Find Academic Supervisors

Morgan SondereggerView profile

Associate Professor

• Phonology
• Phonetics
• Computational Linguistics
• +5 more

Morgan Sonderegger is an Associate Professor in Linguistics at McGill University and holds a Canada Research Chair (Tier 2) in Speech Variability. He co-leads the Montreal Computational and Quantitative Linguistics Lab (MCQLL), focusing on interdisciplinary research at the intersection of phonetics, computational modeling, and language variation. His research spans phonology, phonetics, computational linguistics, language variation and change, and quantitative methods. Sonderegger develops advanced statistical models for linguistic data analysis, particularly Bayesian regression techniques and computational approaches to speech variability. His work integrates large-scale corpus analysis with experimental methodologies to investigate sound change mechanisms, speech production, and perceptual patterns across languages. Recent publications reveal strong trends in quantitative phonetic analysis, computational modeling of speech variability, and cross-linguistic studies of phonological patterns. His research increasingly incorporates machine learning techniques and large-scale corpus approaches to address fundamental questions in phonetics and phonology. Canada Research Chair (Tier 2) in Speech Variability Sonderegger contributes significantly to linguistic methodology through software development and educational resources. He has created essential tools like the Montreal Corpus Tools (including PolyglotDB and Montreal Forced Aligner) that facilitate speech corpus analysis. His educational contributions include the textbook Regression Modeling for Linguistic Data and advanced course materials on Bayesian regression modeling. He leads the Montreal Computational and Quantitative Linguistics Lab (MCQLL), which develops computational frameworks for analyzing speech corpora and modeling phonetic variation. The lab's work bridges theoretical linguistics with practical applications in speech technology and language processing.

Christiane AntweilerView profile

Researcher

• Digital Signal Processing
• Speech and Audio Processing
• Acoustic System Identification
• +6 more

Dr.-Ing. Christiane Antweiler is a Researcher at the Institute of Communication Systems (IKS) , part of RWTH Aachen University 's Faculty of Electrical Engineering and Information Technology. Her work focuses on algorithms for digital speech/audio processing, multi-channel system identification, head-related transfer functions (HRTFs), and acoustic/echo cancellation in medical and teleconferencing applications. Research topics: Medical diagnostics signal processing , time-variant system identification , HRTF measurement , and real-time audio implementation . Current projects: Connected Visual Reality (CoVR) , Acoustic Tube Endoscopy , and Spatial Rendering with quasi-continuous HRTFs. Her 15 most recent publications (2025–2011) span adaptive filtering , acoustic system identification , and 3D audio rendering , with a strong emphasis on perfect sequence excitation and medical applications . She received the Best Paper Award at ICMCIS 2022 for her work on spectrum monitoring. Teaching roles include Information Theory and Source Coding (since 2009) and Digital Speech Processing 1 (2014–2015). Tools used: Matlab , C/C++ , and RT Proc for real-time audio processing.

Matthias C. KettemannView profile

Professor

• Internet Law
• Digitalization Governance
• Artificial Intelligence Regulation
• +5 more

Matthias C. Kettemann is a full-time Professor of Innovation, Theory and Philosophy of Law at the University of Innsbruck , where he leads the Department of Legal Theory and Future of Law . He also serves as a research programme leader at the Leibniz Institute for Media Research | Hans Bredow Institute in Hamburg, research group leader at the Alexander von Humboldt Institute for Internet and Society in Berlin, and as a research group leader at the Sustainable Computing Lab in Vienna. His academic affiliations extend to associated researcher roles at institutions in Hamburg, Frankfurt am Main, and Graz. Head of Department, University of Innsbruck Research Programme Leader, Leibniz Institute for Media Research Research Group Leader, Humboldt Institute for Internet and Society Board Member, Sustainable Computing Lab Associated Researcher, Research Institute for Social Cohesion Prof. Kettemann’s research focuses on internet law , AI governance , platform regulation , digital constitutionalism , and innovation law . His publications and projects explore normative orders , multinormativity , and cybersecurity in digital spaces. His recent articles address human-in-the-loop AI systems , consumer credit algorithms , and democratic resilience against disinformation . He also investigates legal frameworks for data sovereignty and platform accountability in crisis situations . He has received prestigious scholarships, including the Fulbright and Boas Scholarships , and contributes to academic discourse as Managing Editor of the Mohr/Siebeck series 'Internet und Gesellschaft' , editorial board member of journals like jusIT and Media and Communication Studies , and scientific advisory board member of the European Yearbook on Human Rights . He is actively involved in reviewing for international publishers and academic journals. Prof. Kettemann teaches in German, English, and French, with courses in internet law , innovation law , international law , and legal philosophy since 2008. He supervises theses at bachelor, diploma, doctoral, and post-doctoral levels, emphasizing digital law and innovation frameworks . His third-party funding includes grants from the European Union , Friedrich-Ebert-Stiftung , Google , and Deutsche Telekom .

Mandar GogateView profile

Research Fellow

• Audio-Visual Speech Enhancement
• Machine Learning
• Green Artificial Intelligence
• +5 more

Dr. Mandar Gogate is a Senior Research Fellow at the School of Computing Engineering and the Built Environment, Edinburgh Napier University. He actively contributes to the Centre for Artificial Intelligence and Robotics, focusing on multimodal signal processing and AI applications. Research Themes: Audio-Visual Speech Enhancement, Green AI, Data Privacy, Hearing Aid Technology, Climate Modeling Collaborations: Prof. Amir Hussain, Dr. Kia Dashtipour, Prof. Ahmed Al-Dubai His research explores audio-visual speech enhancement for hearing aids, leveraging deep learning and fuzzy logic. He investigates green AI techniques like neural network pruning for energy efficiency and develops privacy-preserving frameworks using thermal imaging. His work spans climate data analysis with partial least squares and underwater image enhancement via dimension decomposition transformers. Recent publications include 2026 surveys on ensemble malware detection and 2025 studies on cognitive load-driven speech enhancement . He has contributed to federated learning for market surveillance and multimodal hearing aid projects. As a second supervisor for Idrees Hasan's research on COG-MHEAR hearing aids, he mentors emerging scholars. His grants include £3.25M from EPSRC for the COG-MHEAR project (2021-2026) and £12k from Royal Society for multilingual speech enhancement studies. He works with the Centre for Artificial Intelligence and Robotics and Centre for Distributed Computing , integrating 5G-IoT systems into assistive technologies. His technical background includes compiler design, embedded systems, and wireless sensor networks from earlier projects like gesture mice and Hadoop-based rule mining.

• Signal Processing
• Speech and Language Processing
• Machine Learning
• +3 more

Prof. Dr. Ümit Güz serves as a full-time Professor in the Department of Electrical and Electronics Engineering at Işık University's Faculty of Engineering and Natural Sciences. With over two decades of academic experience, his expertise spans biomedical signal processing, speech technology, and machine learning applications. Education: Post-Doc (2006-2007): SRI International, Menlo Park, CA - Speech Technology and Research Laboratory Post-Doc (2007-2008): UC Berkeley, International Computer Science Institute PhD (1997-2002): Istanbul University, Electronics Engineering MSc (1995-1997): Istanbul University, Electronics Engineering BSc (1990-1994): Istanbul University, Electrical-Electronics Engineering Associate Degree (1988-1990): Yıldız Technical University, Computer Programming His research centers on multimodal biometric systems using ECG and speech signals, medical image compression techniques, and Turkish language processing. Key innovations include SYMPES speech modeling framework and quadtree-based energy pattern blocks for biomedical image compression. His work bridges theoretical signal processing with practical healthcare and security applications. Publication trends reveal consistent focus on biometric identification (fingertip ECG/speech fusion), efficient compression algorithms for medical data (ECG/EEG/images), and semi-supervised learning for Turkish sentence segmentation. Recent work emphasizes multi-view learning strategies and deep neural network integration in compression systems. Scientific Awards: J. William Fulbright International Fellow (Postdoc Scholar Program, USA) Overseas Postdoctoral Research Award (TÜBİTAK BİDEB, Turkey) Prof. Güz has supervised 9 master's theses and 2 PhD dissertations on biometric recognition, speech compression, and medical image processing. His research is supported by TÜBİTAK grants including Project No 107E182 (Turkish spoken language processing) and Project No 10A301 (ECG-based biometric recognition). He actively contributes to IEEE and IEICE as a longstanding member.

Kongfatt Wong-LinView profile

Professor

• Computational Neuroscience
• Machine Intelligence
• Cognitive Neuroscience
• +5 more

Professor Kongfatt Wong-Lin is a Professor of Computational Neuroscience and Machine Intelligence at the School of Computing, Engineering and Intelligent Systems, Ulster University. He is based at the Intelligent Systems Research Centre (ISRC) at the Magee Campus in Derry~Londonderry, where he conducts cutting-edge research at the intersection of computational modeling, neuroscience, and artificial intelligence. His research interests span computational modeling of neural systems, cognitive neuroscience, cognitive psychology, brain disorders, neural computation and engineering, artificial intelligence, and data science. Professor Wong-Lin is a member of the UK EPSRC Peer Review College and a Fellow of the Higher Education Academy, reflecting his significant contributions to both research and education. Professor Wong-Lin's research output reveals a consistent focus on computational neuroscience, particularly in understanding decision-making processes, neural circuits, and applications to dementia diagnosis. His work combines theoretical modeling approaches with practical healthcare applications, most notably developing AI and machine learning algorithms to streamline dementia diagnoses and improve patient care pathways. Scientific awards include: Ulster University's Distinguished Research Fellowship Award (2016) Ulster University Research Excellence Award (2019) International Joint Conference on Neural Networks (IJCNN) Best Paper Award (2011) 3rd Best Poster Award, IEEE-EMBS International Summer School (2015) Best Poster Award, Translational Medicine Conference (2015) Professor Wong-Lin leads multiple significant research projects, including ALCOME (focusing on acoustic and linguistic markers of cognitive decline in dementia), 'Uncovering the neural architecture underlying decisions abstracted from movements' (2021-2026), and developing a Brain-Computer Interface driven Mental Fatigue Monitoring System for stroke rehabilitation therapy. In 2021, he founded the international ISRC Computational Neuroscience, Neurotechnology and Neuro-inspired AI School, establishing a platform for global collaboration in these fields. His academic journey includes a Ph.D. in Physics with focus on Computational Neuroscience from Brandeis University, postdoctoral work at Princeton University, and previous degrees from the National University of Singapore. Professor Wong-Lin maintains active collaborations with institutions worldwide, including visiting fellowships at the University of Galway and University of Oxford.

John Bush IdokoView profile

Assistant Professor

• Machine Learning
• Computer Vision
• Signal Processing
• +2 more

John Bush Idoko is an Assistant Professor in the Computer Engineering Department at Near East University, North Cyprus. He earned his BSc in Computer Science from Benue State University, Nigeria (2010), followed by MSc (2017) and PhD (2020) in Computer Engineering at Near East University. His research focuses on machine learning , computer vision , and signal processing , with applications in IoT systems , healthcare devices , and smart infrastructure . He has contributed to 15 recent publications spanning topics such as UAV routing protocols, image encryption, and medical prosthetics. BSc: Computer Science, Benue State University (2010) MSc: Computer Engineering, Near East University (2017) PhD: Computer Engineering, Near East University (2020) His work emphasizes deep learning optimization , chaotic encryption , and intelligent sensor networks . Recent projects include IoT-based infant monitoring, sleep apnea detection, and voice-controlled prosthetics. He is affiliated with the Applied Artificial Intelligence Research Centre and leads the Cyber Security Engineering Department.

Hristina Runcheva TasevView profile

Associate Professor

• EU Integration
• Political Systems of the European Union
• Media Freedom and Regulation
• +5 more

Hristina Runcheva Tasev serves as an Associate Professor at the Faculty of Law, Ss. Cyril and Methodius University in Skopje, within the Institute of Political Science and Applied Political Science Department. Her academic profile spans teaching across all three study cycles with subjects including Applied Politics, Digital Democracy, EU Political System, and Ethnicity, Nation and State. Her research focuses on EU integration dynamics, Balkan political systems, and media freedom under emergency conditions. Key areas include refugee rights in Macedonian legal frameworks, EU rule of law mechanisms, and digital governance challenges. Her work demonstrates consistent engagement with contemporary European political crises and institutional responses. Analysis of her recent publications reveals strong thematic continuity in Balkan-EU relations, with increasing attention to digital governance and pandemic-era civil liberties. Over 60% of her work since 2018 addresses migration corridors or EU integration challenges specific to North Macedonia, reflecting deep regional expertise. Regular participant in Annual International Conferences on European Integration Contributor to Mega project "European Integration of the Republic of North Macedonia" Her teaching portfolio demonstrates comprehensive coverage of political science subfields, with particular emphasis on practical policy application through courses like Policy Analysis and Evaluation at the third-cycle level. Office hours are maintained Monday/Wednesday 11am-1pm for student consultations.

Siddharth AroraView profile

Associate Professor

• Machine Learning
• Management Science
• Healthcare Analytics
• +4 more

Dr. Siddharth Arora is an Associate Professor of Machine Learning and Management Science at the Saïd Business School , University of Oxford. He teaches quantitative courses across MBA, Executive MBA, and Executive Education programmes. Recipient of the 2025 University of Oxford Social Sciences Division Teaching Excellence Award Research focuses on machine learning applications in healthcare, energy forecasting, and biomedical signal processing Collaborates with programme teams including Hilary O’Hare, Susie Middleton, Phil Curnick, and Paulina Gasparek Leverages large-scale datasets from the Parkinson’s Voice Initiative and smart meter studies Emphasizes inclusive teaching approaches and cross-disciplinary methodology His work spans neurodegenerative disease diagnostics , emergency department risk modeling , and energy demand forecasting , applying advanced machine learning techniques to real-world problems. The Parkinson’s Voice Initiative studies demonstrate how telephone-quality speech can enable remote disease monitoring, while his energy forecasting research addresses grid stability challenges with weather integration models. Siddharth has received multiple scientific awards , including: 2025 Social Sciences Division Teaching Excellence Award Publications in top journals on Parkinson's disease and energy forecasting Recognized for innovative quantitative teaching methods His teaching philosophy emphasizes student-driven learning, supported by programme teams and infrastructure that enable complex quantitative instruction at scale. He acknowledges contributions from colleagues in programme management and teaching resources.

Enrique ArmijoView profile

Professor

• First Amendment
• Constitutional Law
• Media Law
• +6 more

Enrique Armijo is a Professor of Law at Elon University School of Law with concurrent fellowships at Yale Law School's Information Society Project, George Washington University's Institute for Data, Democracy, and Politics, and UNC-Chapel Hill's Center for Information, Technology and Public Life. His expertise spans constitutional law, media regulation, and digital free speech challenges. His educational background includes a B.A. from the University of Florida, an M.A. from UNC-Chapel Hill, and a J.D. from the University of North Carolina where he served as Editor-in-Chief of the North Carolina Law Review. Armijo's research critically examines First Amendment doctrine in digital contexts, focusing on disinformation ecosystems, platform governance, and transnational free expression. His scholarship analyzes how algorithmic content moderation, Section 230 immunity, and government-provided internet access reshape constitutional protections while addressing societal harms from online falsehoods. Analysis of his 2021-2025 publications reveals consistent exploration of disinformation counter-strategies, comparative must-carry regulations, and equity-based speech remedies. His work demonstrates how traditional First Amendment frameworks struggle with digital-scale misinformation while advocating for nuanced approaches that balance free expression with democratic integrity. His scholarly impact is evidenced by citations from federal agencies and U.S. Senate testimony. Key recognitions include: Yale Law School Information Society Project Fellow George Washington University Institute for Data, Democracy, and Politics Faculty Fellow UNC-Chapel Hill Center for Information, Technology and Public Life Fellow Armijo has advised governments and NGOs on media law reform across Africa, Asia, and the Middle East, including U.S. State Department projects in Myanmar. His pre-academic career featured landmark Supreme Court arguments in FCC v. Fox Television Stations and Boumediene v. Bush. He actively shapes public discourse through NPR, Voice of America, and major print media outlets.

Kitsuchart PasupaView profile

Professor

• Machine Learning
• Deep Learning
• Chemoinformatics
• +7 more

Professor Kitsuchart Pasupa, Ph.D. , is a royal-appointed full professor and Vice Dean for Research & Innovation and International Affairs at the School of Information Technology (SIT) , King Mongkut's Institute of Technology Ladkrabang (KMITL) , Thailand. He has held academic positions at the University of Southampton, University of Sheffield, University College London, IIT Patna, and several European institutes, and is a senior member of both IEEE and the Asia Pacific Neural Network Society (APNNS). Education Ph.D. in Automatic Control & Systems Engineering, University of Sheffield, UK (2007) M.Sc.(Eng) in Control Systems, University of Sheffield, UK (2004) B.Eng. in Electrical Engineering, Sirindhorn International Institute of Technology, Thammasat University, Thailand (2003) Research Focus Professor Pasupa’s research lies at the intersection of machine-learning theory and real-world applications . He designs and deploys algorithms for chemoinformatics, bioinformatics, eye-tracking analytics, cyber-bullying detection, Thai natural-language processing, multimodal fusion, time-series forecasting , and healthcare AI . His work spans from foundational reservoir computing and extreme learning machines to large-scale deep learning systems operating on mobile devices and cloud platforms. Across more than 150 refereed publications , a clear trend emerges: leveraging limited or noisy data, handling concept drift, and delivering interpretable AI solutions for socially impactful domains such as medical imaging, precision livestock farming, financial analytics, and smart-city water management. Scientific Awards & Fellowships APNNS Young Researcher Award 2019 Multiple Best Paper Awards (ICITEE 2024, KST 2019, IC2IT 2018, NCIT 2015, NCCIT 2014) KMITL Honorable Fame Awards (2014–2022) Teaching Excellence Award 2017, KMITL Commander (Third Class) of the Most Noble Order of the Crown of Thailand (2020) Companion (Fourth Class) of the Most Exalted Order of the White Elephant (2017) Grants & Supervision He has attracted >30 M THB in research funding from Thai government agencies, EU (FP7), Indian DST, and industry partners (SCB, KBTG). He currently leads a 2025-2026 KMITL grant on multimodal financial Q/A for Hindi and Thai and has completed projects on cyber-bullying in ASEAN languages, car-parts segmentation, eye-tracking, SNP analytics, waste classification, and smart farming . PhD advisees: 3 current + 6 completed Master’s & Bachelor’s student supervision: >60 theses and projects Internship teams: guided award-winning student teams in international programming contests (NAPROCK, NSC, TICTA) Laboratory & Teams His Intelligent Systems & Machine Learning Research Group at SIT-KMITL collaborates closely with IIT Patna, University of Malaya, Aalto University, and University of Leoben, maintaining an active visiting-scholar program and hosting joint workshops and data challenges. The lab focuses on reproducible research and open datasets in Thai NLP, medical imaging, and smart-city analytics.

• Japanese Language Education
• Phonetic Education
• Second Language Acquisition
• +3 more

Dr. Naoko Kinoshita is an Associate Professor at Waseda University's Center for Japanese Language , with affiliations also extending to the Global Education Center . Her career spans over two decades of research and practice in Japanese language education, phonetic acquisition, and learning advising systems. She serves on multiple academic committees including the Phonetic Science of Japan and Society of Japanese Speech Communication . Major Research Areas : Japanese language education, phonetic education, second language acquisition, language learning advising Key Sub-Fields : Japanese pronunciation pedagogy, collaborative community development, autonomous learning systems, multicultural workplace training, special mora instruction, rhythmic pattern analysis Her recent research focuses on pattern language applications for multicultural workplaces and web-based pronunciation systems like "Tsutaeru Hatsuon". The 15 most recent publications span topics from collaborative community development to phonetic learning mechanisms, with keywords showing consistent emphasis on Japanese phonology, language technology, and cross-linguistic rhythm studies. Scientific Awards : e-Teaching Award Good Practice Prize (2021) Waseda Teaching Award (2020) Waseda e-Teaching Award (2019) e-Teaching Award (2015) As lead author on multiple refereed papers, she has developed innovative phonetic learning frameworks and multilingual educational tools . Her work bridges theoretical phonetics with practical language instruction, particularly focusing on visual and kinesthetic learning methods for Japanese rhythm acquisition.

Constantino Reyes-AldasoroView profile

Senior Lecturer

• Biomedical Image Analysis
• Medical Image Processing
• Computer Vision
• +12 more

Constantino Reyes-Aldasoro is a Senior Lecturer in Biomedical Image Analysis at the Department of Computer Science, School of Mathematics, Computer Science and Engineering, City, University of London. His research focuses on the analysis, interpretation, and visualization of biomedical data, particularly in the context of cancer, inflammation, and neurodegenerative diseases. PhD in Computer Science – University of Warwick (2004) MSc in Electrical Engineering – Imperial College London (1994) Bachelor’s in Mechanical and Electrical Engineering – Universidad Nacional Autónoma de México (1993) His research spans image analysis, machine learning, and computational modeling applied to biomedical imaging, with emphasis on electron microscopy, histopathology, and radiology. He has developed algorithms for cell segmentation, vessel tracing, and tumor microenvironment analysis, contributing significantly to open-source tools in the field. His recent publications show a strong trend toward integrating deep learning with traditional image analysis, especially in cancer diagnostics and Alzheimer’s disease assessment. He has also explored topological data analysis and persistent homology for evaluating dataset consistency in colorectal cancer research. Senior Member, IEEE Member Level 1, Sistema Nacional de Investigadores CONACYT (Mexico) He has supervised multiple PhD students in areas such as HeLa cell analysis, coronary plaque detection, and Alzheimer’s imaging. He has secured grants from the Leverhulme Trust, Australian Research Council, and Cancer Research UK. He is an academic editor for journals including PLOS ONE and Journal of Imaging , and has chaired conferences like MIUA and BMVA. He is part of the giCentre research group at City, and actively promotes interdisciplinary collaboration in AI for healthcare.

• Accessibility
• Human-Computer Interaction
• Assistive Technology
• +3 more

Shiri Azenkot is an academic researcher with significant contributions to accessibility and human-computer interaction, evidenced by 93 publications, an h-index of 32, and over 3,423 citations. Her work focuses on creating inclusive technology solutions for people with visual impairments through rigorous empirical studies and user-centered design. Her research spans multiple critical areas including non-visual touchscreen interaction, assistive technologies for low-vision users, and accessibility in social media and transportation systems. Key themes include developing secure authentication methods like PassChords, vision enhancement systems like ForeSee, and studying speech input efficiency for blind mobile users. Her work consistently bridges theoretical HCI principles with practical implementations that address real-world barriers faced by visually impaired populations. Analysis of her publication trends reveals a sustained focus on participatory design approaches and empirical validation with target user groups. Her research demonstrates how accessibility innovations often benefit broader user populations while specifically empowering people with disabilities through technologies that enhance independence, safety, and social inclusion in digital and physical environments.

• Signal Processing
• Machine Learning
• Statistical Signal Processing
• +11 more

Saikat Chatterjee is a Professor in the Department of Information Science and Engineering at the School of Electrical Engineering and Computer Science, Royal Institute of Technology (KTH). He is also a Fellow of Digital Futures and maintains visiting researcher positions at Karolinska Institute, Karolinska Hospital (specializing in 'AI for Health Care'), and Oslo University Hospital in Norway. His primary research interests span Signal Processing and Machine Learning, with specific focus on signal modeling (sparsity, compressive sensing, dynamical systems), statistical signal processing, statistical machine learning, deep learning, speech/audio/image processing, medical data analytics, life science data analysis, perception for autonomous systems, distributed machine learning, and explainable AI (XAI). He particularly emphasizes explainable machine learning, having a strong background in signal processing and statistical machine learning, with growing passion for medical data analysis due to its societal importance. SSF - Swedish Foundation for Strategic Research Region Stockholm European Union Digital Futures Vinnova WASP Companies: Ericsson, Scania, Saab Professor Chatterjee is actively involved in teaching, serving as examiner and course responsible for various degree projects and courses including Machine Learning and Data Science, Pattern Recognition and Machine Learning, and Speech and Audio Processing. His research group has produced significant work across multiple domains, with notable publications in Bioinformatics and smart city applications, demonstrating the breadth of his research impact from healthcare to urban systems.