Find Academic Supervisors

• Data Science
• Event Detection
• Hate Speech Analysis
• +3 more

Ali Hürriyetoğlu is a dedicated researcher in the field of Data Science, actively contributing to areas such as Event Detection, Hate Speech Analysis, and Climate Change. His work is prominently featured in publications associated with the Association for Computational Linguistics (ACL) and European Union projects like EFRA and ECOREADY. He collaborates across multidisciplinary teams and focuses on advancing AI technologies for socio-political and environmental applications. Current Affiliation: Team Data Science Projects: EFRA (KB-50-005-007), ECOREADY (KB-50-005-008) Academic Role: Researcher, Project Leader, Co-promotor His research spans cutting-edge methodologies in Natural Language Processing (NLP), Explainable Artificial Intelligence (XAI), and BERT-based models, with a particular emphasis on multimodal event detection and ethical AI frameworks. In collaboration with international experts, he has published extensively on topics like hate speech classification during geopolitical crises and climate activism analysis. His recent activities include organizing workshops on AI applications for food risk prevention. While his publications highlight technical innovations in event detection (100% coverage) and climatic change analysis (50%), his work also addresses broader challenges in AI transparency and interdisciplinary collaboration. No scientific awards are documented in the provided materials, but his leadership in EU-funded projects underscores significant recognition in applied AI research.

• Medical Image Analysis
• Computer Vision
• Biomedical Imaging
• +6 more

Constantino Carlos Reyes-Aldasoro is a Professor in the Department of Electrical and Electronic Engineering within the School of Mathematics, Computer Science and Engineering at City, University of London. With an active research career spanning over two decades, he maintains a prolific publication record with recent contributions in 2025 across multiple disciplines including medical image analysis, computer vision, and biomedical engineering. His research interests focus on Medical Image Analysis, Computer Vision, Biomedical Imaging, Cancer Research, and Image Processing. His work bridges engineering and medical sciences, developing computational methods for biomedical applications. He has made significant contributions to tumor microenvironment modeling, vascular analysis, and electropalatography studies. Analysis of his recent publications reveals a strong emphasis on deep learning applications in medical imaging, with particular focus on cancer diagnostics, vascular analysis, and neuroimaging. His research demonstrates consistent methodological innovation in image processing techniques applied to biomedical problems, with publications spanning from fundamental algorithm development to clinical applications. Professor Reyes-Aldasoro has mentored numerous researchers, with several co-authors appearing consistently across multiple publications as likely students and postdoctoral researchers including C. Karabağ, J.A. Solis-Lemus, and M.A. Ortega-Ruiz. His work demonstrates interdisciplinary collaboration across engineering, computer science, medicine, and biology, reflecting the increasingly interconnected nature of modern biomedical research. He maintains active research programs with recent publications indicating ongoing projects in AI implementation in medical imaging, tumor modeling, and cardiovascular analysis.

• 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.

Vladimir GoncharoffView profile

Lecturer

• Signal Processing
• Radio Communication
• Speech Analysis
• +2 more

Vladimir Goncharoff is a Lecturer in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago (UIC). His educational background includes a Ph.D. and M.Sc. in Electrical Engineering from Northwestern University (1983, 1980), a B.Sc. in Electrical Engineering from UIC (1979), and an Associate of Science from William Rainey Harper College (1976). His research focuses on: Analog/Digital Signal Processing : Speech enhancement, spectral analysis, pitch detection, and watermark recovery. Radio Frequency Circuits : Design principles, educational methodologies, and practical applications. Acoustic Systems : Biomedical acoustics and voice communication technologies. Goncharoff's publications emphasize speech algorithms, RF circuit education, and signal reconstruction. Recent works transition toward pedagogical materials, including textbooks on radio frequency circuits (2015–2016) and signal processing (2018). Awards & Honors: UIC Silver Circle Award for Excellence in Teaching (1988, 2000, 2003, 2006, 2009) UIC College of Engineering Harold Simon Award (1985) No information is available regarding grants, student advising, or laboratory affiliations.

Haewoon KwakView profile

Associate Professor

• Network Science
• Machine Learning
• Computational Social Science
• +5 more

Dr. Haewoon Kwak is an Associate Professor at the Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington. He co-directs the Soda Lab research group with Prof. An, focusing on investigating social phenomena through large-scale data and computational tools to address significant societal challenges. His research spans multiple interdisciplinary fields including network science, machine learning, and computational social science. His work examines online social networks, social media dynamics, game analytics, computational journalism, and human-computer interaction. His research has been widely recognized, most notably for the highly cited paper 'What is Twitter, a social network or news media?' (WWW 2010) which has received over 9,500 citations. Dr. Kwak's research portfolio demonstrates consistent innovation across multiple domains. His recent publications show a strong focus on computational journalism, deep learning applications for media analysis, and understanding toxic behavior in online spaces. His work often bridges theoretical insights with practical applications for understanding information flow and social dynamics in digital environments. Outstanding PhD thesis award in Computer Science Department, KAIST Best paper award at IMC '07 for 'I Tube, You Tube, Everybody Tubes' Best paper award at SocInfo 2019 for 'Gender and Racial Diversity in Commercial Brands' Advertising Images on Social Media' Highly cited paper 'What is Twitter, a social network or news media?' (WWW 2010) with over 9,500 citations Dr. Kwak has served on program committees for major computer science and computational social science conferences. His work has been featured in prominent media outlets including Nature News, ACM Tech News, BBC, The Times, The Economist, Slate, and Scientific American. His Soda Lab at Indiana University continues to produce influential research at the intersection of computing and social science.

Yuning DingView profile

Researcher

• Natural Language Processing
• Educational Technology
• Automatic Essay Scoring
• +3 more

Yuning Ding is a PhD Student and Research Assistant in the junior research group 'EduNLP' at the Research Center CATALPA (Center of Advanced Technology for Assisted Learning and Predictive Analytics), FernUniversität in Hagen, since January 2022. Her work focuses on Natural Language Processing applications for educational technology, specifically developing systems for automatic essay scoring and generating formative feedback for learners and summative feedback for teachers. Her educational background includes: M.Sc. in Applied Cognitive and Media Science with Specialization in Cognition & Artificial Intelligence at University of Duisburg-Essen (2017-2019) B.Sc. in Applied Cognitive and Media Science at University of Duisburg-Essen (2014-2017) B.A. in Communications at University of International Relations, Beijing (2009-2013) Ding's research centers on leveraging NLP to enhance writing education through AI-driven assessment and feedback systems. Her work bridges computational linguistics and pedagogy, with particular emphasis on argument mining, cohesion analysis, and cross-lingual content scoring. She investigates how transformer models and multi-task learning can improve the reliability and educational value of automated writing evaluation, while addressing critical issues like fairness and adversarial vulnerability in scoring systems. Her research demonstrates how NLP can provide actionable insights for both students and educators in writing development. Analysis of her publication trends reveals a strategic progression from foundational work on content scoring and error analysis toward sophisticated integrated systems. Recent work emphasizes multimodal feedback generation, argument-cohesion integration, and cross-lingual transfer, with increasing focus on real-world implementation challenges including fairness, robustness, and user experience. Her research spans multiple languages and educational contexts, reflecting a commitment to globally applicable educational technology. Within CATALPA, Ding actively collaborates across disciplines through the center's vibrant knowledge-sharing culture. She participates in project presentations and colloquia that facilitate cross-pollination of ideas between computer science, linguistics, and educational theory. Her work on the DARIUS corpus and FEAT-writing system demonstrates tangible contributions to educational resource development and interactive learning environments.

François JacquenetView profile

Professor

• Machine Learning
• Data Mining
• Natural Language Processing
• +5 more

François Jacquenet is a Professor of Computer Science at the University of Saint-Etienne, where he is a member of the Machine Learning Team at the Hubert-Curien Laboratory. His research focuses on machine learning and data mining applications for natural language processing, with significant contributions to privacy-preserving systems including Hippocratic Multi-Agent Systems and Automata-Based Sequence Mining. His research interests span Machine Learning , Data Mining , Natural Language Processing , and Privacy-Preserving Systems . Jacquenet has led multiple research projects including the PASCAL II Network of Excellence (2008-2012), the Bingo2 project (2008-2010), and the Web Intelligence project (2006-2008), where he focused on ethical web design and privacy protection techniques. His work bridges theoretical foundations with practical applications in areas like fraud detection, meeting summarization, and video tag correction. Analysis of his recent publications reveals a consistent research trajectory in deep learning applications , privacy-preserving techniques , and cross-modal learning . His work shows a progression from foundational research in grammatical inference and automata theory to contemporary applications in neural networks and self-organizing systems. The publications demonstrate strong interdisciplinary connections between computer science, physics, and security applications. Best AI Paper Award at Conference (2006) Professor Jacquenet has supervised numerous PhD students including Maria Galvan, Hoang-Tung Tran, Ludivine Crépin, and Stéphanie Jacquemont. His research has been supported by significant grants including the French Research Agency (ANR), the Rhône-Alpes region, and international networks like PASCAL. He has organized multiple conferences including Privacy on the Web at the ACM Symposium on Applied Computing and the PASCAL Workshop on Teaching Machine Learning. He is actively involved with the Machine Learning Team at Hubert-Curien Laboratory , contributing to the PASCAL Network of Excellence and the REWERSE Network. His research group focuses on developing practical applications of machine learning while addressing fundamental theoretical questions in pattern mining and language learning.

Grzegorz KrynickiView profile

Researcher

• Articulatory Phonetics
• Computer Assisted Pronunciation Teaching
• Laboratory/Experimental Phonology
• +7 more

Grzegorz Krynicki is a Senior Researcher at the Faculty of English , Adam Mickiewicz University, Poznań, Poland. He leads the Speech and Language Processing Laboratory , focusing on experimental phonetics, machine translation, and computer-assisted language learning. With a Ph.D. in English (2006) and MA in English (2000) from Adam Mickiewicz University, he has contributed extensively to articulatory phonetics and Polish-English corpus linguistics. Education MA in English, Poznań (2000) Ph.D. in English, Poznań (2006) His research interests bridge Articulatory Phonetics and Machine Learning , with applications in Computer Assisted Pronunciation Teaching , Automatic Speech Recognition , and Corpus Linguistics . He has developed tools like Wordbuilder for corpus-based exercises and IPA2Polglish for phonetic transcription conversion. The articles reflect his expertise in electropalatography (EPG) for L2 pronunciation teaching, phonetic error detection in Polish learners of English, and machine translation systems like POLENG. His work spans Multilingualism , Speech Technology , and Polish-English Contrastive Analysis . Scientific Awards University of Bielefeld scholarship (1999) Professional Activities include participation in the International Society of Phonetic Sciences and development of the Speech and Language Processing Laboratory . He has presented at conferences such as the International Congress of Phonetic Sciences (2019) and Societas Linguistica Europaea meetings, often collaborating with institutions like the University of Colorado and Linköping University.

Behnaz GhoraaniView profile

Associate Professor

• Non-stationary Data Analytics
• Pattern Recognition and Information Retrieval
• Biomedical and Speech Signal Analysis
• +3 more

Behnaz Ghoraani is an Associate Professor and I-SENSE Fellow at Florida Atlantic University, holding dual appointments in the Department of Electrical Engineering and Computer Science and the Department of Biomedical Engineering. Her office is located at 777 Glades Road, EE 319, Boca Raton, FL 33431-0991. She can be contacted via phone (561.297.4031) or email (bghoraani@fau.edu). She earned her Ph.D. from Ryerson University in Toronto, Canada. Her research encompasses advanced signal processing and machine learning methodologies, with focus areas including: Non-stationary Data Analytics : Techniques for analyzing dynamic systems. Biomedical and Speech Signal Analysis : Applications in healthcare diagnostics. Machine Learning and Classification : Algorithms for pattern recognition. Time-frequency Analysis : Signal decomposition in joint domains. Dr. Ghoraani leads the Biomedical Signal and Image Analysis Lab , driving innovation in computational methods for medical and engineering challenges.

Sheila FlanaganView profile

Lecturer

• Auditory Neuroscience
• Developmental Dyslexia
• Speech Processing
• +3 more

Dr. Sheila Flanagan is an academic researcher affiliated with the Department of Psychology at the University of Cambridge and a Research Associate at the Centre for Neuroscience in Education since 2012. She serves as Director of Studies in Psychological and Behavioural Sciences and Bye-Fellow of Selwyn College. Ph.D. in Experimental Psychology (University of Cambridge) MSc in Music Technology (University of York) Background in psychoacoustics from engineering experience Her research focuses on auditory neuroscience, developmental dyslexia, and speech processing through neural entrainment. Key projects include the Botnar project (assisted listening tech for dyslexia), BabyRhythm project (auditory rhythm processing in infants), and studies of temporal sampling theory in speech encoding. Her work combines EEG analysis, motion capture, and computational modeling across neurotypical and atypical populations. Recent publications highlight trends in decoding speech from neural data, binaural temporal fine structure sensitivity, amplitude rise time processing, and cross-sectional studies of language development in Spanish-speaking contexts. She examines how cortical oscillations track speech rhythms across different modalities (acoustic/visual) and developmental stages. She collaborates with researchers such as Usha Goswami (PI of lab group), Kanad Mandke , and Áine Ní Choisdealbha . Her methodological expertise includes auditory perception studies, speech enhancement algorithms, and longitudinal neuroimaging.

Vijay ParsaView profile

Associate Professor

• Biomedical Engineering
• Acoustic Signal Processing
• Speech Processing
• +3 more

Vijay Parsa is an Associate Professor in the Department of Electrical and Computer Engineering at Western University , Canada. He holds the Oticon Foundation’s Chair in Acoustic Signal Processing, a joint position between the Faculties of Health Sciences and Engineering, focusing on interdisciplinary research in acoustic signal processing for audiology. Education: Ph.D. in Biomedical Engineering, University of New Brunswick M.E.Sc. in Electrical Engineering, University of New Brunswick B.Eng. in Electronics and Communication Engineering, Osmania University, India His research centers on acoustic signal processing for hearing aids, speech quality evaluation, and assistive listening devices. He develops algorithms for frequency compression, noise reduction, and envelope enhancement to improve speech perception for individuals with hearing loss. Prominent trends in his research include applications of machine learning and neural networks in speech processing, computational auditory modeling, and validation protocols for pediatric hearing aid fitting. His work bridges engineering and clinical audiology. Scientific Awards: Shaw Memorial Postdoctoral Award, Canadian Acoustics Association Dr. Parsa has contributed extensively to the field, with publications in journals like Ear & Hearing , Journal of the Acoustical Society of America , and IEEE Signal Processing Magazine . His work informs standards in hearing aid verification and wireless remote microphone systems.

• Psycholinguistics
• Neurolinguistics
• Language Production
• +5 more

Prof. Dr. Katharina Spalek serves as Professor of Psycho- and Neurolinguistics at Heinrich Heine University Düsseldorf's Faculty of Arts and Humanities within the Institute of Linguistics since her appointment in August 2021. Her research examines human language processing across multiple linguistic levels—from phonetics to narrative discourse—with particular emphasis on focus alternatives and memory mechanisms. Current affiliations include leadership of ERC-funded projects and active participation in international research collaborations. Her educational background spans German linguistics and psychology studies at Heidelberg University, University of Oxford, and Humboldt University Berlin, culminating in a doctoral degree from Radboud University Nijmegen (2005). Postdoctoral research followed in the USA and UK before her 2007 appointment as junior professor at Humboldt University Berlin. Spalek's research trajectory evolved from language production in monolingual/bilingual speakers toward language comprehension, investigating how humans process sounds, words, phrases, and narrative discourse. Recent work integrates electrophysiological (ERP), behavioral, and computational methods to explore focus alternatives, cross-linguistic variation (including Vietnamese tonal systems), and the interplay between linguistic and visual information. Her experimental paradigms frequently employ picture-word interference, recall tasks, and discourse analysis to uncover cognitive mechanisms underlying alternative set representation. Analysis of her 15 most recent publications (2019-2024) reveals three dominant trends: (1) neurocognitive investigation of focus alternatives using ERP methodology, (2) cross-linguistic studies of intonation and tonal processing, and (3) computational modeling of human performance in language tasks. These works consistently bridge theoretical linguistics with experimental validation, emphasizing memory encoding for contextual alternatives and individual differences in processing. ERC Starter Grant for 'focus alternatives in the human mind' (2016) Posterpreis at 17th Herbsttreffen Patholinguistik (2023) Her ERC-funded research program examines how focus particles and pitch accents modulate alternative set representation in production and comprehension. Current projects investigate neural correlates of discourse memory, Vietnamese intonation patterns, and computational models of human language processing limitations. Collaborative work spans institutions in Germany, Netherlands, and Vietnam, with methodological emphasis on controlled experiments and cross-linguistic comparison. Spalek leads the Psycho- and Neurolinguistics research group within the Institute of Linguistics, utilizing facilities for ERP recording, eye-tracking, and behavioral experimentation. Her team conducts interdisciplinary research at the intersection of linguistics, cognitive science, and neuroscience, with particular focus on how information structure shapes language processing and memory.

• Machine Learning
• Algorithmic Fairness
• Data Ethics
• +5 more

Sorelle Friedler is the Shibulal Family Professor of Computer Science at Haverford College and a Nonresident Senior Fellow at The Brookings Institution. Her work centers on algorithmic fairness, transparency, and policy, including co-authoring the White House AI Bill of Rights. Ph.D. in Computer Science from the University of Maryland, College Park B.A. from Swarthmore College Research interests include fairness in machine learning , accountability frameworks , and responsible AI , with applications to social networks, materials science, and civic systems. Her recent publications focus on network equity , generative AI bias , and policy-compliant algorithms . Key scientific awards include the Data and Society Research Institute Fellowship. She has secured grants from NSF, DARPA, and Mozilla for projects on algorithmic fairness and responsible computing.

Xenia KlingeView profile

Researcher

• Natural Language Processing
• Computational Linguistics
• Chatbots
• +8 more

Xenia Klinge is a Data Scientist and Computational Linguist at the German Research Center for Artificial Intelligence (DFKI), based at the Saarland Informatics Campus in Saarbrücken and working in Berlin. Her research focuses on human-centric intelligent applications for health, wellbeing, and recreation, particularly in Natural Language Processing , Chatbots , Computational Creativity , and Storytelling in Conversational Systems . Research Interests: Automatic creativity and storytelling in conversational systems Language and conversation in healthcare contexts Behavior Change Support Systems Integration of VR/AR/XR with AI for LARP/roleplaying Computational applications in mental health awareness Hybrid approaches with Large Language Models Publication Trends: Her work spans NLP applications in chatbots, predictive maintenance, and affective computing for mental health. Key subfields include dialogue systems, speech analysis for psychological assessment, and AI-driven gamification for behavioral change. Labs & Teams: Xenia is affiliated with the Ubiquitous Media Technology Lab (UMTL) and collaborates with multidisciplinary teams in Berlin and Saarbrücken.

Jean-Louis GutzwillerView profile

Researcher

• Image Processing
• Signal Processing
• Computer Vision
• +3 more

Jean-Louis Gutzwiller is a Researcher at the Lorrain Laboratory for Research in Computer Science and its Applications (LORIA), a joint research unit of CNRS, Inria, and the University of Lorraine, focusing on advanced image processing and compression techniques for hyperspectral data and transportation systems. His work bridges theoretical signal processing with practical applications in remote sensing and intelligent infrastructure. His research spans hyperspectral image compression, wavelet transforms, vehicle-to-road communication systems, and speaker diarization algorithms. Key contributions include developing exogenous quasi-optimal spectral transforms for MERIS satellite data, optimizing SPIHT coders for hyperspectral imaging, and pioneering electromagnetic loop-based vehicle detection systems. His methodology emphasizes low-complexity solutions suitable for onboard satellite processing and real-time applications. Analysis of his 11 publications (2022-2025) reveals a dominant focus on hyperspectral compression techniques, particularly using exogenous transforms and zero-tree coding for remote sensing data. Secondary themes include vehicle infrastructure communication systems and neural gas algorithms for audio processing. His work consistently addresses computational efficiency challenges in resource-constrained environments like satellite platforms. Gutzwiller operates within LORIA's collaborative framework, contributing to France's national research ecosystem through partnerships with CNRS and Inria. His laboratory affiliation enables interdisciplinary work spanning computer science, aerospace engineering, and transportation technology, with practical implementations in earth observation and smart mobility systems.