جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Learning Sciences
• Educational Technology
• +۲ مورد دیگر

Jennifer Olsen, PhD, is an Assistant Professor of Computer Science at the University of San Diego since 2020. She holds a PhD, MS, and BS in Human-Computer Interaction and Cognitive Science from Carnegie Mellon University, followed by postdoctoral research at the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland. Her research focuses on the intersection of human-computer interaction, cognition, and education, emphasizing collaborative learning and educational technology design from both learner and instructor perspectives. Education: PhD in Human-Computer Interaction, Carnegie Mellon University MS in Human-Computer Interaction, Carnegie Mellon University BS in Cognitive Science, Carnegie Mellon University Research Interests: Dr. Olsen explores how collaboration supports learning, designs technologies to enhance educational practices, and investigates gaze-based metrics for understanding collaborative problem-solving. Her work spans gamified robotics, AI-driven orchestration systems, and virtual reality applications in vocational training. She emphasizes learner-centered design and the integration of social robots and virtual agents in pedagogical settings. Grants/Advising: While no specific grants or advisees are listed, her prolific publication record indicates active involvement in educational technology research and development. Her work addresses challenges in classroom orchestration, multimodal data analysis, and accessibility in educational robotics. Labs/Teams: Collaborates with interdisciplinary teams focused on educational technology, human-robot interaction, and adaptive learning systems. Her research leverages tools like FROG orchestration graphs and eye-tracking technologies to develop practical classroom solutions.

Tijana Gajićمشاهده پروفایل

پژوهشگر

• Language Education
• Digital Learning Tools
• Foreign Language Acquisition
• +۴ مورد دیگر

Tijana Gajić is a researcher at Singidunum University in Belgrade, Serbia. She holds a Ph.D. in Philology (2020), an MA in English Language and Literature (2009), and a BA in the same field (2007) from the University of Belgrade. Her work focuses on the intersection of language education, digital tools, and critical pedagogy. Doctoral Studies: Philology , University of Belgrade (2017-2020) Master Studies: English Language and Literature , University of Belgrade (2008-2009) Bachelor Studies: English Language and Literature , University of Belgrade (2003-2007) Dr. Gajić’s research explores the impact of digital technologies on language acquisition, critical thinking development, and the sociopolitical dimensions of English language learning. She has published extensively on mobile applications like Duolingo, HelloTalk, and WordUp, analyzing their efficacy in modern pedagogy. Her recent publications (2024-2025) examine digital tools’ influence on language education, critical pedagogy in Serbian classrooms, and AI-driven language learning innovations. Earlier works (2020-2016) established her expertise in tandem learning, vocabulary enhancement via apps, and affective factors in language acquisition. Notable collaborations include partnerships with researchers like N. Maenza , A. Gagić , and J. Nikolić . While no specific grants or awards are mentioned, her involvement in conferences such as Sinteza and ELTA Serbia underscores her active role in advancing language education. Her 2022 book, Nastava stranih jezika i razvoj kritičkog mišljenja u eri neoliberalizma , synthesizes her critical pedagogy framework. Current projects likely continue her focus on digital transformation in language teaching.

Maja J Matarićمشاهده پروفایل

استاد

• Socially Assistive Robotics
• Human-Robot Interaction
• Assistive Technology
• +۷ مورد دیگر

Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.

Jimeng Sunمشاهده پروفایل

استاد

• Artificial Intelligence
• Healthcare Analytics
• Drug Discovery
• +۵ مورد دیگر

Dr. Jimeng Sun is a Health Innovation Professor at the Siebel School of Computing and Data Science and Carle Illinois College of Medicine at the University of Illinois Urbana-Champaign. Co-founder of Keiji AI , he leads groundbreaking research at the intersection of artificial intelligence and healthcare, actively deploying clinical AI systems and developing frameworks like PyHealth and Therapeutics Data Commons . His research spans four major areas: Clinical AI Systems : Developing interpretable models (e.g., RETAIN) for patient similarity, temporal event prediction, medication recommendation, and clinical outcome forecasting Drug Discovery : Creating molecular optimization frameworks, drug-target interaction models, and AI-driven platforms Clinical Trials : Pioneering patient-trial matching, outcome prediction, and optimization frameworks using deep learning and graph neural networks Biosignal Analysis : Advancing sleep staging, seizure classification, and automated EEG/Cardiac monitoring systems With over 500 top-tier publications (including in Nature , NEJM AI , and leading AI conferences) and an h-index of 99, his work has been recognized with the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare award. He maintains active collaborations with institutions like Massachusetts General Hospital , Medidata Solutions , and OSF Healthcare . His recent publications reveal a strong focus on: Reinforcement learning applications in medical data analysis Large language model adaptation for clinical tasks Knowledge graph integration with AI systems Synthetic data generation for healthcare Multi-modal learning in clinical contexts Explainable AI for medical applications Dr. Sun's lab ( Sunlab ) emphasizes practical impact over theoretical work, actively collaborating with hospitals and healthtech companies. He welcomes contributions from clinicians, researchers, and industry partners through initiatives like his AI for Health webinar series .

Kevin D. Ashleyمشاهده پروفایل

استاد

• Computational Social Science
• Artificial Intelligence
• Algorithms
• +۷ مورد دیگر

Kevin D. Ashley is a Professor of Law at the University of Pittsburgh School of Law. He is also a senior scientist at the Learning Research and Development Center and an adjunct professor of computer science at the University of Pittsburgh. His interdisciplinary work bridges artificial intelligence, legal analytics, and ethical reasoning. JD, Harvard Law School M.A. and PhD, University of Massachusetts BA, Princeton University His research focuses on computational modeling of legal reasoning , AI and ethics , legal text analytics , and case-based reasoning . He has pioneered AI applications for legal decision support, automated argumentation, and bias detection in legal corpora. Recent publications include studies on large language models in legal annotation, argument mining, and empirical legal analysis. His work has been supported by multiple National Science Foundation grants, emphasizing fairness in AI and access to justice. 2022 Codex Prize for Computational Law 2015 University of Massachusetts Outstanding Achievement Award 2002 AAAI Fellow for AI in Law contributions 2000 Chancellor’s Distinguished Research Award A former President of the International Association for Artificial Intelligence and Law, Ashley has held visiting roles at the University of Bologna, Stanford CodeX, and IBM Watson Research Center. He co-edits the journal Artificial Intelligence and Law and teaches courses on applied legal analytics.

• Learning Sciences
• Technology-Enhanced Learning
• Collaborative Learning
• +۴ مورد دیگر

Professor Nancy W. Y. Law is a leading scholar in Learning Sciences and Technology at the University of Hong Kong's Faculty of Education . She has served as Founding Director of the Centre for Information Technology in Education (CITE) (1998-2013) and currently holds the Chair of Learning Sciences and Technology . Her career spans over 25 years of international comparative studies, policy analysis, and large-scale educational innovation. Current roles: Associate Dean (Strategic Development), HKU Key affiliations: Sciences of Learning Strategic Research Theme (co-convener) Research Expertise Her work focuses on technology-enhanced learning , digital literacy , knowledge building communities , and multilevel educational change . She pioneered network models of teacher innovation and socio-technical frameworks for sustainable pedagogical transformation, particularly in STEM education and Cyberbullying prevention . Scientific Leadership With over 25 major research grants (2000-2023) exceeding HK$50 million, she leads projects like: Learning and Assessment for Digital Citizenship Jockey Club Self-directed Learning in STEM Design-Aware Learning Analytics A Fellow of the International Society of Learning Sciences and recipient of the HKSAR Humanities and Social Sciences Prestigious Fellowship , she has supervised numerous international comparative studies including SITES 2006, ICILS 2013, and longitudinal digital citizenship research (2019-2021).

Maksym Andriushchenkoمشاهده پروفایل

پژوهشگر

• AI Safety
• Adversarial Robustness
• LLM Alignment
• +۳ مورد دیگر

Maksym Andriushchenko is an incoming faculty member at the ELLIS Institute Tübingen and Max Planck Institute for Intelligent Systems , where he will lead the AI Safety and Alignment group as a principal investigator. Currently, he is a Doctoral Assistant at the Theory of Machine Learning Laboratory (TML) within the Department of Computer Science (IINFCOM) at Swiss Federal Institute of Technology in Lausanne (EPFL) . His work focuses on AI safety, adversarial robustness, and alignment of large language models (LLMs) with societal values.

Andrew Headمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Programming
• Reading
• +۱۳ مورد دیگر

Andrew Head is an Assistant Professor at the University of Pennsylvania in the Computer and Information Science department. His research focuses on human-computer interaction, programming, and reading, particularly in developing technology for interactive reading and reasoning. He advises PhD students Alyssa Hwang, Hita Kambhamettu, Litao Yan, Jeffrey Tao, and Jessica Shi, and co-leads the Penn Human-Computer Interaction (Penn HCI) group with Danaé Metaxa. His work is published in top venues like ACM CHI, UIST, and ICSE. Research Interests: Andrew's work bridges interactive systems with programming environments, aiming to enhance how scientists and programmers interact with their tools. Key areas include AI-assisted code understanding, math notation accessibility, and medical note interpretation through interactivity. He employs user studies to identify needs and builds interactive systems to address them. Recent Article Trends: His publications emphasize systems-centric HCI approaches, integrating AI into code and document interfaces. Topics span code explanation (e.g., Ivie), property-based testing (e.g., Tyche), math notation augmentation (e.g., FreeForm), and medical informatics (e.g., Explainable Notes). Recent work also explores notebook environments (e.g., Bolt-on, Tyche) and literate programming (e.g., Colaroid). Scientific Awards: Distinguished Paper Award, ICSE 2024 Best Paper Awards at CHI (2024, 2023, 2022, 2019), UIST (2023, 2018), and others. Nominated for Best Paper at CHI 2023 and VL/HCC 2015. Advising & Grants: Andrew advises multiple PhD students and has secured significant grants, including a $1M NSF award for 'Property-based Testing for the People' (2024). His group collaborates with Penn’s MindCORE center and teams like PLClub and PennNLP. Labs & Teams: He co-leads the Penn HCI group, which works closely with other Penn research teams and labs. The group focuses on creating interactive tools that enhance scientific and programming workflows, supported by grants and cross-institutional partnerships.

José Eduardo Villalobos Grailletمشاهده پروفایل

استادیار

• Spanish Film Studies
• Spanish Medieval Literature
• Latin American and Caribbean Studies
• +۵ مورد دیگر

José Eduardo Villalobos Graillet is an Assistant Professor of Spanish at Idaho State University , specializing in Modern Peninsular Literature and Culture with a focus on visual culture (film and television) . He previously held a position as Spanish Instructor at Wilfrid Laurier University in the Department of Languages and Literatures. Research Areas : Spanish Film Studies, Spanish Medieval Literature, Latin American and Caribbean Studies, Teaching Spanish as a Foreign Language, Visual Culture, and Critical Pedagogy. His scholarly work examines film and television adaptations of 'La Celestina' , analyzing censorship dynamics across Francoist Spain, the Democratic Transition, and contemporary Spain. He also contributes to Spanish pedagogy , developing technological tools like Lang-8 for written expression and culturally immersive teaching units on topics such as winter festivals and Caribbean music. His publications span both critical academic analysis and methodological innovations for language instruction. Key Themes in Publications : Adaptation fidelity, political censorship, intercultural pedagogy, and the role of digital platforms in language learning.

Ray Bobrownickiمشاهده پروفایل

مدرس

• Sport Psychology
• Coaching Instruction
• Motor Learning
• +۴ مورد دیگر

Dr. Ray Bobrownicki is a Lecturer in Sport Psychology and Co-Programme Director of the BSc (Hons) Applied Sport Science at the University of Edinburgh's Moray House School of Education and Sport. He holds affiliations with the Institute for Sport, Physical Education and Health Sciences (ISPEHS) and the Human Performance Science Research Group. As a chartered psychologist (BPS) and licensed athletics coach, his work bridges academic research and real-world sport practice. Educations: PhD (Sport Psychology and Coaching), University of Edinburgh MSc (Performance Psychology), University of Edinburgh AB (Psychology), Brown University PGCert (Academic Practice), University of the West of Scotland His research focuses on optimizing coaching instruction, motor learning, and performance under pressure. He explores how verbal instructions, analogies, and technology (e.g., VR) influence skill acquisition and athlete motivation. Secondary interests include the societal impacts of sporting policies on athlete welfare and identity. Recent work critiques traditional sport science methodologies and advocates for interdisciplinary, applied research. His publications span 2015–2025, emphasizing critical analysis of coaching practices, motor learning mechanisms, and systemic issues in sport. Key themes include instructional design, constraints-led approaches, and translational research validity. Awards: Fellow of the Higher Education Academy Chartered Psychologist (British Psychological Society) Associate Fellow (British Psychological Society) Teaching responsibilities include programme leadership for BSc Applied Sport Science and contributions to MSc Performance Psychology modules. He currently supervises PhD student Tongyu Liu on esports support taxonomies and welcomes inquiries on coaching instruction, performance psychology, and athlete policy impacts. Dr. Bobrownicki’s career integrates athletic experience (Commonwealth Games finalist, high jumper) with coaching expertise (e.g., mentoring record-breaking athletes) to inform evidence-based practice in sport science.

Arman Cohanمشاهده پروفایل

استادیار

• Machine Learning
• Natural Language Processing (NLP)
• Language Modeling
• +۷ مورد دیگر

Arman Cohan is an Assistant Professor of Computer Science at Yale University, affiliated with the School of Engineering & Applied Science. His research focuses on the intersection of Machine Learning and Natural Language Processing (NLP), particularly in language modeling, representation learning, retrieval systems, and applications in specialized domains such as scientific text processing. He earned his Ph.D. in Computer Science from Georgetown University and has received notable awards, including the Dr. Harold N. Glassman Distinguished Doctoral Dissertation Award (2019) and the EMNLP 2017 Best Long Paper Award. His work emphasizes ethical AI, robustness of LLMs, and interdisciplinary applications in healthcare, science, and education. Cohan's research group, the Yale NLP Lab, develops advanced techniques for multi-document summarization, adversarial fact-checking, and LLM-driven tools for scientific discovery. Recent projects include frameworks like SciBERT, Longformer, and ChemAgent, which enhance domain-specific reasoning and safety in AI systems. His publications address challenges in table reasoning, uncertainty expression, and multimodal reasoning, with applications in medical decision-making and educational problem-solving. He collaborates on initiatives like the Roberts Innovation Fund to advance AI in healthcare and environmental technology.

Gail E. Josephمشاهده پروفایل

استاد

• Early Childhood Education
• Child Development
• Social-Emotional Learning
• +۳ مورد دیگر

Gail E. Joseph is a Professor in the College of Education at the University of Washington, with affiliations in Early Childhood & Family Studies and Learning Sciences & Human Development. She teaches courses, advises students, and conducts research on early care and education, focusing on child care quality, social-emotional learning, teacher education, and technology integration. Ph.D., University of Washington Her research projects include statewide surveys on early childhood workforce conditions, studies on digital professional learning tools like Circle Time Magazine, and evaluations of coaching interventions (e.g., FIND in Childcare) to improve teacher-child interactions. She co-created resources such as Teacher Time and the EarlyEdU Alliance, which aims to enhance early childhood education through accessible bachelor’s degrees. Her publications span topics like social-emotional curricula, behavioral interventions, and inclusive education frameworks. She has held leadership roles as Principal Investigator (PI) of the Head Start Center for Inclusion and Co-PI of the National Center for Quality Teaching and Learning (NCQTL). 2018 David R. Thorud Leadership Award (University of Washington) She currently serves as Executive Director of Cultivate Learning at the University of Washington, advancing professional development and quality improvement initiatives nationwide.

• Speech-Language Pathology
• Pediatric Speech Sound Disorders
• Scholarship of Teaching and Learning
• +۳ مورد دیگر

Jennifer C. Dalton serves as Associate Professor and Undergraduate Program Director in the Department of Communication Sciences and Disorders within Appalachian State University's Beaver College of Health Sciences. With over 15 years of higher education experience, she provides strategic leadership in curriculum development, program assessment, and student success initiatives across the undergraduate program. Her educational foundation includes: Ph.D. in Speech and Hearing Sciences, UNC Chapel Hill (2012) M.A. in Communication Sciences and Disorders, Appalachian State University (1999) M.B.A., Appalachian State University B.S. in Speech Pathology and Audiology, Kent State University (1997) Dr. Dalton's research bridges clinical practice and educational innovation, focusing on pediatric speech disorders while advancing scholarship in teaching methodologies. Her work examines how experiential education builds graduate competencies and how employment prospects influence student retention, reflecting her commitment to evidence-based program development. Recent publications demonstrate consistent output in higher education scholarship, with three peer-reviewed articles published between 2023-2024 addressing pandemic-era pedagogy, graduate training, and student retention analytics. These works highlight her dual expertise in clinical communication sciences and educational leadership. Her academic recognition includes: 2021 Beaver College of Health Sciences Outstanding Teaching Award 2023 UNC System Academic Affairs Faculty Fellowship Dr. Dalton actively secures program development grants that enhance student learning outcomes through innovative curriculum design. As program director, she oversees clinical education pathways while maintaining her ASHA clinical certification and Quality Matters online teaching credentials. Her leadership emphasizes inclusive education practices that prepare diverse learners for professional success in dynamic healthcare environments. Though not leading a named laboratory, Dr. Dalton is central to departmental research through her scholarship of teaching and learning, influencing clinical education standards across the discipline.

Ying Xuمشاهده پروفایل

استادیار

• Early Education
• Evidence-Based Intervention
• Families and Community
• +۵ مورد دیگر

Ying Xu is an Assistant Professor at the Harvard Graduate School of Education (HGSE), specializing in the design of AI technologies to support children's language, literacy, STEM learning, and well-being. Her research emphasizes creating AI systems that act as interactive learning companions and language partners for children while fostering human-AI collaboration with educators and families. She holds a Ph.D. in Language, Literacy, and Technology from the University of California, Irvine, and previously served as an Assistant Professor at the University of Michigan from 2022 to 2024. Her work focuses on understanding how AI can complement human interactions, particularly through conversational agents integrated into media like books and educational TV programs. Collaborations include partnerships with PBS KIDS, GBH Education, and Sesame Workshop. Funded by organizations such as the National Science Foundation and Schmidt Futures, her research bridges developmental psychology, education, and human-computer interaction. Xu's studies highlight AI's potential for personalized learning while addressing ethical considerations like AI literacy and social impact. Key achievements include numerous best paper awards and recognition as an Early Career Interdisciplinary Scholar by SRCD. Her interdisciplinary approach involves designing technologies that reflect community values and linguistic/cultural diversity, ensuring equitable access to AI-driven educational tools. Xu advocates for balanced AI integration in children's lives, emphasizing the need for transparency about AI's limitations and the importance of maintaining human connections. She explores how AI can empower stakeholders (e.g., educators, parents) to co-create technologies tailored to their needs, ensuring AI serves as a complement—not replacement—for human interaction. Current projects investigate conversational AI's design principles, children's perceptions of AI, and strategies for fostering critical evaluation of AI-generated content. She also examines how AI affects social interactions and developmental processes, advocating for ethical guidelines to maximize benefits while mitigating risks.

Maj Schian Nielsenمشاهده پروفایل

پژوهشگر

• Multilingualism
• Language Education
• Crosslinguistic Awareness
• +۳ مورد دیگر

Maj Schian Nielsen is a Senior Research Librarian at the University Library of the University of Agder. Her work focuses on multilingualism, crosslinguistic awareness, and German language pedagogy. She is affiliated with the research groups 'Media and Communication Studies' and 'Multilingualism in Society and Education (MUSE).' University of Agder Research Groups: Media and Communication Studies, MUSE Her research explores how multilingual awareness can enhance grammar instruction in German third-language (L3) teacher education programs across Denmark and Norway. Recent publications analyze curriculum structures, educational materials, and the integration of generative AI tools like ChatGPT in multilingual education contexts. Scientific output trends reveal a focus on: Cross-linguistic pedagogy L3 German acquisition Grammar teaching methodologies AI applications in language learning Teacher training for multilingual classrooms Systemic Functional Linguistics (SFL) frameworks She has not been publicly recognized with scientific awards listed in the available data.