Find Academic Supervisors

• Signal Processing
• Acoustic Sensor Networks
• Machine Learning
• +3 more

Roberto Gil Pita is a Professor at the University of Alcalá (Spain), affiliated with the Department of Signal Theory and Communications. He leads the AES3 research group focusing on acoustic and electromagnetic smart sensor networks and signal processing applications. His doctoral work (2006) centered on radar target classification using statistical and AI methods under the supervision of Dr. Manuel Rosa Zurera. His research spans signal processing, machine learning, and their applications in aerospace, biomedical systems, and smart cities. Key areas include UAV detection, emotion recognition from speech, and acoustic localization using microphone arrays. His academic background includes a doctorate from the University of Alcalá and extensive contributions to wireless acoustic sensor networks, hearing aid signal processing, and bioimpedance spectroscopy. He has developed energy-efficient algorithms for real-time audio analysis, acoustic violence detection systems, and robust methods for speech enhancement in noisy environments. His work bridges theoretical signal processing with practical engineering solutions for defense, healthcare, and urban monitoring. Research interests extend to aeroelastic flutter analysis in aviation, wearable biomedical sensors for stress assessment, and data-driven approaches for sound environment classification. He has pioneered the use of deep learning in flutter testing and acoustic event classification, contributing to datasets like REALISED for benchmarking machine learning models. Notable projects include acoustic localization of drones using microphone arrays, real-time emotion detection systems, and collaborative research in smart healthcare technologies. His work emphasizes computational efficiency and energy conservation, particularly for embedded systems and battery-operated devices.

• Acoustic Signal Processing
• Speech Enhancement
• Microphone Array Processing
• +6 more

Dr Alastair Moore is a Researcher in the Dyson School of Design Engineering at Imperial College London, affiliated with the Speech and Audio Processing Laboratory. He holds a PhD from Imperial College and has industrial experience in consumer electronics. His research focuses on microphone array signal processing, speech enhancement in reverberant environments, and applications in augmented reality, hearing aids, and robot audition. Education: MEng in Electronic Engineering with Music Technology Systems (1st class) from University of York (2005); PhD in Binaural Hearing funded by France Telecom R&D (2012). Research Interests: He specializes in speech enhancement algorithms for wearable devices, binaural hearing systems, room acoustics modeling, and acoustic SLAM. His work includes developing virtual reality tools for hearing aid evaluation and room identification techniques for forensic applications. Funding: His projects are supported by EPSRC, EU FP7, Google, Reality Labs Research, and the UK Home Office. Notable grants include EPSRC EP/M026698/1: Environment-aware speech enhancement EPSRC EP/S035842/1: Binaural hearing aids with VR evaluation EU FP7/2007-2013: Robot audition using spherical microphone arrays Google: Speech dereverberation for VoIP UK Home Office: Audio forensics via room geometry inference Labs: Active member of the Speech and Audio Processing group led by Prof. Mike Brookes and Prof. Patrick A. Naylor.

Hassan KaisView profile

Researcher

• Acoustics
• Signal Processing
• Machine Learning
• +2 more

Hassan Kais is a Teacher-researcher affiliated with the Institute of Acoustics at Le Mans University. His work bridges acoustics and telecommunications, focusing on advanced signal processing techniques. Key research areas: Acoustics, Machine Learning, Wireless Communications Institution: Le Mans University, France Hassan's research explores the intersection of acoustic signal analysis and next-generation communication systems. Notably, he has contributed to: Innovative microphone array designs for sound capture SCMA (Sparse Code Multiple Access) systems in telecommunications Machine learning applications in acoustic and wireless signal processing mmWave hybrid MIMO systems for 5G networks Thermo-acoustic and electroacoustic sensor development His publications demonstrate interdisciplinary expertise in: Acoustic wave propagation in complex media Deep learning for communication protocols Signal processing algorithms Metamaterials and transducer design Audio sensor networks Non-linear acoustics applications

Manuel MelonView profile

Professor

• Acoustics
• Electroacoustics
• Sound Field Synthesis
• +7 more

Manuel Melon is a Professor at the Acoustics Laboratory of the University of Le Mans , where he co-supervises the International Master in Electroacoustics (IMDEA) . His career spans institutions like the Conservatoire National des Arts et Métiers in Paris and focuses on advanced acoustic research. His research interests include electroacoustics , sound field synthesis , personalized listening zones , and acoustic material characterization using transducer arrays. He explores both theoretical and applied aspects of wave propagation in complex media. Recent publications highlight trends in acoustic metamaterials for directional sound control, MEMS speaker modeling , and adaptive filtering for automotive sound zones. He also contributes to online acoustic education through the ACOUCOU platform.

• Biomedical Engineering
• Optical Spectroscopy
• Medical Instrumentation
• +3 more

B.H.W. Hendriks is a Professor in the Department of Mechanical Engineering at Delft University of Technology, specializing in Medical Instruments & Bio-Inspired Technology. His research develops optical and signal processing solutions for medical applications, particularly in surgical environments and tissue analysis. His primary research domains include: Biomedical Engineering Optical Spectroscopy (Diffuse Reflectance) Medical Device Development Surgical Technology Cardiac Signal Processing Tissue Characterization Analysis of his 55+ publications reveals dual expertise: (1) Intraoperative optical sensing (e.g., fiber-optic tissue identification during spine surgery and electrosurgery), and (2) Advanced signal processing for cardiac diagnostics (atrial fibrillation mapping via electrograms/ECG). His work bridges mechanical engineering with clinical practice through real-time surgical workflow analysis and tissue-mimicking phantoms. Hendriks actively supervises research students and has generated 3 significant datasets for tissue characterization. His fingerprint shows dominant activity in spectroscopy (100%), surgery (93%), and tissue analysis (91%), with emerging work in human pose tracking for cardiac catheterization laboratories.

• Robotics
• Auditory Perception
• Multimodal Perception
• +3 more

Sylvain Argentieri serves as an Associate Professor at the Institute for Intelligent Systems and Robotics (ISIR) within Sorbonne University, where he has been a member of the ASIMOV research group ("Architectures and Models for Adaptation and Cognition") since 2008. His office is located at ISIR, Campus Pierre et Marie Curie, 4 place Jussieu, BC173, 75005 Paris. He maintains an active research presence with publications spanning from 2006 to 2024. His educational background includes obtaining the highest teaching diploma in France (Agrégation externe) in Electrical Engineering from the École Normale Supérieure in 2002, followed by a Ph.D. in Computer Science from Paul Sabatier University (Toulouse) in 2006, and his Habilitation à Diriger des Recherches (HDR) in 2018. Argentieri's research focuses on artificial perception in robotics with special emphasis on auditory perception, active multimodal perception approaches, and sensorimotor integration. His work demonstrates a consistent trajectory exploring how robots can develop perceptual capabilities through sensorimotor experiences, with particular attention to binaural sound localization, head movement control, and the emergence of spatial representations from uninterpreted sensory signals. His publications reveal a strong interest in how naive agents can structure their understanding of the world through active exploration and sensory prediction. His publication record shows a clear progression from foundational work on sound source localization to more complex investigations of sensorimotor contingencies and embodied cognition. The research spans multiple venues including IEEE conferences, Robotics and Autonomous Systems, and Frontiers journals, with recent work incorporating transformer architectures and neural network approaches to auditory processing. Argentieri maintains active collaborations with researchers including Nicolas Obin, Bruno Gas, and Valentin Marcel, as evidenced by his co-authored publications. His laboratory work takes place within the ASIMOV team at ISIR, which focuses on architectures and models for adaptation and cognition in robotic systems.

Lu SuView profile

Adjunct Associate Professor

• Internet of Things
• Cyber-Physical Systems
• Mobile Computing
• +7 more

Dr. Lu Su is a Volunteer Adjunct Associate Professor in the Department of Computer Science and Engineering at Purdue University's School of Engineering and Applied Sciences. His research focuses on Internet of Things (IoT), cyber-physical systems, mobile computing, wireless networks, and related security challenges in autonomous systems. He has contributed to advancements in acoustic sensing, federated learning frameworks, and adversarial attack mitigation strategies. Dr. Su's work emphasizes practical applications such as 3D hand pose reconstruction using acoustic signals, mmWave-based human activity recognition, and securing sensor fusion in autonomous vehicles. His research also explores federated learning optimization, data poisoning defenses, and incentive mechanisms for mobile crowdsourcing systems. His publications span topics from real-time signal processing to cybersecurity in vehicular networks, with a particular emphasis on developing robust, scalable solutions for distributed and edge computing environments. Dr. Su maintains an active presence in the research community, contributing to conferences and open-source frameworks. His work is accessible via his website and Google Scholar profile .

Antigoni TsiamiView profile

Research Fellow

• Multimodal Signal Processing
• Robotics
• Speech Enhancement
• +7 more

Antigoni Tsiami is a Postdoctoral Research Associate at the National Technical University of Athens (NTUA), affiliated with the School of Electrical and Computer Engineering (ECE) and the CVSP Group. She has been a PhD student since 2013, focusing on audio and speech processing applications. Her work spans robotics, signal processing, and assistive technologies. Education: Diploma in Electrical and Computer Engineering from NTUA (2012) PhD candidate in the CVSP Group, ECE School, NTUA under Prof. Petros Maragos Research interests: Multichannel speech enhancement and acoustic source localization Audiovisual scene perception for human-robot interaction Far-field processing techniques MEMS microphone applications Multimodal perception systems for assistive robotics Home automation control via spoken commands Her research projects include BabyRobot and COGNIMUSE , exploring multimodal signal processing in cognitive robotics and human interaction scenarios. Recent publications demonstrate focus on integrating sensory data for practical robotics applications, emphasizing robustness in real-world environments. She collaborates with interdisciplinary teams including the CVSP Group and EU-funded initiatives. Advising/Grants: While no advisees are listed, her current postdoctoral role suggests ongoing research collaborations. She participates in grant-funded projects such as BabyRobot and COGNIMUSE. Labs/Teams: Active member of the CVSP Group and contributed to the IROS 2015 workshop on Cognitive Mobility Assistance Robots. Engaged with multidisciplinary teams in EU robotics initiatives.

Andrea ToscaniView profile

Researcher

• Power Electronics
• Electric Drives
• Power Converters
• +7 more

Andrea Toscani is a fixed-term researcher at the Department of Engineering and Architecture, University of Parma, where he has been active since 2020. He holds a Ph.D. in Information Technology and an M.S. in Electronics Engineering, both from the University of Parma. He teaches courses in Electrical Machinery and Drives, Principles and Applications of Electrical Engineering, and Technical Systems in Buildings across Mechanical, Management, and Civil Engineering programs. His research focuses on power electronics, electric drives, fault diagnosis, and wide-bandgap devices in aerospace and renewable applications. He has led and contributed to EU-funded projects such as ALEA and RAISE under the Clean Sky initiative, focusing on insulation degradation and reliability of aircraft electrical systems. His work extends to battery aging modeling, partial discharge monitoring, and advanced data acquisition systems for industrial applications. The analysis of his recent publications (2024–2025) reveals a strong trend in condition monitoring, predictive maintenance, and power converter design for sustainable energy systems. His work integrates advanced instrumentation with practical industrial and aerospace applications, emphasizing reliability and efficiency. Andrea Toscani actively engages in technology transfer, having served as CEO of an academic spin-off and holding two industrial patents in food processing. He is a reviewer for top-tier journals from IEEE, Elsevier, and MDPI, contributing to the academic community's quality control. He is involved in multiple research projects focusing on aerospace electrical systems and renewable energy integration. His lab and team activities are centered around power electronics testing, accelerated life testing, and development of monitoring systems for industrial and aerospace applications.

Hyunkook LeeView profile

Professor

• Psychoacoustics
• Spatial Audio
• Virtual Reality
• +5 more

Hyunkook Lee is a Professor of Audio and Psychoacoustic Engineering at the University of Huddersfield , where he directs the Applied Psychoacoustics Lab (APL) and the Centre for Audio and Psychoacoustic Engineering . He joined the university in 2010 and has pioneered research in 3D audio, spatial recording, and psychoacoustic applications in virtual reality. Education: PhD in Psychoacoustics (University of Surrey, 2006) Industry Experience: Senior Research Engineer at LG Electronics Research Interests include: Psychoacoustics : Perception of height in 3D audio and interchannel crosstalk. Spatial Audio : Development of microphone arrays, panning, and upmixing techniques. Virtual Reality : Bridging XR and audio engineering for immersive experiences. Music Technology : Applications in commercial rap production and surround sound. Scientific Awards : 5 US-granted patents h-index of 14 (Scopus) Advising & Grants : Actively supervises PhD students and participates in industry-funded projects with Samsung, Volvo, and MagicBeans. His research includes a £326k grant for 3D sound in the 'Audience of the Future'.

H.P. (Hero) WitView profile

Professor

• Audiology
• Biophysics
• Biomedical Engineering
• +3 more

Prof. H.P. (Hero) Wit is a Professor of Audiology at the Faculty of Medical Sciences, University of Groningen. His research focuses on auditory systems, biophysics of hearing, and biomedical engineering applications in audiology. He has contributed extensively to understanding otoacoustic emissions and cochlear dynamics through mathematical and biomechanical modeling. Research interests include spontaneous otoacoustic emissions, cellular cooperativity in hearing, lizard ear physiology, and vestibular microphonics. His work bridges biophysics, engineering, and clinical audiology, with recent emphasis on fluid-coupled resonator models and evolutionary comparisons of auditory systems. Recent publications analyze interpeak characteristics of emissions, lizard cochlear mechanics, and historical perspectives on vestibular research. He collaborates with institutions like the UMCG and international teams on auditory modeling projects.

Ruslan PodviianiukView profile

Assistant Professor

• Particle Physics
• Dark Matter Research
• Nuclear Physics
• +2 more

Ruslan Podviianiuk is a Research Assistant Professor in the Department of Physics at Syracuse University's College of Arts and Sciences, specializing in experimental particle physics with focus on dark matter detection and cryogenic detector development. His educational background includes: Ph.D. in Nuclear, Particle and High Energy Physics from the National Academy of Sciences of Ukraine (NASU), 2011. Dissertation: Scintillation Detectors Based on Molybdates and Tungstates for Investigation of Double-Beta Decay and Search for Dark Matter Particles. M.Sc. in Nuclear and Elementary Particle Physics from Taras Shevchenko National University of Kyiv, 2001. Dissertation: Digital Signal Processing in Nuclear Spectroscopy. B.Sc. in Physics from Taras Shevchenko National University of Kyiv, 2000. A.S. in Radio Instrumentation from Kyiv Professional College of Electronic Devices, 1995. Dissertation: Microphone with a Sharp Directional Diaphragm. Dr. Podviianiuk's research centers on direct dark matter detection using cryogenic semiconductor detectors, with expertise in low-energy nuclear recoil measurements, background characterization, and signal processing. His work bridges particle physics and detector engineering, focusing on sub-keV energy thresholds for low-mass dark matter candidates through experiments like SuperCDMS. He has pioneered techniques for ionization yield measurements in silicon/germanium and developed novel approaches using the Migdal effect and bremsstrahlung radiation. Analysis of his recent publications reveals a clear progression from surface-based detector characterization to underground operation at SNOLAB, with increasing emphasis on background rejection and low-mass sensitivity. His research spans experimental design, data analysis, and theoretical interpretation across multiple detector technologies. He has received institutional recognition for academic contributions: Statement of Achievement for Course Development and Pedagogy (2021) Statement of Achievement for Inclusive Mentoring (2021) While specific grant details are not provided, his active role in the SuperCDMS collaboration indicates significant research funding involvement. No formal student advising relationships are documented in available sources. Dr. Podviianiuk operates within the SuperCDMS international collaboration framework, conducting research at underground facilities including Soudan Laboratory and SNOLAB. His laboratory work focuses on cryogenic detector arrays for dark matter searches, incorporating advanced electronics and signal processing systems for rare-event detection.

• Engineering Acoustics
• Acoustic Measurement
• Communication Acoustics
• +4 more

Yasuhiro Oikawa is a Professor at the School of Fundamental Science and Engineering, Faculty of Science and Engineering, Waseda University. He holds a Doctor of Engineering degree from Waseda University and has been actively contributing to acoustics, signal processing, and optical measurement techniques. His research spans Sound field visualization using parallel phase-shifting interferometry Phase-aware audio signal processing algorithms Acoustic calibration and microphone sensitivity analysis Real-time sound event localization systems His recent publications focus on advanced time-frequency analysis, optical methods for sound measurement, and deep learning applications in acoustics. Key trends include Improving resolution in spectrogram-based signal processing Integration of physical models with neural networks Development of wearable acoustic sensor arrays Scientific awards recognizing his work include The Fumio Okano Best 3D Paper Awards CSS2018 Best Paper Award Acoustical Society of Japan Contribution Award Institute of Electronics, Information and Communication Engineers Human Communication Award He has served as a committee member for the Acoustical Society of Japan and is affiliated with organizations such as ACM, IEEE, and Acoustical Society of America. His research has been supported by collaborations with institutions like Technical University of Denmark and applications in robotics, museum exhibits, and consumer electronics.

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

Himawan Ivan is a researcher affiliated with Queensland University of Technology (QUT), specializing in computer science with a focus on signal processing, speech recognition, and machine learning. His work spans anti-spoofing in speaker verification, deep learning applications in wildlife monitoring (e.g., koala activity detection), and domain adaptation techniques for robust speaker recognition systems. He completed his PhD in 2010 at QUT, titled 'Speech recognition using ad-hoc microphone arrays,' and has contributed to over 28 peer-reviewed publications since 2008. Research interests include audio processing, neural network architectures for voice biometrics, and perceptual quality optimization in multimedia systems. His collaborations with institutions like the IEEE and ISCA highlight his expertise in interdisciplinary projects, often involving real-world applications such as environmental acoustic analysis and security systems. Publications between 2016–2019 emphasize advancements in deep neural networks (CNNs, RNNs) for speaker diarization, domain adaptation in PLDA models, and adversarial robustness. Earlier work explored microphone array beamforming and region-of-interest coding in low-bitrate video. Though no specific grants or awards are listed, his consistent publication record in top venues like INTERSPEECH and IEEE transactions underscore active engagement in academic research.

Ryan M CoreyView profile

Assistant Professor

• Audio and Acoustic Signal Processing
• Sensor Array and Multichannel Signal Processing
• Adaptive Signal Processing
• +4 more

Ryan M. Corey is an Assistant Professor of Electrical and Computer Engineering at the University of Illinois Chicago and a Research Scientist at the Discovery Partners Institute (DPI), a Chicago-based innovation hub focused on equitable economic development. His work bridges academic research with industry and community engagement, particularly emphasizing technologies for marginalized groups. Ph.D., Electrical and Computer Engineering, University of Illinois Urbana-Champaign (2019) M.S., Electrical and Computer Engineering, University of Illinois Urbana-Champaign (2014) B.S., Electrical Engineering (Highest Honors), Princeton University (2012) Professor Corey’s research focuses on audio and acoustic signal processing to enhance hearing technologies in noisy environments. Key areas include spatial signal processing, microphone arrays, distributed sensor networks, and wireless audio systems. As the first dual-appointed faculty member at DPI, he develops cooperative architectures for multi-device audio sensing and immersive sound remixing applications for augmented reality and assistive systems. His current projects involve creating intelligent audio networks that leverage wearable and mobile devices for improved acoustic inference, and an automated acoustic research system at DPI for generating dynamic datasets. His work emphasizes practical applications in hearing assistive technology, pandemic-related communication barriers, and emergency medical devices. 2022 Future of Science Award (Oak Ridge Institute for Science and Education) 2020 Best Student Paper Award (Acoustical Society of America Meeting) 2019 Best Student Paper Award & IC Postdoctoral Fellowship 2014 NSF Graduate Research Fellowship As a hearing aid user himself, Corey prioritizes real-world usability in assistive technologies while maintaining rigorous academic research standards through collaborations with the Audio Engineering Society, IEEE Signal Processing Society, and Acoustical Society of America.