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Anja Volk is Professor of Music Information Computing at Utrecht University's Faculty of Science , bridging computer science, mathematics, and musicology. With a dual background in mathematics and musicology, she has worked in Germany (1999-2003), the USA (2003-2005), and the Netherlands (2006-present). Her research focuses on music as a fundamental human trait , with applications in music technology for health and wellbeing, particularly through music-driven serious games and inclusivity research . Recipient of NWO-VIDI grant (2010) Awarded Westerdijk Award (2018) and Utrecht University Diversity and Inclusion Award (2020) Co-founder of Transactions of the International Society for Music Information Retrieval (2018) , Women in MIR (WIMIR) mentoring program (2016) , and Society for Mathematics and Computation in Music (2007) Her recent publications cover topics like computational music analysis for therapy, AI-driven education tracks, and music's role in healthcare applications. She actively contributes to interdisciplinary education through workshops and the master's course Sound and Music Technology , leading to collaborations like the AI Song Contest entries and diverse holiday playlist projects featured in NPO Radio 1 .

• Music Information Retrieval (MIR)
• Computational Musicology
• Mathematical Music Theory
• +7 more

Maja Rudling is a Postdoctoral Research Fellow at the Department of Logopedics, Phoniatrics and Audiology at University of Lund. Her primary research focus lies in developmental psychology, autism spectrum disorders, and neurocognitive methods involving eye tracking and pupillometry. She contributes to interdisciplinary research bridging cognition and accessibility in media. Her research interests include: Autism Spectrum Disorder in infants and toddlers Speech and language acquisition mechanisms Event perception in multisensory environments Application of artificial intelligence in neurocognitive studies Recent work explores audio description in films, infant gaze patterns, and comparative assessments of developmental diagnostic tools. She actively participates in collaborative projects and academic presentations, including the AUDEA project (2021–2025) focused on accessible information design. Rudling's methodological expertise spans: Eye-tracking and pupillometry Speech perception analysis Autism diagnostic validity studies Narrative film cognition research

• Developmental Psychology
• Autism Spectrum Disorders
• Cognitive Science
• +7 more

Giuseppina Emma Puglisi is an external lecturer at the Department of Energy (DENERG) of Politecnico di Torino, specializing in interdisciplinary research at the intersection of acoustics, environmental engineering, and medical technologies . Her work focuses on speech intelligibility in complex acoustic environments, particularly for cochlear implant users, and the development of multi-sensor systems for monitoring indoor environmental quality (IEQ) in university and office settings. Research Themes : Classroom acoustics, virtual reality for auditory testing, face mask noise effects, climate-responsive architecture. Leadership : Participated in organizing committees for major acoustics conferences like Forum Acusticum 2023 and serves as Associate Editor for Frontiers in Built Environment . Her recent publications validate virtual reality tools for acoustic assessment and explore cross-linguistic soundscape descriptors. Awards include the Best Paper Award (European Acoustics Association, 2021) and grants for young researchers. She supervises PhD students Virginia Isabella Fissore and Angela Guastamacchia in projects related to IEQ and clinical acoustics.

• Environmental Engineering
• Acoustics
• Speech Intelligibility
• +6 more

Molly Losh serves as the Jo Ann G. and Peter F. Dolle Professor of Learning Disabilities in the Roxelyn and Richard Pepper Department of Communication Sciences and Disorders and Associate Dean for Research at Northwestern University's School of Communication, where she directs the Neurodevelopmental Diversity Lab. Her educational background includes: PhD in Developmental Psychology from UC Berkeley BA in Psychology from San Diego State University Dr. Losh's research centers on autism spectrum disorder (ASD) and related neurodevelopmental conditions, with emphasis on language/communication impairments spanning diagnostic boundaries. Her lab identifies cognitive mechanisms underlying social-communicative differences in autism, bridging observable behaviors and biological underpinnings to advance understanding of etiology. This work employs multi-method approaches including eye-tracking, acoustic analysis, and computational modeling. Analysis of her recent publications (2023-2025) reveals intensifying focus on computational/AI methods for speech analysis, particularly in prosody, pragmatic language, and narrative ability. A consistent theme is examination of the broad autism phenotype in first-degree relatives and FMR1 gene contributions in Fragile X syndrome, with growing cross-cultural and cross-linguistic dimensions. Dr. Losh currently leads three major NIH-funded projects: R01MH091131 (2019-2024): Family-genetic study of autism and Fragile X syndrome examining FMR1 gene roles R01DC010191 (2016-2021): Identification of linguistic markers for autism genetic liability R03DC018644 (2020-2022): Computational analysis of prosody in ASD using machine learning Her Neurodevelopmental Diversity Lab conducts integrated research on visual attention, audio-motor synchronization, and pragmatic language through family studies, with active translation of findings to clinical assessment frameworks.

• Autism Spectrum Disorder
• Neurodevelopmental Disorders
• Language and Communication Disorders
• +4 more

Elena Tenenbaum is an Assistant Professor in Psychiatry and Behavioral Sciences and Psychology and Neuroscience at Duke University, where she is also a Faculty Network Member of the Duke Institute for Brain Sciences . Her research focuses on language acquisition and cognitive development in children with autism spectrum disorder (ASD) , particularly those who are minimally verbal. She employs eye-tracking , EEG , and remote assessment tools to investigate social attention, audio-visual processing, and executive function in ASD. Education: Ph.D. in Psychology from Brown University (2011), Clinical Psychology respecialization at Suffolk University. Her work bridges neuroscience and clinical psychology to understand ASD heterogeneity, with a focus on early intervention and perinatal influences . Recent publications highlight scalable remote methodologies like the RISE Battery for infant cognitive studies and LVIS for assessing communicative competence in low-verbal ASD. She has received grants including the Meeting on Language in Autism (2025-2028) and Shenoy Undergraduate Research Fellowship in Neuroscience (2025-2026). Awards include fellowships and research grants for ASD and developmental disorders. Her lab collaborates on digital phenotyping , audio-visual synchrony , and social attention mechanisms .

• Language Acquisition
• Cognitive Development
• Autism Spectrum Disorder
• +7 more

Cynthia D'Angelo is an Associate Professor in the Department of Educational Psychology at the University of Illinois, Urbana-Champaign. Her research focuses on science education , technology-enhanced learning environments (including simulations, games, and augmented/virtual reality), and collaborative learning . She leverages multimodal data from online technologies to understand STEM concept acquisition and improve instructional practices. NSF-funded PI for $1.5M project on speech analytics in collaborative learning Division Chair of Curriculum, Instruction, and Teacher Education (CSTL) Active in NGSS-aligned curricular development and assessment Her publications demonstrate expertise in learning analytics for both traditional and immersive environments, with key contributions to collaborative problem-solving models and multimodal educational technologies . While known for science education research, her 2022 hybrid law degree program evaluation extended methodological insights to professional graduate education. Current teaching includes EPSY 555 (Advanced Educational Technologies) and CI 542 (Science Education & Philosophy of Science), emphasizing technology integration and data-driven pedagogy . Her work bridges cognitive science and educational design, creating tools that translate classroom dialogue into actionable insights.

• Science Education
• Technology-Enhanced Learning Environments
• Collaborative Learning
• +3 more

Abir De is an Assistant Professor at the Department of Computer Science and Engineering, Indian Institute of Technology Bombay. His research focuses on designing machine learning models for structured objects like graphs and sets, emphasizing data-efficient learning and human-machine collaboration. Academic Rank: Assistant Professor Institution: Indian Institute of Technology Bombay Department: Computer Science and Engineering Research Interests : Differentiable surrogates for combinatorial graph algorithms (e.g., subgraph isomorphism detection) Data-efficient machine learning through strategic subset selection Neural models for submodular set functions Human-in-the-loop machine learning Information diffusion with capacity constraints Scientific Awards : Qualcomm Innovation Fellowship Winner (2022) and Superwinner (2023) Indian National Academy of Engineering Young Engineer Award (2021) Prof. Krithi Ramamritham Award for Creative Research (2020) Google India PhD Fellowship (2013) Advising and Community Contributions : Co-advising PhD students Indradyumna Roy and N Lokesh Program Co-chair of IndoML 2023 Co-organizer of CSE Research Symposium (2023) and SubSetML workshop (2021) Tutorial creator at AIML Systems Conference (2021) and AAAI (2022) Serving on Senior PC at AAAI (2022-2024), PC member at NeurIPS (2016-2023), and ICLR (2018-2023)

• Machine Learning
• Graph Neural Networks
• Data-efficient Learning
• +3 more

Denys J.C. Matthies is an Associate Professor at Technical University of Applied Sciences Lübeck and affiliated with Fraunhofer IMTE Lübeck . He specializes in Human-Computer Interaction , particularly focusing on Wearable Computing , Tactile Feedback Systems , and Activity Recognition through smart footwear and body-worn sensors. Key Collaborations: Augmented Human Lab (NUS), Fraunhofer IGD, City University of Hong Kong Research Themes: Smart wearables, haptic interfaces, physiological sensing, assistive technologies His recent work explores: PhantomFolds (2025) - Spatial tactile feedback via fingernail-mounted LRAs PAVES (2025) - Pneumatic terrain simulation in VR Cyber-Placebo (2024) - Ethical implications of fake-AI in CPHS He has contributed to smart footwear systems like ShoeTect2.0 (2024) and SurfSole (2024), integrating capacitive sensing with neural networks for real-time activity and surface recognition. His work spans medical applications (e.g., 2025 study on hepatic encephalopathy screening) and novel interaction paradigms (e.g., Kavy conversational AI 2024).

• Human-Computer Interaction
• Wearable Computing
• Tactile Interfaces
• +4 more

Vikranth Rao Bejjanki is an Associate Professor of Psychology at Hamilton College. His research focuses on the neural and computational mechanisms underlying human learning, employing methods such as psychophysics, computational modeling, and functional neuroimaging. He is affiliated with the Princeton Neuroscience Institute as a former postdoctoral researcher and maintains memberships in the Society for Neuroscience, Vision Sciences Society, Sigma Xi Scientific Honor Society, and the American Association for the Advancement of Science. Ph.D. in Brain and Cognitive Sciences, University of Rochester M.A. in Brain and Cognitive Sciences, University of Rochester B.A. in Cognitive Science, State University of New York at Buffalo B.S. in Computer Engineering, State University of New York at Buffalo Bejjanki’s research explores how humans learn from experiences through probabilistic inference, cue integration, and neural plasticity. His work bridges experimental psychology with computational models to understand visual perception, spatial localization, and the impact of video game training on cognitive adaptability. He has contributed to journals like Nature Neuroscience , Proceedings of the National Academy of Sciences , and PLoS Computational Biology , often integrating neuroimaging and behavioral analysis to decode learning mechanisms. His publications highlight interdisciplinary themes, merging neuroscience with artificial intelligence, cognitive modeling, and sensory processing. Key trends include the role of noise correlations in brain pattern classification, the development of perceptual templates through video games, and the application of Bayesian inference to spatial tasks. Scientific Awards & Affiliations: Sigma Xi Scientific Honor Society Society for Neuroscience Vision Sciences Society American Association for the Advancement of Science Bejjanki has taught courses such as Fundamentals of Human Neuroscience and Psychology and Neuroscience of Learning , reflecting his expertise in cognitive systems and neural mechanisms of learning. While his student advising record is not explicitly detailed, his collaborative research with institutions like Princeton underscores his commitment to advancing neuroscience through both theoretical and empirical approaches.

• Neuroscience
• Psychology
• Computational Modeling
• +3 more

Dr. Ben Nassi is a faculty member at the Fleischman Faculty of Engineering , Tel Aviv University since 2025 and a Black Hat board member (Asia & Europe) since 2022. He was previously a research fellow at the Technion’s Faculty of Electrical and Computer Engineering, a postdoctoral researcher at Cornell Tech (hosted by Tom Ristenpart), and earned his PhD at Ben-Gurion University of the Negev (supervised by Yuval Elovici). Research Focus: Security of Large Language Model (LLM) applications, side-channel attacks, cryptanalysis via optical signals, and security/privacy of IoT and autonomous systems. Key Contributions: Lamphone (sound recovery from light bulbs), Glowworm attack (speech recovery from power LEDs), Game of Drones (detecting spying drones), Phantom of the ADAS (split-second phantom attacks on autonomous vehicles), and Piping Botnet (IoT smart irrigation system exploitation). Scientific Awards: Pwnie Award for Best Cryptographic Attack (2023) Best Demo Award (AutoSec'21) CSAW'19 and CSAW'20 Runner-up BGU Dean Award for Excellence in Ph.D. (2023) Mid. Way Negev-Faran Scholarship (2023) SIGSAC Doctoral Dissertation Award Nomination (2023) Media Recognition: Work featured in Wired , Forbes , Ars Technica , The Wall Street Journal , MIT Technology Review , and Two Minute Paper , with YouTube videos amassing ~600K views.

• AI Security
• Security of LLM Applications
• Side-channel Attacks
• +6 more

Chris Callison-Burch is a Professor of Computer and Information Science at the University of Pennsylvania , where he leads research in Natural Language Processing , Large Language Models , and Multimodal Learning . Previously, he worked at Johns Hopkins University’s Center for Language and Speech Processing for six years. Research Areas Automated paraphrasing and natural language understanding Machine translation without bilingual parallel corpora Crowdsourcing for NLP and social justice applications Generative AI and vision-language models Recent work focuses on LLM soundness guarantees, multimodal reasoning, AI-generated text detection, and ethical applications of language models. His research has been cited over 25,000 times, and he testified before Congress in 2023 on generative AI and copyright law. Awards & Funding Sloan Research Fellow Faculty awards from Google, Microsoft, Amazon, Facebook, and Roblox Grants from DARPA, IARPA, and NSF He chairs major NLP conferences (ACL 2017, EMNLP 2015) and contributes to editorial boards of TACL and Computational Linguistics .

• Natural Language Processing
• Machine Translation
• Paraphrasing
• +5 more

Dr. Teodora Vuković is a computational linguist at the University of Zurich's Faculty of Arts, specializing in multimodal analysis of human interaction and language technology. As Principal Investigator of the CAPIRE and LCP projects, she leads development of automatic tools for analyzing speech, gestures, and facial expressions to identify person-specific patterns while implementing data anonymization techniques.

• Computational Linguistics
• Multimodal Analysis
• Human-Computer Interaction
• +5 more

Dr. Palina Salanevich is an Assistant Professor at Utrecht University's Mathematical Institute, specializing in Mathematical Modeling. Her work bridges harmonic and time-frequency analysis, geometric functional analysis, signal and image processing, and high dimensional probability theory. Her research focuses on: Geometric properties of random frames and matrices, particularly Gabor frames Phase retrieval problems and their applications in ptychography and speech recognition Machine learning with randomization, especially Random Vector Functional Link networks Data processing using non-negative matrix factorization for audio and EEG signals Harmonic and time-frequency analysis on graphs Dr. Salanevich's recent publications show a strong focus on phase retrieval with Gabor frames, random matrix theory applications in signal processing, and randomized approaches to machine learning. Her work consistently bridges theoretical mathematics with practical signal processing applications, particularly in developing stable and efficient algorithms for complex inverse problems. Her notable scientific achievements include: NWO Veni grant (2021) for "Time-frequency structured measurements in phase retrieval: stability and reconstruction" Board member of the NDNS+ research cluster (2024) Dr. Salanevich actively supervises students, including PhD student Olov Schavemaker (since December 2021), and offers various projects for Bachelor and Master students in areas related to mathematical modeling and signal processing. She has been involved in several collaborative research projects with institutions like CWI and researchers including Deanna Needell, Goetz E. Pfander, and others. She is organizing the "Phase retrieval in mathematics and applications" workshop at the Lorentz Center in August 2024, demonstrating her leadership in her research community.

• Signal Processing
• Data Analysis
• Graphs
• +9 more

Prof. Biing-Hwang Fred Juang is the Motorola Foundation Chair Professor and a Georgia Research Alliance Eminent Scholar at Georgia Institute of Technology. He has held honorary positions at multiple universities and has an extensive background in speech processing and signal modeling. Ph.D., University of California, Santa Barbara Former Director of Acoustics and Speech Research at Bell Labs (1996-2001) Contributions include vector quantization, robust vocoders, and discriminative methods in machine learning Research Interests: His work spans speech recognition, data compression, secure communication, and deep learning. He pioneered accretionary learning methods that emulate human cognition in neural networks. Scientific Awards: IEEE Signal Processing Society Technical Achievement Award (1998) IEEE Third Millennium Medal (2000) IEEE Fellow (1991), Bell Labs Fellow (1999) Member of the US National Academy of Engineering (2004) Charter Fellow of the National Academy of Inventors (2014) IEEE Field Award in Audio, Speech and Acoustics (2014) Publications & Patents: Co-authored the seminal book "Fundamentals of Speech Recognition" with L.R. Rabiner and holds about two dozen patents.

• Speech Recognition
• Signal Processing
• Machine Learning
• +5 more

Camilla Bernardasci serves as an Academic Associate at the Phonogram Archive within the Institute of Phonetics and Speech Processing, Faculty of Arts and Social Sciences, University of Zurich. Her work centers on preserving and analyzing historical audio recordings with global linguistic and cultural significance. Her research expertise includes: Phonetics Speech Sciences Language Documentation Historical Recordings Acoustic Analysis Linguistic Anthropology Contact details: Room KOL-H318a at Rämistrasse 71, Zurich; Phone +41(0)44 634 39 76. The Phonogram Archive functions as a critical hub for endangered language preservation and cross-cultural audio heritage studies, though no specific projects or collaborations are detailed in the source text.

• Phonetics
• Speech Sciences
• Language Documentation
• +3 more