جست‌وجوی استاد و پژوهشگر

Jean Ohمشاهده پروفایل

پژوهشگر

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +۵ مورد دیگر

Jean Oh is a Researcher at the Robotics Institute of Carnegie Mellon University (CMU) , leading the interdisciplinary Bot Intelligence Group (BIG) . Her work focuses on developing persistent robots that co-exist and collaborate with humans in shared environments, emphasizing continuous improvement through training, exploration, and human interaction. Education: Ph.D. in Language and Information Technologies, CMU M.S. in Computer Science, Columbia University B.S. in Biotechnology, Yonsei University Oh's research integrates vision, language, and planning systems in robotics, with applications in human-robot teaming , self-driving cars , disaster response , eldercare , and creative robotics . She has pioneered projects like socially-compliant robot navigation in human crowds and AI-driven robotic painting systems. Recent publication trends highlight her work in vision-language planning , social navigation , computational creativity , and human-robot collaboration . Notable contributions include the StyleCLIPDraw algorithm for text-to-art generation and Social-PatteRNN for human-like trajectory prediction. Scientific Awards: Best Paper Award in Cognitive Robotics (ICRA'18, ICRA'15) Best Systems Paper Finalist (HRI'25) Best Oral Paper Finalist (Humanoids'24) Best Paper in Entertainment (IROS'24) Argoverse Challenge Winner (CVPR'24) Best Student Paper (AIAA'24) Best Demo Finalist (RoboSoft'24) Oh mentors a diverse team of PhD, MS, and undergraduate students from CMU departments including Robotics, Computer Science, and Mechanical Engineering. Her research is funded by US Army Research Lab , DiDi Chuxing , and DARPA , with collaborations across industry and academia .

Alane Suhrمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Computer Vision
• +۵ مورد دیگر

Alane Suhr is an Assistant Professor at UC Berkeley's Electrical Engineering and Computer Sciences (EECS) department and a member of the Berkeley Artificial Intelligence Research Lab (BAIR). Her research focuses on natural language processing (NLP), machine learning, and computer vision, emphasizing systems that interact with humans through language. She designs models and datasets for language grounding (e.g., NLVR) and develops algorithms for learning through interaction. Education: PhD in Computer Science, Cornell University (2022), advised by Yoav Artzi Bachelor's in Computer Science and Engineering, Ohio State University (2016), with a Linguistics minor Research Interests: Interactive systems for collaborative language use (e.g., CerealBar) Language grounding in multimodal contexts Embodied agents and reinforcement learning Generalization in NLP and the role of language in learning Key Contributions: Developed the NLVR dataset for visual reasoning with natural language Pioneered work on SWE-Gym for training software engineering agents Contributed to research on language models' sensitivity and commonsense reasoning Awards: ACM Doctoral Dissertation Award (2022) Outstanding Paper Awards at ACL 2023 and EMNLP 2021 Professional Activities: Organized workshops at ICML, NeurIPS, and ACL on topics like agents, generalization, and theory of mind Active in academic outreach and conference speaking (e.g., ICML, NeurIPS, CVPR) Labs/Teams: Berkeley Artificial Intelligence Research (BAIR) Lab SWE-Gym research group

Mina Leeمشاهده پروفایل

استادیار

• Writing with AI
• Human-AI Interaction
• Natural Language Processing
• +۳ مورد دیگر

Mina Lee is an Assistant Professor in Computer Science at the University of Chicago, affiliated with the Data Science Institute and Cognitive Science. Her research focuses on 'Writing with AI,' exploring how AI transforms writing processes, content, and identities. She designs AI writing assistants and evaluates human-AI collaboration through user studies and experiments, addressing ethical implications like authorship norms and educational impacts. Education: Ph.D. in Computer Science from Stanford University (2023), advised by Percy Liang. B.S. in Computer Science from Korea University (2016). Postdoctoral research at Microsoft Research's Computational Social Science group (2023–2024). Research interests span Human-Computer Interaction (HCI), NLP, and computational social science. She co-founded workshops on Intelligent Writing Assistants and Human-centered Evaluation of Language Models. Notable awards include MIT Technology Review's Innovators Under 35 Korea (2022) and a Best Paper Award at GPCE 2016. Her work has been published in top venues like CHI, ACL, NeurIPS, and Nature Human Behavior. She advises PhD students on AI-assisted writing, cognitive augmentation, and safe generative models. Current lab projects include designing explainable AI tools and studying AI disclosure norms in writing.

Julian Jara-Ettingerمشاهده پروفایل

دانشیار

• Cognitive Development
• Social Cognition
• Computational Modeling
• +۵ مورد دیگر

Julian Jara-Ettinger is an Associate Professor of Psychology and Computer Science at Yale University. He holds a Ph.D. from MIT (2016). His research focuses on understanding the cognitive and computational mechanisms underlying human social behavior, including fairness, linguistic communication, gesture, moral reasoning, and pedagogy. He employs interdisciplinary methods such as computational modeling, eye-tracking, cross-cultural studies, and developmental research to bridge psychology and artificial intelligence. Key research areas include the development of social cognition in children, the integration of theory of mind with communication, and the application of cognitive science principles to build socially intelligent machines. His work emphasizes how humans infer others' knowledge, intentions, and desires, with implications for AI safety and ethical systems design. Publications span topics like epistemic inference, moral judgments, and the computational foundations of social interaction. His lab's research often intersects with evolutionary simulations, neural modeling, and cultural psychology. No scientific awards are explicitly mentioned in the provided text. Collaborations involve cross-disciplinary teams addressing challenges in developmental science, AI ethics, and cognitive robotics. His work has practical applications in educational strategies, social policy, and human-AI collaboration frameworks.

Sibel Adaliمشاهده پروفایل

استاد

• Trust in Networks
• Social Networks
• Databases
• +۵ مورد دیگر

Sibel Adali is a Professor in the Department of Computer Science at Rensselaer Polytechnic Institute’s School of Science. She joined RPI in 1996 after earning her PhD from the University of Maryland. Her academic roles include Associate Head and Graduate Program Director of the Computer Science Department (2015-2018) and currently serving as Associate Dean of Science for Research and Graduate Studies at RPI. She teaches foundational Computer Science courses in problem-solving and databases. Education: PhD from University of Maryland. Adali’s research focuses on trust modeling, social networks, information retrieval, and semantic analysis. She has led cross-cutting projects addressing cognitive science intersections with network theory, including roles as ARL-lead CTA Trust Coordinator and SCRNARC Associate Director. Her work explores misinformation mitigation, semantic shifts in language, and expert identification in social media ecosystems. Recent publications highlight her contributions to fake news detection, semantic change modeling, and AI-driven misinformation interventions. Her research trends emphasize interdisciplinary approaches combining machine learning, computational linguistics, and behavioral studies. Scientific Awards: Trustees' Outstanding Teacher Award (2015), Rensselaer Polytechnic Institute’s highest teaching honor. Adali actively collaborates on grants and projects through research centers including MOCA, IDEA, SCNARC, and ARL CTA partnerships. She advises students on advanced computational research and participates in military communications technology initiatives.

• Islamic Theology
• Pastoral Care
• Interreligious Dialogue
• +۴ مورد دیگر

Mahmoud Abdallah is a Researcher at the Center for Islamic Theology , University of Tübingen, where he has worked since 2020. His career includes roles as Senior Scientist at the University of Innsbruck (2019–2020), Project Leader at ZITh (2016–2019), and Post-Doc researcher (2013–2018). He also held guest lectures at Marmara University (2017) and served as an Arabic Editor (2012–2013). Education : PhD in Comparative Linguistics (2012, Heinrich Heine University Düsseldorf), Master’s summa cum laude (2002, University of Minia), State Examination (1998, Al-Azhar University). Research Interests focus on Islamic Theology , Pastoral Care , Interreligious Dialogue , and Religious Institutions in Pluralistic Societies . He explores hermeneutics in Islamic counseling, Ḥisba in public order, and Umma dynamics in multicultural contexts. Recent Publications (2014–2022) analyze Qur’anic ambiguity , interfaith education , religious responses to crises (e.g., pandemic pastoral care), and Islamic social ethics . Key themes include Abrahamic unity , contextual theology , and religious hermeneutics . Scientific Awards : Master’s degree with summa cum laude distinction (University of Minia, 2002). Advising & Projects : Co-editor of Grundlagen muslimischer Seelsorge (2020) and Theologie des Zusammenlebens series (2017–2022). Led the 2016 project Scientific Education and Social Responsibility (Baden-Württemberg Ministry). Currently working on books about Prophetic Hermeneutics (2023) and Religious Transformations in Crisis (2022). Committee Memberships : Member of the German Islam Conference (since 2018), Scientific Advisory Boards at Zukunftsforum Islam e.V. (since 2017), and the DAVO (German Working Group on the Middle East, since 2009).

Lyle H. Ungarمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Affiliations & Roles Professor of Computer and Information Science at University of Pennsylvania Faculty in Graduate Groups: Bioengineering (School of Engineering) Genomics & Computational Biology (School of Medicine) Operations, Information & Decisions (Wharton School) Psychology (School of Arts & Sciences) Research Affiliations: Annenberg Public Policy Center (Distinguished Fellow) Center for Cognitive Neuroscience Institute for Translational Medicine Research Interests Focuses on explainable AI, natural language processing (NLP), and machine learning applications in psychology and medicine. Key areas include: Language analysis for well-being and mental health Spectral methods for NLP (e.g., Eigenwords) Forecasting and decision-making models Bioinformatics and genomics Teaching Teaches advanced courses in Machine Learning, Deep Learning, and AI ethics, including: CIS 5200: Machine Learning CIS 5220: Deep Learning CIS 6200: Advanced Topics in Deep Learning Key Collaborations Works with interdisciplinary teams on projects like the Good Judgment Project (forecasting) and WWBP (Well-Being and Language). Collaborators include Martin Seligman (positive psychology), Dean Foster (statistics), and Michael Collins (NLP).

Piotr Winkielmanمشاهده پروفایل

استاد

• Emotion and Consciousness
• Social Cognition
• Embodied Cognition
• +۵ مورد دیگر

Piotr Winkielman is a Professor of Psychology at the University of California, San Diego (since 2007), with affiliations at Warwick Business School (UK) and the Warsaw School of Social Sciences and Humanities (Poland). His research focuses on the interplay of emotion, cognition, embodiment, and consciousness in social cognition, employing methods from social/cognitive psychology and neuroscience. Key interests include unconscious emotion processing, facial mimicry, decision-making under emotional influence, and the neural basis of social perception. Education: PhD in Social Psychology (1997), University of Michigan MSc in Psychology (1991), University of Bielefeld, Germany BSc in Psychology (1988), University of Warsaw, Poland Research Interests: Winkielman explores how fleeting affective reactions influence behavior without conscious awareness, studying facial feedback mechanisms, emotional contagion, and the role of physiological signals in decision-making. His work bridges theories like Affect-As-Information and Facial Feedback, while challenging assumptions about the necessity of conscious processes in emotion. Grants & Funding: Supported by NSF Grant BCS-0350687 for studies on unconscious emotion and physiological feedback. Collaborations include projects on mimicry, stress effects, and cross-modal perception. Labs & Teams: Leads research at UCSD on embodied cognition and social neuroscience, with studies involving EEG, EMG, and behavioral experiments. International collaborations span UK, Poland, and Germany.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

Margaret Greenwaldمشاهده پروفایل

دانشیار

• Adult neurogenic communication disorders
• Cognitive neuropsychology
• Stroke rehabilitation
• +۳ مورد دیگر

Margaret Greenwald serves as Associate Professor and Ph.D. Coordinator in the Department of Communication Sciences and Disorders (CSD) within Wayne State University's College of Liberal Arts and Sciences. Previously department chair (2014-2020), she is a Licensed and Certified Speech-Language Pathologist (CCC-SLP) recognized in 2022 as Wayne State's Outstanding Graduate Mentor in the health sciences. Her academic credentials include: M.A. in Speech-Language Pathology (University of Florida) Ph.D. in Communicative Sciences and Disorders (University of Florida) Post Doctoral Research Training in Cognitive Neuropsychology (University of Maryland, Department of Neurology) Dr. Greenwald's research centers on adult neurogenic communication disorders , specializing in aphasia, traumatic brain injury, and stroke rehabilitation through cognitive neuropsychology. Her work employs Magnetoencephalography (MEG) to map brain-behavior relationships during language and musical processing tasks, revealing critical insights for rehabilitation. She actively bridges clinical practice with neuroscience to develop evidence-based interventions. Analysis of her recent publications shows consistent focus on neuroimaging applications for understanding language disorders, with growing emphasis on telepractice implementation and the cognitive effects of musical training. Her work demonstrates strong translational value, connecting basic neuroscience to clinical rehabilitation protocols while maintaining rigorous methodological standards. Her scientific recognition includes: Outstanding Graduate Mentor in the Health Sciences, Wayne State University (2022) As an educator, Dr. Greenwald teaches graduate courses in aphasia, neuromuscular speech disorders, research methods, and doctoral seminars, plus undergraduate speech-language pathology instruction. She supervises doctoral research as Ph.D. coordinator and mentors students through clinical research projects. Her teaching integrates current neuroscience findings with clinical practice standards. She maintains active professional engagement through memberships in the American Speech-Language Hearing Association (ASHA), Academy of Aphasia, and International Neuropsychological Society, contributing to both clinical guidelines development and research community advancement.

• Computational Linguistics
• Psycholinguistics
• Language Processing
• +۴ مورد دیگر

Richard Futrell is an Associate Professor at the University of California, Irvine (UCI), affiliated with the Department of Language Science. He leads the Language Processing Group, focusing on computational models of human and machine language processing. His work bridges information theory, Bayesian cognitive modeling, and natural language processing (NLP) interpretability. University of California, Irvine Department of Language Science Language Processing Group leader His research examines how linguistic structures emerge from cognitive and communicative pressures. Key areas include dependency locality, surprisal theory in sentence processing, and efficiency-driven language evolution. He investigates how memory constraints, predictability, and information density shape syntactic and morphological patterns across languages. Recent publications analyze code-switching efficiency, syntactic priming, ERP component modeling, and agent-based language contact simulations. His work frequently employs Bayesian modeling, neural network analysis, and cross-linguistic corpora to uncover universal principles in language processing. ACL Best Paper Award (2024) Best Paper Award for Computational Modeling of Language (2023) Marr Prize for Best Student Paper (2017) He has developed datasets like SPACER for error repair analysis and contributed to phonotactic learning frameworks. His collaborations span cognitive scientists, computational linguists, and neuroscientists, advancing understanding of language production, comprehension, and structural optimization.

• Cognitive Neuroscience
• Bilingualism
• Infant Cognition
• +۳ مورد دیگر

Nuria Sebastian Galles is a Full Professor at the Universitat Pompeu Fabra (UPF), affiliated with the Department of Engineering and the UPF Center of Studies in Natural and Artificial Intelligence. Her career includes roles as Associate Professor (University of Barcelona, 1988-2002) and Full Professor (since 2002). She leads the Speech Acquisition and Perception (SAP) Research Group and coordinates major projects such as the BRAINGLOT consortium on bilingualism and cognitive neuroscience. Dr. Galles has received notable awards including the James S. McDonnell Foundation Award and ICREA Academia Prize, and served on the European Research Council Scientific Council. Her research focuses on cognitive neuroscience, bilingualism, and infant language development, leveraging EEG, brain imaging, and behavioral studies. Education: PhD in Experimental Psychology (University of Barcelona, 1986), postdoctoral training at Max Planck Institute and LSCP-CNRS (Paris). Visiting scholarships include University of Pennsylvania, University College London, and University of Chicago. Research Interests: Bilingualism's impact on cognition, neurobiological foundations of language acquisition, infant speech perception, and social cognition. Current projects include ERC-funded studies on attention-language links and cognitive effects of walnut consumption in adolescents. Publications: Over 100 peer-reviewed articles in journals like Science , PNAS , and Developmental Science , with a focus on bilingualism, phonetic categorization, and social hierarchy processing in infants. Editor of Developmental Science and Language Learning and Development . Grants & Teams: ERC Advanced Grant (Under Control), Consolider-Ingenio 2010 (BRAINGLOT). Lab collaborations include multi-country studies on traffic pollution’s cognitive impact and walnut-based dietary interventions.

• Smart Cities
• Geovisual Analysis
• Urban Dynamics
• +۵ مورد دیگر

Dr. Gavin McArdle is an Associate Professor at the University College Dublin (UCD) School of Computer Science, specializing in spatial data analysis and smart cities. He holds academic affiliations with the National Centre for Geocomputation (Maynooth University) and CeADAR (Data Analytics Centre). His research focuses on urban dynamics, geovisual analytics, smart transportation, and remote sensing applications. He has received a College of Science Teaching Excellence Award for his contributions to education. McArdle earned his BSc, PhD, and a Prof Dip in University Teaching & Learning from UCD. His work bridges academia and industry through collaborative grants, including those from Science Foundation Ireland and EU funding. Notable projects include the Dublin Dashboard (urban analytics platform) and DubSim (traffic simulation using digital footprints). His research outputs span over 147 publications, with recent work addressing Airbnb's impact on urban gentrification, sustainable mobility, and environmental monitoring via satellite data. He actively contributes to professional committees, including roles in the UCD Data Protection Impact Assessment Committee and international conferences like Web and Wireless GIS. McArdle coordinates courses such as Research Practicum and Computer Programming II, emphasizing practical research and technical skills. His interdisciplinary approach integrates machine learning, spatial statistics, and urban informatics to address real-world challenges in smart cities and environmental sustainability.

Bogusława Whyattمشاهده پروفایل

استاد

• Psycholinguistics
• Translation Studies
• Translation Process Research
• +۵ مورد دیگر

Bogusława Whyatt is a Professor at the Faculty of English, Adam Mickiewicz University, Poznań. She holds a D.Litt. in linguistics (2014), Ph.D. in English (2000), and MA in English (1992) from Poznań institutions. Her academic profile spans psycholinguistics, translation studies, and cognitive approaches to translation processes. Key research themes include: Translation process dynamics and directionality effects Eye-tracking applications in translation reception studies Development of translation competence and pedagogy Psycholinguistic analysis of language processing Metacognitive skill transfer between translation and paraphrasing Recent publications focus on cognitive effort metrics, directionality impacts, and empirical methodologies combining eye-tracking and key-logging data. She leads major projects like Read Me (2021-2025) and EDiT (2016-2019), examining translated text reception and translation directionality respectively. Scientific honors include three consecutive Adam Mickiewicz University Rector's Awards for Organizational Excellence (2018, 2023, 2024). She supervises PhD research in translation cognition and has mentored four doctoral candidates to completion. Active in professional networks like the MC2 Lab and TREC consortium, she contributes to cognitive translation studies through methodological innovations and international conference organization. Her methodological expertise includes psychometrics, EEG research, and ATLAS.ti data analysis tools.

• Digital Twins
• Blockchain
• Internet of Things (IoT)
• +۵ مورد دیگر

Dr. Cor Verdouw is a Senior Researcher in Information Technology and Data Science, focusing on innovation in agri-food systems. He is affiliated with Wageningen University & Research (WUR), though the specific school/department isn't explicitly stated. Research Interests : Digital Twin architectures for horticulture and pharmaceutical production Blockchain applications in agri-food supply chains IoT systems for smart farming Transparency and traceability frameworks Knowledge engineering in food industry contexts Organizational design for digital innovation ecosystems Selected Article Trends : His 2023-2025 work spans digital twins (cannabis/pharma production), blockchain (food supply chains), and IoT (smart agriculture). Key themes include system integration, circular economy models, and data-driven decision-making. Projects : Leads EU-funded STREAMING project (2025-) and LVVN projects on AI in agri-food systems (2025-2028), data-driven fisheries (2024-2025), and information management (2016-2025).