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Vidhyasaharan SethuView profile

Associate Professor

• Speech Signal Processing
• Machine Learning
• Emotion Recognition
• +3 more

Vidhyasaharan Sethu is an Associate Professor at the School of Electrical Engineering and Telecommunications, UNSW Sydney. His educational background includes a PhD from UNSW, a Master of Engineering Science in Signal Processing from UNSW, and a Bachelor of Engineering in Electronics and Communication Engineering from Anna University. His research focuses on speech signal processing with emphasis on machine learning applications. Primary interests include: Speech-based emotion and mental state recognition systems Affective computing and voice biometrics Integration of machine learning with signal processing Uncertainty quantification in speech systems Adaptive audio front-ends and acoustic modeling Recent publications (2021-2025) demonstrate strong focus on: Ambiguity-aware emotion recognition using advanced ML techniques Speaker verification and biometric security systems Novel acoustic modeling frameworks Applications of large language models in speech processing Cross-disciplinary work in materials science via ML approaches Research Funding: ARC Discovery Projects (2020, 2019) ARC LIEF Grant (2019) UNSW Research Infrastructure grants (2018-2019) Huawei Innovation Research Program (2018) ARC Linkage (2017) NICTA International Postgraduate Award (2006-2009) Teaching includes courses in: Data Science for Electrical Engineers (ELEC9741) Speech Processing (ELEC9723) Digital Signal Processing (ELEC3104) Electrical Systems Design (ELEC2117)

• Acoustics and noise control
• Dynamics, vibration and vibration control
• Signal processing
• +3 more

Dr. Sipei Zhao is a Senior Lecturer at the School of Mechanical and Mechatronic Engineering at the University of Technology Sydney (UTS), where he has been employed since January 2021. Prior to this, he worked as a Post-doctoral Research Fellow at the Centre for Audio, Acoustics and Vibration of UTS from July 2018 to December 2020. His educational background includes a PhD in Electrical Engineering from RMIT University (2018), a Master's degree in Acoustics from Nanjing University (2015), and a Bachelor's degree in Electronics Engineering from Nanjing University (2012). Dr. Zhao's research focuses on acoustics and noise control, dynamics and vibration control, and signal processing. His work spans theoretical development and practical applications in active noise control, architectural acoustics, and machine learning for acoustic analysis. He has made significant contributions to distributed acoustic systems, neural network applications in sound field reconstruction, and innovative approaches to sound zone control. His recent publications demonstrate a strong trajectory in distributed acoustic systems, neural network applications in acoustics, and innovative approaches to sound field control and reproduction. His work combines theoretical rigor with practical implementations, often resulting in significant reductions in computational complexity while maintaining or improving performance. Best Student Paper at the 22nd International Congress on Sound and Vibration (ICSV22) in 2015 Best Paper Prize at the 21st International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRA2016) in 2016 Best Paper Award at the 23rd International Congress on Acoustics (ICA2019) in 2019 Young Professionals Grant from the International Institute of Noise Control Engineering (I-INCE) Ford Publication Commendation Prize from RMIT University in 2017 ARC Early Career Industry Fellowship in 2024 Dr. Zhao has successfully secured multiple research grants and contracts from organizations including the Australian Research Council, NSW Environment Protection Authority, and industry partners like Noizend Pty Ltd. His research has practical applications in industrial settings, transportation, and building acoustics. He serves as a peer reviewer for prestigious journals including the Journal of Sound and Vibration and IEEE/ACM Transactions on Audio, Speech, and Language Processing.

Vikram KaushalView profile

Senior Lecturer

• Live Performance
• Interactive Media Design
• Biofeedback Systems
• +5 more

Vikram Kaushal is a Senior Lecturer at the Manchester School of Architecture, focusing on the intersection of live performance, interactive media design, and biofeedback-driven environments. His work explores collective experiences through technology and spatial innovation. Academic Rank: Senior Lecturer University: Manchester Metropolitan University School: Manchester School of Architecture His research examines how performance, space, and technology foster community connection. Projects include immersive installations utilizing dynamic video, biofeedback, and real-time systems, often hosted in unconventional venues like disused buildings and railway arches. Key themes include British cybernetics, urban regeneration, and deconstructing cultural consumption models. Recent works such as 'Repercussion' (2025) and 'HomoBloc Festival' (2024) highlight his engagement with responsive environments and participatory art. Earlier outputs like 'Verfasst' (2017) and 'Manchester Urban Pioneers' (2015) emphasize biometric data integration and post-industrial urban strategies. Scientific Awards Shortlisted for the Colvin Prize (2025) Second Place in 'Murder Children During the Bombing' Competition (2021) Kaushal's collaborative consultancy, Logan & Wilcox, extends his practice into community arts and cultural projects. He frequently participates in international exhibitions, residencies, and academic conferences.

Mazdak ZamaniView profile

Associate Professor

• Cybersecurity
• Artificial Intelligence
• Digital Watermarking
• +5 more

Dr. Mazdak Zamani is an Associate Professor of Cybersecurity and Associate Dean of Computer Science and Cybersecurity at Felician University , NJ. He earned his PhD in Computer Science from Universiti Teknologi Malaysia in 2011. His research focuses on Cybersecurity and Artificial Intelligence , with publications spanning video watermarking , IoT authentication , mobile cloud security , and digital forensics . His recent work addresses heterogeneous device authentication and optimized steganography for secure data transmission. 2019 : Video watermarking performance evaluation, data mining for energy systems 2018 : LSB image steganalysis, spatial domain watermarking 2017 : Botnet forensics, illumination normalization for face recognition 2016 : Mobile cloud authentication, image/video watermarking techniques At Felician, he teaches Network Security , Digital Forensics , and Advanced Cryptography . Previously, he served as a Senior Lecturer at Universiti Teknologi Malaysia and as an Assistant Professor at Wenzhou-Kean University .

Michael MossView profile

Assistant Professor

• Music Production
• Audio Engineering
• MIDI Technology
• +7 more

Michael Moss is an Assistant Professor in the Department of Electronic Production and Design (EPD) at Berklee College of Music. He holds advanced degrees in Jazz Performance from the New England Conservatory of Music and brings decades of professional experience in music production, performance, and sound design for education, advertising, and media. Master of Music, Jazz Performance – New England Conservatory (1984) Bachelor of Music, Jazz Performance – New England Conservatory (1981) His research and creative interests span music technology, audio engineering, MIDI, sound design for educational and industrial applications, audiobook scoring, and jazz performance . He emphasizes real-world skills in his teaching, drawing directly from his work at Soundscape Productions, his studio in Boston. His creative output includes over 130 audiobook scores, work for major clients like Coca-Cola, Gillette, Warner Bros., and National Public Radio, and performances with legends such as Aretha Franklin and Cab Calloway. His work blends technical precision with artistic expression. Notable honors include: Audie Award Oppenheim Platinum Certificate Three Grammy Award nominations Moss actively mentors students, often hiring Berklee graduates into his studio. He runs an associate engineer program each summer, integrating students into professional workflows. He has secured contracts and grants through client work with major publishers and corporations, though specific grant titles are not listed. He is the founder and owner of Soundscape Productions , a Boston-based studio serving education, medical, and technology sectors. The studio functions as both a creative hub and a training ground for emerging audio engineers.

Steven FentonView profile

Senior Lecturer

• Low Power Systems
• Health Innovation
• Remote Health/Wound Monitoring
• +6 more

Steven Fenton is a Senior Lecturer and Subject Area Leader in Engineering at the Department of Engineering & Technology, School of Computing and Engineering, University of Huddersfield. He holds a 1st Class Honours degree in Electronic & Information Engineering from the University of Huddersfield and has extensive industry experience in audio engineering, DSP, and embedded systems design. Current research focuses on low power systems, remote health monitoring, audio signal processing, and immersive audio technology. Active member of the Audio Engineering Society and Centre for Audio and Psychoacoustic Engineering. His work spans audio quality measurement , dynamic range optimization , and assistive technologies for the visually impaired. Recent publications highlight innovations in immersive audio mixing and ultra-low energy distributed monitoring systems. Scientific contributions include a Fellow of the Higher Education Academy and an h-index of 67. Available for PhD supervision in engineering and audio technology domains.

• Spatial Audio
• Psychoacoustics
• Binaural Audio Reproduction
• +7 more

Florian Klein is a Postdoctoral Researcher and Research Assistant at the Electronic Media Technology Group within the Department of Electrical Engineering and Information Technology at Technische Universität Ilmenau. He holds a Dr.-Ing. degree from 2021 and conducts research in spatial audio, binaural synthesis, and auditory perception. Research Interests: His work focuses on psychoacoustics, auditory adaptation, room acoustics, and augmented reality audio. He investigates how listeners perceive and adapt to spatial audio cues, particularly in binaural reproduction systems. His research includes perceptual experiments on externalization, localization, auditory memory, and the impact of room acoustics on virtual auditory experiences. The analysis of his recent publications reveals a strong trend toward understanding perceptual thresholds and memory in spatial audio contexts, with increasing focus on augmented and virtual reality applications. Key themes include just-noticeable differences in reverberation, robust room acoustics estimation, and the creation of open datasets for spatial audio research. Scientific Contributions: Developed methodologies for robust reverberation time estimation in non-ideal conditions. Conducted perceptual studies on auditory memory and room identification. Created and published open datasets (R3VIVAL, SRIR collections) for spatial audio research. Explored perceptual matching of room acoustics for auditory augmented reality. Advising and Grants: While no specific students or grants are mentioned in the provided text, his active publication record and leadership in dataset creation suggest involvement in research projects and potential mentoring of junior researchers. His work is likely supported by institutional or project-based funding related to audio engineering and perception research. Labs and Teams: He is a core member of the Electronic Media Technology Group at TU Ilmenau, working on advanced audio systems and perceptual evaluation. His research utilizes specialized facilities for measuring spatial room impulse responses, including mobile robotic platforms and variable acoustics laboratories.

Sourya RoyView profile

Assistant Professor

• Theoretical Computer Science
• Pseudorandomness
• Coding Theory
• +4 more

Sourya Roy is an Assistant Professor in the Department of Computer Science at the University of Iowa. Prior to his academic career, he worked as a Data Scientist at Foursquare. He earned his PhD in Computer Science from the University of California, Riverside in 2022, advised by Silas Richelson and Amey Bhangale. Education: PhD in Computer Science (University of California, Riverside, 2022) His research spans theoretical and applied domains, focusing on pseudorandomness, coding theory, and cryptography in theoretical computer science, while also contributing to computer vision and machine learning applications. Recent publications emphasize expander graph theory, coding algorithms, and spatio-temporal modeling. Dr. Roy is actively seeking PhD students to collaborate on theoretical computer science projects. His publications highlight expertise in pseudorandomness, expander graphs, and scalable unsupervised learning techniques. Key conferences include FOCS, ECCV, and IEEE Transactions on Information Theory.

Thom CorahView profile

Senior Lecturer

• Mobile Technology
• Interactive Audio
• Binaural Audio
• +7 more

Thom Corah is a Senior Lecturer at De Montfort University, affiliated with the Leicester Media School within the Faculty of Computing, Engineering and Media. He teaches undergraduate and postgraduate courses in web development, multimedia, and audio production, and serves as programme leader for the BSc Audio and Recording Technology. His research focuses on innovative uses of mobile technology and intuitive interaction methods, particularly through binaural audio delivered via smartphones. Previous work has explored mobile applications in cultural heritage contexts. Key research areas include: Interactive audio displays Binaural and spatial sound Mobile user experience Digital media in heritage Audio-visual integration Technology-enhanced learning The absence of listed publications suggests limited public scholarly output or incomplete data; however, his ongoing PhD indicates active research engagement. Thom supervises independent study projects at MA/MSc and BA levels within music technology and media studies. He has not been mentioned as receiving any scientific awards. He is based at De Montfort University's campus in Leicester, UK, and can be contacted at tcorah@dmu.ac.uk .

• Multisensory Perception
• Physiological Computing
• Neurofeedback
• +5 more

Aleksander Väljamäe is an Associate Professor in Physiological Computing at Tallinn University's School of Digital Technologies (HCI group) and a Grant Consultant at Tartu University. His research focuses on multisensory perception, physiological computing, and neurofeedback applications in brain disorders, BCI, and neurocinema. He has held postdoctoral roles at institutions like Pompeu Fabra University and Graz University, and was a Marie Skłodowska-Curie Fellow (2013–2015). He actively participates in EU projects (e.g., Future BNCI) and art-science collaborations, such as the Multimodal Brain Orchestra. His administrative roles include chairing Tallinn University’s internal research committee and advising for the European Commission and Italian Ministry of Health. Education: PhD in Applied Acoustics (Chalmers University, 2007) M.Sc. in Digital Communication (Chalmers, 2003) BSc in Radio Engineering (Tallinn University of Technology, 2000) Research Interests: Developing novel methods for diagnosing brain disorders (e.g., depression, migraine) using audiovisual media and BCI. Explores wearable technologies, affective computing, and the psychophysiology of emotion. Recent projects include SoniWeight Shoes (2024) and Magic Lining (2019), which investigate body-perception modulation via wearable devices. Grants & Awards: Marie Skłodowska-Curie International Outgoing Fellowship (2013–2015). Active in EU-funded initiatives like POEMS and BrainAble. Labs/Teams: Leads the HCI group at Tallinn University, collaborating with institutions globally. Co-developed the eXperience Induction Machine for mixed-reality interaction studies.

Flemming ChristensenView profile

Associate Professor

• Acoustics
• Audio Engineering
• Binaural Synthesis
• +6 more

Flemming Christensen is an Associate Professor in the Department of Electronic Systems at Aalborg University, part of The Technical Faculty of IT and Design. His research focuses on acoustics, audio engineering, and binaural systems, with strong contributions to sound zone control, spatial audio, and headphone technology. He has led or participated in projects addressing noise measurement in ships, 3D audio systems for vehicle safety, and age-related ear growth acoustics. Research interests include binaural synthesis, dynamic sound environments, and the application of virtual reality in acoustic evaluation. He has authored over 60 publications, including works on real-time room auralization and perceptual evaluation of audio systems. His work bridges theoretical acoustics with practical applications in automotive safety, headphone design, and environmental noise management. Notable projects include the development of a low-frequency noise measurement device and investigations into head movements' impact on binaural synthesis. He actively contributes to academic events, such as organizing conferences and participating in workshops on acoustics and virtual reality. Christensen’s research also explores the intersection of audio technology and human perception, with studies on loudspeaker design, sound localization, and user experience with audio devices. His work emphasizes interdisciplinary collaboration, integrating engineering principles with psychoacoustic insights.

Huacheng ZengView profile

Associate Professor

• Computer Networking
• Wireless Communication Systems
• Sensing Technologies
• +3 more

Huacheng Zeng is an Associate Professor in the Department of Computer Science and Engineering (CSE) at Michigan State University (MSU), part of the College of Engineering. His research focuses on computer networking, wireless communication systems, and sensing technologies with applications in IoT security, signal processing, and machine learning. He received his Ph.D. in Computer Engineering from Virginia Tech in 2015 and was awarded the NSF CAREER Award in 2019. Dr. Zeng’s work spans innovative areas such as radar-based human motion tracking (e.g., RadEye), acoustic emotion decoding, and mmWave network optimization. His recent publications address challenges in device localization, vehicular communication, and secure RFID systems. His research often integrates machine learning techniques with traditional signal processing to enhance system performance and security. Education: Ph.D., Computer Engineering, Virginia Tech (2015) Awards: NSF CAREER Award (2019) His contributions to interference management, jamming-resilient communications, and distributed inference frameworks have advanced both theoretical and applied aspects of wireless networks. While no specific grants or advising details are listed, his extensive publication record reflects active collaboration in cutting-edge research domains.

Matias HomarView profile

Visiting Assistant Professor

• Sound Art
• Music Technology
• Audio Engineering
• +3 more

Matias Homar serves as Visiting Assistant Professor of Music-Sound Studio at Alfred University's School of Art & Design. A member of the faculty in the Miller Building, he contributes to creative and technical education in sound arts through his expertise in audio production and digital sound design. Research Interests: His work focuses on the intersection of music technology and interactive media, exploring applications in sound installation, spatial audio, and experimental composition techniques within contemporary art frameworks. Contact: Email: homar@alfred.edu Phone: 607-871-2568

Aidan SlingsbyView profile

Senior Lecturer

• Data Visualization
• Geographic Information Systems (GIS)
• Spatial Analysis
• +5 more

Dr. Aidan Slingsby is a Senior Lecturer in the Department of Computer Science at City, University of London, where he is part of the giCentre Research Centre. He serves as the Director of the MSc in Data Science programme and oversees the department's entire postgraduate offerings. His academic career at City spans over a decade, progressing from Research Fellow to his current position as Senior Lecturer since 2018. His educational background includes: PhD in Geography from University College London (2006) MSc in Geographical Information Science from University of Edinburgh (2002) BSc (Hons) in Geology from University of Edinburgh (2001) Dr. Slingsby's research focuses on data visualization for spatial and temporal data analysis. His work involves creating, designing, applying and evaluating both static and interactive information visualization techniques for data exploration and analysis. He specializes in integrating cartographic principles with information visualization methodologies to address complex analytical challenges. His research spans multiple application domains including insurance risk modeling, population studies, human movement patterns, animal tracking, and ecological monitoring. He has developed innovative visualization techniques such as glyphmaps, tilemaps, and OD maps that enable analysts to explore complex multivariate spatial datasets effectively. His publication record demonstrates a consistent focus on advancing visualization techniques for spatial-temporal data, with recent work exploring intersections with emerging technologies like large language models and advanced train delay modeling. His research shows a clear trajectory from foundational work in cartographic visualization to increasingly sophisticated applications in domains ranging from pandemic modeling to rail performance analysis. Notable scientific achievements include: Best VIS Short Paper award for 'Gridded Glyphmaps for Supporting Spatial COVID-19 Modelling' at IEEE VIS conference Multiple honorable mentions for visualization innovations Efficient Use of Visualization award for network monitoring visualization Dr. Slingsby has successfully supervised multiple PhD students to completion and currently mentors several doctoral candidates working on cutting-edge visualization research. He has secured funding for significant projects including an EPSRC-funded multi-university initiative on visual analytics for combating COVID-19 and industry collaborations with Risk Solutions on rail performance modeling. His professional service includes editorial roles with IEEE VIS and GIS Research UK, demonstrating his standing in the visualization research community. As part of the giCentre Research Centre, he contributes to a vibrant research environment focused on geographic information and visualization. His work bridges theoretical visualization research with practical applications across multiple domains, maintaining strong connections with both academic collaborators and industry partners including Leicestershire County Council and the Willis Research Network.

Anna KrauseView profile

Researcher

• Machine Learning
• Deep Learning
• Time Series Analysis
• +7 more

Dr.-Ing. Anna Krause is a researcher at the Chair of Data Science (Informatik X) within the Faculty of Mathematics and Computer Science at the University of Würzburg. She leads the Deep Learning for Dynamical Systems Group and has been actively involved in teaching at the university since 2019, including courses on Machine Learning for Time Series Analysis and Data Mining. Doctoral degree in Electrical Engineering (2019), University of Hannover Diploma in Electrical Engineering (2009), Technical University Dresden Her research focuses on Environmental Sensing and Time Series Analysis , particularly on enhancing physics-based models using machine learning techniques for meteorological applications and sparse sensor networks. She has made significant contributions to explainable AI, climate modeling, and fraud detection systems. Anna's recent publications demonstrate expertise in climate modeling (ConvMOS, ICLR 2024-2025), physics-informed neural networks (TaylorPDENet, ECMLPKDD 2023), and fraud detection (MIDAS workshops, ECMLPKDD 2020-2023). She actively contributes to conferences as organizer and PC member, including ECMLPKDD and ICLR workshops. Scientific Awards Best ML Innovation Award (2020) for Deep Learning in Climate Modeling Best Student Paper Award (2020) for Multi-Task Land Use Regression Best Paper Award (2020) for Financial Fraud Detection with INALU The DynaBench dataset introduced in 2023 provides benchmark tools for learning dynamical systems from low-resolution data. Her work combines theoretical advancements with practical implementations, including edge computing applications for beekeeping monitoring systems.