Associate Professor Ng Bing Feng leads research in Additive Manufacturing, Aerospace Engineering, and Thermofluids at Nanyang Technological University's School of Mechanical & Aerospace Engineering. As Cluster Director for Smart & Sustainable Building Technologies at NTU's Energy Research Institute, he oversees projects spanning energy-efficient cooling technologies, advanced filtration systems, and bio-inspired materials. His interdisciplinary work integrates advanced manufacturing with environmental engineering, focusing on sustainable solutions for air quality management and thermal regulation. Current research explores radiative cooling technologies, acoustic agglomeration for emissions control, and crashworthy structures via biomimetic design. Professor Ng's publications demonstrate consistent innovation in multi-scale manufacturing and fluid dynamics, with growing emphasis on sustainable urban technologies. Methodologies combine experimental fluid dynamics with computational modeling and AI-driven design. Leadership Roles: Cluster Director, Energy Research Institute @ NTU Principal Investigator for multiple industry collaborations in sustainable materials Research Output: 42+ publications in high-impact journals Multiple patents in filtration technologies and cooling systems
Tara McAllister is an Associate Professor and Director of the Doctoral Program in Communicative Sciences and Disorders at New York University’s Steinhardt School. She leads the Biofeedback Intervention Technology for Speech (BITS) Lab , focusing on speech learning mechanisms and biofeedback treatments for speech disorders. Her work emphasizes acoustic and ultrasound biofeedback efficacy in resolving residual speech sound disorders, particularly in children. McAllister directs development of the staRt iOS app, expanding access to biofeedback training. She holds degrees from Harvard, MIT, and Boston University, with clinical expertise in speech-language pathology. Education: A.B./A.M., Linguistics, Harvard University (2003) M.S., Communication Disorders, Boston University (2007) Ph.D., Linguistics, MIT (2009) Research Interests: Speech motor control, perception-production links, bilingual phonological development, and technology-driven interventions. Her NIH-funded studies investigate biofeedback applications for speech disorders and crowdsourcing methodologies for perceptual analysis. Grants & Labs: NIH/NIDCD-funded BITS Lab research staRt app development since 2014 Teaching: Courses include Critical Evaluation of Research and Speech Science Instrumentation , emphasizing evidence-based practices in communication sciences.
Dhruv Jain is an Assistant Professor in the Computer Science and Engineering Department at the University of Michigan , with affiliations in the School of Information and Michigan Medicine . He leads the Soundability Lab , focusing on transforming hearing into a programmable interface through human-centered AI systems. PhD from University of Washington MS from MIT Media Lab Formerly worked at Microsoft Research, Google, and Apple Research Interests intersect Human-Computer Interaction (HCI) , Audio AI , Accessibility , and Hearing Health . His work develops systems like SoundWatch (smartwatch-based sound awareness) and HomeSound (IoT sound visualization) to expand auditory access for DHH individuals and other domains. Recent Publications (2023–2025) span top venues like CHI , ASSETS , and ICMI , with trends including generative AI for real-time captioning , adaptive soundscapes , and clinical communication tools . SIGCHI Outstanding Dissertation Award (2023) William Chan Memorial Dissertation Award (2023) Best Poster Award at ASSETS 2024 Google Academic Research Award (2024) NIH Grant ($450k, 2023) William Demant Foundation Grant ($740k, 2025) Teaching includes Accessible Computing (undergraduate) and Advanced Accessibility (graduate), alongside global DIY workshops in five countries. The Soundability Lab collaborates with neuroscientists, clinicians, and Deaf scholars to create deployable systems like clinical communication tools now at Michigan Medicine and features integrated into Apple devices.
Prof. Dr. Steffen Marburg is a Full Professor at the Chair of Acoustics of Mobile Systems within the TUM School of Engineering and Design at the Technical University of Munich. His research focuses on numerical methods in vibroacoustics, structural optimization, and acoustic modeling for applications in automotive, maritime, and musical instrument domains. Education: PhD from Technical University of Dresden (1998). Academic Career: Junior Professor at TU Dresden (2004), Chair of Technical Dynamics at University of the Federal Armed Forces Munich (2010), Full Professor at TUM (2015–present). Editorial Roles: Co-Editor-in-Chief of Journal of Theoretical and Computational Acoustics, Associate Editor of Journal of the Acoustical Society of America, Editor of Acoustics Australia and Mechanical Systems and Signal Processing. His research integrates computational acoustics, boundary element methods, and machine learning to address noise control and structural optimization challenges. Recent work explores acoustic metamaterials, viscothermal losses, and data-driven modeling. He has co-authored over 150 publications and led advancements in multifrequency solution methods and noise-insulating structures. Scientific awards include the Innovation Award of the Industrieclub Sachsen e.V. (1999). His editorial contributions and leadership in journals highlight his influence in computational acoustics and structural dynamics.
Takako Fujioka is an Associate Professor of Music at Stanford University, affiliated with the Center for Computer Research in Music and Acoustics (CCRMA). Her research focuses on the neural mechanisms underlying auditory perception, auditory-motor coupling, and music-supported therapy for neurorehabilitation. She holds a Ph.D. in Physiology from the Graduate University for Advanced Studies, Japan, and M.Sc./B.Eng. degrees in Electrical Engineering from Waseda University. Her work combines neurophysiological techniques such as MEG and EEG to study brain plasticity in development, aging, and stroke recovery. Notable contributions include investigating how music influences motor and cognitive recovery in stroke patients, as well as exploring the neural basis of musical perception through rhythmic synchronization and pitch discrimination studies. Supported by awards from the Canadian Institutes of Health Research during her postdoctoral work at the Rotman Research Institute, her research bridges clinical neuroscience and music cognition. Dr. Fujioka’s expertise spans auditory neuroscience, neurorehabilitation, and technology-assisted music therapy. She has pioneered studies on tactile mapping for cochlear implant users and networked music performance systems, emphasizing cross-modal perception and human-technology interaction. Her findings contribute to both theoretical understanding of auditory processing and practical applications in medical and educational settings. Awards: Canadian Institutes of Health Research Awards (postdoctoral phase) Labs/Teams: CCRMA, Stanford Music Perception Laboratory, Rotman Research Institute collaborations Key Themes: Neuroplasticity, Music-Mediated Rehabilitation, Auditory-Motor Integration, Multisensory Processing Her recent work examines aging-related changes in binaural hearing and the role of beta/gamma oscillations in rhythmic processing. She advocates for translational research that connects neural mechanisms with real-world therapeutic interventions.
Dr A. I. Shihab is a Senior Lecturer at Kingston University's Faculty of Engineering, Computing and the Environment, Department of Networks and Digital Media. He teaches programming languages (C++/Java), data structures, web development, and AI/machine learning. His research focuses on affective computing and machine learning applications including: Acoustic event detection in sports environments Audio signal analysis for tennis match modeling Multi-camera visual surveillance systems Medical imaging analysis using fuzzy clustering techniques Publications demonstrate expertise in combining audio/video modalities for sports analytics (tennis rallies, court-shots) and developing Markov models for sound event sequence analysis. Contact: a.shihab@kingston.ac.uk
Britney Schmidt is Associate Professor in Earth and Atmospheric Sciences and Astronomy at Cornell University, where she leads the Planetary Habitability and Technology Lab. She develops robotic tools like the Icefin underwater vehicle to study Earth's ice shelves and glaciers, providing insights into climate change and analogs for ocean worlds like Europa. Her research bridges glaciology, planetary science, and astrobiology. Research focuses on ocean world habitability, ice-ocean interactions, and Antarctic climate systems. Fieldwork includes extensive campaigns in Antarctica and the Arctic using robotic explorers. Recent publications explore Europa's habitability, Thwaites Glacier dynamics, microbial communities in hypersaline environments, and planetary analog studies. Technical developments include novel instrumentation for under-ice exploration. Awarded the 2024 Blavatnik National Award for groundbreaking research. Leads multiple international collaborations including NASA's Europa Clipper mission and Thwaites Glacier projects.
Rong Zheng is a Professor in the Department of Computing and Software and a member of the School of Biomedical Engineering at McMaster University, Canada. She holds a Tier-1 Canada Research Chair in Mobile Computing and serves as Acting Chair of the Computing and Software department from July to December 2025. She is also an Associate Member of the Electrical & Computer Engineering department. Education: Ph.D. in Computer Science, University of Illinois, Urbana-Champaign, USA Master of Engineering (thesis) in Electrical Engineering, Tsinghua University, Beijing, China Bachelor of Engineering in Electrical Engineering, Tsinghua University, Beijing, China Dr. Zheng's research lies at the intersection of mobile computing, wireless networking, and machine learning, with a strong focus on applications for aging populations. She directs the NSERC Smart Mobility for the Aging Population CREATE program. Her work encompasses sensor development, wireless network design, and mobile data analytics to address real-world challenges in healthcare, mobility, and data center monitoring. She has developed innovative solutions like the MacQuest campus navigation app and has captured first prize in indoor localization competitions. Her recent publications demonstrate a clear trajectory toward applying wireless sensing technologies (particularly acoustic, Wi-Fi, and mmWave) to health monitoring and mobility assessment for older adults. There's a strong emphasis on developing efficient edge computing solutions that can process data in real-time on resource-constrained devices, as exemplified by her TeamNet framework for collaborative inference on the edge. Her work bridges theoretical advances with practical applications that have social impact. Scientific Awards: Tier-1 Canada Research Chair in Mobile Computing US National Science Foundation CAREER Award (2006) Joseph Ip Distinguished Engineering Fellow (2015-2018) Dr. Zheng leads the Wireless System Research Group (WiSeR) at McMaster University, which has secured significant funding including a $1.65M NSERC CREATE grant for smart mobility research for older adults. Her research has been supported by multiple funding agencies including NSERC, NSF, UH GEAR, and DURIP. She actively mentors graduate students and has developed specialized courses including CAS 772 (Mobile Data Analytics) and CAS 781 (Mobility in the Aging Population). The WiSeR group conducts impactful research on communication, networking, and data analytics issues in Cyber Physical Systems, with applications spanning healthcare, smart infrastructure, and data center monitoring. Their work on data center infrastructure monitoring networks has been featured in EurekAlert and Data Center Dynamics, and they've made significant contributions to indoor localization technology.
Mark Lee is an Adjunct Professor in the People Analytics department at NYU’s Tandon School of Engineering, specializing in Technology Management and Innovation. He holds a Ph.D. in Engineering Psychology from Georgia Institute of Technology (1996). Currently, he serves as Head of Research, Analytics, and Business Development at UL ComplianceWire, focusing on pharmaceutical and medical device manufacturing training. His research leverages large datasets to improve healthcare safety through regulatory compliance and best practices. Courses taught include Human Factors Engineering, Workplace Design, and Predictive Analytics. Education: Ph.D. in Engineering Psychology, Georgia Tech (1996) Key Roles: Adjunct Professor, Head of Research at UL ComplianceWire Research Focus: Human Factors, Training Systems Design, Healthcare Compliance His work spans auditory display systems for aviation (e.g., 3D audio cockpit interfaces) and ergonomic design for industrial products. Recent projects emphasize data-driven solutions for regulatory challenges in life sciences. Publications highlight studies on visual search strategies, age-related cognitive performance, and application of signal detection theory in decision-making. He actively collaborates with industry and government entities, exemplified by the FDA-UL Cooperative Research Agreement.
Atsuo Takanishi is a distinguished Professor at Waseda University's Faculty of Science and Engineering, School of Creative Science and Engineering, with appointments in both the Department of Bioscience and Biotechnology and the Department of Modern Mechanical Engineering. With over 700 publications, 10,399 citations, and an h-index of 47, Professor Takanishi has established himself as a leading figure in robotics research. His work spans multiple institutions, including visiting positions at Showa University School of Dentistry and KDDI Research, Inc. Professor Takanishi received his Doctor of Engineering degree from Waseda University in 1985, following his undergraduate studies in the Faculty of Science and Engineering at the same institution, which he completed in 1980. His academic journey began with positions as an Assistant at Waseda University (1985-1988), Lecturer (1988-1990), and Associate Professor (1990-1997) before achieving his current Professor status. Professor Takanishi's research interests center around robotics and intelligent systems, with particular expertise in humanoid robotics, surgical dentistry applications, and biomechatronics. His work demonstrates a unique integration of mechanical engineering principles with biological systems, resulting in innovative robotic platforms that mimic human capabilities. Notably, his laboratory has developed the Waseda Anthropomorphic Saxophonist Robot series and various medical training simulators that have significantly advanced the field of human-robot interaction. His research in experimental psychology complements his robotics work, particularly in human-robot interaction studies. Analysis of Professor Takanishi's recent publications reveals a strong focus on practical applications of robotics technology, particularly in assistive devices for elderly mobility, medical training simulators, and agricultural robotics for Synecoculture environments. His work consistently bridges theoretical robotics with real-world implementation, with recent papers emphasizing reinforcement learning approaches, haptic feedback systems, and computer vision techniques for complex environments. The Waseda Anthropomorphic Saxophonist Robot series represents a culmination of decades of research in humanoid robotics and musical expression. IEEE Fellow (2020-present) Robotics Society of Japan Fellow (2012-present) Japan Society of Mechanical Engineers Fellow (2007-present) Multiple Best Paper Awards from IEEE conferences (ICRA, IROS, ROMANSY) BusinessWeek Asia's Stars Bloomberg (2001) IFToMM Award of Merit (2010) Professor Takanishi has maintained extensive collaborations with research institutions worldwide, particularly with Italian institutions through the Italy-Japan Workshop series. His laboratory has secured substantial funding from Japanese government agencies including the Japan Science and Technology Agency, with particular emphasis on projects bridging robotics with medical applications and human-centered technologies. His international recognition is evidenced by his numerous visiting professorships and collaborative projects across continents. Professor Takanishi leads the Takanishi Laboratory at Waseda University, which maintains specialized facilities for humanoid robotics development, medical robotics research, and human-robot interaction studies. The laboratory has developed several notable robotic platforms including the WABIAN series of bipedal humanoid robots, the WASEDA FLUTIST ROBOT, and various medical training simulators used in clinical education settings. His work on the WASEDA SAXOPHONIST ROBOT represents a unique fusion of musical artistry and robotics engineering.
Jeremy Dahl is a Professor of Radiology (Pediatric Radiology) at Stanford University School of Medicine. He directs the Ultrasound Imaging & Instrumentation Lab and serves as Director of Research Academic Affairs in the Department of Radiology since 2020. He holds multiple affiliations across Stanford including Bio-X, the Cardiovascular Institute, Wu Tsai Human Performance Alliance, Maternal & Child Health Research Institute, Stanford Cancer Institute, and Wu Tsai Neurosciences Institute. Dr. Dahl received his B.S. in Electrical Engineering from the University of Cincinnati (1999) and Ph.D. in Biomedical Engineering from Duke University (2004). His research focuses on developing ultrasonic beamforming and image reconstruction methods for diagnostic imaging applications, particularly techniques that generate high-quality images in difficult-to-image patients. His laboratory specializes in B-mode and Doppler imaging techniques that utilize additional information from ultrasonic wavefields to improve image quality and develop real-time imaging systems for clinical applications including cardiac, liver, and fetal imaging. Dr. Dahl's research has led to significant advancements in ultrasound molecular imaging platforms, sound speed estimation, aberration correction, and reverberation noise suppression. His work often bridges engineering innovation with clinical applications for cancer detection and other diseases. His recent publications demonstrate strong focus on machine learning applications in ultrasound, distributed aberration correction, and molecular imaging techniques. Fellow, American Institute of Ultrasound in Medicine (2021) Senior Member, Institute of Electrical and Electronics Engineers (2020) Distinguished Investigator Award, The Academy for Radiology & Biomedical Imaging Research (2018) Outstanding Paper Award, IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society (2011) Dr. Dahl serves in editorial roles for major journals including IEEE Transactions on Medical Imaging (2017-2024) and IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control (2013-Present). His laboratory has successfully translated numerous innovations into clinical applications, with multiple patents including recent developments in pulsed focused ultrasound therapy and speed of sound quantification.
Fabio Miranda is an Assistant Professor at the Department of Computer Science, University of Illinois at Chicago (UIC) . His research bridges visualization , machine learning , data management , and computer graphics to enable interactive visual analysis of large-scale urban datasets . He has developed systems like UrbanRama (for VR navigation) and The Urban Toolkit (a grammar-based framework), which have been deployed in academia, industry, and government agencies. Education: Ph.D., Computer Science , New York University (2018) M.S., Computer Science , Pontifical Catholic University of Rio de Janeiro (2011) B.S., Computer Science , Federal University of Minas Gerais (2009) Research Interests center on urban visual analytics , 3D analytics , and machine learning for accessibility . His work addresses challenges like sunlight access , sidewalk quality assessment , and commuting flow modeling , often collaborating with urban planners, climate scientists, and occupational therapists. Scientific Recognition includes awards at IEEE VIS , SIBGRAPI , and SIGMOD . His research is funded by NSF , NIH , DOT , and DPI , with media coverage in The New York Times , The Economist , and Architectural Digest . Teaching includes courses like CS 524: Big Data Visualization and Analytics and CS 424: Visualization and Visual Analytics . He emphasizes web-based systems, dataflow frameworks, and interdisciplinary collaboration, with open positions for PhD , MSc , and undergraduate researchers .
Professor Thomas Blumensath is a Professor of Signal and Image Processing at the University of Southampton and a Fellow at the Alan Turing Institute. He is the Academic Lead in Image Processing and Reconstruction at the University's μ-VIS X-ray Imaging Centre and Director of Research at the Institute of Sound and Vibration Research (ISVR). His research focuses on advanced algorithms for solving inverse problems in tomographic imaging, combining machine learning, optimization, and statistical methods. Key areas include X-ray tomography strategies, GPU-accelerated reconstruction, and multimodal imaging applications. Education: B.Sc. (Hons) Music Technology and Audio System Design, University of Derby (2002) PhD in Electronic Engineering (Bayesian Signal Processing), University of London (2006) Research Interests: Professor Blumensath's work spans theoretical and applied signal/image processing, with emphasis on tomographic imaging techniques. His current projects address efficient reconstruction methods, spectral X-ray CT, and applications in manufacturing and plant science. He collaborates with advanced imaging facilities like Diamond Light Source and ISIS neutron imaging beamline. Key Contributions: His research bridges computational methods (e.g., compressed sensing) with practical imaging challenges, including limited-angle tomography and stereo imaging strategies. He leads the National Research Facility for Lab X-ray CT and has developed the TIGRE reconstruction toolbox. Grants & Projects: Active funding includes EPSRC projects on tomographic sensitivity monitoring and CT-based manufacturing inspections. Completed projects cover constrained reconstruction, AM process verification, and industrial CT metrology. Awards: Alan Turing Institute Fellowship Teaching & Leadership: He teaches modules on machine learning, biomedical image processing, and robotics. Leads the BEng Control Engineering program at the Joint Education Institute with Harbin Engineering University. Labs/Teams: Active in the Signal Processing, Audio and Hearing research group (SPAH) and the Institute for Life Sciences. Oversees the μ-VIS X-ray Imaging Centre's research initiatives.
Georgia Zellou is an Associate Professor in the Department of Linguistics at the University of California, Davis, where she co-directs the Phonetics Lab and conducts award-winning research at the intersection of phonetics, speech perception, and human-AI interaction. Her work investigates how phonetic detail is cognitively represented through variations in speech production, with significant contributions to understanding speech alignment with voice assistants, face-masked speech intelligibility, and cross-linguistic perception of synthetic voices. Her academic credentials include a Ph.D. in Linguistics from the University of Colorado at Boulder (2012), an M.A. in Linguistics from Stony Brook University (2007), and a B.A. in Linguistics & Anthropology from the University of Florida (2005, Cum Laude, Phi Beta Kappa). Ph.D., Linguistics, University of Colorado at Boulder (2012) M.A., Linguistics, Stony Brook University (2007) B.A., Linguistics & Anthropology, University of Florida (2005) Professor Zellou's research program centers on laboratory phonology approaches to real-world communication challenges, examining how acoustic-phonetic details influence speech perception across contexts. Her studies span speech alignment with voice-AI systems (e.g., Amazon Alexa), sociophonetic variation in bilingual speech, and the cognitive mechanisms underlying perceptual compensation for coarticulation. She employs experimental methods including eye-tracking, acoustic analysis, and perceptual testing to uncover how phonetic variation functions pragmatically in human communication and human-machine interaction. Analysis of her 15 most recent publications (2023-2025) reveals three dominant research trajectories: (1) human-AI voice interaction dynamics, including prosodic alignment and social evaluation of TTS voices; (2) intelligibility optimization in challenging contexts (face masks, clear speech for diverse listeners); and (3) cross-linguistic phonetic variation in vowelless words and consonant clusters. These works consistently bridge theoretical phonology with applied speech technology, demonstrating how fine-grained phonetic detail influences communication effectiveness in both human-human and human-machine contexts. Her scientific recognition includes: Fulbright Scholar (2022) for research in France Chancellor’s Award for Excellence in Undergraduate Mentoring (2019) Fellow of the Linguistic Society of America (2020) Amazon Faculty Research Award (2019) for Alexa-related speech studies Dean’s Fellow designation at UC Davis (2020-2023) Professor Zellou maintains an active mentoring practice recognized with the Chancellor’s Award, supervising undergraduate researchers in the Phonetics Lab while teaching core linguistics courses from introductory to advanced graduate levels. Her research program is supported by competitive grants including NSF funding, Amazon Research Awards, and UC Davis internal grants (Hellman Foundation, ISS Junior Faculty Grant), reflecting the translational value of her work for speech technology development. She has co-directed major initiatives including the 2019 LSA Linguistic Institute. The Phonetics Lab she co-leads serves as a hub for experimental phonetics research, focusing on speech production-perception relationships through projects investigating vocal accommodation to voice assistants, nasal coarticulation dynamics, and cross-linguistic prosody. Current collaborations with industry partners aim to implement human speech adaptation principles into voice assistant design to enhance naturalness and engagement.
Professor Peter F. Driessen is a faculty member in the Department of Electrical and Computer Engineering at the University of Victoria, with a cross-appointment in the School of Music. He holds a BSc and PhD from the University of Victoria and is a Professional Engineer (PEng). His research focuses on communication systems, signal processing, control, and interdisciplinary projects in computer music and wireless technologies. Key areas include audio/video signal processing, radio propagation, sound recording, and multimedia systems. He leads the University of Victoria Propagation Laboratory, which explores radio wave propagation and Amateur radio integration with engineering education. His work spans theoretical research and applied projects like ECOSat satellite systems, software-defined radio (SDR), and innovative musical instruments such as the Radio Drum. He supervises undergraduate and graduate projects in these domains through ELEC 499 courses. Notable contributions include the APEGBC Editorial Board Award for Best Paper (2002) and patents in wireless networking and signal processing. His teaching includes courses in signal analysis and electromagnetics, and he collaborates on interdisciplinary programs like the Music/Computer Science degree. Education: BSc in Electrical Engineering, University of Victoria PhD in Electrical Engineering, University of Victoria Research Interests: Audio and video signal processing for music and media Software-defined radio and Amateur radio technologies Satellite communication and ground station development Gesture-based interfaces and musical instrument design Error mitigation in streaming audio/video Optical and microwave-photonic systems Labs & Collaborations: Propagation Laboratory (radio wave research) UVic Experimental Radio Group (Amateur radio club) UVic Satellite Design Team (ECOSat projects) UVic Centre for Aerospace Research Grants & Awards: APEGBC Editorial Board Award (2002) Multiple US patents in wireless systems and signal processing
