact of question phrasing, parental support roles, and jurors’ perceptions of child testimony credibility. Recent publications (2025-2023) highlight trends in analyzing defense attorneys’ questioning tactics, improving forensic interviewer training, and exploring how language nuances affect child witnesses’ reliability. Her work underscores the need for standardized, developmentally appropriate legal questioning methods to protect vulnerable populations. As part of the Lifespan Developmental Psychology group, she operates the Law Development Lab to bridge academic research and practical legal applications. While no formal awards are listed, her contributions reflect a commitment to impactful, applied research. Grant and advising specifics are not detailed in the provided text.

Thomas Lengauerمشاهده پروفایل

استاد

• Computational Biology
• Bioinformatics
• Applied Algorithmics
• +۱۰ مورد دیگر

Prof. Dr. Thomas Lengauer is a leading figure in computational biology and applied algorithmics at the Max Planck Institute for Informatics, part of the Max Planck Society in Saarbrücken, Germany. He heads the Department of Computational Biology and Applied Algorithmics, where he drives research at the intersection of computer science, genomics, and medicine. His work integrates algorithm development with biological applications, particularly in viral genomics, epigenetics, and personalized treatment prediction. Research Interests: His research focuses on computational methods for analyzing complex biological data. Key areas include HIV and hepatitis virus evolution, antiretroviral therapy outcome prediction, DNA methylation and epigenomic analysis, machine learning applications in medicine, and the integration of big data in biological research. He has made significant contributions to understanding viral drug resistance and host-pathogen interactions through computational modeling. The recent publications (2019–2025) reflect a strong trend toward integrating temporal genomic data, machine learning, and public health surveillance. His work spans from fundamental algorithm development (e.g., RnBeads, MeDeCom) to applied clinical research (e.g., dolutegravir resistance, SARS-CoV-2 interventions). Key domains include epigenomics , virology , machine learning in healthcare , and biological database systems , increasingly incorporating AI-driven approaches. Scientific Awards: No specific awards are mentioned in the provided text. Advising and Grants: While no formal list of students is provided, Prof. Lengauer leads a large collaborative research group, evidenced by frequent co-authorship with researchers such as Walter, Bock, Müller, Kaiser, and Pirkl. He participates in major consortia (e.g., DEEP Consortium, Respiratory Virus Network), suggesting leadership in funded collaborative projects. His work is likely supported by Max Planck Society core funding and competitive third-party grants, though specific grants are not listed. Labs and Teams: He leads the Computational Biology and Applied Algorithmics group at the Max Planck Institute for Informatics. The team develops computational tools for epigenomic data analysis (e.g., RnBeads, DecompPipeline), viral resistance prediction, and public health modeling. The group collaborates extensively with clinical and biological researchers across Europe, functioning as a hub for interdisciplinary bioinformatics research.

Christos Thrampoulidisمشاهده پروفایل

استادیار

• Machine Learning
• Deep Learning Theory
• Mathematical Optimization
• +۴ مورد دیگر

Christos Thrampoulidis is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), Vancouver. Previously, he held positions at the University of California, Santa Barbara (UCSB). His research focuses on machine learning theory, deep learning principles, mathematical optimization, and statistical signal processing. He leads the Machine Intelligence and Learning Design (MILD) group at UBC, emphasizing foundational studies of large language models, neural collapse, and high-dimensional data analysis. Education: PhD and MS in Electrical Engineering from the California Institute of Technology (Caltech), with a minor in Applied and Computational Mathematics. Undergraduate degree (Diploma) in Electrical and Computer Engineering from the University of Patras, Greece. Research interests include the implicit geometry of next-token prediction, optimization bias in neural networks, and robust generalization in overparameterized models. Key contributions include work on adversarial training, neural collapse phenomena, and safe reinforcement learning. His group actively explores theoretical frameworks for language models and develops methodologies to analyze their mechanics and limitations. Awards: NSERC Discovery Grant (2021). Teaching includes courses on optimization and signals & systems at UBC. He has advised numerous graduate students (PhD and MSc) and undergraduates, focusing on rigorous mathematical approaches to machine learning problems. Active collaborations span academia and industry, with publications in top venues such as NeurIPS, ICASSP, and AAAI. Current projects include understanding language model geometry, decentralized learning, and mitigating imbalances in training data. The group prioritizes equity and diversity, welcoming students with strong mathematical backgrounds and curiosity about foundational ML questions.