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Shrikanth (Shri) Narayanan is University Professor and Niki & C. L. Max Nikias Chair in Engineering at the University of Southern California (USC), with appointments spanning Electrical & Computer Engineering, Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, and Otolaryngology-Head & Neck Surgery. He serves as Research Director of the Information Sciences Institute and Director of the Ming Hsieh Institute. PhD in Electrical Engineering (UCLA, 1995) Engineer and MS in Electrical Engineering (UCLA, 1992 and 1990) BE in Electrical Engineering (Anna University, India, 1988) His interdisciplinary research focuses on human-centered signal processing and machine intelligence , addressing societal challenges in health, education, defense, and media arts. Key areas include: Behavioral signal processing Affective computing Multimodal signal processing Computational speech science Biomedical applications Scientific Awards : IEEE James L. Flanagan Speech and Audio Processing Award (2025) Edward J. McCluskey Technical Achievement Award (2024) ISCA Medal for Scientific Achievement (2023) Claude Shannon-Harry Nyquist Technical Achievement Award (2023) ACM ICMI Sustained Accomplishment Award (2020) USC Distinguished Faculty Service Award With over 1,000 publications and 19 patents , his work has been commercialized through startups like Behavioral Signals Technologies and Lyssn . He leads transformative university initiatives and has served in editorial roles for top journals including Computer Speech and Language and IEEE Transactions on Affective Computing .

• Human-centered signal processing
• Machine intelligence
• Affective computing
• +10 more

Sebastian Möller is a Professor at the Faculty for Electrical Engineering and Computer Science at Technical University of Berlin and leads the Speech and Language Technology research department at the German Research Center for Artificial Intelligence (DFKI) since 2017. His work bridges speech technology, natural language processing, and quality engineering, with a focus on usable security, virtual reality applications, and ethical AI. Born in 1968, studied electrical engineering at Ruhr University Bochum, Université d'Orléans, and University of Bologna Doctorate in 1999 from Ruhr University Bochum on speech quality prediction Adjunct Professor at University of Technology Sydney since 2018 His research spans speech signal processing, quality assessment of AI systems, and ethical challenges in medical AI applications. Recent work includes fairness in clinical AI decision-making, audio deepfake detection using self-supervised learning, and collaborative approaches to natural language explanation generation. All three 2025 publications reflect his focus on AI quality assessment and ethical implementation across domains: medical AI fairness, audio deepfake detection, and collaborative explanation frameworks. These works demonstrate expertise in natural language processing, speech technology, and model interpretability. Johann-Philipp-Reis-Prize (2009) Heisenberg Scholarship (2005) Lothar Cremer Prize (2003) VDE ITG Prize (2001) Geers Foundation award (1998) Möller has held leadership roles at TU Berlin including Vice Dean for Research (2015-2017) and Dean (2017-2019). He contributes to international standardization through ITU-T (since 1997) and has served in key positions at DEGA, VDE, and ISCA, including ISCA presidency (2021-2023).

• Speech signal processing
• Speech technology
• Natural language processing
• +5 more

Dr. rer. nat. Thomas Hermann is a faculty member at Bielefeld University's Faculty of Engineering, leading the Ambient Intelligence Group and coordinating the Computer Science program. He specializes in sonification, auditory data science, and smart environments. Head of Ambient Intelligence Working Group Computer Science Program Coordinator Member of multiple academic advisory boards His research focuses on interactive sonification for biomedical applications, quantum systems, and smart environments. Key projects include ECG sonification for cardiac diagnosis, real-time auditory feedback in swimming, and sonic interfaces for AR cooperation. Recent publications span 2025 with Python-based sonification tools ( pya AGen ), quantum system sonification, and ST-elevation myocardial infarction monitoring. He contributes to open-access supplementary materials and interdisciplinary workshops. As a researcher , Hermann develops practical sonification frameworks like Panson for facial behavior analysis, CardioScope for portable ECG monitoring, and Base Cube One for smart environments. His work bridges academic research with industry applications.

• Auditory Data Science
• Interactive Sonification
• Smart Environments
• +5 more

Ana Serrano is an Associate Professor at Universidad de Zaragoza, Spain, where she is affiliated with the Graphics & Imaging Lab in the EINA (Edificio Ada Byron) school. She earned her PhD at the same institution under the supervision of Prof. Diego Gutierrez and Prof. Belen Masia, and completed a postdoctoral fellowship at the Max-Planck-Institute for Informatics under Prof. Karol Myszkowski. Her research focuses on visual computing , particularly in computational imaging , material appearance perception and editing , and virtual reality . She is especially interested in developing perceptually-driven methods that leverage knowledge of the human perceptual system to enhance user experiences and assist content creation in immersive environments. Her recent publications (2023–2025) span top-tier venues such as SIGGRAPH, CVPR, IEEE TVCG, and Eurographics. These works explore topics like saliency prediction in 3D and 360° video, crossmodal perception in VR, gloss modeling, radiance fields, and perceptual evaluation of immersive content. The research demonstrates a strong integration of machine learning, human perception, and computer graphics to solve real-world problems in visual computing. She has received several prestigious awards, including: Eurographics 2023 Young Researcher Award VGTC VR 2024 Significant New Researcher Award Eurographics 2020 PhD Award Adobe Research Fellowship (honorable mention, 2017) NVIDIA Graduate Fellowship (2018) Ana Serrano actively supervises PhD and Master’s students and has taught courses such as Virtual Reality, Computational Imaging, and Deep Learning applications. She serves as an Associate Editor for Computer Graphics Forum , ACM Transactions on Applied Perception , and Computers and Graphics , and has held leadership roles in major conferences including Eurographics (Tutorials co-chair, 2023), ACM SAP (Program co-chair, 2022), and CEIG (Program co-chair, 2022). Her professional service includes extensive program committee and reviewer roles for SIGGRAPH, IEEE VR, ISMAR, and others. She leads a vibrant research group focused on human perception in virtual environments, with current projects on computational models of attention and perception, integrated with physiological signals. Her lab, the Graphics & Imaging Lab, fosters interdisciplinary collaboration and innovation in visual computing.

• Visual Computing
• Computational Imaging
• Material Appearance Perception
• +7 more

Prof. Helen Blank is a Professor leading the Multisensory Perception Group and the Prediction in Communication Lab at the Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf. Her work focuses on understanding how sensory information is integrated and predicted in contexts like speech perception and face recognition. She holds a Marie Curie Fellowship for her research on prior information's role in human communication. Fluent in German, English, and French, she contributes to experimental medicine and systems neuroscience. Her research spans predictive coding, neuroimaging, and clinical applications in Parkinson’s and developmental disorders. Education: Not explicitly stated in text, inferred as advanced degrees in neuroscience or related fields. Her research interests emphasize multisensory integration, predictive processing in speech and vision, and the neural bases of perception. Recent articles explore topics such as pupil responses to auditory surprise, face expectation hierarchies, and audio-visual speech processing. Awards include the Marie Curie Fellowship supporting her predictive communication work. She leads interdisciplinary teams within the Center for Experimental Medicine, advancing knowledge on perceptual mechanisms and their clinical implications.

• Multisensory Perception
• Predictive Processing
• Speech Perception
• +3 more

Prof. Bernhard U. Seeber is an Extraordinary Professor at the Technical University of Munich (TUM), leading the Chair of Audio Signal Processing within the TUM School of Computation, Information and Technology. His work bridges auditory neuroscience and engineering, focusing on improving hearing aids, cochlear implants, and virtual acoustic systems. He holds affiliations with the Bernstein Center for Computational Neuroscience, Munich Institute of Biomedical Engineering, and others. Education: Studied and earned his PhD (2003) in Electrical Engineering and Information Technology at TUM. Postdoctoral research included time at UC Berkeley and the MRC Institute of Hearing Research (UK), where he pioneered studies on binaural hearing and cochlear implant optimization. Research Interests: Combines experimental and theoretical approaches to explore auditory scene analysis, binaural unmasking, and spatial hearing. Key areas include signal coding for cochlear implants, virtual acoustics, and non-destructive acoustic monitoring. His work emphasizes interdisciplinary collaboration with industry and academia. Awards: Lothar Cremer Award (2010), Emmy Noether Fellowship (2007), and recognition from the German Acoustical Society. Teaching: Offers courses on audio communication, computational neuroscience, and technical acoustics. Projects: Leads initiatives like HAPPAA and Auralization, advancing sound field synthesis and hearing aid algorithms. Current Roles: Head of Chair of Audio Signal Processing, Board Member of DEGA, and spokesperson for the ITG Technical Committee on Hearing Acoustics.

• Audio Signal Processing
• Psychoacoustics
• Cochlear Implants
• +5 more

Berit Greinke is an Assistant Professor of Wearable Computing at the Berlin University of the Arts (UdK) and the Einstein Center Digital Future (ECDF) since 2018, previously serving as a researcher at UdK's Design Research Lab and DFKI (2016-2018). Her academic foundation includes a PhD from Queen Mary University of London (2017), an MA from Central St Martins (2009), and a Diploma from Weissensee Academy of Art Berlin (2007). Her educational trajectory: PhD in Media and Arts Technology, Queen Mary University of London (2017) MA in Design for Textile Futures, Central St Martins College of Art and Design (2009) Diploma in Textile and Surface Design, Berlin Weissensee School of Art (2007) Greinke's research pioneers the convergence of craft, textile design, and digital technology, with core expertise in electronic textiles and smart materials. She investigates metamaterial-based 'metatextiles' for electromagnetic applications and explores transdisciplinary collaboration between designers and scientists, particularly regarding 'negative data' in creative and scientific workflows. Her current UdK work focuses on four interconnected domains: performing materials for expressive textile/fashion design; multi-modal sensing converting visual processes into haptic/audible experiences; micro-to-macro material design spanning nanostructures to final products; and transdisciplinary processes for technology-art-science collaboration. Analysis of her 2020-2025 publications reveals dominant trends in sustainable textile electronics, with emphasis on knitted/folded sensor structures, origami-inspired capacitive shape estimation, and social sustainability in e-textile communities. Her work uniquely bridges fundamental material science (e.g., textile metamaterials) with artistic applications (e.g., interactive orchestra garments) and industrial production challenges. Berit Greinke supervises PhD students including Giorgia Petri. Her junior professorship is co-financed by SAP under a public-private partnership model, supporting projects like WEAR (Wearable technologists engage with artists for responsible innovation) and STELEC (Sustainable Textile Electronics), which emphasize ethical co-design and industry-academia collaboration. She leads research within UdK's Institute for Product and Process Design and collaborates with the Design Research Lab (formerly part of Connected Textiles group), focusing on sustainable industrial production of electronic clothing and transdisciplinary innovation frameworks.

• Wearable Computing
• Electronic Textiles (E-Textiles)
• Smart Materials
• +4 more

Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.

• Machine Learning
• Computer Vision
• Signal Processing
• +6 more

Prof. Gabriele Schrag holds the Professorship of Microsensors and Actuators at the Technical University of Munich (TUM), within the TUM School of Computation, Information and Technology. Her research focuses on MEMS (Micro-Electro-Mechanical Systems), including microsensors, actuators, and their applications in acoustics, microfluidics, and bioengineering. She has pioneered work in virtual prototyping for system-level modeling to enhance device robustness and performance. Education: PhD (summa cum laude) from TUM on 'Modeling coupled effects in microsystems' Habilitation in sensor systems technology (2018) Acting head of the Chair of Technical Electrophysics (2018-2023) Research emphasizes acoustic MEMS transducers , electrohydrodynamic printing , and physics-based modeling . Notable projects include developing piezoelectric MEMS microphones with corrugated membranes and integrated micropump systems. Awards include the Bavarian Prize for Good Teaching (2021) and Eurosensors Fellow Award (2019). Her work bridges virtual prototyping with real-world applications , addressing challenges in miniaturization, energy efficiency, and sensor integration for medical and industrial systems.

• MEMS Technology
• Microfluidics
• Acoustic Sensors
• +3 more

Christof Weiß is a Professor for Computational Humanities at the CAIDAS / Institute of Computer Science, Julius-Maximilians-Universität Würzburg (JMU), Germany. He serves as Head of the DFG-funded Emmy Noether group on Computational Analysis of Music Audio Recordings: A Cross-Version Approach. His academic journey includes previous positions as Visiting Researcher at University Télécom Paris (2021), Visiting Lecturer at Karlsruhe University of Music (2020, 2021), and Research Assistant at International Audio Laboratories Erlangen (2015-2022) and Fraunhofer Institute for Digital Media Technology (2012-2015). His educational background encompasses a PhD in Media Technology from University of Technology Ilmenau (2017), Concert Diploma in Composition from Würzburg University of Music (2012), Physics Diploma from University of Würzburg (2012), and Music Diploma in Composition from Würzburg University of Music (2011). This unique combination of technical and artistic training forms the foundation of his interdisciplinary research approach. Weiß's research operates at the critical intersection of computer science and musicology, developing novel computational methods for analyzing musical structures in audio recordings. His work bridges technical audio processing with musicological insights, creating methodologies for tonal analysis, key estimation, and cross-version comparison of musical performances. His approach combines deep learning techniques with music theory to extract meaningful patterns from large music corpora, enabling new forms of musicological corpus studies that were previously impossible. His recent publications reveal a clear research trajectory toward integrating advanced machine learning with fundamental musicological questions. The consistent theme across his work involves analyzing classical music structures through computational lenses, with particular emphasis on cross-version consistency in performances, tonal complexity measurement, and developing datasets that support computational musicology. His publications span both highly technical audio processing journals and musicology-focused venues, demonstrating his commitment to bridging these disciplines. Best paper award at the 4th conference on Computational Humanities Research (CHR), 2023 KlarText award for science communication of the Klaus Tschira Foundation, 2018 2nd prize at Festival Pablo Casals composition competition, Prades (France), 2013 Youth Cultural Advancement Award (Kulturförderpreis) of the city of Amberg, Germany, 2011 As principal investigator of the DFG Emmy Noether group, Weiß leads a multidisciplinary research team investigating computational analysis of music audio recordings through a cross-version approach. His research has secured significant funding including the prestigious Emmy Noether program, supporting doctoral and postdoctoral researchers working on various aspects of music information retrieval and computational humanities. His collaborative network spans institutions across Europe, including University Télécom Paris, Queen Mary University of London, and multiple German research centers. Weiß leads the Computational Humanities research group at CAIDAS, which focuses on developing computational methodologies for music analysis with particular emphasis on classical repertoire. The lab creates specialized datasets (including the Wagner Ring Dataset and Schubert Winterreise Dataset), develops algorithms for structural music analysis, and applies these tools to address musicological questions that require computational scale and precision. Their work bridges the gap between technical audio processing capabilities and humanities research questions, creating new pathways for understanding musical structure and evolution.

• Computational Humanities
• Music Information Retrieval
• Audio Analysis
• +7 more

Marina L. Gavrilova is a Professor at the University of Calgary, Canada. Her research focuses on biometric systems, computer vision, and machine learning with an emphasis on multimodal recognition and security applications. She has authored numerous publications in top journals and conferences, contributing to advancements in fields like emotion-aware de-identification, generative adversarial networks, and ethical AI frameworks in healthcare. Her work spans social behavioral biometrics, gait recognition, masked face recognition, and aesthetic-based person identification. Key contributions include frameworks for ethical AI in care systems, fusion algorithms for multi-biometric systems, and innovations in visual and audio signal processing. Collaborations with experts like Osvaldo Gervasi, Jon G. Rokne, and Padma Polash Paul highlight her interdisciplinary approach. Publications emphasize practical applications such as privacy-preserved biometrics, emotion detection from social media, and adaptive systems for template aging. Despite no explicit mention of grants or labs, her extensive co-author network and frequent citations indicate significant academic influence.

• Biometrics
• Computer Vision
• Machine Learning
• +4 more

Felicitas Kleber is a Professor of Speech Science at the Department of Language Science and Technology, Saarland University. Her research focuses on experimental phonetics and laboratory phonology, emphasizing the interplay between speech production and perception in sound change processes. Research Areas : experimental phonetics, laboratory phonology, coarticulation dynamics, prosody and intonation, diachronic sound change, German dialects. Projects : Directed DFG-funded research on vowel/consonant quantity typology in Southern German varieties (2016–2024); DAAD-funded study on prosodic structure in Hungarian and German (2015–2016). Collaborations : Key partnerships with Jonathan Harrington (phonetics), Ulrich Reubold (acoustic analysis), and interdisciplinary teams in computational linguistics and sociophonetics. She serves as Associate Editor for the Journal of the Acoustical Society of America , integrating cognitive and social dimensions into sound change models.

• Experimental Phonetics
• Laboratory Phonology
• Speech Production and Perception
• +4 more

Prof. Dr. Angelika Braun is a full Professor of Phonetics at the University of Trier since October 2009, with a career spanning forensic phonetics, sociophonetics, and cross-cultural speech analysis. She previously held roles at the Bundeskriminalamt (Wiesbaden/Düsseldorf) and Philipps-Universität Marburg, where she habilitated in Phonetics and Speech Processing (2000). Her work bridges academic research with forensic practice. Research Focus: Her Sociophonetics (language and emotions, gender-specific speech) Forensic Phonetics (speaker identification, voice analysis) Contrastive and Hawaiian Phonetics Speech prosody and toxin effects (smoking, alcohol) Intercultural dubbing studies Academic Contributions: Over 15 recent articles explore voice quality, emotional speech, forensic age estimation, and cross-cultural dubbing effects. Key conferences include Interspeech, International Congress of Phonetic Sciences, and ISCA. Her work appears in journals like Forensic Linguistics and The Phonetician . Scientific Honors: Fellow of the American Academy of Forensic Sciences (AAFS) Founder Member and former Chairperson of the International Association for Forensic Phonetics (IAFP) Life-Member of the International Phonetic Association (IPA) Leadership roles in ISPhS and GAL Practical Impact: Developed the Almeida-Braun Transcription System for dialect analysis and contributed to forensic audio enhancement protocols (e.g., Rodney King case). Serves as reviewer for Language and Speech , Forensic Linguistics , and JIPA . Collaborates on longitudinal studies of vocal aging and speaker identification.

• Sociophonetics
• Forensic Phonetics
• Contrastive Phonetics
• +6 more

Li Wei is a distinguished academic affiliated with Tsinghua University, with a focus on interdisciplinary research spanning artificial intelligence, machine learning, and computer vision. His work often intersects with medical informatics, remote sensing, and signal processing, demonstrating a commitment to advancing technological solutions in healthcare, environmental monitoring, and engineering systems. Research interests include deep learning applications in clinical diagnostics, satellite data analysis for climate modeling, and optimization of energy storage systems. He has contributed to innovative solutions in areas such as UAV-enabled edge computing, privacy-preserving blockchain protocols, and thermal-based surveillance systems. His collaborative projects often involve multidisciplinary teams across institutions. Publications reflect a strong emphasis on practical applications, such as mobile health tools for tumor recognition, transformer-based super-resolution techniques for oceanography, and AI-driven risk classification models for respiratory diseases. While no specific awards or grants are listed, his prolific output across top-tier journals indicates sustained research impact. Professional activities include contributions to conferences like RecSys, MICCAI, and AAAI, and editorial roles are implied through his extensive publication record. Collaborations with industry partners (e.g., in energy systems and medical imaging) suggest engagement with real-world problem-solving.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +3 more

Herbert Buchner is a researcher affiliated with the University of Cambridge in the Information Engineering Division , focusing on Machine Learning for Signal Processing and Human-Machine Interfaces . Research Interests : Acoustic scene analysis, biomedical interfaces, haptic systems, wave-domain adaptive filtering, and sensor networks. Applications : Speech recognition, wavefield synthesis, active noise control, and full-duplex communication systems. His work explores TRINICON (a framework for broadband adaptive MIMO filtering), blind source separation, and wave-domain filtering, emphasizing theoretical rigor and real-time implementation. Key Awards : Best Paper Award at ITG Conference on Speech Communication (2008) Best Student Paper Award at IEEE Intl. Workshop on Acoustic Echo and Noise Control (2001) Publications highlight 15 recent articles in areas like: Wave-Domain Adaptive Filtering Blind Source Separation for Convolutive Mixtures Robust Extended Multidelay Filters Multichannel Acoustic Echo Cancellation Active Room Compensation Biomedical Signal Processing

• Digital Signal Processing
• Acoustics
• Speech Recognition
• +9 more