Lee M. Miller is a Professor and Vice Chair of Academic Affairs in the Department of Neurobiology, Physiology and Behavior at the University of California, Davis, affiliated with the Center for Mind and Brain. His research focuses on neuroengineering, computational neuroscience, and neural mechanisms underlying attention, speech processing, and multisensory integration. Research interests include the development of neural prosthetics, decoding of neuromuscular signals for prosthetic control, and understanding how auditory and visual systems interact during speech perception and attentional processes. His work bridges clinical applications (e.g., cochlear implants) with fundamental neuroscience, leveraging tools like electrophysiological recordings, EEG/MEG, and advanced signal processing techniques. Recent publications highlight innovations in electromyographic speech neuroprosthetics, the topology of neuromuscular signals, and the neural basis of speech-in-noise processing. Miller’s studies emphasize translational potential, such as improving speech synthesis from brain signals and designing haptic feedback systems for motor coordination. His contributions have advanced understanding of neural mechanisms in sensory integration, auditory attention, and the impact of cognitive factors on perception. Miller maintains a lab dedicated to these interdisciplinary efforts, with a focus on both basic science and clinical applications.
Philippe Souères is a Researcher at LAAS-CNRS (Laboratory for Analysis and Architecture of Systems) within the University of Toulouse. He leads the Gepetto team, focusing on advanced robotics, humanoid motion generation, and the integration of human biomechanics into robotic systems. His work bridges robotics, neuroscience, and biomechanics, emphasizing optimal control, sensor-based systems, and human-robot interaction. Research interests include robot control (optimal control, nonlinear systems), neurosciences (human motor control, sensorimotor integration), and biomechanics (organization of human movement). Notable contributions include models for humanoid locomotion, human-like motion generation using inverse dynamics, and studies on task-dependent balance in humans and robots. Souères has authored/co-authored over 50 publications, including award-winning work on human movement modeling for robotics. He has supervised numerous PhD students and contributed to projects like the EAR initiative (Robot Audition) and the development of the Pyrène humanoid robot. His research also extends to aerial robotics, ducted fan vehicles, and interdisciplinary collaborations with neuroscientists and biomechanics experts. Awards include the Best Conference Paper Award (2010) for integrating human movement invariants into humanoid robotics. Souères is actively involved in academic outreach, appearing in media discussions on robotics ethics and technological innovation.
Ajita Rattani is an Assistant Professor in the Department of Computer Science and Engineering at the University of North Texas, affiliated with Discovery Park. Her research focuses on biometrics, AI fairness, deepfake detection, and machine learning applications in health and security. She holds a Ph.D. in Computer Science and Engineering, with expertise in facial recognition, ocular biometrics, and multimodal authentication systems. Research Interests: Her work addresses algorithmic fairness in facial attribute classification, robustness of biometric systems against adversarial attacks, and developing lightweight models for on-device authentication. She also explores applications of machine learning in health informatics, such as BMI prediction from facial images and analyzing social determinants of health. Publications Trends: Recent work emphasizes bias mitigation in AI systems (e.g., gender/racial fairness), deepfake detection through fusion of audio-visual cues, and advancing ocular biometric recognition under challenging conditions. Notable contributions include frameworks like CodeIT for data-efficient deepfake detection and PatchBMI-Net for lightweight BMI prediction. Advising & Grants: Leads research projects funded by NSF SaTC grants (e.g., probing fairness in ocular biometrics). Active in organizing competitions like VISOB 2.0 for mobile ocular biometrics evaluation. Her lab develops practical solutions for real-world challenges in biometrics and AI ethics. Labs/Teams: Involved in interdisciplinary teams addressing transdisciplinary collaboration challenges and applying AI to disaster detection (wildfires, droughts) using satellite and sensor data fusion.
Edward Delp is the Charles William Harrison Distinguished Professor of Electrical and Computer Engineering at Purdue University's College of Engineering. He holds affiliations with both the Department of Electrical and Computer Engineering and the Department of Biomedical Engineering. His research spans computer vision, medical imaging, and data forensics with a focus on synthetic media detection, deep learning applications, and healthcare technologies. Education: Not explicitly listed in the provided text. His work includes developing algorithms for speech forensics, microscopy image analysis, and food/nutrition assessment systems. He leads projects on synthetic speech detection, medical image segmentation, and automated crop disease measurement using RGB imaging. Delp collaborates across disciplines, integrating machine learning with healthcare and agricultural challenges. Recent work emphasizes ethical AI through fairness in synthetic media detection and explainable artifacts in biomedical imaging. He contributes to large-scale datasets like MetaFood3D and 3D nuclear segmentation frameworks for microscopy analysis. His grants and advising focus on interdisciplinary applications, though specific grant details are not provided. Delp is affiliated with the Purdue School of Biomedical Engineering and maintains active collaborations in medical imaging, computer vision, and aerospace anomaly detection.
Professor Bruce N. Walker holds a joint appointment in the School of Psychology and School of Interactive Computing at Georgia Institute of Technology, within the College of Sciences. His research focuses on human-centered technology design, emphasizing accessibility, auditory displays, and human-AI interaction. He leads the Sonification Lab, pioneering multimodal interfaces and inclusive technology solutions. He earned his Ph.D. in Human Factors and Human-Computer Interaction from Rice University in 2001. Research Interests: Trust in technology, accessible interfaces, sonification, AI-human collaboration, and HCI in non-traditional environments. Current projects include the AccessCORPS VIP initiative to enhance course accessibility and studies on automated vehicle interaction. Awards: Best Paper Award at AudioMostly 2014 for auditory weather reports research. Active in professional organizations like the International Community for Auditory Display and Human Factors and Ergonomics Society. Teaching: Courses include Research Methods for Human Factors, Sensation and Perception, and HCI Foundations. Supervises interdisciplinary teams in the Sonification Lab R&D Studio and AccessCORPS VIP. Labs/Teams: Sonification Lab (multimodal data exploration) and AccessCORPS (disability-inclusive course design). Collaborates on international projects like the Mwangaza initiative for learners with vision impairment in Kenya.
Prof. Sophie Schwartz is a leading neuroscientist at the University of Geneva , where she heads the Sleep & Cognition Lab within the Faculty of Medicine . Her research integrates neuroimaging (fMRI, hd-EEG, MEG) , behavioral testing , and computational modeling to unravel the neural mechanisms underlying memory consolidation , emotion processing , and dreaming during sleep, while also developing clinical interventions to enhance sleep in neurological and psychiatric disorders.
Maxwell Tfirn is a Lecturer and Director of Creative Studies at Christopher Newport University , Department of Music, Theatre and Dance, where he teaches Music Composition, Sound Synthesis, and Music Technology. His research focuses on real-time recursive compositions and data sonification for scientific analysis. PhD in Composition and Computer Technologies - University of Virginia M.A. in Music Composition - Wesleyan University His work bridges music composition with bacterial behavior studies through NSF-funded research on Data Sonification of Bacterial Chemotaxis . Notable performances include works at ICMC, SEAMUS, and Subtropics Music Festival. Collaborations with ensembles like Jack Quartet and Loadbang highlight his impact in contemporary music circles. Key Trends in Publications: Articles span real-time algorithmic compositions, sensor-based live performance tools, and interdisciplinary sonification projects merging microbiology with auditory analysis. Subfields include neural network integration, audiovisual data mapping, and glitch-based performance aesthetics. Scientific Awards: Best Use of Sound (Academic) - ICAD (2023) Research Collaborations: National Science Foundation grant exploring bacterial chemotaxis sonification. Mentorship roles include advising students at Christopher Newport University and contributing to experimental music festivals globally.
Anthony Hornof is a Professor in the Department of Computer Science at the University of Oregon, part of the College of Arts and Sciences. He has been a faculty member since 1999 and was granted tenure in 2005. His research is centered on human-computer interaction, with strong emphases on cognitive modeling, eye tracking, and assistive technology. He leads an active research laboratory and has secured substantial funding from the National Science Foundation and the Office of Naval Research. University: University of Oregon School: College of Arts and Sciences Department: Department of Computer Science Position: Professor Email: hornof@uoregon.edu, hornof@cs.uoregon.edu Office: 356 Deschutes Hall Phone: (541) 346-1372 Education: B.A. in Computer Science, Columbia University, 1988 M.S. in Computer Science and Engineering, University of Michigan, 1996 Ph.D. in Computer Science and Engineering, University of Michigan, 1999 Research Interests: Dr. Hornof's research lies at the intersection of human cognition and computing. He is particularly interested in understanding and modeling the perceptual, cognitive, and motor processes involved in human-computer interaction. His work uses eye tracking both as an evaluation tool for cognitive models and as a real-time input method for creative expression and accessibility. A major focus is assistive technology, especially developing tools like EyeDraw that enable children with severe motor impairments to create art using only eye movements. He also explores eye-controlled musical compositions, bridging technology and artistic expression. His research is grounded in participatory design, involving end-users directly in the development process. Publication Trends: His recent publications demonstrate a consistent focus on modeling human behavior in complex interactive tasks. Key themes include visual search strategies, dual-task performance, cognitive modeling using eye-tracking data, and accessibility. His work spans top venues in HCI (CHI, TOCHI), cognitive science (CogSci, ICCM), and specialized conferences like ETRA and NIME. There is a strong methodological thread involving data calibration, model validation, and the development of predictive tools for interface design. Scientific Awards: Best Paper Award (Top 1%) at CHI 2014 (two papers) Honorable Mention Paper (Top 5%) at CHI 2010 Siegel-Wolf Award for Best Applied Paper at ICCM 2010 Advising and Grants: Dr. Hornof actively seeks to mentor exceptional undergraduate students, graduate students, and postdoctoral researchers in his lab. He emphasizes rigorous and creative scientific research. He has been awarded over $2.9 million in single-investigator research grants from prestigious agencies including the National Science Foundation (NSF) and the Office of Naval Research (ONR). Notably, he served as an NSF Program Director from 2012 to 2014, contributing to funding decisions for approximately $65 million in research. Labs and Teams: He leads the Human-Computer Interaction Laboratory at the University of Oregon, where interdisciplinary research is conducted on cognitive modeling, eye tracking, and assistive technologies. His team has developed software such as VizFix for visualizing eye-tracking data and has ported the Eyegaze system to Macintosh. The lab fosters collaborations with new media artists and musicians, and engages in participatory design with children who have disabilities.
Abhinav Dhall is an Associate Professor in the Department of Data Science & AI at Monash University. His research focuses on computer vision, affective computing, and human-centered AI, with a particular emphasis on deepfake detection, multimodal analysis, and ethical AI applications. He is actively involved in organizing workshops like the Multimodal and Responsible Affective Computing (MRAC) and chairs conferences such as ACCV. Dhall accepts PhD students and has contributed significantly to datasets like AV-Deepfake1M and EmotiW challenges. His work spans topics including HDR imaging, facial expression recognition, and AI ethics in multimedia systems.
Tom Mitchell is a Professor of Audio and Music Interaction at the University of the West of England (UWE), Bristol . As leader of the Creative Technologies Laboratory , his research focuses on interactive technologies for creative expression, blending computer science, music, and artificial intelligence. He is the principal investigator for the UKRI Future Leaders Fellowship project "Sensing Music Interactions from the Outside-In" and co-investigator for the Bridge , a £3M creative technology facility. His research spans digital musical instrument design , GPU-accelerated audio processing , and sonification of scientific data . Recent work includes accessibility improvements in virtual environments, AI-driven DMI development, and interdisciplinary collaborations like the MiMU Gloves with Imogen Heap. He also contributes to robotics teleoperation through auditory feedback systems. Selected publications highlight trends in GPU acceleration for audio , generative AI in musical contexts , and human-robot collaboration via sonification. As a software developer , he specializes in C++ and the Juce library , with applications in live performance systems and scientific visualization projects like Soma and danceroom Spectroscopy . UKRI Future Leaders Fellow Active in AHRC and WECA-funded projects Best paper nominations at EvoMUSART and International Faust Conference Mitchell collaborates with institutions including the Bristol Robotics Laboratory , Computer Science Research Centre , and Pervasive Media Studio . His work bridges academic research with commercial applications through ventures like May Productions and x-io Technologies.
Prof. Dr. Volker Dellwo is an Associate Professor of Phonetics and head of the Department of Computational Linguistics. His research focuses on phonetics, speech recognition, computational linguistics, and dialectology, with applications in forensic analysis, voice biometrics, and multimodal emotion recognition. Academic Rank: Associate Professor Department: Computational Linguistics His work explores phonetic convergence , speaker discrimination, and the role of prosodic features in voice recognition. Recent studies analyze whispered speech processing, cross-dialect accommodation, and neural mechanisms of speaker identity encoding. Key article trends include self-supervised learning for speech recognition , multimodal emotion detection , and forensic voice analysis . Subfields span acoustic variability, temporal envelope dynamics, and voice quality metrics. Publications emphasize computational phonetics , cross-linguistic studies , and neural network applications in speaker identification. Research also addresses challenges in forensic audio analysis and synthetic speech dataset generation.
Jonathan Ragan-Kelley is the Esther and Harold E. Edgerton Assistant Professor of Electrical Engineering & Computer Science at MIT and an Assistant Professor of EECS at UC Berkeley. He leads the Visual Computing group at CSAIL, focusing on high-efficiency visual computing, compilers, and architectures for image processing, machine learning, and 3D rendering. His research bridges systems, compilers, and hardware design, emphasizing scalable solutions for computational challenges. Education: PhD in Computer Science from MIT (2014), postdoc at Stanford University, and visiting researcher at Google. He co-created the Halide language and has developed multiple domain-specific languages (DSLs) and compiler systems. Research interests include compiler optimization, scheduling languages (e.g., Exo), and efficient computing frameworks. He has received awards such as the NSF CAREER Award and ACM SIGGRAPH’s Significant New Researcher Award. Awards: ACM SIGGRAPH Award, NSF CAREER, Intel Outstanding Researcher Award Key Contributions: Halide compiler framework, Exo scheduling language, machine learning acceleration techniques Labs/Teams: Visual Computing at MIT CSAIL
Kevin Chetty is a Professor of Wireless Sensing at University College London (UCL), leading the Urban Wireless Sensing Lab within the Department of Security and Crime Science. His work bridges radar technology, machine learning, and healthcare applications, with a focus on passive sensing systems. Education: PhD in Medical Ultrasound Physics (Imperial College London, 2004-2007), MRes in Image and X-Ray Physics (King's College London, 2003), BSc in Physics (King's College London, 1999) Research spans radar micro-Doppler signature analysis for human behavior classification, software-defined radar development, and integrated communication-sensing systems, with applications in security, healthcare, and smart environments. Recent work emphasizes privacy-preserving technologies and edge processing for real-time operations. Scientific awards include the 2022 IET Radar Systems Best Paper Runner-Up, 2022 IEEE Radar Conference 2nd Place, and 2015 National Instruments Engineering Impact Award. He has received funding from government and industry sectors in telecommunications, IoT, security, and healthcare. Teaching roles: Programme Convener for MSc Crime Science and IEP Minor in Crime and Security Engineering; Module Convener for Security Technologies and Crime Mapping & Spatial Analysis Consultancy: Huawei Technologies (2020-2022), Metropolitan Police Service (2019)
Gustav Henter is an Assistant Professor in Intelligent Systems at KTH Royal Institute of Technology, specializing in Machine Learning. He is affiliated with the Division of Speech, Music and Hearing (TMH) within the School of Electrical Engineering and Computer Science. His research focuses on deep generative models for applications like speech synthesis, 3D character animation, and human-computer interaction. He holds a Docent degree from KTH and has held post-doctoral positions at the University of Edinburgh and the National Institute of Informatics in Tokyo. Education: PhD in Electrical Engineering (KTH, 2013), MSc in Engineering Physics (KTH, 2007). He supervises doctoral students in areas like gesture synthesis and multimodal interaction. His work is supported by grants from the Wallenberg AI, Autonomous Systems, and Software Program (WASP) and South Korea's MOTIE. He co-founded Motorica AB to commercialize motion synthesis research. Awards include Best Paper Awards at ICMI 2020 and IVA 2020, and recognition for student theses. His research spans generative AI, perceptual evaluation, and robust statistical models. He organizes the GENEA Challenge and Workshop series for gesture generation benchmarking.
Taein Kwon is a postdoctoral research fellow at the Visual Geometry Group (VGG) within the Department of Engineering Science at the University of Oxford, working under Prof. Andrew Zisserman. Previously, he completed his PhD at ETH Zurich under Prof. Marc Pollefeys and earned master's and bachelor's degrees from UCLA and Yonsei University, respectively. His educational background includes: Bachelor's in Electrical Engineering from Yonsei University, Seoul, Korea Master's degree from UCLA PhD from ETH Zurich (defended July 2024) His research spans Egocentric Vision, Action Recognition, Hand-object Interaction, Video Understanding, AR/VR, and Multi-modal Learning, with emphasis on first-person perspective analysis for AI assistants and human-computer interaction. His work integrates 3D reconstruction, pose estimation, and multimodal signals to model complex human activities and physical interactions. Analysis of his 2021-2025 publications reveals a consistent focus on egocentric vision datasets (H2O, HoloAssist, EgoPressure) and novel frameworks for hand-object interaction, action recognition, and gesture understanding. His research demonstrates strong interdisciplinary connections between computer vision, robotics, and human-centered AI, with increasing emphasis on pressure sensing, co-speech gestures, and cross-modal alignment. His scientific recognition includes: CVPR Egovis 2022/2023 Distinguished Paper Award for HoloAssist (July 2024) SNSF Postdoc.Mobility fellowship (May 2024) He actively mentors students on egocentric vision projects, supervising master's theses, semester projects, and collaboration initiatives leading to publications at top conferences. His research is supported by the SNSF fellowship and industry collaborations with Meta Reality Labs and Microsoft Research. As part of Oxford's Visual Geometry Group, he contributes to cutting-edge computer vision research while maintaining strong ties with ETH Zurich's computer vision community through ongoing collaborations and dataset development efforts.
