Qingguo Li is a Professor and Associate Head at the Department of Mechanical and Materials Engineering , Queen's University , and a member of the Ingenuity Labs Research Institute . He specializes in biomechanical system design, energy harvesting, wearable sensors, gait analysis, and load carriage systems. His research integrates robotics, biomedical engineering, and sensor technology to develop human-centric devices and mobility aids. Current Roles : Professor, Associate Head, Queen's University Research Institute : Ingenuity Labs Research Institute Lab : Bio-Mechatronics and Robotics Laboratory His work focuses on biomechanical energy harvesting , IMU-based motion analysis , and assistive device development . Key applications include stroke rehabilitation, gait monitoring, and wearable power generation systems. Articles span cable-driven robots , smart walkers , and 3D printing mechanisms , emphasizing human-robot interaction and dynamic modeling . The lab explores sensor calibration , adaptive control algorithms , and human movement optimization . Areas of impact include rehabilitation engineering , load carriage stability , wearable sensor accuracy , and assistive robotics . His team develops solutions for gait asymmetry detection , post-stroke mobility , and low-cost energy systems , leveraging machine learning and kinetic modeling .
Shuangquan (Peter) Wang is an Assistant Professor of Computer Science at Salisbury University. He holds a PhD in Computer Science from the College of William & Mary (2020) and a PhD in Pattern Recognition and Intelligent Systems from Shanghai Jiao Tong University (2008), along with earlier degrees from Wuhan University of Technology and Wuhan Institute of Technology. His research focuses on mobile/wearable computing, activity recognition, smart health, and machine learning. He has over 10 years of experience in academia and industry, including roles at Philips Research East Asia and Nokia Research Center (Beijing). His work emphasizes wearable sensor-based health monitoring, such as fall detection, mastication analysis, and Parkinson’s disease monitoring. He leads the WISH Research Lab and serves as an Associate Editor for Elsevier's Smart Health Journal. Recent contributions include papers on salinity anomaly detection (2024), LLM-based user requirement analysis (2024), and socially acceptable food recognition (2022). His research trends emphasize interdisciplinary applications of machine learning in healthcare and sensor-driven human activity analysis. Professional service roles include coordinating Salisbury University’s Center for Applied Mathematics and Science (2021–2024) and chairing ACM/IEEE CHASE conferences. He has delivered invited talks on artificial intelligence and its societal impacts to diverse audiences, including the Institute of Retired Persons at Salisbury University. His lab, WISH Research Lab, explores innovative solutions in smart health and mobile computing, integrating wearable technologies with machine learning for real-world health applications.
Oscar Mendez Maldonado is a Lecturer in Robotics and Artificial Intelligence at the University of Surrey's School of Computer Science and Electronic Engineering, affiliated with the Robotics Department and CVSSP Centre. He holds a PhD (2018) and BEng (2013) from the University of Surrey. His research focuses on Machine Learning, Computer Vision, and Robotics, with emphasis on autonomous systems, localisation, and SLAM applications. Key projects include the Autonomous Valet Parking (AVP) system for indoor navigation and the SMILE project for sign language assessment using AI. He has supervised students like James Ross (Autonomous Vehicles), Xihan Bian (Reinforcement Learning), and Nimet Kaygusuz (Visual Odometry). Notable achievements include the Sullivan Thesis Prize (2018) and impactful publications in IEEE conferences (e.g., ICRA, CVPR, IROS). Research spans topics like 3D hand pose estimation via diffusion models, graph-based visual odometry fusion, and Raman spectroscopy for localisation. He contributes to open-source tools (e.g., RaSpectLoc GitHub) and collaborates with industry partners like Parkopedia. His work bridges theoretical advances with real-world applications in autonomous systems and healthcare.
Bryan Gick is a Professor in the Department of Linguistics at the University of British Columbia's Faculty of Arts, where he directs the UBC Integrated Speech Research Laboratory (ISRL) and co-directs UBC Language Sciences. He holds additional affiliations as a Senior Researcher at Haskins Laboratories in New Haven, CT, and as an Associate Member of the UBC Department of Psychology and UBC School of Audiology & Speech Sciences. His educational background includes a Ph.D. (1999), M.Phil. (1997), and M.A. (1995) from Yale University, and a B.A. (1992) from the University of Pennsylvania. Gick's research centers on understanding how the human body functions as a communication device, focusing on physical mechanisms of movement control and sensation in speech production, perception, and phonetics. His work spans normal and disordered speech, children's speech development, signed languages, singing, and emotional expression. He has pioneered techniques for applying ultrasound imaging to speech research and developed protocols for studying haptic and multimodal perception of speech. Analysis of his recent publications reveals a strong focus on tongue bracing phenomena, speech biomechanics, neurological bases of speech production, and applications to clinical conditions including Parkinson's Disease and Alzheimer's. His research increasingly incorporates cross-disciplinary approaches from neuroscience, biomechanics, and computer modeling. His significant scientific recognition includes: John Simon Guggenheim Memorial Foundation Fellow Fellow of the Royal Society of Canada (FRSC) Fellow of the American Association for the Advancement of Science Gick leads multiple research initiatives including the UBC Integrated Speech Research Laboratory and contributes to the ArtiSynth project for biomechanical simulation of speech. His work connects theoretical linguistics with practical applications in speech pathology, language learning, and human-computer interaction.
Dr. Diane Brentari is the Mary K. Werkman Professor of Linguistics at the University of Chicago and Co-Director of the Center for Gesture, Sign, and Language. Her research focuses on sign language grammars, phonology, and the emergence of protactile systems in DeafBlind communities. She holds a Ph.D. from the University of Chicago (1990) and has taught there since 2011. Key interests include modality effects on language structure, language variation, and typological comparisons. Her work has been supported by the National Science Foundation, a Guggenheim Fellowship, and the Neubauer Collegium. Notable contributions include books like Sign Language Phonology (2019) and edited volumes on sign language creation and phonological theory. Awards include Fellow of the Linguistic Society of America and membership in the American Academy of Arts and Sciences. Research Highlights: Analysis of Nicaraguan Sign Language emergence, tactile phonology in protactile communities, and cross-modal comparisons of gesture and sign. Courses Taught: Phonological Analysis, American Deaf Community Studies, and Seminars on Multiple Verb Predicates. Dr. Brentari's lab investigates sign language morpho-phonology and its sociocultural dimensions. Recent projects explore how tactile languages utilize touch and proprioception as linguistic resources. Her work bridges theoretical linguistics with empirical studies of language emergence and variation.
Mingyuan Chu is a Lecturer in the School of Psychology at the University of Aberdeen, with research focusing on the interplay between nonverbal behavior and cognitive processes. Affiliated with the School of Psychology within the College of Life Sciences and Medicine, Chu maintains an active research profile utilizing EEG, virtual reality, motion tracking, and eye-tracking methodologies. Chu's educational background includes a PhD in Psychology from the University of Birmingham (2008), an MSc in Neuropsychology from the University of Bristol (2005), and a BSc in Applied Psychology from Nankai University (2004). Professional memberships include being an Editorial Board member for GESTURE, the Experimental Psychology Society, and the International Society for Gesture Studies. Research centers on four key areas: (1) language-action system interactions, (2) gesture facilitation in problem-solving and language processing, (3) pragmatic and emotional processing during communication, and (4) individual differences in gesture-speech integration. Methodologically, the work combines electrophysiological, virtual reality, motion tracking, eye-tracking, and behavioral experimentation approaches. Publication analysis reveals consistent focus on nonverbal communication across 22 publications (2008-2025), with recent work emphasizing cross-cultural gesture differences, subliminal pain perception, and individual differences in gesture production. The research demonstrates strong continuity in gesture-cognition relationships while expanding into cultural and clinical dimensions. EPS Small Grant (2022-2023) Leverhulme Research Project Grant (2020-2022) EPS Symposium Grant (2020) Research Enhancement Scheme, University of Aberdeen (2019) Carnegie Incentive Grant (2018-2019) British Academy Small Grant (2016-2018) Teaching responsibilities include Advanced Psychology A, Methodology A/B, Memory and Language, and Current Topics in Psychological Studies at Levels 2-4. As Senior Personal Tutor and International Exchange Officer, Chu plays significant administrative roles within the School of Psychology. The research program maintains active collaborations across cognitive neuroscience, linguistics, and cross-cultural psychology domains.
Dr. Salem Ameen is a Lecturer in Artificial Intelligence, Robotics, and Automation at the University of Salford’s School of Science, Engineering & Environment. He is affiliated with the Centre for Future Engineering. He earned his Ph.D. in 2017 from the University of Salford, focusing on optimizing deep learning with multi-armed bandits, and his Master’s in Computer Science and Engineering (2007–2009). Research Interests : Deep Learning Optimization (e.g., multi-armed bandit algorithms) Neural Network Pruning for resource-constrained environments AI in healthcare diagnostics and patient care Robotics integration with AI (e.g., healthcare automation) Educational technology leveraging AI Teaching & Supervision : He teaches courses across levels 3–7, including Artificial Intelligence, Robotics, Mathematics, and Mechatronics. He supervises Master’s projects in areas like Computer Vision, Deep Reinforcement Learning, and Robotics. He offers PhD supervision in topics such as Explainable AI, Federated Learning, and Soft Robotics. Affiliations & Labs : He is part of the Centre for Future Engineering, focusing on innovative automation and smart technologies.
Susan Goldin-Meadow is the Beardsley Ruml Distinguished Service Professor of Psychology at the University of Chicago . Her research focuses on the interplay between gesture, language, and cognition, particularly in deaf children who invent gesture systems (homoesign) and how nonverbal communication shapes thinking. She has held leadership roles including Editor of Language Learning and Development , President of the Cognitive Development Society , and current President of the International Society for Gesture Studies . Her work bridges developmental psychology, linguistics, and neuroscience. Education: Ph.D. in Developmental Psychology from the University of Pennsylvania. Her research lab investigates gesture's role in learning, communication, and language creation. She has authored influential books such as The Resilience of Language (2003) and Hearing Gesture (2003), and her findings highlight how gesture reveals and transforms mental processes. Key contributions include discovering that deaf children without language models develop structured gesture systems and that gestures in hearing individuals convey unspoken cognitive processes. Awards include election to the American Academy of Arts and Sciences (2005) and a 2019 best paper award in Language . Teaching includes courses on Language Development and Nonverbal Communication . Her lab's work appears in Psychological Science , Cognitive Science , and Proceedings of the National Academy of Sciences . Current projects explore gesture's impact on math learning, cross-cultural gesture systems, and the neural bases of gesture-language interactions.
Dimitrios Kosmopoulos serves as Professor in the Computer Engineering and Informatics Department at the University of Patras, Greece, with extensive experience across multiple academic institutions including National Technical University of Athens (NTUA), Rutgers University, and University of Texas at Arlington. His research bridges theoretical computer science with practical applications in accessibility, agriculture, and cultural heritage preservation. Education: B.Eng. in Electrical and Computer Engineering, National Technical University of Athens (1997) PhD in Electrical and Computer Engineering, National Technical University of Athens (2002) Professor Kosmopoulos' research integrates computer vision, machine learning, and signal processing to solve real-world problems. His primary focus areas include sign language recognition systems for museum accessibility, precision agriculture applications for crop monitoring and disease detection, and digital restoration of ancient scripts like Mycenaean Linear B. His methodological innovations frequently involve geometric analysis, time-series modeling, and multimodal data fusion techniques that advance both theoretical frameworks and practical implementations. Analysis of his recent publications (2023-2025) reveals three dominant research thrusts: accessibility technologies for deaf communities (particularly museum navigation systems), agricultural automation using computer vision (olive grading, tomato disease detection), and computational archaeology (Linear B tablet restoration). His work consistently employs cutting-edge approaches including geometric knowledge distillation, coupled learning architectures, and 3D motion analysis, demonstrating strong interdisciplinary connections between computer science, agriculture, and humanities. No scientific awards were documented in the provided source materials. While specific advising details and grant information were not explicitly stated, his leadership in projects like HealthSign (sign language healthcare systems) and MuseLearn (museum accessibility platforms) indicates substantial research funding and collaborative supervision activities spanning computer vision, robotics, and assistive technology domains. Professor Kosmopoulos operates within the Division of Hardware and Computer Architecture at the University of Patras, collaborating with the Computer Technology and Architecture Laboratory, VLSI Microelectronics Laboratory, Signals and Telecommunications Laboratory, and Computer Communications Networks Laboratory. His current research integrates these facilities to develop systems like the SignGuide project for museum tours and frameworks for early pest detection in greenhouse crops, emphasizing practical implementations of machine learning in constrained environments.
Devin Balkcom is a Professor of Computer Science at Dartmouth College, currently serving as Department Chair. He co-directs the Reality and Robotics Lab, focusing on efficient robot design and motion, including knot-tying, autonomous construction, and human motion training. His research spans robotics, motion planning, and human-robot interaction. Affiliations: Dartmouth College, Thayer School of Engineering, Department of Computer Science Labs: Reality and Robotics Lab Research Interests: Efficient robot motion, autonomous underwater construction, modular robotics, robot manipulation, and systems for teaching human movement (e.g., dance, sign language). Recent articles highlight advancements in energy-optimal trajectories for skid-steer rovers, autonomous underwater cement block assembly, and interactive dance lesson systems derived from TikTok videos. His work bridges robotics with applications in education and marine engineering. Grants & Students: Advised numerous PhD/Master’s students (e.g., Yinan Zhang, Weifu Wang) and collaborates on projects involving grants for robotics innovation. Notable student contributions include work on interlocking structures, soft robotics, and human motion analysis.
Claude Mauk is a Teaching Professor and Director of the Less-Commonly-Taught Languages Center at the University of Pittsburgh. His research focuses on phonetics, phonology, and psycholinguistics, particularly as they relate to American Sign Language (ASL). He investigates how phonetic and phonological targets manifest in both spoken and signed languages, with a special emphasis on acoustics, kinematics, and first-language acquisition. His work explores topics such as phonetic reduction, sign lowering, and spatial semantics in ASL, alongside broader linguistic questions about gesture dynamics and cross-modal comparisons between speech and sign. Mauk’s contributions include foundational studies on children’s early sign development and the application of motion-capture technology to sign-phonetic analysis. No academic awards or grants are explicitly mentioned in the provided materials. He advises no named students. His current role involves directing the LCTL Center, which supports underrepresented languages at Pitt. Mauk’s research is characterized by interdisciplinary approaches, integrating linguistics with cognitive science and technology to understand language structure and acquisition. His work bridges theoretical and applied linguistics, with implications for language education and clinical linguistics.
Dr. Zhidong Xiao serves as Principal Academic (Associate Professor) at Bournemouth University's National Centre for Computer Animation within the Faculty of Media and Communication. With over ten years of leadership experience including roles as Programme Leader, Head of Education, and Deputy Head of Department, he drives academic strategy and research innovation in computer animation and digital media. His work bridges technical excellence with creative industry applications through extensive collaborations across the UK and China. Dr. Xiao's educational foundation includes a PhD in Computer Graphics (2010) and postgraduate certificates in Education Practice (2010) and Research Degree Supervision (2011) from Bournemouth University, complemented by a BEng (Hons) in Thermodynamics from Taiyuan University of Technology, China (1994). PhD in Computer Graphics, Bournemouth University (2010) PGCE in Education Practice, Bournemouth University (2010) PGCE in Research Degree Supervision, Bournemouth University (2011) BEng (Hons) in Thermodynamics, Taiyuan University of Technology (1994) His research spans Computer Graphics, Motion Capture, Artificial Intelligence, and Virtual Reality with focus on physics-based simulation, sign language recognition, and motion synthesis. Recent work integrates partial differential equations with machine learning to solve animation challenges in facial realism, deformation simulation, and 3D reconstruction. His interdisciplinary approach connects computer science with creative industries, healthcare applications, and educational technology while advancing core techniques in neural rendering and motion analysis. Analysis of his 15 most recent publications reveals consistent innovation in physics-based animation techniques (40%), motion capture processing (25%), and neural approaches to 3D reconstruction (35%). Key trends include the fusion of analytical physics models with deep learning architectures, development of efficient real-time simulation methods, and expansion into accessibility applications through sign language recognition systems. Scientific recognitions include: Fellow of British Computer Society (2023) Fellow of Higher Education Academy (2011) Best Poster Award at Pacific Graphics 2014 He maintains active peer review roles for EPSRC, ESRC, IEEE Transactions on Multimedia, and ACM SIGGRAPH conferences. Dr. Xiao has supervised seven PhD students to completion while currently guiding Alexandra Sergeeva Alexdottir's research on Phantom Touch phenomena. His grant portfolio demonstrates strong industry-academia collaboration: Principal Investigator Capturing and representing sign language (British Council, 2025) VE Communication Programme (Erasmus+, 2020) Co-Investigator Rehabilitation Enhancement via Motion Capture (BU Fusion Fund, 2013) Cross-Channel Film Lab (Interreg, 2012) Digital Beijing Opera Project (2010) As a core member of Bournemouth's Computer Graphics and Visualisation Research Group and Centre for Digital Entertainment, he leads initiatives in motion capture technology through AccessMocap Studio. His international outreach includes invited lectures across China on computer animation education and visual effects techniques, strengthening global partnerships in creative technology development.
Jason Riggle is an Associate Professor in the Department of Linguistics at the University of Chicago, serving as Director of the Chicago Language Modeling Lab and Resident Dean of The Max Palevsky Residential Commons. He holds a PhD from UCLA (2004) and has taught at UChicago since 2004. His research focuses on computational linguistics, phonology, and learnability, particularly exploring how models of grammar and learning predict linguistic typology. He investigates articulatory frequencies across languages, dialects, and contexts, with special attention to phonetic and phonological patterns. Recent courses include Introduction to Phonetics and Phonology , The Language of Deception and Humor , and Computational Models in Phonology . His work spans theoretical frameworks like Optimality Theory and computational methods for analyzing sign languages (e.g., ASL fingerspelling), with publications on topics such as vowel harmony, constraint-based grammars, and linguistic universals. Riggle’s research emphasizes interdisciplinary approaches, combining formal models with empirical data to address questions in phonological typology and learnability. His academic contributions include co-editing The Handbook of Phonological Theory (2nd ed., 2011) and developing tools like Erculator for constraint-based phonology. No scientific awards are listed in the provided materials, though his extensive publication record reflects sustained academic impact. Riggle advises students in phonetics, computational linguistics, and related fields, though specific advisee names are not detailed here.
Aphrodite Galata is a Lecturer in Advanced Interfaces at the Human Computer Systems department. She holds a Doctor of Philosophy from the University of Leeds (2001) in Learning Variable Length Markov Models of Behaviour. Her research focuses on Computer Vision and Machine Learning, with special emphasis on sign language processing, human-robot interaction, and embodied learning systems. She has contributed to advancements in artificial agents learning sign language through imitation, phonological property recognition, and dataset development for American Sign Language analysis. Her research interests also span robotics, 3D pose estimation, and real-time tracking systems. Key topics in her work include gesture analysis, multimodal communication, and neural network architectures for feature representation. She has published widely in top-tier conferences including IEEE ICASSP and ACL, with notable contributions to datasets like WLASL-LEX. Notable projects include developing algorithms for hand tracking from monocular RGB data and exploring anisotropic cost functions for facial landmark detection. She has collaborated with researchers like Angelo Cangelosi on embodied sign language systems. Her work bridges computer vision techniques with cognitive modeling to enhance human-agent communication systems. Her research is aligned with the Digital Futures research beacon, emphasizing innovation in human-computer systems. While no specific awards are noted, her work has garnered significant readership on platforms like Mendeley, reflecting its academic impact. She has supervised 8 research works, contributing to the training of future scholars in advanced interface technologies.
Prof. Dr. Doris Mücke is a leading experimental phonetician at the University of Cologne , specializing in speech production and perception, with a focus on dynamic systems theory and the interplay between prosody, articulation, and phonology . Her work bridges linguistic theory with clinical research, particularly in neurodegenerative diseases like Parkinson’s and Essential Tremor, analyzing how Deep Brain Stimulation and Levodopa affect speech motor control. She is a member of the CRC1252 Prominence in Language and an elected member of the IPA Permanent Council (2023-2031). Key research areas: Experimental phonetics, Laboratory phonology, Prosody and articulation, Acoustic and kinematic measurement techniques, Speech motor control in aging and disease. She has developed innovative tools like the ema2wav-converter and Vowel Hunter software for phonetic analysis. Her publications span acoustic and kinematic studies in German, Persian, Polish, Italian, and Tashlhiyt Berber, with recent emphasis on sign language coarticulation (LSF) and multimodal speech accommodation . She has supervised over 30 doctoral and MA theses, with her students receiving awards like the IPA Student Award and Offermann-Hergarten Prize . Her interdisciplinary collaborations with neurologists and institutions like Université Sorbonne and LMU Munich highlight her integrative approach.
