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Leonidas GuibasView profile

Professor

• Computer Vision
• Computer Graphics
• Machine Learning
• +5 more

Leonidas Guibas is the Paul Pigott Professor of Computer Science at Stanford University, leading the Geometric Computation group. He is a Hans Fischer Senior Fellow at the Technical University of Munich (TUM), associated with the Visual Computing Focus Group under Prof. Matthias Nießner. His research bridges computer vision, graphics, and machine learning, focusing on 3D data processing, geometric modeling, and sensor networks. Guibas holds prestigious awards including the Vannevar Bush Fellowship and ACM Allen Newell Award, and is a member of the US National Academy of Engineering and American Academy of Arts and Sciences. Education: Ph.D. from Stanford University under Donald Knuth, with prior appointments at Xerox PARC, MIT, and international institutions. His work emphasizes algorithms for sensing, reasoning, and acting in physical environments, with contributions to robotics, computational geometry, and discrete algorithms. Research interests span 3D vision (e.g., generative models for shape synthesis), deep learning architectures for spatiotemporal data, and multimodal sensor integration. Recent projects include object pose estimation, functional relationship learning in scenes, and deformation-aware 3D model retrieval. Publications highlight advancements in 3D reconstruction, point cloud analysis, and geometric deep learning. His TUM fellowship supported work on digital twins and visual computing, emphasizing high-fidelity environmental modeling. Awards also include IEEE and ACM Fellowships, underscoring his impact on theoretical and applied computer science.

Christos SakaridisView profile

Lecturer

• Computer Vision
• Autonomous Vehicles
• Semantic Segmentation
• +1 more

Christos Sakaridis is a Lecturer at ETH Zurich's Department of Information Technology and Electrical Engineering, based in ETF C 112. His primary research focuses on computer vision systems for autonomous vehicles, particularly addressing perception under challenging environmental conditions. Research emphasizes: Robust semantic segmentation for driving scenes Depth estimation in adverse conditions Multi-sensor fusion approaches

• Computer Vision
• Machine Learning
• Document Analysis
• +5 more

Ujjwal Bhattacharya is affiliated with the Indian Statistical Institute, India. His primary research focuses on computer vision, machine learning, and document analysis with a strong emphasis on multimodal perception systems and deep learning applications. He has published extensively in top-tier venues like ICPR, ICDAR, CVPR, and BMVC, contributing to advancements in autonomous driving, image processing, and privacy-aware machine learning. His work spans from developing robust pedestrian detection systems using multimodal sensors to enhancing degraded document image processing through domain adaptation and advanced neural architectures. Recent contributions include semi-supervised 3D object detection frameworks and privacy-preserving clustering techniques. Key research areas include: Multimodal sensor fusion for autonomous systems Deep learning for document analysis and OCR Privacy-aware metric learning Efficient neural network compression techniques Image enhancement and restoration His publication trends reflect a focus on solving real-world challenges in autonomous driving, degraded document processing, and privacy-sensitive machine learning applications.

Krishan RanaView profile

Research Fellow

• Robotics
• Artificial Intelligence
• Reinforcement Learning
• +3 more

Dr. Krishan Rana is a Research Fellow at the QUT Centre for Robotics, specializing in robot learning at the intersection of AI and robotics. His work focuses on enabling robots to intelligently plan and interact with the world, particularly through projects like From Chat to Chores: The Future of LLM-Powered Service Robots and Robot Learning for Everyday Tasks with Large Language Models . He explores reinforcement learning, visuomotor control, and sim-to-real policy deployment. His research interests include robot navigation, policy learning, and embodied AI, with applications in service robotics and medical imaging. He leads projects involving semantic maps, affordance-centric task frames, and multi-modal perception. His work bridges theoretical advancements with practical deployments in dynamic environments. Recent contributions include developing datasets like LHManip for cluttered manipulation tasks and Robohop for visual navigation. He collaborates on open-source robotics tools through initiatives like Open X-Embodiment. His research emphasizes scalability, sample efficiency, and integration of large language models into robotic systems.

• Neuroscience
• Brain Pathophysiology
• Speech and Language Disorders
• +4 more

Nabin Koirala is an Associate Research Scientist at Yale University's Child Study Center, where he conducts interdisciplinary research at the intersection of neuroscience, engineering, and clinical applications. His work focuses on understanding brain pathophysiology in neurological and neuropsychological disorders and developing disease-specific brain biomarkers. Dr. Koirala's educational background reflects a strong interdisciplinary foundation: PhD in Neuroscience from Johannes Gutenberg University (2019) MSc in Engineering & Neuroscience from Christian Albrechts University (2014) BE in Engineering from Tribhuvan University (2010) Postdoctoral Researcher at Haskins Laboratories (2022) His research program investigates the neural correlates of speech, hearing, and language-related disorders using multi-modal brain imaging and electrophysiological data. He applies state-of-the-art frameworks of complex network algorithms and machine learning approaches to analyze brain connectivity and function. Dr. Koirala's work spans several key areas including cochlear implant research, brain network analysis in neurological conditions, machine learning applications in neuroscience, deep brain stimulation mechanisms, and speech and language processing in the brain. His publication record demonstrates significant contributions to understanding how socioeconomic status influences brain circuitry for literacy, neural characteristics affecting literacy outcomes in children with cochlear implants, and the application of artificial intelligence in epilepsy care, particularly in resource-limited settings. His research often employs advanced neuroimaging techniques including EEG and functional near-infrared spectroscopy to examine cross-modal plasticity and sensory integration. Dr. Koirala collaborates extensively with researchers across disciplines, with frequent co-authorship with Vincent Gracco and Nicole Landi. His work bridges basic neuroscience with clinical applications, particularly in pediatric populations and neurological conditions including Parkinson's disease, multiple sclerosis, and stroke.

• Virtual Reality
• Augmented Reality
• Educational Technology
• +7 more

Roghayeh Barmaki is a researcher with extensive publications in virtual reality, augmented reality, and educational technology. Her work spans rehabilitation systems, autism therapy, and neuroimaging analysis using fNIRS. She collaborates with institutions including Georgia Institute of Technology and University of Florida. Key Collaborators : Anjana Bhat, Jicheng Li, Shayla Sharmin, Vuthea Chheang Research Themes : Wearable sensors, LSL framework, movement synchrony, multimodal learning analytics Research Interests She focuses on immersive technologies for education and therapy, with expertise in: Functional Near-Infrared Spectroscopy (fNIRS) for cognitive engagement Wearable sensor integration in rehabilitation Gender perspectives in AR/VR education Multimodal affect analysis for autism Privacy-preserving behavioral analytics 3D visualization for anatomy training Publication Trends Recent work emphasizes fNIRS applications in gaming environments and hybrid deep learning models for cognitive analysis. Earlier studies focused on gesture recognition, movement synchrony estimation, and autism intervention datasets. Impactful Projects She developed the MMASD dataset for autism research and contributed to VR therapy systems. Her collaborations include: Georgia Tech's Autism Technology Research University of Florida's TeachLivE virtual classroom Germany's AIxVR conference contributions International collaborations on sensor systems

Elisabeth AndréView profile

Professor

• Tangible user interfaces
• Perceptive user interfaces
• Interactive multimodal user interfaces
• +10 more

Elisabeth André is a Full Professor of Computer Science and Chair of Multimedia Concepts and Applications at University of Augsburg, where she has been faculty since 2001. She previously served as Managing Director of the Institute for Computer Science at Augsburg University from 2004 to 2006. Professor André has received multiple prestigious professorship offers, including W3-Professorships in Human-Computer Interaction and Cognitive Systems from University of Stuttgart and Human-Machine Interaction from Otto-Friedrich-Universität Bamberg in 2009. Her academic journey began with a Diploma in Computer Science (1988) and Dr. rer. Nat. (1995) from Saarland University. Before joining Augsburg, she spent over a decade as a Scientific Researcher at DFKI GmbH (German Research Center for Artificial Intelligence), where she rose to Principal Researcher and was appointed a DFKI Research Fellow. Professor André's research focuses on designing and evaluating interactive multimodal user interfaces, experimental learning environments with animated characters, and affective computing. She is internationally recognized as a pioneer in embodied conversational agents, having organized one of the first international workshops on the topic in 1997. Her work stands out for its empirical foundation, including extensive corpus studies of human behaviors to inform virtual agent behavior modeling. Notably, she has conducted significant cross-cultural research with Japanese partners to develop culture-specific behaviors in virtual agents. Her publication record shows a consistent trajectory of innovation in human-computer interaction, with particular emphasis on multimodal analysis, gaze behavior simulation, and emotion recognition systems. The research trends in her recent work demonstrate increasing sophistication in input recognition methods and the development of practical toolboxes (AuBT, EmoVoice, SSI) that have been adopted by research institutions worldwide. 2007 Alcatel-Lucent Fellowship at Universität Stuttgart Best Paper Finalist at International Conference on Intelligent Virtual Agents (2007-2009) 2005 Convivio Best Demo Award 2000 Best Paper Award at International Conference on Intelligent User Interfaces 1998 RoboCup Scientific Award Multiple student projects winning international awards including GALA Awards and TEI conference awards Professor André has supervised 2 completed dissertations and is currently guiding 11 PhD students and 1 Habilitation candidate. Her leadership extends to major research projects including EU-funded initiatives (METABO, E-Circus, IRIS, DynaLearn, CALLAS) and DFG projects (CUBE-G, OC-Trust). She serves on numerous editorial boards and has held significant organizational roles in major conferences including IUI, IVA, and CASA. Her laboratory has developed multiple software toolkits that are used internationally in large-scale research projects, demonstrating the practical impact of her work. Current research directions include advanced emotion recognition systems, culture-adaptive virtual agents, and applications of her technology to educational and healthcare domains.

Makeba Parramore WilbournView profile

Associate Professor

• Developmental Psychology
• Language Acquisition
• Cognitive Development
• +4 more

Makeba Parramore Wilbourn is an Associate Professor of the Practice in Psychology and Neuroscience at Duke University, affiliated with Trinity College of Arts & Sciences. She holds additional affiliations with the Center for Biobehavioral Health Disparities Research and the Sanford School of Public Policy's Center for Child and Family Policy. Education: Ph.D., Cornell University, 2008 M.A., California State University, Fullerton, 2001 B.A., California State University, Fullerton, 1997 Research Interests: Her work explores how cognition and language interact across development, focusing on the role of gestures, bilingualism, and socio-cultural factors. Key themes include emotion perception in infants, racial biases in emotion reasoning, and the impact of socio-economic status on language development. Grants & Service: Principal Investigator on grants from NSF, RIKEN Brain Science Institute, and others. Service roles include IRB membership, grant review panels, and advocacy for minority faculty. Awards: Notable honors include the Presidential Early Career Award for Scientists and Engineers (PECASE) and NSF CAREER Award. Teaching: Courses span developmental psychology, research methods, and the role of race in development. Wilbourn Infant Lab (WILD): Studies how infants learn language through gestures and cultural contexts, emphasizing equity in early education.

Patrizia Di Campli San VitoView profile

Researcher

• Human-Computer Interaction (HCI)
• Assistive Technology
• Human-AI Interaction
• +3 more

Patrizia Di Campli San Vito is a Researcher in the School of Computing Science at the University of Glasgow, focusing on Human-AI Interaction and Assistive Technologies. She holds a PhD from the University of Glasgow and prior degrees from the University of Ulm, Germany. Her current work involves participatory harm auditing of AI systems through the PHAWM project and developing adaptive radio systems (RadioMe) for dementia care. Previously, she contributed to ENTER and RadioMe projects addressing aging populations' needs through multimodal interfaces. Education: PhD: University of Glasgow Master's & Bachelor's: Media Informatics, University of Ulm Research Interests: Human-Computer Interaction (HCI), Assistive Technology for Aging Populations, Thermal/Haptic Feedback Systems, Automotive UIs, and Ethical AI Evaluation. She explores how multimodal interactions (e.g., thermal, haptic, audio) can improve accessibility and safety in healthcare and automotive domains. Key Projects: RADIO-ME: Adaptive radio system with agitation detection and music intervention for dementia patients PHAWM: Tools for non-experts to evaluate AI systems' societal impacts ENTER: Multimodal interaction for older adults Recent Work: Her publications focus on stress detection systems, in-car thermal feedback for navigation, and dementia-friendly calendar interfaces. She collaborates with Prof. Simone Stumpf (GIST Lab) and Prof. Stephen Brewster (Multimodal Interaction Group). Labs/Teams: Active in the Glasgow Interaction Systems Team (GIST) and previously contributed to the Multimodal Interaction Group.

Thomas FerrisView profile

Associate Professor

• Human Factors Engineering
• Cognitive Ergonomics
• Human-automation Interaction
• +5 more

Dr. Thomas Ferris is an Associate Professor in Industrial & Systems Engineering at Texas A&M University, with an affiliation in Environmental & Occupational Health. He holds a Ph.D. in Industrial & Operations Engineering (Cognitive Ergonomics) from the University of Michigan (2010). His research focuses on human factors in complex systems, emphasizing tactile display design, cognitive workload management, and human-automation interaction. Key areas include driver distraction mitigation, medical anesthesiology support systems, and aviation weather alerting technologies. Education: Ph.D., Industrial & Operations Engineering (Cognitive Ergonomics), University of Michigan, 2010 Bachelor's Degree (Engineering Valedictorian), University of Iowa, 2003 Research Interests: Human factors in aviation and automotive systems Design of tactile and multimodal interfaces Cognitive efficiency in multitasking environments Psychophysiological workload assessment Emergency response system human factors Recent work emphasizes developing vibrotactile warning systems for construction operators, fatigue detection in aviation, and collaborative robot productivity analysis. His lab (Human Factors & Cognitive Systems) explores VR applications in remote physical examination and cybersickness mitigation strategies. Awards include the NSF Graduate Research Fellowship (2005-2008) and World Haptics Best Paper (2009). He has advised over 30 graduate students and published widely in Human Factors, IEEE Transactions, and Aviation safety journals.

Nicole LandiView profile

Professor

• Reading Development
• Language Development
• Developmental Cognitive Neuroscience
• +4 more

Nicole Landi is a Professor and Director of Developmental Psychology in the Department of Psychological Sciences at the University of Connecticut. She holds a Ph.D. in Cognitive Psychology from the University of Pittsburgh (2005). Her research utilizes cognitive neuroscience approaches (ERP, MRI, neuroimaging genetics) to study reading and language development, focusing on disorders like dyslexia and specific reading comprehension disability. Education: Ph.D., Cognitive Psychology, University of Pittsburgh, 2005 Dr. Landi's research investigates neural mechanisms underlying reading disorders through collaborations with schools like AIM Academy and The Windward School. Her work examines predictors of intervention response and includes projects on neurochemistry, genetics, and technology-based interventions such as the HBN-EDUCATE program with the Child Mind Institute. Analysis of her recent publications (2022-2025) reveals consistent themes: neural correlates of reading ability, socioeconomic impacts on literacy, intervention effectiveness during COVID-19, and specialized populations (autism, cochlear implant users). Methodologies predominantly feature fMRI, ERP, and DTI to explore brain-behavior relationships across development. Scientific Awards: James McKeen Cattell Sabbatical Fellowship (2020-2021) Dr. Landi advises multiple graduate and undergraduate students, including recipients of the Isabelle Y. Liberman Award (Meaghan Perdue), Goldwater Scholarship (Katie Mahaffy), and Holster Scholar (Katie Hooker). Her lab secures funding for research projects through partnerships and fellowships, including international collaborations on imaging genetics. The LandiLab operates within the Bousfield Psychology Building, collaborating with the Yale Child Study Center, Language Sciences Consortium, and community schools. These partnerships enable translational research through in-school laboratories and longitudinal studies of reading intervention outcomes.

Rikke GadeView profile

Associate Professor

• Computer Vision
• Image Processing
• Robot Vision
• +5 more

Rikke Gade is an Associate Professor at the Department of Architecture, Design and Media Technology within The Technical Faculty of IT and Design at Aalborg University. Her research focuses on Visual Analysis and Perception, AI for the People, and Mobility and Tracking Technologies. She has established herself as a leading researcher in computer vision applications across multiple domains including sports analytics, animal welfare, and human-computer interaction. Dr. Gade earned her PhD in Computer Vision from Aalborg University in 2015 with her dissertation "Taking the Temperature of Sports Arenas - Automatic Analysis of People." Prior to this, she completed her M.Sc. in Informatics with specialization in Vision, Graphics and Interactive Systems in 2011, and her B.Sc. in Electronic and Electrical Engineering in 2009. Her research interests span Computer Vision, Image Processing, Robot Vision, and Thermal Imaging with applications in diverse fields. She has pioneered work in using thermal imaging for sports analytics, developing systems for tracking athletes and analyzing movement patterns in sports arenas. More recently, her research has expanded into AI applications for animal welfare, particularly developing computer vision systems for detecting pain and stress in horses through facial expression analysis. Dr. Gade's publications reveal a clear progression from foundational work in thermal imaging and sports analytics toward more complex applications in healthcare, animal welfare, and smart building systems. Her most recent work shows increasing focus on ethical AI applications that serve societal needs, as evidenced by projects like "AI for the People" and research on equine pain detection. Best Paper Award at Conference CISBAT 2021 (Lausanne, Switzerland) Dr. Gade actively supervises PhD students, including Alves, J.M. on equine affective state assessment. She has secured significant research funding, including a major grant from the Independent Research Fund Denmark for developing AI systems to detect pain in horses. Her collaborative approach is evident in her involvement in multiple interdisciplinary projects spanning computer science, veterinary medicine, and building science. She leads the Visual Analysis and Perception research group at Aalborg University, focusing on practical applications of computer vision technologies. Her team works closely with industry partners on real-world implementations, particularly in sports analytics and animal welfare applications. Current projects include developing AI systems for road damage detection in collaboration with Faxe Kommune and creating advanced tracking systems for sports performance analysis.

• Digital Marketing
• Consumer Behavior
• Influencer Marketing
• +5 more

Andreas Bayerl is an Assistant Professor of Marketing at the Erasmus School of Economics, Erasmus University Rotterdam. He holds a PhD in Quantitative Marketing from the University of Mannheim and conducts interdisciplinary research at the intersection of digital behavior, consumer psychology, and data science. His research focuses on how individuals generate, process, and are influenced by digital information, particularly in the context of online reviews and influencer marketing. Using a mixed-method approach—combining large-scale observational data, text and image analysis, and field and laboratory experiments—Andreas investigates behavioral patterns in digital ecosystems. His work has been published in leading journals including Journal of Marketing , Harvard Business Review , MIT Sloan Management Review , and Nature Human Behavior . The most recent publications reveal a consistent focus on digital influence, credibility, and consumer decision-making. Key themes include the effectiveness of micro-influencers, the psychological impact of fake reviews, multimodal analysis of visual and textual content, and experimental validations of marketing strategies across platforms. His methodological rigor and real-world relevance are evident across these works. Andreas has received significant recognition for his contributions, including: H. Paul Root Award for groundbreaking research in influencer marketing He actively teaches in the area of data science and marketing analytics, contributing to the next generation of analytically skilled marketers. While no formal advisees are listed, his role as an assistant professor suggests involvement in student supervision and academic mentorship. His research program appears to be supported by empirical rigor and industry relevance, though specific grants or lab affiliations are not mentioned in the provided text.

Catherine LaingView profile

Senior Lecturer

• Developmental Linguistics
• Infant Language Acquisition
• Phonetics
• +9 more

Catherine Laing is a Senior Lecturer in Developmental Linguistics at the Department of Language and Linguistic Science, University of York, where she has been a faculty member since 2021. She previously served as a Lecturer in Linguistics at Cardiff University (2017–2021) and as a Postdoctoral Research Associate at Duke University (2016–2017). She earned her PhD in Linguistics from the University of York in 2015. Her research focuses on infant language development, especially phonological and phonetic aspects of early word learning, babbling, and the role of iconicity (e.g., onomatopoeia and sound symbolism) in lexical acquisition. She uses acoustic, computational, observational, and experimental methods to explore how sensorimotor feedback and caregiver input shape early vocal development. She is the Principal Investigator of the ERC/UKRI-funded SENFM project, which uses lingual ultrasound to study infants aged 2–18 months. Her recent publications demonstrate a strong trend in analyzing phonological networks, caregiver speech patterns, and the influence of social and environmental factors (e.g., siblings, lockdown conditions) on early language. She frequently collaborates with leading researchers such as Elika Bergelson, Tamar Keren-Portnoy, and Ghada Khattab. General Editor, Language and Cognition PI, SENFM Project (senfm.york.ac.uk) Active contributor to open science via GitHub and OSF She is currently on a two-year research leave starting February 2024. Her work bridges developmental linguistics, cognitive science, and experimental psychology, contributing significantly to our understanding of the mechanisms underlying early language acquisition.

Ahmed YousefView profile

Research Fellow

• Voice Disorders
• Acoustic Voice Analysis
• Laryngeal Imaging
• +5 more

Ahmed Yousef is a Postdoctoral Research Scholar at the University of Iowa, affiliated with the Department of Communication Sciences and Disorders within the College of Liberal Arts and Sciences. His work bridges engineering and clinical speech science, focusing on improving voice disorder diagnosis through advanced technology. Research Interests: Dr. Yousef's research explores the biomechanics and acoustics of voice production, particularly in hyperfunctional voice disorders. He employs a multidisciplinary framework combining laryngeal imaging , acoustic analysis , and machine learning to develop objective, automated tools for clinical voice assessment. His work aims to enhance diagnostic accuracy and accessibility in speech-language pathology. His current projects, conducted under the mentorship of Dr. Eric Hunter, investigate the impact of clinic room acoustics on voice evaluation and pioneer machine learning models for real-time voice disorder detection. Future directions include integrating multimodal data—such as high-speed laryngeal videos and acoustic signals—for comprehensive voice health assessment. Scientific Recognition: Sataloff Award (2022) Advising and Grants: While no formal students are listed, Dr. Yousef collaborates closely with Dr. Eric Hunter on federally or institutionally funded research in voice science. His dual expertise in mechanical engineering and communication sciences positions him at the forefront of translational research in speech pathology. Labs and Teams: He is part of the voice research team at the University of Iowa’s Speech and Hearing Science program, contributing to cutting-edge studies in auditory perception, speech production, and clinical innovation.