جست‌وجوی استاد و پژوهشگر

Hanna N. Haydarمشاهده پروفایل

دانشیار

• Mathematics Education
• Bilingual Education
• Special Education
• +۵ مورد دیگر

Hanna N. Haydar is an Associate Professor in the Department of Childhood, Bilingual and Special Education at Brooklyn College, School of Education (CUNY). Her work focuses on mathematics education, equity, and teacher preparation, with a particular emphasis on bilingual learners and inclusive settings. Ph.D. in Mathematics Education from Columbia University (2002) Her research explores: Culturally responsive-sustaining pedagogy in math instruction Integration of computational thinking and digital literacies Using children's literature and historical storytelling for mathematization Clinical interview methods for assessing student reasoning Addressing educational policy dissonance in urban teaching Supporting emergent bilinguals in mathematics Recent publications examine global education frameworks, teacher professional development, and equity in mathematics pedagogy. She leads CUNY-funded research projects on Algebra for All implementation and computational thinking integration. Awards include the 2025 Claire Tow '52 Award for Excellence in Teaching and multiple CUNY research grants. She co-founded Mathkind's Education Advisory Board and serves on EDULEARN's International Scientific Advisory Board. Haydar collaborates with international scholars (e.g., Betina Zolkower, Meral Kaya) on lesson study groups and teacher professional development. She contributes to global dialogues on educational inclusion and cultural relevance through invited talks in Turkey, Oman, and Guatemala.

Allan Wuمشاهده پروفایل

دانشیار بالینی

• Movement Disorders
• Neuromodulation
• Neurorehabilitation
• +۳ مورد دیگر

Allan Wu, M.D., serves as an Associate Clinical Professor in the Department of Neurology at the David Geffen School of Medicine, University of California, Los Angeles (UCLA). He is based at the Reed Neurological Research Center in Los Angeles, where he contributes to clinical care and research in movement disorders through his academic appointment and active clinical engagement. Dr. Wu's research program centers on movement disorders, with a particular focus on Parkinson's disease and dystonia. His work integrates cutting-edge neuromodulation techniques such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and transcranial direct current stimulation (tDCS) to develop novel therapeutic approaches. Additionally, he explores the application of health informatics and electronic health records to improve patient safety and clinical decision-making in neurology. His interdisciplinary collaborations span neurology, psychiatry, biomedical engineering, and data science, fostering a comprehensive approach to understanding and treating complex neurological conditions. Movement Disorders (Parkinson's, dystonia, tremor) Neuromodulation (TMS, DBS, tDCS) Neurorehabilitation and motor learning Clinical neurophysiology and cortical excitability Health informatics for neurological care Analysis of his recent publications (2017-2024) reveals a strong emphasis on technological innovation in clinical neurology. Key trends include standardizing electronic health record tools for Parkinson's disease management, developing quantitative movement assessment using markerless 3D kinematics, and investigating non-invasive brain stimulation for cognitive and motor rehabilitation. His work consistently bridges laboratory neuroscience with practical clinical applications, focusing on measurable improvements in patient safety, diagnostic accuracy, and therapeutic outcomes for movement disorder patients. Dr. Wu actively collaborates with multidisciplinary teams at UCLA's Reed Neurological Research Center and beyond. His clinical work integrates closely with research initiatives, particularly in developing and validating novel assessment tools and therapeutic protocols for movement disorders. His contributions to clinical neurology demonstrate a commitment to translating scientific discoveries into improved patient care pathways and healthcare system efficiencies.

Wei Panمشاهده پروفایل

دانشیار

• Causal inference and propensity score analysis
• Multilevel, longitudinal, and structural modeling
• Research synthesis and meta-analysis
• +۳ مورد دیگر

Dr. Wei Pan serves as Associate Professor and Faculty Lead for the Research Area of Excellence in Methods and Analytics at Duke University School of Nursing. He holds a PhD in Measurement and Quantitative Methods from Michigan State University (2001) and an MS in Statistics from Fuzhou University, China (1989). His educational credentials include: PhD in Measurement and Quantitative Methods, Michigan State University, 2001 MS in Statistics, Fuzhou University, China, 1989 Dr. Pan specializes in advanced statistical methodologies including causal inference, propensity score analysis, multilevel modeling, and meta-analysis. His research bridges methodological innovation with critical applications in adolescent health, substance abuse, symptom management, and health disparities. He has developed significant expertise in reducing selection bias in observational studies, as evidenced by his book Propensity Score Analysis: Fundamentals and Developments . His work consistently addresses measurement challenges in social, behavioral, and health sciences contexts. Analysis of Dr. Pan's recent publications (2024-2025) reveals a dominant focus on health equity and methodological rigor. His work spans sickle cell disease management, HIV outcomes in global contexts, adolescent mental health, and systemic biases in healthcare delivery. He frequently employs latent profile analysis, meta-analytic techniques, and causal modeling to investigate complex phenomena like nurse burnout during emergencies, digital media impacts on cognition, and racial disparities in anesthesia. His research demonstrates strong alignment with NIH-funded priorities in health services and implementation science. Dr. Pan has secured continuous funding from major federal agencies including the National Institutes of Health (NIH), National Science Foundation (NSF), and U.S. Department of Education. His collaborative projects emphasize interdisciplinary approaches to chronic disease management, healthcare transitions, and mental health equity. While no formal students are listed in his directory, his methodological expertise supports numerous trainees through the PhD in Nursing and Doctor of Nursing Practice programs at Duke.

Laure Soulierمشاهده پروفایل

مدرس

• Design of language models for Information Retrieval (IR) and Natural Language Processing (NLP)
• Data-to-Text Generation
• Search-Oriented Conversational Systems
• +۳ مورد دیگر

Laure Soulier is a HDR (Habilitation à Diriger des Recherches) Lecturer at Sorbonne University within the MLIA team at the ISIR (Institute for Intelligent Systems and Robotics) laboratory. Her research focuses on the design of language models for Information Retrieval (IR) and Natural Language Processing (NLP) applications, including data-to-text generation , search-oriented conversational systems , language models for robotics , and continual learning with domain adaptation . Recent publications highlight her work on cross-encoders, co-speech gesture generation, and latent space metrics. She supervises an ANR-funded postdoctoral researcher position (SCAI/BnF program) and collaborates on projects involving multimodal techniques, user interaction analysis, and document vectorization. Her scientific contributions include best paper awards at CORIA 2021, SCAI@EMNLP 2019, CORIA 2015, and AIRS 2013. Laure Soulier’s work spans collaborative information retrieval models, entity ranking in heterogeneous networks, and neural approaches for knowledge-based IR. She has contributed to evaluation frameworks for LLMs in IR and co-speech gesture generation, with applications in e-commerce search, medical information retrieval, and social media-based collaboration. Her research integrates user roles, document representations, and reinforcement learning techniques.

• Mathematics Education
• Didactics
• Cultural Comparisons in Education
• +۳ مورد دیگر

Benedetto Di Paola is an Associate Professor at the University of Palermo , affiliated with the School of Human Sciences and Cultural Heritage . His primary teaching role involves mathematics education for elementary and kindergarten schools, focusing on pedagogical methodologies and didactic implementations. His research interests center on mathematics education, particularly exploring cross-cultural cognitive differences between Chinese and European educational systems. Key areas include: Epistemological foundations of mathematical demonstration Impact of natural language on mathematical reasoning Argumentation processes in multicultural primary schools Role of cultural context in algorithmic thinking Integration of rhythm and movement in mathematical learning His publications (2007-2011) systematically investigate the intersection between: Chinese logographic writing systems and mathematical cognition Fuzzy logic applications in common sense reasoning Comparative analysis of chess/Weich’i strategies Statistical implicational analysis in educational research Historical mathematical texts (e.g., Liu Hui's Nine Chapters)

• Collaborative Learning
• Uncertainty Management in STEM
• Feedback Mechanisms
• +۱۲ مورد دیگر

Chandan Dasgupta is an Assistant Professor in the Educational Technology department at Indian Institute of Technology Bombay. He holds a Ph.D. in Learning Sciences from the University of Illinois at Chicago and a Master’s in Human-Computer Interaction from Georgia Institute of Technology. His research focuses on collaborative learning, uncertainty management in STEM, and distributed creativity in makerspaces. Education: Ph.D. in Learning Sciences, University of Illinois at Chicago M.S. in Human-Computer Interaction, Georgia Institute of Technology Dasgupta designs technology-enhanced environments for STEM education, emphasizing embodied learning, inquiry-based pedagogy, and artificial intelligence integration. His recent work explores AR/VR applications for spatial reasoning and critical action curricula in engineering education. Analysis of his 88 research outputs reveals trends in collaborative learning technologies (19 publications in 2023-2025), uncertainty management frameworks (13 papers), and makerspace creativity (7 studies). Key technologies include augmented reality (GeoSolvAR, MathReality), virtual reality conversational agents, and adaptive learning systems. Dasgupta actively contributes to EdTech policy discussions in India, advocating for contextualized solutions aligned with UN Sustainable Development Goals. His collaborations span institutions in the USA (Purdue, Georgia Tech) and India (IIT Bombay, Tulna partnership).

Daniel Braunمشاهده پروفایل

پژوهشگر

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

Daniel Braun is a Researcher at the Digital Society Institute , affiliated with Technical University of Munich . His work bridges Artificial Intelligence , Natural Language Processing , and LegalTech , focusing on automated legal assessment of contracts, ethical dimensions of AI, and consumer protection in the digital era. Education: Bachelor in Artificial Intelligence at Saarland University PhD in Automated Semantic Analysis, Legal Assessment, and Summarization of Standard Form Contracts at Technical University of Munich Master in Creating Textual Driver Feedback from Telemetric Data at University of Aberdeen Research Interests revolve around applying NLP to legal and engineering domains. Key areas include machine learning for contract analysis , ethical AI frameworks , and consumer protection through automated systems . His recent work explores adversarial attacks on text detectors, lexical alignment in chatbots, and robustness in generative AI detection. Publications (2024-2025) highlight advancements in German consumer contract analysis , disagreement handling in legal datasets , and regulatory debates around AI . Notable outputs include the AGB-DE corpus and studies on black-box neural text detectors . Technical Expertise spans data mining , process mining , and domain-specific NLP . He has contributed to smart contract analysis , conversational AI , and language models for engineering and legal contexts .

Isidora Stojanovicمشاهده پروفایل

عضو هیئت علمی

• Philosophy of Language
• Semantics
• Pragmatics
• +۹ مورد دیگر

Isidora Stojanovic is a Research Director at the Jean Nicod Institute (CNRS, Paris) and a Distinguished Research Fellow at Pompeu Fabra University (Barcelona, 2024-2029). She leads the ERC Advanced Grant project Valence Asymmetries , examining evaluative language and cognition. Her work bridges philosophy of language , value theory , and semantics-pragmatics intersections. Education : Details not explicitly provided in the text. Research Themes : Context sensitivity, evaluative discourse, indexicality, semantics-pragmatics boundaries, and the role of valence in language and morality. Her articles focus on slurs, thick terms, taste and moral predicates, and de se content. These works are grounded in experimental philosophy , semantic theory , and interdisciplinary analysis . She coordinates the STAL network (Slurring Terms Across Languages) and has participated in modeling and using context conferences. Scientific Awards : ERC Advanced Grant No. 101142133 (2024-2029) Advising : Supervised multiple PhD students, including Bianca Cepollaro (2017), Andrés Soria Ruiz (2019), and Victor Carranza Pinedo (2022), with committees involving institutions like ENS Paris and University of Milan. Labs & Teams : Affiliated with the MIND AND LANGUAGE team at the Jean Nicod Institute and the STAL network for interdisciplinary slurs research.

• Robotics
• Autonomous Systems
• Spatial Cognition
• +۶ مورد دیگر

Patric Jensfelt is a full-time Professor at the Robotics, Perception and Learning (RPL) division within the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology . He contributes to robotics and autonomous systems through research, teaching, and industry collaboration. Academic Rank: Professor Department: Robotics, Perception and Learning (RPL) School: School of Electrical Engineering and Computer Science (EECS) University: KTH Royal Institute of Technology His research focuses on robotics and autonomous systems , particularly spatial cognition for enabling robots to understand and model their environments. He integrates sensor data with high-level symbolic reasoning to advance navigation, mapping, and system integration. Recent work includes applications in service robotics, 3D foot scanning (via the company Volumental ), and drone-based perception. The 15 most recent articles highlight advancements in scene flow estimation, autonomous driving, LiDAR processing, and domain adaptation. They emphasize self-supervised learning , dynamic environment modeling , and robust spatial representations for autonomous systems. Patric supervises Master’s and PhD students, particularly in project courses like DD2410 Introduction to Robotics , DD2419 Project Course in Robotics and Autonomous Systems , and the doctoral course FDD3356 System Integration for Robotics . He is actively involved in the WASP Graduate School , teaching Autonomous Systems annually. He leads the Robotics, Perception and Learning (RPL) division, which fosters innovation in robotics through experimental projects and industry partnerships like Intelligent Machines . The division supports internships (unpaid) and encourages applicants to demonstrate prior engagement with his research.

Arne Bewersdorffمشاهده پروفایل

پژوهشگر

• AI Literacy
• Educational Technologies
• Science Education
• +۴ مورد دیگر

Dr. Arne Bewersdorff is a Post Doctoral Researcher in Educational Sciences at the Technical University of Munich (TUM), School of Social Sciences and Technology. He coordinates the TUM-DigiLLab (Digital Teaching and Learning Lab), which promotes digital skills in secondary and vocational teacher training. His work focuses on fostering AI literacy and developing AI tools for STEM education through research and teaching activities. Dr. Bewersdorff's research interests center on AI literacy, educational technologies, science education, and teacher training. His work explores how AI can enhance science education through adaptive feedback systems, experimentation protocols, and digital learning environments. He investigates AI attitudes, self-efficacy, and the development of AI literacy among university students and pre-service teachers. His research spans both theoretical frameworks and practical implementations of AI in educational contexts. His recent publications reveal a strong trend toward AI applications in education, particularly focusing on AI literacy assessment, adaptive feedback systems, and the integration of large language models in science education. His work spans multiple methodologies including systematic reviews, test development, experimental studies comparing AI and human performance, and multinational assessments of AI literacy. The research consistently addresses practical applications of AI in educational settings while maintaining strong theoretical foundations in educational psychology and science pedagogy. Fellow of the TUM Center for Educational Technologies Recipient of ESERA Travel Award Member of winning HOLA Innovation Pitch team at Medien- und Filmgesellschaft Baden-Württemberg Dr. Bewersdorff coordinates multiple significant research projects including the TUM-DigiLLab infrastructure, EPIC-AI (an AI feedback tool for student experimentation protocols), Junior Fellowship Artificial Intelligence (developing AI literacy courses for pre-service science teachers), and the Knowledge Hub project providing Open Educational Resources on emerging technologies. He has received funding from the Joachim Herz Foundation and through TUM's Excellence Strategy initiative. His work bridges research and practice through close collaboration with educational institutions and practitioners. As coordinator of the TUM-DigiLLab, Dr. Bewersdorff leads a multidisciplinary team focused on creating innovative digital teaching and learning environments. The lab serves as both a research and development space for digital competencies and a practical training ground for future educators. His team collaborates across disciplines to develop and assess AI tools specifically designed for STEM education contexts.

Mina Sonمشاهده پروفایل

مدرس

• Psychometrics
• Industrial-Organizational Psychology
• Natural Language Processing
• +۴ مورد دیگر

Mina Son is an academic at George Mason University's Department of Psychology, specializing in Industrial-Organizational Psychology. She holds a Master's degree in Personality and Social Psychology from Yonsei University (2015) and a Bachelor's in Urban Planning and Engineering from the same institution (2013). Her work focuses on psychometrics, forced-choice measurement techniques, natural language processing in personality assessment, and employment testing fairness. She teaches courses such as PSYC 300 (Statistics in Psychology), PSYC 435 (Personnel Training and Development), and lab sections for advanced statistical modeling courses. Dr. Son's research emphasizes innovative applications of technology in assessment, including generative AI for test development and machine learning approaches to detect faking in personality assessments. Her recent work explores the historical evolution of forced-choice measurements and the impact of situational strength on behavioral consistency. She has been recognized with a Best Papers (top 10%) award at the 2025 Academy of Management conference for her work on generative AI in testing validation. Her professional activities include presentations at major conferences like the Society for Industrial and Organizational Psychology and Academy of Management. Current research collaborations involve projects on political will measurement and adverse impact analysis in personnel selection systems. She maintains an active role in the academic community through teaching, research supervision, and contributions to psychological assessment methodologies.

• Educational technology
• Information and communication technology
• Intercultural communication
• +۲ مورد دیگر

Douglass Scott is a Professor at Waseda University's School of Human Sciences in Tokyo, Japan, where he has made significant contributions to educational technology and intercultural communication research. His academic career spans over two decades with a particular focus on digital communication patterns, emotional expression in mobile media, and online education systems. He is closely associated with Waseda University's e-School, Japan's first complete undergraduate online degree program established in 2003. Dr. Scott earned his PhD in 1997 from the University of Michigan's School of Education with a specialization in Educational Foundations and Policy and Educational Technology. He also holds an MA in East Asian Studies (Japan) from the University of Michigan (1987) and a BS in Political Science from the University of Oregon (1985). His educational background includes a period at Waseda University's International Division during 1983-1984. His research primarily focuses on educational technology, information and communication technology, and intercultural communication, with special attention to how emotions are transmitted through digital channels. His work often compares Japanese and American communication patterns, particularly examining gender differences and cultural variations in mobile phone email usage. He has documented the development and implementation of Waseda University's pioneering e-School program across multiple publications. Analysis of his publication record reveals consistent scholarly contributions examining emotional expression in digital communication, with particular emphasis on how gender and cultural background influence emotional transmission through mobile devices. His research shows a clear trajectory from foundational work on educational telecommunications models to applied research on specific communication technologies in educational contexts. Dr. Scott maintains active research projects including comparative studies of mobile telephone use across countries and investigations into the role of social networks in cultural adjustment of exchange students. His work has been supported by Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research. As an educator, he teaches across multiple programs at Waseda University including the Graduate School of Human Sciences and the School of Human Sciences Online Degree Program. His teaching portfolio encompasses Information and Communication Technology courses, Academic Writing, Intercultural Communication, and English language instruction.

• Empirical Software Engineering
• Requirements Engineering
• Applied Natural Language Processing
• +۷ مورد دیگر

Dr. Chetan Arora is a Senior Lecturer in Software Engineering at Deakin University's School of Information Technology, part of the Faculty of Science Engineering and Built Environment. He holds a PhD from the University of Luxembourg where he received the best PhD thesis award in the ICT domain. His research focuses on applied Artificial Intelligence in Software Engineering, with particular emphasis on Empirical Software Engineering, Requirements Engineering, and Applied Natural Language Processing. PhD in Computer Science from University of Luxembourg Masters in Software Engineering from Technische Universitat Kaiserslautern (Germany) Bachelors in Engineering (CS) from Thapar University (India) Arora's research interests center on the intersection of AI and Software Engineering, particularly how machine learning and natural language processing can enhance software development processes. His work explores requirements engineering, test automation, software trustworthiness, and human-centric software development. He investigates how large language models can be effectively deployed for tasks like test case generation, requirements analysis, and traceability. His recent publications reveal a strong focus on practical applications of AI in software engineering, with numerous studies examining the real-world implementation challenges and benefits. His publication record shows significant activity in top software engineering venues, with a notable emphasis on AI applications in software engineering processes. His recent work demonstrates expertise in retrieval-augmented generation systems, requirements-driven testing, and human-centric software development approaches. The publications collectively highlight his focus on bridging theoretical AI advancements with practical software engineering challenges. Best Ph.D. thesis award in the ICT domain at University of Luxembourg Arora actively supervises doctoral students working on cutting-edge topics including satellite communication systems, extended reality applications, and human-centered AI requirements engineering. His industry collaborations include work with Department of Defence on projects like Contextually Situated Anomaly Detection and Planning and Optimisation of Resources in Defence Satellite Communication Systems. He previously worked at SES Satellites on applied AI for IoT and Satcom, and as an FNR-PPP research fellow at the University of Luxembourg in software quality assurance. His laboratory work focuses on developing practical AI solutions for software engineering challenges, particularly in requirements engineering and test automation. Current projects involve multi-orbit satellite constellation optimization, dynamic radio resource management, and extended reality enabled human-centric requirements engineering.

Sam Malekمشاهده پروفایل

استاد

• Software Engineering
• Software Analysis and Testing
• Mobile Computing
• +۳ مورد دیگر

Sam Malek is a Professor in the Department of Informatics at the University of California, Irvine's School of Information and Computer Sciences, where he directs the Software Engineering and Analysis Laboratory. Previously serving as Director of the Institute for Software Research (2018-2022), his academic leadership spans software engineering research and institutional management. His research centers on software engineering with specialized expertise in software analysis and testing , mobile computing , security , software architecture , and accessible computing . Malek's work consistently focuses on developing practical techniques and tools for constructing, analyzing, and maintaining large-scale software systems, with recent emphasis on accessibility challenges in mobile and web environments. His publication trends reveal a strategic shift toward accessible computing since 2020, where he pioneered frameworks like Ma11y for web accessibility testing and Groundhog for mobile app crawling. Earlier work established foundations in energy testing (2020), GUI input generation (2021), and architectural analysis, demonstrating methodological evolution from core software engineering to human-centered accessibility solutions. ACM SIGSOFT test-of-time award (2020) National Science Foundation CAREER award (2013) GMU Emerging Researcher/Scholar/Creator award (2013) GMU Computer Science Department Outstanding Faculty Research Award (2011) Malek serves on editorial boards for ACM Transactions on Software Engineering and Methodology and ACM Transactions on Autonomous and Adaptive Systems , while frequently acting as a software expert witness in intellectual property litigation. His research group actively recruits PhD students through UCI's Software Engineering PhD program, with current projects focusing on AI-driven accessibility solutions and mobile testing frameworks. The Software Engineering and Analysis Laboratory under his direction maintains strong industry connections through sponsored research and tool development, particularly in accessibility testing and mobile application quality assurance.

• Artificial Intelligence
• Machine Learning
• Argumentation Theory
• +۳ مورد دیگر

Benoît ALCARAZ is a Researcher affiliated with the Department of Computer Science at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM). His work focuses on advancing artificial intelligence and machine learning, particularly in ethical AI frameworks, argumentation systems, and natural language processing. He is based at the Maison du Nombre research facility in Esch-sur-Alzette. Research Interests include developing algorithms for ethical decision-making in AI, optimizing machine learning models through evolutionary techniques, and creating user-centric NLP tools for real-time applications. His work bridges theoretical computer science with practical ethical considerations, as seen in his exploration of bias mitigation in visual learning and argumentation-based reinforcement learning agents. Notable contributions include frameworks like Ajar for ethical reinforcement learning and IRRMA for image-based meeting assistants. While no explicit awards or grants are listed, his publications indicate active involvement in interdisciplinary AI research with a focus on societal impact.