جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Accessibility
• AI and Machine Learning
• +۳ مورد دیگر

Leah Findlater is a Professor at the University of Washington , Seattle, WA, USA. Her research focuses on Human-Computer Interaction (HCI) and Accessibility , particularly in developing AI and Machine Learning systems for users with disabilities. Key areas: Assistive Technologies , Speech Recognition , Visual Privacy Collaborators: Jon E. Froehlich, Dhruv Jain, Emma J. McDonnell, Abigale Stangl Her recent work includes sound personalization for Deaf users , AI-driven sign language generation , and privacy tools for blind individuals . She explores interactive machine learning and user-centered design to improve accessibility in smartwatches , AR , and generative AI . Articles highlight cross-disciplinary collaborations with disability communities , focusing on inclusive AI , sensory augmentation , and ethical technology design . She advocates for user-driven accessibility solutions in social media and urban environments .

Ezgi Akarمشاهده پروفایل

استادیار

• Social networks
• Online communities
• Social media analytics
• +۴ مورد دیگر

Dr. Ezgi Akar is an Assistant Professor in the Department of Business Communication and Information Systems at the University of Wisconsin-Eau Claire's College of Business. She holds a Ph.D. in Management Information Systems from Bogazici University, complemented by graduate certificates in data analytics from institutions including MIT xPRO and Google. Her research focuses on social networks, online communities, data analytics, and consumer behavior in digital environments. Her scholarly contributions examine online community dynamics, misinformation propagation, and digital consumerism during crises. Recent work analyzes mental health communities on Reddit, exploring how network structures influence toxicity and support efficacy. Additional research investigates pandemic-driven shifts in e-commerce behavior using behavioral theory frameworks. Dr. Akar has received multiple academic honors including the International Doctoral Research Fellowship from TÜBİTAK and Bogazici University's Tolga Ulus Special Award for academic excellence. She teaches courses in database management systems, business analytics, and programming languages.

• Social Work
• Political Conflict
• Mental Health Reform
• +۳ مورد دیگر

Dr. Reima Ana Maglajlic is an Associate Professor in Social Work at the University of Sussex's School of Education and Social Work. Her work focuses on social work's role in political conflict, mental health reform, and disability rights. She holds dual roles as Co-Editor of the British Journal of Social Work (2020-2024) and has extensive experience in post-conflict social welfare reform across South-East Europe. Education: Studied social work in Croatia, earned PhD from Swansea University. Professional milestones include: 1994-1997: Social work practice and research at Anglia Ruskin University 1999-2011: Consultancy work on social welfare reforms in Bosnia and Herzegovina 2011-2013: Research Director at Mental Disability Advocacy Center 2013-present: Academic roles at Sussex University Research emphasizes: Social work's response to armed conflict Community mental health system reform UNCRPD implementation for persons with disabilities Co-production with service users Current projects include studying humanitarian shelter impacts in Ukraine (Medair, 2024-2025) and post-war mental health alternatives in Bosnia (British Academy, 2021-2023). Her publications critically engage with social work's role in crises, technology ethics, and global inequalities. Grant leadership includes 6 funded projects on topics like: Social care innovations for safeguarding youth Self-neglect inter-agency collaboration Mental health co-production methodologies Advocacy work includes steering committees for citizenship rehabilitation services and international social work networks like SWAN (2010-2017). She continues frontline practice support for refugee organizations.

Pamela Souzaمشاهده پروفایل

استاد

• Auditory Processing
• Hearing Aids
• Speech Recognition
• +۴ مورد دیگر

Pamela Souza is a Professor in the Department of Communication Sciences & Disorders at Northwestern University's School of Communication. She holds secondary appointments in Linguistics and Otolaryngology-Head and Neck Surgery. Her research focuses on auditory and cognitive factors influencing hearing aid outcomes, particularly in aging populations. She is affiliated with the Hearing Aid Laboratory and is a Fellow of prominent organizations like the Acoustical Society of America and the American Speech-Language-Hearing Association. Dr. Souza earned her PhD in Audiology from Syracuse University. Her clinical interests include severe hearing loss management, tinnitus, and hearing assistive technologies. She has led NIH-funded projects investigating hearing aid signal processing and cognitive-auditory interactions. Notable contributions include developing the Spectral Correlation Index and advancing remote hearing aid assessment methods. Her research spans 30+ years, with over 100 peer-reviewed articles. Key themes include speech recognition in complex environments, working memory effects on hearing aid performance, and individualized treatment approaches. She has pioneered studies on reverberation and noise reduction technologies, emphasizing real-world acoustic challenges. Dr. Souza's grants include NIH R01 awards for studying hearing aid outcomes and compression dynamics. She has advised multiple trainees and collaborates internationally on projects like the E-LOSPHERES initiative. Her lab develops tools like the Portable Automated Rapid Testing (PART) system for auditory research.

• Cognitive Neuroscience
• Neuroimaging
• Attentional Control
• +۴ مورد دیگر

Christopher L. Asplund is an Associate Professor at the National University of Singapore (NUS), affiliated with the Department of Biomedical Engineering and Yale-NUS College. He serves as Head of Studies for Psychology at Yale-NUS and holds courtesy appointments in NUS Psychology, Institute for Digital Medicine (WiSDM), Centre for Sleep and Cognition, and Duke-NUS Neuroscience & Behavioural Disorders program. His research explores attentional control, consciousness, and the neural basis of cognition through behavioral experiments, fMRI, and EEG. Research Focus: Understanding attentional states and their modulation by surprise Investigating individual differences in attention, including ASD/ADHD Exploring surprise's role in learning and pain perception Developing digital therapeutics for cognitive training Examining how consciousness and intelligence emerge from neural networks Methodological Expertise: Behavioral experimentation, functional neuroimaging (fMRI, EEG), eye-tracking, and physiological measures.

• Biomedical Engineering
• 3D Printing in Healthcare
• Pediatric Medical Devices
• +۳ مورد دیگر

Dr. Tegan Cheng is an NHMRC Emerging Leadership Fellow and Adjunct Lecturer in the School of Biomedical Engineering at the University of Sydney. She leads the EPIC Lab at Kids Research, Children's Hospital at Westmead, focusing on pediatric medical devices and 3D printing applications. Her work bridges engineering and clinical needs to address musculoskeletal challenges in children. She holds a BE(Mechanical/Biomedical) and BMedSc from the University of Sydney (2011) and a PhD (2016). Research Interests: Developing implantable/wearable medical devices for children, 3D printing in healthcare, pediatric orthotic design, and commercialization pathways. Her Printhotics initiative aims to create equitable access to personalized ankle-foot orthoses (AFOs) using 3D scanning and AI. Key collaborations include clinicians, engineers, and designers to advance pediatric device solutions. Grants and Awards: 2021 Young Tall Poppy Science Award, NHMRC Investigator Grant for Printhotics (2020), and grants from the American Orthotic & Prosthetic Association and University of Sydney's Educational Innovation Fund. Active projects include smart orthotics with embedded sensors and biodegradable bone implants. Labs/Teams: Group Leader of the EPIC Lab, collaborating with Kids Research, University of Sydney, and industry partners. Focus areas include translational research, medical device innovation, and interdisciplinary education using 3D-printed anatomical models.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Ioannis Maniadis Metaxas is a lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. He teaches undergraduate and postgraduate courses including Artificial Intelligence, Machine Learning, and Machine Learning for Visual Data Analysis. His research focuses on: Unsupervised representation learning Computer vision systems Large vision-language models Deep clustering techniques Generative models for data augmentation E-commerce personalization systems Recent publications demonstrate consistent focus on efficient learning methods for visual data, particularly investigating unsupervised pretraining, cluster optimization, and model fine-tuning approaches. His work shows progression from foundational 3D data augmentation to cutting-edge vision-language model optimization.

Raoul C.Y. Nuijtenمشاهده پروفایل

مدرس

• Behavior Change
• Health Promotion
• Gamification
• +۴ مورد دیگر

Raoul C.Y. Nuijten is a University Lecturer at the Eindhoven University of Technology, affiliated with the Department of Information Systems IE&IS within the School of Industrial Engineering and Innovation Sciences. His email is r.c.y.nuijten@tue.nl , and he holds an ORCID identifier: 0000-0003-0125-7708 . Education: Master's thesis: "Our Quality of Life, Our Responsibility: Exploration of the effectiveness of a game that empowers end users to improve their quality of life" (Eindhoven University of Technology, 2017) PhD thesis: "Energize: Exploring the impact of gamification strategies on engagement with mobile health apps" (Eindhoven University of Technology, 2022) Research Interests: Nuijten specializes in leveraging apps to drive behavior change for health and work performance. He employs data science techniques to create personalized strategies and tests their efficacy through empirical experiments. His work emphasizes gamification in digital health tools, personalization approaches for mHealth, and the integration of scientific knowledge to inform health behavior models. He also explores how neighborhood environments and digital interventions can enhance physical activity and well-being. Key Projects: He contributed to the GOAL: Gamification for Overweight prevention and Active Lifestyle project (2018–2021), focusing on gamification and AI-driven health strategies. This project aimed to establish evidence-based frameworks for promoting active lifestyles. Awards: In 2018, he received the Best Poster Presentation Certificate (Health track) at ICT.OPEN, recognizing his early contributions to health-focused research. Advising & Grants: Nuijten supervised 4 works (not listed by name) and has presented at conferences, such as a contributed talk in 2020 on mHealth tools. His research has garnered 110 Scopus citations and involved collaborations across disciplines and institutions. Labs/Teams: While specific lab affiliations are not mentioned, his work aligns with TU/e’s focus on digital health and innovation, including the development of platforms like GameBus and SciModeler.

Damian Trillingمشاهده پروفایل

استاد

• Computational Social Science
• Political Communication
• Digital Journalism
• +۸ مورد دیگر

Prof. Damian Trilling is a Full Professor at the Vrije Universiteit Amsterdam's Faculty of Social Sciences and Humanities in the Department of Communication, and concurrently holds the same rank at the Network Institute. He also serves as a Medewerker (employee) at the Universiteit van Amsterdam and Universitetet i Bergen since February 2024, reflecting his active interdisciplinary and international collaborations. His research focuses on computational methods applied to communication science, particularly exploring how algorithms and digital platforms shape media exposure, political behavior, and information dissemination. Key areas include analyzing selective exposure in recommender systems, measuring ethnic biases in news content, and studying the agenda-setting role of dark platforms. He emphasizes transparency in news algorithms and the ethical implications of data donation frameworks, often employing machine learning techniques like word embeddings and agent-based modeling to address these topics. Trilling's recent articles (2024-2025) reveal a strong focus on understanding algorithmic impacts across media ecosystems. They highlight concerns about filter bubbles, dark platform dynamics, and the interplay between user behavior and platform design. His work bridges communication theory with computer science, offering practical tools such as the INCA infrastructure for automated content analysis and the 3bij3 framework to study recommender systems' effects on news diversity. He teaches courses like Impact van journalistieke producten , Inleiding Media en Journalistiek , and collaborates internationally, as seen in the Introduction to Machine Learning for Text Analysis with Python at GESIS (Mannheim, Germany). His pedagogical contributions complement his research agenda, aiming to equip students with computational skills for modern communication analysis.

Cunjian Chenمشاهده پروفایل

عضو هیئت علمی

• Computer Vision
• Deep Learning
• Medical Imaging
• +۴ مورد دیگر

Cunjian Chen is an Adjunct Lecturer at the Department of Data Science & AI, Monash University, and a Research Fellow at Monash University Suzhou. He holds a PhD in Computer Science from West Virginia University and serves as an Associate Editor for journals like Neural Processing Letters and IET Image Processing. His research focuses on computer vision, deep learning, adversarial machine learning, and cross-spectral biometric systems. Notable contributions include advancements in thermal-to-visible face recognition, medical image segmentation, and robust adversarial defense mechanisms. Dr. Chen has received the Outstanding Area Chairs award at ICME 2021. He actively contributes to academic governance roles, including Tutorial Chair for IJCB and Area Chair for ICME, ICIP, ICASSP, IJCNN, and FG. He is currently accepting PhD and research assistant students in computer vision and deep learning, emphasizing innovative applications in security and healthcare. His research collaborations span global institutions, with recent work addressing challenges in cross-spectral imaging, medical AI, and adversarial robustness. Professional activities include patent engagements with the Monash Suzhou Research Institute. For further details, visit his personal website or Google Scholar profile .

Courtney Chrimesمشاهده پروفایل

مدرس

• Digital Fashion Marketing
• Metaverse Retail
• Customer Experience Analysis
• +۵ مورد دیگر

Courtney Chrimes is a Lecturer in Digital Fashion Marketing at The University of Manchester, Department of Fashion Business Technology. She holds an External Examiner role for the BA (Hons) Fashion Promotion and Communication Programme at Buckinghamshire New University (2021-2026). Her academic background includes a Bachelor of Science in Fashion Buying and Merchandising from The University of Manchester (2017) and a PhD focused on product page design impacts on clothing fit appraisal (2021). Her research interests span digital fashion marketing innovations, metaverse retail experiences, sustainable supply chain practices, and consumer behavior analysis. Notable areas include blockchain applications in circular economies, body shape impacts on garment fit satisfaction, and AI-driven marketing strategies. She actively contributes to the UN Sustainable Development Goals related to responsible consumption and production. Dr. Chrimes has published 12 peer-reviewed articles and chapters, with recent focus on metaverse retailing (2025), AI-generated advertising (2024), and blockchain transparency (2023). She received four awards, including the 2024 Teaching Excellence Award for inclusive pedagogy and 2019 recognition for research excellence. Her advisory work includes supervising PhD research on digital fashion marketing and collaborating with industry partners on omnichannel strategies. Current projects explore immersive technologies in fashion retail and digital tools for sustainable product development.

Nicole Salomonsمشاهده پروفایل

مدرس

• Artificial Intelligence
• Robotics
• Human-Robot Interaction
• +۳ مورد دیگر

Dr. Nicole Salomons is a Lecturer in the Department of Computing and I-X at Imperial College London. Her research focuses on human-robot interaction, developing AI and robotic systems for personalized learning, therapy, and societal benefit. She emphasizes ethical considerations like privacy in domestic robotics deployments. Education: BSc in Computer Science from Universidade Federal do Paraná (Brazil), with early robotics involvement through university clubs and research. Research Interests: Designing robots that understand human needs, particularly for vulnerable populations such as children with ASD and elderly individuals. Key areas include adaptive tutoring systems, long-term human-robot interaction, and ethical AI deployment. Recent work explores speech recognition for dementia care and social robots' impact in educational settings. Lab Affiliation: Personal, Assistive, and Intelligent Robotics (PAIR Lab), focused on robots enhancing daily interactions. Her team collaborates closely with healthcare professionals and users to co-design effective solutions.

Bernd Schmittمشاهده پروفایل

استاد

• Brand Management
• Consumer Behavior
• Experiential Marketing
• +۳ مورد دیگر

Bernd Schmitt is the Robert D. Calkins Professor of International Business at Columbia Business School , where he has been affiliated since 1988. He specializes in branding, innovation, creative strategy, and customer experience, serving as Editor-in-Chief of the Journal of Consumer Research and co-founder of TPM (Theory and Practice in Marketing) . Schmitt's work bridges academic rigor with practical applications, influencing global marketing practices through his publications and consulting. Education: Diplom, University of Heidelberg (1984) PhD, Cornell University (1988) Research interests focus on consumer behavior, experiential marketing, brand management, and the intersection of AI with marketing. His recent work explores generative AI, robot adoption, and cross-cultural consumer psychology, particularly in Asian markets. Schmitt has also contributed to understanding digital transformation and phygital customer experiences. Scientific awards include recognition for innovation in the classroom for his course Corporate Creativity. His publications, courses, and leadership roles reflect his commitment to advancing marketing theory and practice globally.

Santosh Kumarمشاهده پروفایل

استاد

• Mobile Health (mHealth)
• Artificial Intelligence for Wearables
• Wireless Sensor Networks
• +۴ مورد دیگر

Dr. Santosh Kumar is a Professor and Lillian & Morrie Moss Chair of Excellence in Computer Science at the University of Memphis. He leads the NIH mDOT Center and MD2K Center of Excellence, focusing on mobile health (mHealth) and wearable AI. His research develops computational models to infer health behaviors from sensor data, with applications in stress, smoking cessation, oral hygiene, and cocaine use detection. Education: PhD in Computer Science from The Ohio State University (2006). Notable awards include Popular Science's 'Brilliant Ten' (2010), Early Career Research Award (2008), and Tennessee’s first state-endowed Chair of Excellence (2015). Research spans sensor-based biomarkers, privacy risks in mHealth, and interventions. He oversees $18M in NIH/NSF grants, involving 20+ institutions. Key projects include AutoSense and mCerebrum sensor platforms, and the mDOT Center for temporally-precise interventions. Collaborates with experts in computing, medicine, and behavioral science. Advises over 20 students, many now in tech leadership roles at Amazon, Apple, and Samsung. Labs: mHealth Systems Lab, NIH mDOT Center. Leadership roles include Director of MD2K and advisor to NSF Engineering Research Centers.

Wei-Yin Lohمشاهده پروفایل

استاد

• Machine Learning
• Classification and Regression Trees
• Data Analysis
• +۴ مورد دیگر

Wei-Yin Loh is a Professor in the Department of Statistics at the University of Wisconsin–Madison, affiliated with the School of Computer, Data & Information Sciences. His primary research focuses on classification and regression trees, with applications in machine learning, healthcare, and engineering. He has contributed extensively to the development of algorithms and methodologies in tree-based modeling, including the GUIDE software package. Dr. Loh's work spans theoretical advancements and practical implementations, addressing challenges such as missing data imputation, subgroup identification in precision medicine, and variable importance assessment. His research integrates statistical rigor with real-world problems in public health, federal agency performance analysis, and environmental modeling. Key contributions include studies on tobacco use prediction, cardiovascular health modeling, and pandemic-related mortality analysis. He has also explored applications in engineering, such as pavement thickness analysis and project delivery system evaluation. His publications emphasize interpretable models with strong predictive power, balancing complexity and practical utility. Awards and grants are not explicitly listed in the provided text, though his prolific publication record underscores his academic impact. Advising activities and student mentorship are not detailed here, but his research collaborations likely involve training the next generation of statisticians and data scientists.