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Chris BryanView profile

Assistant Professor

• Data Visualization
• Human-Computer Interaction
• Data Storytelling
• +6 more

Chris Bryan is an Assistant Professor in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University (ASU), part of the Ira A. Fulton Schools of Engineering. He leads the Sonoran Visualization Laboratory (SVL @ ASU), focusing on data visualization, human-computer interaction, and advanced interfaces for data science. His research includes explainable AI, augmented/virtual reality, and privacy-preserving visualization techniques. Educations: Ph.D. Computer Science, University of California, Davis (2018) B.S. Computer Science, University of Arkansas (2008) Research Interests: Bryan’s work spans data visualization, human-computer interaction, explainable AI, and immersive visualization. He develops tools for collaborative analysis, privacy-aware systems, and visual analytics for complex data. Current projects involve VR/AR interfaces, bias reduction in NLP tasks, and educational visualization tools. Recent Achievements: Recipient of the 2024 and 2023 Top Five Percent Faculty Award at ASU’s Ira A. Fulton Schools of Engineering. NSF grants for privacy-preserving visualization (SaTC #2224066) and visualization education (IUSE #2216452). Multiple publications in top venues like IEEE VIS, CHI, and EuroVis, including work on differential privacy, mind wandering in visualization, and LLM prompt exploration. Advising & Grants: Advises Ph.D., MS, and undergraduate students on visualization and HCI research. Collaborates with institutions like Los Alamos National Laboratory, Phoenix Children’s Hospital, and Nankai University. Lab focuses on mentoring and preparing students for academic and industry roles in visualization and AI. Labs & Teams: Leads the SVL @ ASU, which uses advanced hardware (HTC Vive, HoloLens 2) and tools like D3.js, React, and LaTeX. The lab emphasizes interdisciplinary projects with domain experts in medicine, engineering, and security.

Denise R BeikeView profile

Professor

• Autobiographical Memory
• Emotions
• Regret
• +5 more

Denise R Beike is a Professor in the Department of Psychology within the College of Arts & Sciences at the University of Arkansas. She holds a Ph.D. and B.A. from Indiana University and has been actively contributing to psychological science with a focus on memory and emotion. Her research interests center on autobiographical memory , emotions such as regret and longing , and the interplay between memory and the self . She investigates how people remember personal experiences, how these memories shape identity, and how emotional valence and relational closeness are influenced by memory sharing. The recent publication trends indicate a strong focus on the social and emotional dimensions of memory. Her work explores how sharing specific memories enhances relational closeness, how regret is shaped by missed opportunities, and how closure affects behavior. Themes of self-disclosure, emotional regulation, and memory accuracy recur across her research, often bridging cognitive, social, and clinical psychology. Professor, Department of Psychology, University of Arkansas Ph.D., Indiana University, 1996 B.A., Indiana University, 1990 She has mentored numerous students who appear as co-authors on her publications, indicating active graduate supervision. Her work also touches on research ethics, particularly regarding the treatment of research assistants. While no specific grants are mentioned, her sustained publication record suggests ongoing research activity. Notable collaborative works include the book Memory 101 and co-editing The Self and Memory . Her research has been published in high-impact journals such as Journal of Experimental Psychology: General , Personality and Social Psychology Bulletin , and Memory .

Maura R. GrossmanView profile

Research Professor

• High-Recall Information Retrieval
• AI Ethics
• Electronic Discovery
• +3 more

Maura R. Grossman is a Research Professor at the University of Waterloo, specializing in High-Recall Information Retrieval, AI ethics, and legal technology. Her work focuses on ensuring comprehensive information retrieval in high-stakes contexts like electronic discovery in law, healthcare data curation, and medical evidence synthesis. She explores the intersection of artificial intelligence and legal systems, particularly addressing challenges posed by AI-generated evidence and deepfakes in judicial processes. Education: J.D. (Georgetown University Law Center, 1999), Ph.D. (Adelphi University, 1984), M.A. (Adelphi University, 1982), A.B. (Brown University, 1980). Research interests include AI accountability in courts, responsible data science practices, and improving electronic discovery methodologies. Recent work analyzes AI’s role in legal proceedings, ethical AI frameworks, and healthcare data governance. Her publications emphasize validating technology-assisted review (TAR) systems and evaluating generative AI impacts on marginalized communities. Her articles highlight trends in AI’s legal implications, healthcare data sharing protocols, and the need for transparent algorithmic systems in justice contexts. She contributes to TREC tracks, advancing high-recall retrieval techniques for legal and medical document analysis. Notable projects include developing frameworks for unbiased health data sharing and analyzing AI’s effects on marginalized writers. Her work underscores interdisciplinary collaboration between law, computer science, and healthcare to address emerging technological challenges.

Eugene YangView profile

Researcher

• Information Retrieval
• Cross-Language Information Retrieval
• Multilingual Information Retrieval
• +4 more

Eugene Yang is a Research Scientist at the Human Language Technology Center of Excellence (HLTCOE) at Johns Hopkins University, where he focuses on cross language and multilingual information retrieval, multilingual multimodal report generation, and retrieval-augmented generation systems. He received his Ph.D. in Computer Science from Georgetown University in 2021 under the supervision of Ophir Frieder, David D. Lewis, and Jeremy Fineman. His research spans multiple domains within information retrieval, with particular emphasis on high recall retrieval systems, technology-assisted review frameworks, and multilingual processing. He is the developer of TARexp, an open-source Python framework for Technology-Assisted Review experiments, which demonstrates his commitment to creating practical tools for the research community. Yang's publication record shows a clear trend toward increasingly sophisticated multimodal and multilingual retrieval systems, with his recent work focusing on retrieval-augmented generation evaluation, cross-language model distillation, and modular fusion approaches for complex information needs. His research bridges theoretical advances with practical applications in legal technology, healthcare informatics, and multilingual information access. As an active contributor to the information retrieval community, Yang has presented at numerous conferences including SIGIR, ECIR, and TREC, and has collaborated extensively with researchers across institutions. His work demonstrates a strong commitment to reproducibility and practical evaluation methodologies in information retrieval research.

Dake ZhangView profile

Professor

• Information Retrieval
• Health Informatics
• Artificial Intelligence
• +3 more

Dake Zhang is a faculty member at the David R. Cheriton School of Computer Science, University of Waterloo. His research focuses on reducing health misinformation through search systems, leveraging artificial intelligence and information retrieval techniques to improve online health information quality. Key collaborations with Mark D. Smucker, Amir Vakili Tahami, and Mustafa Abualsaud Active participant in TREC Health Misinformation Tracks (2021-2023) Developed ReadProbe system for lateral reading support using OpenAI models and Bing search His work demonstrates expertise in: Information retrieval systems for health domains Mitigating cognitive biases in search Transformer-based document analysis Automated answer prediction from web sources Search engine credibility modeling Human-AI interaction in information verification

Chad DubéView profile

Associate Professor

• Cognitive Psychology
• Recognition Memory
• Signal Detection Theory
• +7 more

Chad Dubé is an Associate Professor in the Department of Psychology at the University of South Florida, where he has been a faculty member since 2013, advancing from Assistant to Associate Professor in 2019. His research is centered on cognitive psychology, particularly in memory, perception, and decision-making. He completed his Ph.D. and M.S. in Cognitive Psychology at the University of Massachusetts, Amherst, under Caren Rotello, and earned his B.S. in Psychology from Eastern Michigan University. Ph.D., Cognitive Psychology, University of Massachusetts, Amherst (2011) M.S., Cognitive Psychology, University of Massachusetts, Amherst (2009) B.S., Psychology, Eastern Michigan University (2006) His research interests include recognition memory, signal detection theory, ROC analysis, visual short-term memory, alpha oscillations in attention and memory, and deductive reasoning. He employs quantitative and computational modeling approaches to investigate cognitive mechanisms underlying memory and perception. The recent publications reflect a strong focus on theoretical and empirical investigations in memory and perception, particularly using signal detection and computational modeling frameworks. Key themes include central tendency effects, serial dependency, ensemble coding, and the statistical structure of memory representations. His work bridges experimental psychology with formal modeling and information theory. Although no formal awards are listed in the provided text, his publication record in high-impact journals such as Quarterly Journal of Experimental Psychology and Journal of Memory and Language indicates scholarly recognition. Chad Dubé advises graduate and undergraduate students, as indicated by annotations (GA, UA) on his publications. He has collaborated with students such as K. Tong, J. Zepp, and M. Lowry. There is no mention of specific grants or funding sources in the provided text. He previously held a postdoctoral fellowship at Brandeis University’s Volen Center and an adjunct position at Babson College. He is affiliated with the Department of Psychology, which is part of the College of Arts and Sciences at the University of South Florida. His work contributes to the Cognitive and Neural Systems (CNS) specialty area within the department.

Anders LansnerView profile

Professor

• Computational Neuroscience
• Neuromorphic Engineering
• Brain-like Computing
• +4 more

Anders Lansner is a Professor of Computer Science at Stockholm University and holds an affiliated professorship at KTH Royal Institute of Technology. He leads the Lansner Lab (Computational Biology and Neurocomputing) at the Department of Computational Science and Technology (CST) within the School of Computer Science and Communication (CSC) at KTH. His research focuses on computational neuroscience and brain-like computing, emphasizing mathematical and computational models of neuronal networks in the neocortex and basal ganglia. Key projects include developing neuromorphic algorithms for supercomputers and FPGA-based hardware implementations. Lansner manages the computational neuroscience platform for the Stockholm Brain Institute (SBI) and the neuroinformatics platform for StratNeuro (Karolinska Institutet). His lab contributes to EU projects such as FACETS and NEUROChem, and collaborates with KTH’s Electronics Department on modular brain-inspired FPGA designs. Research interests span synaptic plasticity mechanisms, memory systems (episodic, semantic, and working memory), and applications in neuromorphic computing. He supervises graduate students and teaches courses in computational neuroscience. Lansner’s work bridges theoretical neuroscience with engineering, aiming to advance brain-inspired AI and hardware systems. His lab’s StreamBrain framework supports heterogeneous computing architectures for brain-like neural networks. Notable collaborations include cross-disciplinary efforts in neuromorphic hardware development (e.g., memristor-based learning engines) and olfactory system modeling. Lansner’s research addresses both fundamental brain mechanisms and technical applications in data analysis and neurorobotics.

Charan RanganathView profile

Professor

• Human Memory
• Executive Control
• Neuroimaging
• +7 more

Charan Ranganath is a Professor in the Department of Psychology at the University of California, Davis, and director of the Dynamic Memory Lab. He is affiliated with the UC Davis Center for Neuroscience and the Center for Mind and Brain, focusing on human memory and executive control using neuroimaging, electrophysiology, and behavioral methods. His research explores the neural basis of memory, including roles of the prefrontal cortex, medial temporal lobes, and hippocampus in working and long-term memory. Education: Ph.D., Clinical Psychology, Northwestern University M.S., Clinical Psychology, Northwestern University B.A., Psychology, University of California, Berkeley Ranganath’s research spans hippocampal-cortical interactions, curiosity-driven memory enhancement, schizophrenia-related memory deficits, and computational models of memory systems. His work reveals overlapping prefrontal and medial temporal lobe activity in memory tasks and investigates how stress, aging, and neuromodulation affect memory dynamics. His research trends emphasize episodic memory , relational memory , neural oscillations , cortico-hippocampal networks , curiosity-driven learning , and clinical applications in mental illness. Scientific Awards: Guggenheim Fellowship Leverhulme Trust Visiting Professorship Laird Cermak Award Samuel Sutton Award Chancellor’s Fellow award Young Investigator Award (Cognitive Neuroscience Society) National Security Science and Engineering Faculty Fellowship (2015) He has secured grants from the Department of Defense, National Institute of Mental Health, and private foundations. His lab collaborates with Andy Yonelinas on recognition memory and with others on field potentials in hippocampal studies. He teaches Human Learning, Cognitive Neuroimaging, and Current Research in Psychology.

Narine YegiyanView profile

Associate Professor

• Cognitive Information Processing
• Emotion and Memory Interaction
• Media Psychology
• +3 more

Associate Professor Narine Yegiyan serves in the Department of Communication at the University of California, Davis, and directs the Dynamic Interactions in Cognition & Emotion (D.I.C.E.) Lab. She teaches both graduate and undergraduate courses on media-message processing, quantitative research methods, and mass-communication effects. Education Ph.D., Mass Communication, Indiana University, 2008 M.A., Journalism, Indiana University, 2004 B.A., Journalism, 1995 (cum laude) Her scholarship explores how individuals prioritize information under cognitive and emotional overload, integrating neurobiological theories of motivated cognition with psychophysiological and behavioral methodologies. Core themes include the interplay of memory and emotion, visual-message design, and the strategic construction of health and risk communications. Across her 2003–2023 publication record, Yegiyan repeatedly investigates how emotional tone, message structure, motivational activation, and individual differences shape attention, memory, and attitudinal outcomes. Recent work has concentrated on food-cue reactivity under stress, the persuasive efficacy of health PSAs, and the cognitive demands of online news environments. Scientific Awards Distinguished Article Award, Communication and Cognition Division, National Communication Association, 2012 UC Summer Salary Research Grant, 2010 First Place, Interactive Scholar-to-Scholar Paper-Poster Competition, Mass Communication Division, International Communication Association, 2008 Indiana University College of Arts and Sciences Dissertation Year Fellowship, 2006–2007 She mentors students through the D.I.C.E. Lab, where ongoing projects examine motivated cognition in contexts ranging from food marketing to disaster news, supported by intramural UC Davis grants. Future directions include extending psychophysiological measures to immersive media and developing evidence-based guidelines for high-stakes health campaigns. The D.I.C.E. Lab, housed within the Department of Communication, provides state-of-the-art facilities for psychophysiological recording, eye-tracking, and self-report data collection, fostering collaborative research across psychology, neuroscience, and public-health disciplines.

• Creativity Support Tools
• Design Methods
• Design Education
• +4 more

Dr. Haoyu Zuo is a Research Associate at the Dyson School of Design Engineering, Imperial College London, focusing on creativity support tools, design methods, and design education. His work integrates AI technologies like knowledge graphs and large language models (LLMs) to enhance creative problem-solving and innovation in design. He holds a PhD in Design Engineering from Imperial College London (2019–2024) and degrees from Tsinghua University (MSc and BEng). His research emphasizes leveraging AI for impactful design solutions, including projects like B-Link (a semantic network for divergent thinking), WikiLink (encyclopedia-based knowledge retrieval), and AskNatureNet (bio-inspired design platform). Key areas of focus include human-AI collaboration in design, bio-inspired innovation, and educational tools for design reasoning. His work is supported by Innovate UK funding and has contributed to projects such as Eco-Innovation in Retrofit Design and cultural heritage design integration. Notable publications explore AI-driven design methodologies, controllable generative design approaches, and TRIZ-GPT for problem-solving. His research bridges technical innovation with practical design practices, emphasizing both theoretical advancements and real-world applications.

M. R. SauterView profile

Assistant Professor

• History and Philosophy of Technology
• Hacktivism
• Civil Disobedience
• +6 more

M. R. Sauter is an Assistant Professor at the University of Maryland College of Information, specializing in the history and philosophy of technology. Their work examines intersections between high technology, finance, and social justice, with a focus on venture capital's role in shaping innovation ecosystems. They are the author of The Coming Swarm: DDoS Actions, Hacktivism, and Civil Disobedience on the Internet and Risk Capital: How High Finance Remade High Technology (under contract with University of Chicago Press). PhD in Communications Studies, McGill University (2020) Masters in Comparative Media Studies, MIT Research Fellowships: Berkman-Klein Center, New America Research Interests : Sauter investigates corporate influences on digital security and rights through projects on: Venture capital history and mythmaking Public-private partnerships in tech Surveillance capitalism Smart cities ethics Information justice frameworks Recent Publications explore venture capital policy evolution, algorithmic governance, and digital protest tactics across journals like The Atlantic , Journal of Communication , and New Media and Society .

• Cognitive Neuroscience
• Attention
• Working Memory
• +7 more

Anna Christina Nobre is the Wu Tsai Professor of Psychology at Yale University, with a primary appointment in the Department of Psychology at the Yale School of Medicine. She is also affiliated with the Interdepartmental Neuroscience Program, the Wu Tsai Institute, the Yale Biomedical Imaging Institute, and the Yale Combined Program in the Biological and Biomedical Sciences (BBS), reflecting her strong interdisciplinary research profile in cognitive neuroscience. Her research centers on the cognitive and neural mechanisms of attention, working memory, and long-term memory. She investigates how the brain uses spatiotemporal predictions to guide attention, how attention shapes memory processes, and how these systems interact dynamically. Her work often employs advanced neuroimaging techniques such as magnetoencephalography (MEG) and functional MRI to capture the fast neural dynamics of cognitive control. The recent publications highlight consistent themes in cognitive neuroscience, particularly in attentional prediction, memory reselection, neural dynamics in Alzheimer’s disease, and metacognitive aspects of memory. Her research spans healthy cognition and clinical populations, with implications for neurodegenerative and psychiatric disorders. While no specific scientific awards are listed in the provided text, her publication record in high-impact journals such as Nature Communications , Journal of Neuroscience , and Trends in Cognitive Sciences underscores her significant contributions to the field. She collaborates with prominent researchers including Dana Small, Todd Constable, and Elizabeth Roessler. Although no formal list of advisees is provided, her leadership in major research programs suggests active mentorship. She is deeply embedded in Yale’s neuroscience ecosystem and continues to lead cutting-edge research at the Wu Tsai Institute.

Rosanna OlsenView profile

Associate Professor

• Cognitive Neuroscience
• Memory Systems
• Medial Temporal Lobe Function
• +4 more

Dr. Rosanna Olsen is an Associate Professor (Status Only) at the University of Toronto and a Scientist at the Rotman Research Institute (RRI), Baycrest. She leads the Olsen Lab, which investigates the neural organization of human memory systems using advanced neuroimaging techniques (fMRI, MEG), eye-tracking, and studies of amnesia patients. Her research focuses on medial temporal lobe function, memory formation across lifespan, eye-movement patterns in memory, thalamo-cortical interactions, and early biomarkers of cognitive decline in aging. Education: • PhD in Psychology (Cognitive Neuroscience) from Stanford University • Postdoctoral fellowship at Rotman Research Institute Research Focus: The Olsen Lab specializes in: 1) Structural and functional characterization of medial temporal lobe subregions in memory-impaired populations; 2) Neural oscillations and short-delay memory maintenance; 3) Eye-movement patterns as indirect memory measures; 4) Roles of thalamic nuclei in associative memory; 5) Promoting diversity in neuroscience. Methodologies include high-resolution MRI, fMRI, MEG, and behavioral paradigms. Article Trends: Recent publications (2020-2024) predominantly explore hippocampal subfield volumetry, aging-related memory decline, eye-movement patterns, thalamic contributions to memory, and inclusive academic practices. Over 70% involve neuroimaging analyses, with consistent focus on preclinical Alzheimer's biomarkers and hormonal influences on cognition. Advising: Actively mentors graduate students (Psychology, University of Toronto) and oversees postdoctoral fellows. Current trainees include 4 PhD candidates and 2 postdocs researching thalamic memory pathways, oscillatory dynamics, and visual discrimination in aging. The lab employs 5 research assistants. Lab & Collaborations: Directs the Olsen Lab at Baycrest with 11 active members. Collaborates with Drs. Jennifer Ryan (Baycrest), Brad Buchsbaum (Baycrest/UofT), Morris Moscovitch (UofT), and international consortia including the Hippocampal Subfields Group. Research has been featured in Science Daily and Neuroscience News .

• Educational Psychology
• Cognitive Psychology
• Working Memory Research
• +5 more

Judith Schweppe is Professor of Digital Learning Environments Didactics at the University of Erfurt's Faculty of Educational Sciences. Her research bridges cognitive psychology and educational practice, focusing on how memory processes influence learning in educational contexts. She maintains an active research program with numerous publications in top-tier journals. Her research interests span educational psychology, cognitive psychology, working memory, multimedia learning, and educational technology. Schweppe investigates how cognitive principles can inform instructional design, particularly examining how memory processes like retrieval practice, testing effects, and cognitive load impact learning outcomes. Her work often employs experimental methodologies to test theoretical claims in authentic educational settings. Analysis of her recent publications reveals a strong focus on retrieval practice effects, particularly examining open-book versus closed-book testing, interleaved practice in language learning, and the combination of retrieval practice with generative learning strategies. Her research consistently applies cognitive psychology principles to practical educational challenges, with a growing emphasis on digital learning environments and educational technology integration. Professor Schweppe has established herself as a significant contributor to the field of educational psychology through her theoretically grounded experimental work. Her publications appear consistently in high-impact journals such as Journal of Educational Psychology, Memory & Cognition, and Applied Cognitive Psychology, demonstrating both scholarly rigor and practical relevance. Her research program shows a clear trajectory from fundamental cognitive processes toward applied educational contexts, with increasing attention to digital learning environments. She collaborates with researchers across multiple institutions, suggesting an active research network and engagement with the broader scholarly community.

• Computational Neuroscience
• Theoretical Neuroscience
• Memory Systems
• +3 more

Misha Tsodyks is a Professor at the Weizmann Institute of Science in Rehovot, Israel, where he has held a faculty position since 1995 and achieved full professorship in 2005. Prior to this, he held research appointments in Moscow, Rome, Jerusalem, and San Diego. His educational background includes a Ph.D. in Theoretical Physics from the Landau Institute of Theoretical Physics in Moscow. Professor Tsodyks specializes in computational and theoretical neuroscience, with a primary focus on the mathematical foundations of memory systems. His research integrates advanced modeling techniques to explore memory formation, recall dynamics, and forgetting mechanisms. Key contributions include theoretical frameworks for power-law forgetting, retroactive interference, and hierarchical organization in memory representations. His work bridges cognitive psychology and neuroscience through rigorous mathematical analysis of neural information processing. Analysis of his recent publications (2017-2020) reveals a concentrated effort on developing fundamental laws of memory using computational approaches. His studies consistently employ attractor neural networks, Bayesian inference models, and synaptic plasticity mechanisms to explain complex memory phenomena across multiple scales. This research demonstrates strong interdisciplinary connections between theoretical physics, cognitive science, and neurobiology, with particular emphasis on hippocampal function and visual perception systems. He serves as Specialty Chief Editor for Frontiers in Computational Neuroscience, reflecting his leadership in the field. His research impact is evidenced by substantial publication views (over 180,000) and a robust professional network including 268 followers and collaborations with prominent neuroscientists.