Find Academic Supervisors

• Signal Processing
• Biomedical Engineering
• Machine Learning
• +2 more

Alireza Malekmohammadi is a doctoral student and researcher at the Technical University of Munich's Department of Electrical and Computer Engineering, affiliated with the Institute for Cognitive Systems. He holds a BSc in Electrical Engineering from Shahid Beheshti University (2013) and an MSc in Digital Electronics Engineering from Sharif University of Technology (2015). His research focuses on signal processing (EEG, LFP, MEG), machine learning applications for brain-computer interfaces, and decoding neural responses to auditory stimuli. Key areas include: Brain-sound computer interfaces Hardware implementation of biomedical algorithms Neural correlates of music perception Recent publications explore musical familiarization effects on brain connectivity patterns and oscillatory dynamics, employing advanced EEG analysis techniques. Research demonstrates consistent focus on neuromodulation during auditory processing across multiple frequency bands. He contributes to teaching in biosignal processing courses and mentors students in practical neural signal analysis.

• Quantum Optics
• Photonics
• Quantum Gases
• +3 more

Dr. Julian Schmitt is a researcher at the University of Bonn, affiliated with the Institute of Applied Physics within the Faculty of Mathematics and Natural Sciences. His work focuses on experimental quantum many-body physics, particularly exploring quantum gases of light and matter. He investigates fundamental questions in topological physics, condensed matter systems, and quantum communication technologies. Key achievements include the landmark observation of Bose-Einstein condensation of photons and contributions to understanding topological BKT superfluidity. Research interests span quantum optics, photonics, thermodynamics, and the realization of novel quantum states such as room-temperature superfluidity and topological edge states. His studies employ advanced experimental techniques to probe nonlinear dynamics, thermalization processes, and phase transitions in photon-based systems. Recent work highlights include dimensional crossover phenomena in quantum gases, non-Hermitian phase transitions, and the emergence of isotropy in two-dimensional wave turbulence. These findings advance foundational understanding of quantum systems while offering applications in robust quantum technologies. Dr. Schmitt collaborates internationally and has published extensively in top journals such as Science , Nature , and Physical Review Letters . His research bridges theoretical predictions with experimental validation, driving progress in quantum science and engineering.

Nils PetersView profile

Assistant Professor

• Audio Signal Processing
• Spatial Audio
• Machine Learning
• +5 more

Dr. Nils Peters is an Assistant Professor in Electronic & Electrical Engineering at Trinity College Dublin (TCD). He specializes in audio signal processing, spatial audio, and machine learning applications in acoustics. Previously, he held roles at Qualcomm and the International Audio Laboratories Erlangen (Fraunhofer IIS/FAU). His research spans psychoacoustics, XR technologies, and accessibility in audio systems. Education: PhD in Music Technology, McGill University (Canada) Postdoctoral work at UC Berkeley MSc in Electrical and Audio Engineering, Graz University of Technology (Austria) Research Interests: Dr. Peters focuses on bridging audio engineering with human perception. Key areas include spatial audio rendering, emotion preservation in anonymized speech, and acoustic localization systems. His work integrates machine learning for audio signal analysis and IoT applications in sound environments. Recognition: 2023 Best Paper Award at IS2 (Internet of Sounds) 2023 Teaching Excellence Award (FAU) Multiple Qualcomm Qualstar Diamond Awards (2015-2020) Advising & Leadership: Serves as AES Co-Chair for Spatial Audio and steering board member of IEEE's Internet of Sounds Initiative. Advises on audio engineering projects and lab courses at TCD. Labs & Teams: Collaborates with Qualcomm, Fraunhofer IIS, and UC Berkeley teams. Active in interdisciplinary projects involving 3D audio, XR, and accessibility technologies.

Pablo RipollésView profile

Assistant Professor

• Neuroscience of Music
• Cognitive Neuroscience
• Auditory-Motor Integration
• +3 more

Pablo Ripollés is an Assistant Professor of Psychology and Associate Director of the Music and Audio Research Laboratory (MARL) at New York University. He holds a joint appointment in the Department of Psychology and MARL, focusing on the intersection of music, reward, memory, and language learning. His research explores how intrinsic reward mechanisms influence cognitive processes like word learning and how music interacts with brain plasticity and reward systems. Education: B.Sc. in Computer Engineering and Telecommunications (University of València, 2009), M.Sc. in Biomedical Engineering (University of Navarra, 2010), Ph.D. in Biomedicine with a focus on Neuroscience (University of Barcelona, 2016). He completed a postdoctoral fellowship in David Poeppel's Lab at NYU (2017–2020). Research Interests: Neuroscientific basis of music perception, reward-driven learning, auditory-motor synchronization, and applications of music in neurorehabilitation. His work combines neuroimaging (fMRI, EEG) with behavioral studies to understand how dopamine signaling and memory systems shape cognitive functions. Key Contributions: Demonstrated the role of subcortical reward regions in word learning (Current Biology, 2014); pioneered music-based therapies for stroke recovery (Brain Imaging Behavior, 2016); investigated dopamine's role in musical reward (PNAS, 2019); and explored intrinsic reward's impact on adolescent language acquisition (Developmental Science, 2024). Awards: Formación Profesorado Universitario (FPU) fellowship, La Caixa Foundation Postgraduate Scholarship. Labs: Leads the Ripolles Lab within the Center for Language Music and Emotion, collaborating with NYU's MARL and Poeppel Lab. Active in developing tools like CHILLER for real-time emotional response tracking.

Stefano FascianiView profile

Associate Professor

• Sound and Music Computing
• Machine Learning
• Musical Interfaces
• +5 more

Stefano Fasciani is Associate Professor in the Department of Musicology at the University of Oslo's Faculty of Humanities, leading research in sound computing and interactive music systems. As Head of Creative Computing Oslo Hub and Director of the Music, Communication and Technology Master's program, he develops novel approaches to digital instrument design. Education includes: Ph.D. Integrative Sciences and Engineering, National University of Singapore (2014) M.Sc. Electronic Engineering, University of Rome Tor Vergata (2006) B.Sc. Electronic Engineering, University of Rome Tor Vergata (2003) Research integrates signal processing, machine learning, and embedded systems to create responsive musical interfaces and synthesis architectures. Current projects include neural modeling of acoustic instruments, optical sensor-based controllers, and multi-agent music systems. Manages the Nordic Sound and Music Computing network and Self-playing Guitars project. Secured funding from EU Erasmus+ and NordForsk for international collaborations in creative technologies. Supervises 15+ graduate students in projects spanning hardware design, evolutionary sound systems, and AI-driven composition tools. Teaching includes Music and Machine Learning, Interactive Music Systems, and Sound Programming courses.

Cagri ErdemView profile

Research Fellow

• Human-Computer Interaction
• Music Technology
• Machine Learning
• +3 more

Çağrı Erdem is a Postdoctoral Fellow at the University of Oslo's Department of Informatics, exploring human-AI co-performance through embodied interaction and machine learning. Research focuses on: Shared control systems in musical performance Biosignal interfaces for artistic expression Machine learning for motion-sound relationships Multimodal interaction design His publications examine interactive instruments, AI improvisation systems, and cross-modal perception. Current projects include self-playing guitars and Nordic Sound and Music Computing initiatives. Teaching includes courses on interactive music, sound programming, and machine learning applications in creative computing.

Tomas ÖsterlindView profile

Assistant Professor

• Manufacturing Engineering
• Machining Systems
• Mechanical Engineering
• +4 more

Tomas Österlind is an Assistant Professor of Machining Systems at KTH Royal Institute of Technology, affiliated with the School of Industrial Engineering and Management (ITM) and the Industrial Innovation Platform (IIP). He serves as Co-Director of the Centre for Design and Management of Manufacturing Systems at KTH and the International Grinding Center at Chalmers IGC. He also participates in the Working Group for Digitalized Industry and is part of the Digital Futures Faculty. His research focuses on advanced manufacturing technologies, including machining dynamics, surface quality prediction, and digital signal processing for process optimization. He co-founded the Digital Futures research center, which explores digital technologies to address global challenges, collaborating with Stockholm University and RISE Research Institutes of Sweden. His work integrates mechanical engineering, mechatronics, and materials science to enhance manufacturing system capabilities and quality outcomes. The research centers he leads aim to bridge academia and industry through innovations in grinding, robotics, and smart manufacturing. Key research themes include vibration analysis in machining processes, tool steel performance optimization, and the development of damping solutions to suppress chatter. His contributions advance both theoretical understanding and practical applications in precision manufacturing and industrial digitalization. Though no specific scientific awards are listed, his leadership roles and publications indicate significant contributions to manufacturing engineering. Collaborations in Digital Futures and his involvement in cross-disciplinary initiatives highlight a focus on applied research with high industrial relevance.

Andrea CavallaroView profile

Professor

• Machine Learning
• Computer Vision
• Audio Processing
• +4 more

Andrea Cavallaro is a Full Professor and Director of the Centre for Intelligent Sensing at Queen Mary University of London (QMUL), a Russell Group university. He also serves as Editor-in-Chief of Signal Processing: Image Communication and a Fellow of the International Association for Pattern Recognition (IAPR) and the Higher Education Academy. His roles include Director of Research for the School of Electronic Engineering and Computer Science. Education: Received a Ph.D. in Electrical Engineering from the École polytechnique fédérale de Lausanne (EPFL) in 2002. Prior roles include Research Fellow at British Telecommunications (BT) and multiple editorial roles across IEEE journals. Research Interests: Focus on machine learning for multimodal perception, computer vision, audio processing, robot perception, and privacy in multimedia systems. He leads projects like CORSMAL (Collaborative Object Recognition, Shared Manipulation, and Learning) and GraphNEx (Graph Neural Networks for Explainable AI). Notable Contributions: Over 270 journal/conference papers, one monograph on video tracking (Wiley, 2011), and three edited books. Awards include the Royal Academy of Engineering Teaching Prize (2007), IEEE AVSS Best Paper Award (2009), and Turing Fellowship (2018). Labs & Affiliations: Leads the Centre for Intelligent Sensing and contributes to the Centre for Multimodal AI. Active in IEEE technical committees and international research collaborations.

Aidan HoggView profile

Lecturer

• Spatial Acoustics
• Immersive Audio
• Deep Learning
• +3 more

Aidan Hogg is a Lecturer in Computer Science at Queen Mary University of London (QMUL), affiliated with the Centre for Digital Music (C4DM) and the School of Electronic Engineering and Computer Science. He holds a PhD and is an Honorary Research Associate at Imperial College London. His research focuses on deep learning applications for spatial acoustics, immersive audio, and statistical signal processing in audio systems. Key interests include HRTF upsampling, speaker diarization, and binaural audio technologies. He holds qualifications including PhD, DIC, MEng, ACGI, and AFHEA. His work bridges theoretical advancements with practical applications in virtual and augmented reality audio, with notable contributions to the SONICOM HRTF dataset and GAN-based spatial audio rendering techniques. He teaches advanced control systems (ECS654U) and leads the Virtual, Immersive, Augmented and Binaural Audio Lab (VIABAL). Recent grants include £65,621 from L-ACOUSTICS UK LIMITED for 'Online Speech Enhancement in Low Direct-to-Reverberant-Ratio Scenarios' (2024–2025). His research outputs span over 15 peer-reviewed articles between 2019–2025, emphasizing machine learning for audio signal processing and multimodal AI integration. Aidan collaborates widely, hosting international institutions such as the Central Conservatory of Music, China, and presents at major conferences like IEEE WASPAA and ICASSP. His lab focuses on advancing immersive audio technologies through interdisciplinary approaches.

Charalampos SaitisView profile

Lecturer

• Cognitive Representations of Timbre
• Multimodal Perception
• Music Technology
• +3 more

Dr Charalampos Saitis is a Lecturer in Digital Music Processing at Queen Mary University of London's School of Electronic Engineering and Computer Science, affiliated with the Centre for Digital Music (C4DM). He leads the Communication Acoustics Lab, focusing on cognitive representations of timbre, crossmodal perception, and interactive technologies. His research integrates empirical and computational methods to explore human-sound interactions, with applications in music production, public engagement, and ethical AI. Holds a PhD and is a Fellow of the Higher Education Academy (FHEA). Co-editor of Timbre: Acoustics, Perception, & Cognition (2019) and Musical Haptics (2018) . Recipient of the Turing Fellowship (2021–2023) for data-driven human values research. Teaching includes postgraduate courses on interactive multimedia and undergraduate modules in engineering mathematics and professional practice. Research interests span timbral semantics, moral value modeling via music data, and accessibility technologies. Active in university governance, serving on equality committees and research ethics boards.

Anna Xambo SedoView profile

Senior Lecturer

• Human-Computer Interaction (HCI)
• Sound and Music Computing (SMC)
• New Interfaces for Musical Expression (NIME)
• +9 more

Dr Anna Xambo Sedo is a Senior Lecturer in Sound and Music Computing at Queen Mary University of London (QMUL), affiliated with the School of Electronic Engineering and Computer Science and the Centre for Multimodal AI. Her research focuses on human-computer interaction (HCI), sound and music computing (SMC), new interfaces for musical expression (NIME), and live coding, with a particular interest in collaborative, participatory, and non-hierarchical algorithmic systems. She actively promotes diversity in music technology through initiatives like the EECS Women in Higher Education Network (QMUL, 2024–present) and has co-founded organizations such as WiNIME (2019–2022) to improve women’s representation in the field. Grants & Projects: Principal Investigator (PI) of Sensing the Forest: Let the Forest Speak (AHRC, £136,153, 2023–2025), integrating IoT, acoustic ecology, and creative AI. PI of MIRLCAuto: A Virtual Agent for Music Information Retrieval in Live Coding (EPSRC, 2020–2021). Co-Investigator on the UKRI CDT in Artificial Intelligence and Music (EPSRC, £6.5M, 2019–2028). Teaching: Interactive Digital Multimedia Techniques (Postgraduate): Focuses on real-time interactive systems using Arduino, Processing, and Max/MSP. Digital Media Social Networks (Undergraduate/Postgraduate): Explores analysis, privacy, and societal impacts of online social networks. Labs/Teams: Active contributor to the Centre for Multimodal AI and collaborates on interdisciplinary projects blending music technology with environmental and societal challenges.

• Computer Vision
• Robust Estimation
• Object Tracking
• +6 more

Professor Jiri Matas is a Vice Chancellor Fellow at the University of Surrey's School of Computer Science and Electronic Engineering, affiliated with the Centre for Vision, Speech and Signal Processing (CVSSP). His primary research focuses on computer vision, robust estimation, and neural network applications in domains like autonomous systems, medical imaging, and audio-visual perception. He has contributed to advanced tracking algorithms, including discriminative filters and Siamese networks for object tracking, as well as methods for binaural sound processing and anomaly detection in autonomous vehicles. His academic work spans over 50 peer-reviewed publications since 2020, covering topics such as robust geometric estimation (MAGSAC++), lightweight depth estimation architectures, and AI-driven species recognition systems for fungi and plants. Notable collaborations include developing the Danish Fungi 2020 dataset and deploying citizen-science platforms for mycology. He also explores interdisciplinary applications, such as transgenerational immunity in ant colonies and audio-based vehicle monitoring systems. His grants and advising span both technical and biological domains, with labs focused on advancing perception systems in real-world conditions. Recent work emphasizes energy-efficient tracking (FEAR tracker), cross-modal learning (Binaural SoundNet), and handling prior shifts in classification tasks.

Chaz FirestoneView profile

Associate Professor

• Perception
• Attention
• Visual Cognition
• +5 more

Chaz Firestone is an Associate Professor and Director of Graduate Studies in the Department of Psychological & Brain Sciences at Johns Hopkins University, within the Krieger School of Arts & Sciences. His research focuses on the intersection of perception, attention, and higher-level cognition, particularly exploring how visual perception interacts with intuitive physics, language, emotion, and memory. He directs the Hopkins Perception & Mind Laboratory, employing methods ranging from computer-based psychophysics to real-world experiments and neuroimaging studies. Notably, his work has examined physical intuition prediction (e.g., predicting block tower stability), perspectival shape representation, and cross-cultural visual perception phenomena like the Müller-Lyer illusion. Firestone’s studies also address foundational questions such as how higher-order cognitive factors influence perception and the nature of perceptual awareness. His research portfolio includes investigations into inattentional blindness, perceptual similarity judgments, and the limits of human vs. machine perception. He has conducted experimental work in diverse settings, including urban environments like New York City’s Times Square, and collaborates with computational models and brain-imaging techniques. Awards and grants are not explicitly mentioned here, but his lab’s interdisciplinary approach bridges psychology, philosophy, and neuroscience. He advises graduate students in cognitive science and perception studies, though specific advisee names are not listed in the provided materials. Firestone’s work often challenges traditional assumptions about the separation between perception and cognition, arguing for a more integrated understanding. His recent articles highlight topics like 'seeing physics,' perspectival interference, and the psychological mechanisms underlying 'impossible' somatosensory experiences. The lab’s current projects explore perceptual compositionality, the role of expectation in tactile perception, and the empirical basis of philosophical debates about perception’s limits.

• Physical Oceanography
• Acoustical Oceanography
• Marine Acoustics
• +5 more

David Barclay is an Associate Professor and Graduate Coordinator in the Department of Oceanography at Dalhousie University's Faculty of Science. His research focuses on acoustical oceanography, physical oceanography, and environmental monitoring, with specialties in ambient noise analysis, hydrothermal vent dynamics, and underwater instrumentation. He leads a lab exploring the acoustic properties of marine environments, including Arctic regions, deep-sea trenches, and hydrothermal vent fields. His work integrates field measurements, numerical modeling, and sensor development to address challenges in ocean health, climate change, and marine conservation. Barclay's research topics include sediment acoustics, oceanographic instrumentation, and the impact of anthropogenic noise on marine life. He has contributed to projects such as passive acoustic monitoring of North Atlantic right whales, real-time Arctic soundscapes, and the development of autonomous underwater vehicles for bathymetric surveys. His laboratory website provides access to acoustic datasets and tools for environmental acoustic analysis. Key research trends in his publications (2022–2025) emphasize the application of acoustics to measure ocean acidity, track vessel noise, and study hydrothermal vent soundscapes. He has also explored the effects of environmental changes, such as reduced shipping noise during the 2020 pandemic, on marine ecosystems. His work bridges engineering, physics, and biology to advance sustainable ocean management practices. Notably, Barclay coordinates graduate programs in oceanography, fostering interdisciplinary training in marine acoustics and environmental science. His lab collaborates with organizations like Ocean Networks Canada to deploy cabled observatories and conduct long-term acoustic monitoring in the Northeast Pacific. Current initiatives include developing autonomous hovercraft for shallow-water surveys and improving geoacoustic inversion techniques for seabed characterization.

Søren BechView profile

Professor

• Acoustics
• Audio Engineering
• Sound Zones
• +4 more

Søren Bech is a Professor at the Department of Electronic Systems within The Technical Faculty of IT and Design at Aalborg University. His academic qualifications include a PhD from the Technical University of Denmark (1988) and an MSc in Electrical Engineering (1982). His primary research focuses on audio quality, acoustics, and sound zone technologies, with emphasis on perceptual audio evaluation, spatial audio systems, and cortical auditory attention decoding. He leads projects such as ISOBEL (Interactive Sound Zones) and SOUNDS (Service-Oriented, Ubiquitous, Network-Driven Sound), addressing challenges in dynamic audio environments and networked audio systems. Key research areas include automotive audio systems, headphone technology, and the integration of EEG-based attention decoding for personalized sound experiences. He has received recognition, including the Best Student Paper award in 2024. Collaborations span academia and industry, with involvement in organizations like the Danish Sound Cluster and Danmarks Forsknings- og Innovationspolitiske Råd. His work bridges theoretical acoustics with practical applications in consumer electronics and immersive media.