جست‌وجوی استاد و پژوهشگر

Mohamad Eidمشاهده پروفایل

دانشیار

• Haptics
• Multi-modal Human-Computer Interaction
• Affective Haptics
• +۷ مورد دیگر

Mohamad Eid is an Associate Professor of Electrical and Computer Engineering at New York University Abu Dhabi (NYUAD), with a Global Network Associate Professor appointment at NYU Tandon School of Engineering. He leads the Applied Interactive Multimedia Laboratory (AIMLab), focusing on cutting-edge research in haptics and multimodal interaction. His research interests include haptics, affective haptics, EEG-based neurohaptics, soft haptics, biofeedback technologies, and human-computer interaction. He explores how tactile feedback can enhance virtual and augmented reality, assistive technologies, and medical simulation. His recent publications demonstrate strong activity in IEEE Transactions on Haptics, ACM TOMM, and other top venues, with work spanning vibrotactile alarms, mid-air haptics, emotion communication via touch, and haptic dental simulation. His research integrates engineering, neuroscience, and multimedia to create immersive and affective user experiences. Best Paper Award, ICBAE 2016 Best Paper Award, DS-RT 2008 ACM Multimedia 2009 Grand Challenge Most Entertaining Award Mohamad Eid advises students through capstone projects in computer science and biology and has contributed to educational initiatives such as robotic handwriting assistance for Arabic script. He holds multiple patents in haptic feedback systems and is an active editor for IEEE Transactions on Haptics. His work is supported by grants and has been featured in media outlets like Wired and The National. He leads the Applied Interactive Multimedia Laboratory (AIMLab), a multidisciplinary research group developing innovative haptic and interactive systems for healthcare, education, and entertainment.

Richard Wicentowskiمشاهده پروفایل

استاد

• Natural Language Processing
• Computational Linguistics
• Computational Morphology
• +۴ مورد دیگر

Richard Wicentowski is a Professor of Computer Science at Swarthmore College. His research focuses on computational linguistics, including computational morphology, semantic disambiguation, and sentiment analysis. He teaches courses like CS 65 (Natural Language Processing) and CS 21 (Introduction to Computer Science). Ph.D. , Computer Science, Johns Hopkins University, 2002 M.S. , Computer Science, University of Pittsburgh, 1995 B.S. , Computer Science, Rutgers University, 1993 Wicentowski’s research spans Natural Language Processing , Computational Linguistics , Medical Informatics , and Computer Science Education . He has developed systems for sentiment classification using Twitter data, emotion detection in clinical texts, and cross-lingual lexical substitution. His work bridges machine learning with linguistics and health informatics. Recent publications highlight trends in sentiment analysis (2015–2025), medical text mining (2006–2012), and educational innovation (2005–2015). He has collaborated with students on NLP projects and explored diversity in computing education in 2025. Wicentowski advises students through co-authorship in projects like SWATCS65 and SWATAC. Notable collaborations include courses on machine learning and image processing (2005).

• Variational Linguistics
• Dialectology
• Political Communication
• +۳ مورد دیگر

Heiko Girnth is an Adjunct Professor at the Research Center Deutscher Sprachatlas (DSA) under the Department of German Studies and Arts at Philipps-University Marburg. His research spans multiple domains including Variational Linguistics , Dialectology , Political Communication , Grammaticalization , and Text Linguistics . Research Focus: Political discourse analysis, grammaticalization processes in German dialects, multimodal communication in political talk shows, and geolinguistic mapping of language variation. Key Publications: Authored and co-authored works on political rhetoric, dialectological studies, and text typology, including books on language in politics and edited volumes on political talk shows. Teaching: Offers courses like 'Sagen und Meinen' (Seminar) and 'Textlinguistik' (Lecture) at Philipps-University Marburg. Collaboration: Active in interdisciplinary projects, notably the Mittelrheinischer Sprachatlas (MRhSA), focusing on morphological and phonological dialect variation. Labs/Teams: Affiliated with the Research Center Deutscher Sprachatlas , contributing to linguistic mapping and dialectological research.

• Psychiatry
• Neurosciences
• Adolescent Mental Health
• +۹ مورد دیگر

Tony Yang, MD, PhD , is a Professor in the School of Medicine at the University of California, San Francisco (UCSF) , and a key member of the UCSF Weill Institute for Neurosciences . His research is dedicated to understanding the neural mechanisms underlying adolescent psychiatric disorders, with a strong focus on major depressive disorder, trauma, and neurodevelopment. Dr. Yang's research interests span adolescent mental health , neuroimaging (particularly fMRI and connectome analysis), emotional processing , mindfulness-based interventions , and the neuropsychiatric consequences of traumatic brain injury . His work investigates how brain network connectivity, especially in regions like the amygdala and prefrontal cortex, is altered in depression and how these changes relate to symptoms and treatment response. He is also deeply involved in large-scale international collaborations, most notably the ENIGMA consortium , which allows for powerful, multi-site analyses of brain structure and function in psychiatric conditions. The trends in his publication record show a consistent and high-impact focus on using advanced neuroimaging and machine learning to identify biomarkers for depression and suicide risk. His articles frequently explore the structural and functional brain alterations associated with psychiatric disorders in youth, the effects of interventions like mindfulness and cognitive therapy, and the interplay between biological systems (e.g., gut microbiota, HPA axis) and brain health. Dr. Yang has been the Principal or Co-Principal Investigator on several significant NIH-funded research projects, including: NIH R61AT009864 : Neural mechanisms of meditation training in healthy and depressed adolescents. NIH R01MH085734 : A cross-sectional and longitudinal fMRI study of adolescent depression. NIH K23MH070791 : Magnetic Resonance Imaging in Depressed Adolescents. NIH F30MH010174 : An early grant in the Neurosciences. His research is conducted in collaboration with a wide network of scientists, including prominent researchers like Jeffrey Max, Martin Paulus, and Alan Simmons. He leads a research team that investigates brain circuitry in adolescents, utilizing MRI to study the effects of training programs like TARA (Training for Awareness, Resilience, and Action) and to understand the long-term psychiatric outcomes following pediatric traumatic brain injury.

Sofia De La Fuente Garciaمشاهده پروفایل

پژوهشگر ارشد

• Speech technology for cognitive health monitoring
• Intangible cultural heritage and wellbeing
• AI and digital biomarkers
• +۴ مورد دیگر

Sofia De La Fuente Garcia is a Research Fellow at the University of Edinburgh's Usher Institute within the College of Medicine and Veterinary Medicine. She leads pilot studies and evaluation for the EU Horizon-funded INT-ACT project on intangible cultural heritage, wellbeing, and artificial intelligence. Her work bridges cognitive health assessment with cultural narratives through speech technology. Her educational background includes: PhD in Precision Medicine (AI and speech as a digital marker for cognitive health) MSc in Methodology for Behavioural and Health Sciences BSc (Hons) in Psychology Additional credentials include Fellowship of the Higher Education Academy, a Diploma on Systems and Family Therapy, and Gestalt Psychotherapy training. Her research integrates cognitive health monitoring with cultural heritage through: Development of speech collection methodologies based on Scottish folklore AI-driven analysis of speech as biomarkers for dementia Investigation of mindfulness and flow states in ancient crafts for mental wellbeing Personal narrative studies linking cultural heritage to emotional health Recent publications reveal strong emphasis on zero-shot learning for depression detection, interpretable speech foundation models, and cultural heritage interventions for older adults. Key scientific recognition: Fellow of the Higher Education Academy She currently holds a Horizon Europe Research Fellowship for INT-ACT (grant 101132719) and a Brain Health ARC 2025 Pump Priming Award. While not currently supervising PhD students, her Prevent-ED methodology has been implemented in the Centre for Dementia Prevention's cohort studies. Her work extends through collaborations with Karolinska Institutet, Universidad Autonoma de Madrid, and industry partner PST Inc. Active in the Edinburgh Centre for Medical Informatics, she contributes to the ADReSS Challenge series at Interspeech conferences and maintains laboratory partnerships focused on speech technology for neurodegenerative disease monitoring.

• Symbolic Practice and Modern Subjectivity
• Political Culture and Civil Society Engagement
• Educational Inequality
• +۷ مورد دیگر

Professor Michael Corsten is a full Professor of Sociology at the University of Hildesheim, Germany, affiliated with the Institute of Social Sciences within the Faculty of Educational and Social Sciences. He maintains an active research and teaching profile, with consultation hours listed during lecture periods. His institutional roles include serving as Academic Advisor for multiple programs including International Information Management (BA) and International Communication and Translation (BA), as well as handling credit transfer issues for Sociology in teacher training programs. He participates in significant university governance as a member of the Doctoral Committee FB 1, Budget Committee Department 1, and as Deputy Senate Member for Department 1. Professor Corsten's research spans several interconnected domains focused on modern social phenomena. His primary interests include symbolic practice and modern subjectivity, political culture and civil society engagement, educational inequality, and communication with digital media. His work often examines how individuals construct identity within societal frameworks, with particular attention to mythologization processes, generational differences, and social classification systems. Recent projects have investigated narrated educational and childhood experiences in the GDR, the analytical potential of qualitative longitudinal interviews in socialization research, and solidarity discourses in times of crisis. His publication record from 2022-2025 reveals consistent scholarly output across multiple high-impact venues. His research demonstrates a methodological diversity spanning qualitative and quantitative approaches, with particular strength in biographical and narrative analysis. Thematically, his work shows evolving focus from foundational questions of self and subjectivity toward increasingly applied concerns regarding political polarization, educational inequality, and social cohesion in contemporary Germany. As an academic leader, Professor Corsten contributes significantly to institutional development through his committee work and academic advising responsibilities. His research projects often involve interdisciplinary collaboration, particularly with colleagues working at the intersection of sociology, political science, and education studies. He appears to maintain active connections with multiple research networks focused on social inequality, political culture, and educational processes in German society.

• Human-Robot Interaction
• Human-Centered AI
• Affective Computing
• +۳ مورد دیگر

Dr. Leimin Tian is a Senior Lecturer at the Robotics Lab of Monash University and a Senior Scientist leading the Human-Robot Interaction Team within the Robotics Group of CSIRO's Data61 . His interdisciplinary research bridges Human-Robot Interaction , Human-Centered AI , and Affective Computing , focusing on developing socially intelligent robots capable of emotional perception, decision-making, and collaboration in diverse applications. Education: PhD in Informatics (University of Edinburgh, 2018) Master in Artificial Intelligence (University of Edinburgh, 2013) Bachelor in Intelligent Science and Technology (Beijing University of Posts and Telecommunications, 2012) His research emphasizes integrating social-emotional intelligence into robotic systems, enabling adaptive interactions through multimodal perception and context-aware decision-making. Key contributions include frameworks for error-tolerant human-robot collaboration and emotion recognition in dynamic environments. At CSIRO, he leads a robotics team exploring emotionally responsive agents, while at Monash University, he contributes to robotics education and innovation.

Annika Schoeneمشاهده پروفایل

پژوهشگر

• Responsible AI
• AI Safety
• Ethics of Artificial Intelligence
• +۵ مورد دیگر

Annika Schoene is a Research Scientist at Northeastern University's Institute of Experiential AI (EAI), working within the AI + Health Team and Responsible AI Practice. She holds additional appointments as Faculty Fellow at the Institute for Health Equity and Social Justice Research, and as Visiting Scientist at MaineHealth and the University of Southampton (UK). She is transitioning to an Assistant Professor role at Bouvé College of Health Science. Her educational background includes a PhD in Computer Science from the University of Hull (UK), where her doctoral research focused on sentiment/emotion classification in social media and suicide note detection using deep learning and linguistic analysis. Prior to EAI, she completed a postdoctoral fellowship at the University of Manchester's National Centre for Text Mining (NaCTeM). Dr. Schoene's research specializes in developing Responsible AI frameworks for healthcare applications, with emphasis on large language model (LLM) safety in sensitive domains like mental health. She investigates LLM robustness against jailbreak vulnerabilities and harmful outputs, designing evaluation metrics, guardrails, and value-alignment systems to ensure ethical deployment. Her work bridges technical AI development with policy considerations to mitigate algorithmic harm in clinical settings. She actively collaborates with interdisciplinary teams across EAI's AI + Health and Responsible AI Practice units, generating peer-reviewed publications featured in press discussions about ethical AI deployment in mental healthcare. Her current projects directly inform non-technical stakeholders and policymakers through evidence-based risk assessment frameworks.

• Political Communication
• Network Analysis
• Digital Extremism
• +۳ مورد دیگر

Harald Sick is a Researcher at the Institute of Journalism, Johannes Gutenberg University Mainz, affiliated with the Chair of Political Communication led by Prof. Dr. Marcus Maurer. Concurrently, he serves as a Research Associate for Network Analysis at the Institute for Democracy and Civil Society (IDZ), contributing to the project "Network against Online Hate and Disinformation." His work is supported by the DFG project "Identification and Classification of Radical and Extremist Actors on Telegram." He holds a degree in Political Science from Friedrich-Alexander University Erlangen-Nuremberg (2005–2011) and has pursued doctoral studies at Goethe University Frankfurt since 2015, focusing on lobbying influence in EU legislative processes. His research specializes in: Political communication dynamics, particularly right-wing extremism in digital spaces Computational methods including (discourse) network analysis, Graph Neural Networks, and LLMs Cross-platform strategies of extremist communities (e.g., Telegram, YouTube) Monetization of online hate speech and AI-driven radicalization His publications reveal a consistent focus on digital extremism, disinformation ecosystems, and computational social science. Recent works analyze generative AI in hate networks, meme-based radicalization, and economic incentives for extremist content. Trends indicate deep expertise in network statistics, crisis exploitation by extremists, and multi-platform discourse manipulation. He collaborates with interdisciplinary teams (e.g., Machine Against the Rage research collective) and maintains freelance roles in political data analysis. No advising activities or scientific awards are documented.

Kristin Martinsenمشاهده پروفایل

دانشیار

• Clinical Child and Adolescent Psychology
• Prevention of Emotional Disorders
• Cognitive Behavioral Therapy (CBT)
• +۳ مورد دیگر

Kristin Martinsen is an Associate Professor and Head of Department at the Department of Psychology, University of Oslo . She specializes in Clinical Child and Adolescent Psychology , focusing on anxiety and depression prevention in children and evidence-based intervention implementation. As a Fulbright scholar (2016) , she maintains international collaborations with Temple University and University of Texas at Austin. 2018: PhD in Psychology (University of Oslo) 2004: Cand.psychol. (University of Oslo, with exchange at University of Sydney) 1988: MBA (Kansas State University) 1986: Bachelor in Business Administration (Heriot-Watt University) Her research explores anxiety/depression screening , CBT intervention development , and school mental health programs . Recent studies examine parental involvement's impact on emotional disorders, CBT competence in therapists, and pandemic effects on youth mental health. Key publication trends include transdiagnostic CBT optimization, psychometric validation of youth anxiety tools, and implementation barriers in school settings. She has secured grants from the Norwegian Research Council , DAM Foundation , and Kavlistiftelsen . Scientific awards include: Fulbright scholar (2016) Employee-elected board representative (RBUP East and South, 2nd term) She leads the ANSA Edinburgh Cooperation and contributes to the DRIVE Research Initiative , focusing on developmental pathways to depression and treatment mechanisms.

• Digital Media
• Youth Studies
• Social Class
• +۷ مورد دیگر

Martin Danielsson is a Senior Lecturer at Halmstad University's School of Health and Welfare . Holding a PhD in media and communication studies (2014), he directs the three-year undergraduate program in Media and Communication Studies while conducting research on digital media practices among youth. Research Focus Digital inequalities and social class dynamics Emotional dimensions of digital life Media practices during involuntary disconnection Boredom in digital contexts Cultural capital and cosmopolitan cultivation Publication Trends show consistent exploration of digital media's societal impact, with recent work emphasizing emotional experiences during platform outages and boredom in digital environments. Older works examine class conditioning, media literacy interventions, and network society peripheries.

• Wireless Communications
• Intelligent Signal Processing
• Biomedical Engineering
• +۳ مورد دیگر

Sanam MOGHADDAMNIA serves as an Assistant Professor in the Department of Electrical and Electronics Engineering at the Faculty of Engineering, Turkish-German University, Turkey. He holds a BSc from Tabriz University (2002), and both MSc (2006) and PhD (2012) degrees in Electrical Engineering from Leibniz Universität Hannover, Germany. Prior to his current position, he worked as a Research Assistant and Postdoctoral Researcher at Leibniz Universität Hannover from 2006 to 2018. His educational background includes: BSc in Electrical and Electronics Engineering from Tabriz University, Iran (1997-2002) MSc in Electrical Engineering and Information Technologies from Leibniz Universität Hannover, Germany (2003-2006) PhD in Electrical Engineering and Computer Science from Leibniz Universität Hannover, Germany (2006-2012) His research spans wireless communications, telemetry, intelligent signal processing, and data analysis with significant applications in healthcare (including ECG-based diagnostics, sepsis prediction, and gait analysis), telecommunications, and industrial sectors. He demonstrates expertise in machine learning applications for biomedical signal interpretation and has contributed to both theoretical wireless communications frameworks and practical medical device assessments. Analysis of his 2016-2024 publications reveals a strategic pivot toward biomedical engineering applications while maintaining core wireless communications research. His work shows increasing focus on non-invasive medical diagnostics using physiological signals, machine learning for healthcare analytics, and precision assessment of medical devices, alongside continued contributions to MIMO systems and channel estimation techniques. Scientific Awards: None mentioned in source material. He actively manages and acquires collaborative research projects with industrial partners across healthcare and telecommunications sectors. No student advisement details are provided in the available documentation. His research involves interdisciplinary collaboration with industrial partners but no specific laboratory or team names are documented in the source material.

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +۷ مورد دیگر

Professor Julie Weeds is a faculty member at the School of Engineering and Informatics , University of Sussex. Her academic journey includes a DPhil in Natural Language Processing (2003), MPhil in Computer Speech and Language Processing (2000), and MA in Computer Science (1998). She has held positions including Postdoctoral Research Fellow (2003-2005, 2012-2016, part-time), Lecturer in Data Science (2016-present), and Professor of Artificial Intelligence (2023-present). MA Computer Science - Trinity Hall, Cambridge University (1995-1998) MPhil Computer Speech and Language Processing - Cambridge University (1999-2000) DPhil Natural Language Processing - University of Sussex (2000-2003) Her research spans Natural Language Processing , Machine Learning , and Computational Linguistics , focusing on semantic compositionality , vector representation analysis , and linguistic variation . Recent work applies NLP to dream reports , wildlife conservation , and mental health support . She leads grants related to hate speech analysis , suicide prevention , and illegal wildlife trade detection . Publications reveal trends in semantic entailment modeling , dream analysis using LLMs , and ecological informatics applications . Key themes include syntax-driven compositionality , multilingual modeling , and structure-aware paraphrase identification . Professor Weeds supervises research projects and teaches courses including Advanced Natural Language Engineering, Natural Language Processing, and Data Science methods. Collaborators include David Weir, Luca Bertolini, and Qi Peng, with affiliations to CASM Consulting LLP and Innovate UK projects.

Elizabeth Teelمشاهده پروفایل

استادیار

• Concussion
• Neurophysiology
• Rehabilitation
• +۳ مورد دیگر

Elizabeth Teel is an Assistant Professor in the Department of Health, Kinesiology and Applied Physiology at Concordia University. Her research focuses on concussion neurophysiology and rehabilitation, utilizing neuroimaging and clinical assessments to improve brain function recovery. Education: BA (Highest Honors) in Exercise and Sport Science, University of North Carolina at Chapel Hill PhD in Human Movement Science, University of North Carolina at Chapel Hill MSc in Kinesiology, Penn State University Research Highlights: Dr. Teel directs the Concussion Neurophysiology and Rehabilitation Research Lab (CeRebRaL Lab), aiming to reduce repeat injury risk and enhance return-to-activity protocols. Her work spans concussion recovery, neuroimaging, and clinical assessment technologies. Teaching: EXCI 310 Research Methods EXCI 421 Honors Seminar: Current Topics in Health and Exercise Science EXCI612/HEXS 810 Laboratory Techniques EXCI 624/HEXS801 Special Topics Seminar Labs & Teams: Director of the CeRebRaL Lab Collaboration with CARE Consortium Investigators Research partnerships with McGill University and NCAA-DoD institutions

Mascha Kurpicz-Brikiمشاهده پروفایل

استاد

• Applied Natural Language Processing
• Fairness and Diversity in AI
• Augmented Intelligence for Mental Health
• +۲ مورد دیگر

Prof. Dr. Mascha Kurpicz-Briki is a computer science professor at the Bern University of Applied Sciences, leading the Applied Machine Intelligence research group within the Institute for Data Applications and Security (IDAS). Her work focuses on human-centered applications of natural language processing in mental health and societal challenges, particularly addressing bias mitigation in AI systems. Education: PhD in energy-efficient cloud computing from University of Neuchâtel Expertise: Applied NLP, fairness in AI, augmented intelligence for health Leadership: Deputy lead of Applied Machine Intelligence Research Group Her research emphasizes augmented intelligence - creating AI systems that support rather than replace humans. Current projects investigate NLP applications for: Burnout and depression detection in clinical psychology Fairness measurement in word embeddings and language models Human augmentation through AI in industrial and healthcare settings Recent publications highlight her contributions to: Bias detection frameworks for European languages Machine learning in eating disorder diagnostics Generative AI integration in art therapy She maintains active memberships in IEEE, ACM, ACL, and the Swiss Center for Augmented Intelligence, with expertise in German, English, and French language technologies.