Prof. Yair Weiss is a faculty member at the School of Computer Science and Engineering, The Hebrew University of Jerusalem . He holds a PhD in Brain and Cognitive Sciences from MIT and an MSC in Applied Mathematics from Tel-Aviv University. Education: MSc in Applied Mathematics, Tel-Aviv University (1993) PhD in Brain and Cognitive Sciences, MIT (1998) His research focuses on Human and Machine Vision , Machine Learning , Bayesian Methods , and Neural Computation . Recent work explores adversarial examples, generative models, and robustness in neural networks. Recent publications highlight trends in: Understanding neural network representations Advancements in GANs and adversarial training Image restoration and translation techniques Perceptual distance modeling Bayesian approaches to computer vision Mathematical analysis of deep learning architectures
Professor Brett Hayes is a distinguished cognitive psychologist at the University of New South Wales, serving in the School of Psychology. He is the founding Director of the Sydney Thinking and Reasoning (STAR) Laboratory, which he has led for over 15 years, securing more than $4 million in competitive research funding. Professor Hayes has previously held the position of Head of the School of Psychology and served as a member of the Australian Research Council (ARC) College of Experts. His research expertise spans reasoning, concept learning, memory, and developmental changes in these cognitive processes. Professor Hayes employs both experimental investigation and computational modeling in his work, with a particular focus on applying fundamental cognitive research to practical problems in forensic and clinical decision-making, early childhood education, and climate change science communication. His research has significant interdisciplinary applications across psychology, education, and environmental science. Professor Hayes has published extensively in top cognitive science journals, with his most recent work focusing on inductive reasoning, sampling assumptions, learning traps, and consensus perception. His research demonstrates consistent innovation in understanding how people process information, make decisions under uncertainty, and develop reasoning abilities across the lifespan. His scientific contributions include numerous journal articles, book chapters, and co-authored textbooks on developmental psychology. Professor Hayes has also contributed to teaching through courses such as PSYC3341 Developmental Psychology (which he chairs), PSYC3221 Cognitive Science, and PSYC2061 Developmental and Social Psychology. Professor Hayes maintains an active research program with ongoing collaborations across multiple institutions, as evidenced by his numerous co-authored publications. His laboratory continues to advance our understanding of human cognition through rigorous experimental work and theoretical development.
Eliese-Sophia Lincke is a Junior Professor at the Department of History and Cultural Studies, Freie Universität Berlin, since May 2022. Her work bridges computational methods with Egyptology, focusing on digital tools for studying ancient texts. Bachelor's and Master's in Egyptology, Humboldt-Universität zu Berlin (2007) PhD in "The Conception of Spaces in Language" (TOPOI Cluster, 2012) Research interests include: Digital Humanities : Developing machine learning models for Hieroglyphic, Demotic, and Coptic text processing Linguistic Typology : Analyzing classifier systems in Ancient Egyptian and Sign Languages Spatial Linguistics : Investigating prepositions and spatial adverbs in Egyptian-Coptic Recent publications focus on Neural Lemmatization , OCR for Coptic , and Classifier Semantics , demonstrating her commitment to computational Egyptology. Scientific awards include the Humboldt-Preis 2008 for best Master's thesis and the Prize for Good Teaching 2014 . She has co-organized workshops like "Wege zum Ägyptischen" and served as Co-Editor for Lingua Aegyptia . Her teaching contributes to the Digital Studies of Ancient Texts Master's program.
Pierre-Henri Paris is an Associate Professor (Maître de Conférences) at Paris-Saclay University since September 2024. Previously, he worked as a Postdoctoral Researcher at Telecom Paris (Institut Polytechnique de Paris) from September 2020 to August 2024. His academic journey includes a PhD in Artificial Intelligence from Sorbonne University and CNAM (Conservatoire National des Arts et Métiers) completed in 2020. Education: PhD in Artificial Intelligence, 2020, Sorbonne University and CNAM M.Sc. in Artificial Intelligence, 2016, CNAM M.Sc. in Mathematics, 2008, CY Cergy Paris University (incomplete) Pierre-Henri Paris's research focuses on the intersection of artificial intelligence, knowledge representation, and natural language processing. His work particularly emphasizes knowledge graphs, entity linking, and data quality. He has made significant contributions to projects like YAGO 4.5, which enhances knowledge bases with cleaner, logically consistent structures, and MAFALDA, a benchmark for fallacy classification. His research often bridges theoretical foundations with practical applications, particularly in how knowledge can be effectively represented, extracted, and utilized in complex systems. His recent publications reveal a strong focus on knowledge graph enhancement, semantic representation, and natural language understanding. The work on YAGO 4.5 demonstrates his commitment to creating more robust knowledge bases, while MAFALDA shows his interest in the intersection of language understanding and logical reasoning. His research trajectory indicates a consistent exploration of how structured knowledge can be integrated with linguistic analysis to create more intelligent systems. Advising: PhD students: Simon Coumes (2022-), Chadi Helwe (2022-2024), François Amat (2022-) Master's students: Syrine El Aoud (2021), Ayoub Mountassir (2013-2015) Bachelor's students: Khalil Halloul (2013-2014) Pierre-Henri Paris is actively involved in teaching at Paris-Saclay University, where he instructs courses including Introduction to Machine Learning, Introduction to Neural Networks, Algorithms for Data Science, Databases, and Data Warehousing. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications in artificial intelligence and data science.
Jeffrey L. Krichmar is a Professor in the Department of Cognitive Sciences and Department of Computer Science at the University of California, Irvine. His academic journey includes a B.S. in Computer Science from the University of Massachusetts Amherst (1983), an M.S. in Computer Science from The George Washington University (1991), and a Ph.D. in Computational Sciences and Informatics from George Mason University (1997). Prior to UCI, he served as Assistant Professor at George Mason University (1997-1999) and Senior Fellow at The Neurosciences Institute (1999-2007). University of California, Irvine (2007-present) George Mason University (1997-1999) The Neurosciences Institute (1999-2007) His research focuses on neurorobotics , exploring how embodied cognition and biologically plausible neural models can enhance robotic systems. Key areas include spiking neural networks , neuromodulation , path planning , and interactive tactile robots for therapeutic applications. His work bridges neuroscience , robotics , and cognitive science , with applications in autonomous vehicles , neuroprosthetics , and AI explainability . Recent publications emphasize spiking neural networks for navigation , neuromodulated attention , and neuromorphic hardware integration. The development of CARLsim, a GPU-accelerated spiking neural network simulator now in version 6.0, represents a major technical contribution. His team's work on socially assistive robots like CARL-SJR targets therapeutic applications for autism and ADHD. Scientific Awards IJCNN 2020 Best Paper Award Finalist for Best Student Paper at IJCNN 2018 Best Paper Award at IEEE IJCNN 2009 Grants include National Science Foundation funding for neural models of decision-making (2009). His lab (Cognitive Anteater Robotics Laboratory) develops systems that use large-scale brain simulations for autonomous behavior , with applications in adaptive robotics , sensorimotor learning , and neuroethology . Current projects explore neuromodulatory influences on attention systems and cognitive flexibility .
Seth Frey is an Associate Professor in the Department of Communication at the University of California, Davis, with affiliate status at Indiana University's Ostrom Workshop and as Research Director at Metagov. His research focuses on computational social science approaches to understanding self-governance in complex social systems, particularly through the lens of online communities as model institutions. Education: Ph.D. in Cognitive Science and Informatics (complex systems), Indiana University, 2013 B.A. in Cognitive Science, UC Berkeley, 2004 Research Interests: Frey specializes in computational approaches to institutional analysis and the cognitive science of strategic behavior . His work examines how communities design governance systems to overcome collective action problems, with emphasis on: Emergent institutional structures in digital commons Policy-as-data through NLP and institutional grammar frameworks Cognitive mechanisms underlying cooperative behavior Design principles for participatory change in online platforms His methodology integrates large-scale data analysis, web-based experiments, and computational modeling across diverse contexts including Minecraft, Reddit, and professional sports ecosystems. Publication Trends: Recent publications (2023-2025) demonstrate a cohesive trajectory toward computational institutional analysis, with increasing focus on NLP-driven policy analysis (e.g., NLP4Gov), decentralized governance architectures (DAOs, multi-level platform governance), and the cognitive foundations of collective action. His work consistently bridges theoretical institutional analysis with practical applications in digital community design, showing particular growth in translating Ostrom's design principles into computational frameworks. Awards: Honorable Mention Award for Best Paper at ACM CSCW 2019 Advising and Grants: Frey mentors students interested in data science applications at the intersection of communication, cognition, and complex systems, emphasizing resourcefulness and intellectual curiosity. His research has secured substantial funding from: National Science Foundation (NSF) NASA Ford Foundation Google Open Source Foundation He actively encourages aspiring graduate students with strong self-directed research skills to explore computational approaches to social phenomena. Labs and Teams: He leads the Computational Communication Lab at UC Davis and co-directs the Institutional Grammar Research Initiative. Through Metagov, he develops the 'Governance API' framework for modular community governance. His past affiliations include Disney Research (Walt Disney Imagineering) where he applied complexity science to theme park systems, and the New England Complex Systems Institute (NECSI). Current collaborations span Ethereum governance, Minecraft server ecosystems, and Colorado's cannabis monitoring infrastructure.
Audrey Bowden is an Associate Professor at Vanderbilt University in both the Department of Biomedical Engineering and Department of Electrical and Computer Engineering . She is also the Dorothy J Wingfield Phillips Chancellor Faculty Fellow . Education: PhD in Biomedical Engineering (2007) from Duke University BSE in Electrical Engineering (2001) from Princeton University Research Interests: Bowden's work focuses on biomedical optics and point-of-care diagnostics , with a strong emphasis on addressing healthcare disparities through low-cost technologies. Key areas include: Biomedical Imaging Biophotonics Image Processing Machine Learning in Medical Imaging Optical Coherence Tomography (OCT) Functional Near-Infrared Spectroscopy (fNIRS) Publication Trends: Recent work combines machine learning with endoscopic imaging to differentiate cancer from inflammation, develops low-cost OCT systems for smartphones, and improves fNIRS accessibility for diverse patient populations. Her lab also focuses on 3D reconstruction algorithms for urological applications and specular reflection removal in endoscopic videos. Lab & Clinical Collaborations: The Bowden Biomedical Optics Laboratory (BBOL) collaborates with clinical departments including urology , dermatology , otolaryngology , and women's health . The lab integrates optics , microfluidics , and computer science to create hardware/software tools for resource-constrained environments.
Jessica Glazier is an Assistant Professor in the Frances L. Hiatt School of Psychology at Clark University, Worcester, MA. She completed her Ph.D. and M.S. in Psychological Science at the University of Washington (2022 and 2019, respectively) and a B.A. in Psychology & Music from Albion College (2015). Her research focuses on challenging societal norms about social categories like gender, race, and sexual orientation, emphasizing inclusivity for marginalized groups such as transgender, multiracial, and asexual individuals. She employs methods from social, developmental, cognitive psychology, and interdisciplinary approaches like feminist and LGBT studies. Research Interests Exploring how social categorization affects perceptions and experiences of individuals who defy traditional norms Examining consequences of gender/racial essentialism on prejudice and discrimination Investigating gender development in youth, including transgender and cisgender children Addressing statistical methodology limitations in psychological science Recent Research Trends Her 2024 work highlights challenges in LGBTIQ+ research inclusivity and examines gender attitudes across diverse children. Recent projects (2023–2024) emphasize statistical frameworks for meaningful inference, intersectionality in harassment perceptions, and the role of adult beliefs in shaping children’s identity autonomy. Earlier studies (2019–2022) established foundational insights into gender categorization mechanisms and transgender children’s developmental similarities to cisgender peers. Teaching & Mentoring Teaches Advanced Social Psychology (PHD) and Statistics (undergraduate), prioritizing student learning through dedicated skill-building sessions. Mentored research assistants (e.g., Liza Moore, Martina Khurana) and supervised Elizabeth Abel’s honors project on race and gender essentialism. Actively supports early-career researchers via peer mentoring programs. Labs & Collaborations Conducts research within Clark University’s Frances L. Hiatt School of Psychology lab environments, collaborating with institutions like Northeastern University and international teams on child development and social categorization projects.
Philipp Koralus is the McCord Professor of Philosophy and AI at the University of Oxford and serves as Director of the Human-Centered AI Lab (HAI Lab) within the Institute for Ethics in AI. He is also a member of St Catherine's College. Koralus holds a Ph.D. in Philosophy and Neuroscience from Princeton University and a B.A. from Pomona College. His research focuses on the human capacity for reasoning and decision-making, exploring how these processes relate to artificial intelligence agents and large language models like GPT. He advocates for the Erotetic Theory of Reason (ETR), which posits that reason aims to resolve issues or questions directly, explaining both human rationality and fallibility. His work extends to moral judgment, definitions of intelligence, and interdisciplinary collaboration with computer scientists, psychologists, linguists, and neuroscientists. Koralus is preparing to launch the HAI Lab in Fall 2024, aiming to advance human-centered AI ethics and cognition research. His educational background includes advanced studies in philosophy and neuroscience, combining analytical rigor with empirical insights. Collaborations span diverse fields, including fisheries management through agent-based modeling and healthcare ethics in AI applications. He has published widely on topics such as attention mechanisms, visual perception, and the theoretical foundations of AI reasoning. Koralus regularly teaches graduate seminars on philosophy and AI, including upcoming sessions like 'Building the Philosophy to Code Pipeline' starting in 2025. He has supervised doctoral students in both philosophy and computer science but currently lists no specific advisees. His research has been recognized in symposia and commentary, though no formal scientific awards are explicitly mentioned.
Inna Fishman, Ph.D., is a Research Associate Professor at San Diego State University's Department of Psychology within the College of Sciences. Her research investigates brain network organization in autism spectrum disorder (ASD) using multimodal MRI techniques, focusing on developmental trajectories from toddlerhood to adulthood. She directs studies on sensory processing, socioeconomic influences, and neural connectivity patterns in ASD. Research Focus: Dr. Fishman's work bridges social neuroscience and clinical neuropsychology, examining: Early biomarkers of ASD via functional/diffusion MRI Impact of bilingualism and socioeconomic factors on neurodevelopment Sleep disorders and sensory sensitivities in autistic children Aging-related neural changes in adults with ASD Publication Trends: Her recent articles (2021-2025) emphasize: 1) Advanced neuroimaging of ASD across lifespan stages, 2) Machine learning applications for diagnostics, 3) Socioeconomic and environmental modulators of brain development, and 4) Sleep/auditory processing comorbidities. Student Advising & Grants: She mentors doctoral candidates (Lindsay Olson, Jiwandeep Kohli, Bosi Chen) and leads NIH-funded projects including a clinical psychology fellowship for autism evaluation across ages. Laboratory Affiliation: Dr. Fishman co-directs the Brain Development Imaging Laboratories (BDIL), which investigates ASD manifestations through behavioral and neuroimaging approaches.
Didar Zowghi is a Senior Principal Research Scientist and Science Team Leader at CSIRO Data61, Australia's national science agency. His work focuses on advancing ethical AI systems, data quality frameworks, and requirements engineering methodologies. He leads research initiatives addressing challenges in AI governance, diversity/inclusion in technology, and human-centered AI development. Research interests include AI ethics, data completeness in healthcare systems, and the application of machine learning in requirements engineering. His contributions span theoretical frameworks for responsible AI patterns, empirical studies on user perceptions of AI tools like M365 Copilot, and analysis of AI's role in global diplomatic practices. Zowghi has published extensively on topics ranging from blockchain in supply chains to pedagogical innovations in software engineering education. His work often bridges technical systems and societal impacts, emphasizing real-world implementation challenges through collaborative industry-academia projects. Notable outputs include the Responsible AI Pattern Catalogue and studies examining barriers to data quality in IoT platforms. He has pioneered frameworks linking innovation initiatives to occupational skill requirements and developed tools like Elica for dynamic requirements knowledge extraction in agile teams.
Jianhua Zhang is a Professor of Computer Science and founding deputy head of the AI Lab at the Department of Computer Science, OsloMet - Oslo Metropolitan University, Norway. He holds affiliations with the Faculty of Technology, Art and Design. His career includes roles as Scientific Director at Vekia (France), Head of Machine Learning Lab, and Professorships at East China University of Science and Technology and Beijing University of Technology. He has held visiting positions at TU Berlin, TU Dresden, and the University of Catania. Educations: PhD in Electrical Engineering and Information Sciences (Ruhr University Bochum, 2005), Postdoctoral Research at the University of Sheffield (2005-2006). Research focuses on artificial intelligence, computational intelligence, cognitive human-machine systems, neuroergonomics, affective computing, and AI-driven neuroergonomics. Applications span engineering, biomedicine, finance, and business. He has led over 20 large-scale projects and published extensively (4 books, 13 chapters, ~200 papers). Leadership roles include Chair of IFAC Technical Committee on Human-Machine Systems (2017-2023), Vice Chair of IEEE Norway Section, and editorial roles at journals like Frontiers in Neuroscience and Cognitive Neurodynamics . He organized major conferences like IFAC HMS2025 (Beijing) and ICMLT 2024 (Oslo). Awards: Stanford/Elsevier Top 2% Scientists (2023/2024), Senior Research Fellowship (CSC, 2012), Max Planck Fellowship (2011), Shanghai Pujiang Talent (2007), DAAD Scholarship (2002-2004). Grants and advising: PI for 20+ projects, advising PhD students in AI, machine learning, and control systems. Teaching includes courses on computational intelligence, IoT, and fuzzy systems at both undergraduate and graduate levels. Labs/Teams: AI Lab at OsloMet, Machine Learning Lab (Vekia), and collaborations with institutions globally. Current work emphasizes AI ethics, neuroergonomics in smart cities, and adaptive human-machine systems.
Kris Baetens is a Professor in the Department of Psychology Brain, Body and Cognition at Vrije Universiteit Brussel (VUB). His research focuses on the neural mechanisms underlying social cognition, mentalization, and inhibitory control, particularly exploring the role of the cerebellum and prefrontal cortex in these processes. He employs techniques such as transcranial direct current stimulation (tDCS), EEG, and fMRI to investigate cognitive and clinical phenomena. Leading projects like ANI423 (neural correlates of inhibitory control in adolescents) and FWOAL1160 (cerebellum's role in social cognition). Recipient of the EUTOPIA Young Leaders Academy fellowship (2024-2026). Active collaborations in the PRISM network for mental health research. Key research interests include: - Cerebellar contributions to cognitive and social functions - Neurostimulation techniques for mental health interventions - Mentalizing processes in social action prediction - Personality and learning mechanisms His articles consistently analyze the interplay between neural structures like the cerebellum and behavioral outcomes in clinical and cognitive contexts. Recent work emphasizes applications of tDCS in treating alcohol use disorders and disordered eating, highlighting translational research in non-invasive brain stimulation. Advising/Grants: Supervises student research projects and manages grants from FWO and OZR agencies. Labs/Teams: Core member of the PRISM network and involved in the EUTOPIA fellowship initiative.
Dr. Will Grant is an Associate Professor in Science Communication at the Australian National University’s Australian National Centre for the Public Awareness of Science. His work focuses on science communication, public policy, and the intersection of science with politics and technology. He holds a PhD from The University of Queensland and has been at ANU since 2008. His research explores science communication strategies, misinformation dynamics, and the societal impacts of emerging technologies. He has authored over 100 publications in outlets like Public Understanding of Science and Environmental Communication , and his work has reached 1.8 million readers on The Conversation . He co-founded PostAc, a platform analyzing PhD job markets, and has advised organizations including the Office of the Chief Scientist and CSIRO. Grant’s research interests include science communication pedagogy, the role of social media in shaping public discourse, and the ethical dimensions of geoengineering. He has organized high-impact outreach initiatives like the Long Conversations dialogue series and hosts the podcast The Wholesome Show . His awards include the Vice Chancellor’s Award for Public Policy and Outreach (2015) and the Sidney Sax Medal (2020). He supervises numerous graduate students and teaches courses on science communication ethics, digital media, and science-policy interaction.
Dr. Kristen Lindquist is an incoming Professor and Robert K. and Dale J. Weary Chair in Social Psychology at The Ohio State University. She holds a A.B. in Psychology and English from Boston College (2004) and a Ph.D. in Psychology from Boston College (2010). Her research focuses on the psychological and neural basis of emotions, integrating tools from social cognition, neuroscience, and big data. She previously served as an Assistant Professor (2012–2018) and Associate Professor (2018–2022) at the University of North Carolina at Chapel Hill before being promoted to Professor in 2022. Her work emphasizes how emotions emerge from interactions between bodily states, cultural learning, and neural processes across the lifespan. She leads the Affective Science Lab, exploring cultural influences on emotion perception and the role of language in shaping emotional experiences. Lindquist’s research has been featured in Science , NeuroImage , and Trends in Cognitive Sciences , among others. Education: A.B. in Psychology and English, Boston College, 2004 Ph.D. in Psychology, Boston College, 2010 Research Interests: Lindquist investigates emotion construction theory, the neurobiological underpinnings of affect, interoception, and cultural influences on emotion semantics. Her work bridges cognitive, social, and developmental psychology with neuroscience, emphasizing interdisciplinary methods. Recent studies explore how language shapes emotional understanding and the impact of aging on physiological-emotional linkages. Key Contributions: Developed the theory of constructed emotion, challenging traditional discrete emotion models. Conducted large-scale meta-analyses mapping brain networks underlying emotion. Explored cultural variation in emotion semantics using linguistic and neuroimaging data. Labs/Teams: Her Affective Science Lab at OSU will continue investigating emotion’s neural and cultural foundations, with a focus on translational applications in mental health and education.
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