Find Academic Supervisors

Rozenn DahyotView profile

Professor

• Computer Vision
• Machine Learning
• Digital Signal Processing
• +4 more

Rozenn Dahyot is a Professor of Computer Science at Maynooth University within the Faculty of Science & Engineering. She previously held roles as Assistant and Associate Professor in Statistics at Trinity College Dublin (2008-2021) and Lecturer in Computer Science (2005-2008). Her research interests bridge Digital Signal Processing, Computer Vision, Machine Learning, and Statistical Analysis. She organized the European Signal Processing Conference (EUSIPCO2021) in Dublin and served as President of the Irish Pattern Recognition and Classification Society (IPRCS) from 2014-2020. Her work spans topics like semantic scene understanding, CNN compression, and medical image segmentation. Key contributions include advancements in graph-based image analysis, reinforcement learning optimization, and AI-driven systems for disaster management. Dahyot is a member of IEEE, ACM, and EURASIP, contributing to both academic and industrial collaborations.

• Spoken Language Processing
• Natural Language Processing (NLP)
• Paralinguistics
• +6 more

Sarah Ita Levitan is an Assistant Professor in the Department of Computer Science at Hunter College, CUNY, and a member of the doctoral faculty in both Computer Science and Linguistics PhD programs at the CUNY Graduate Center. She previously served as a Postdoctoral Research Scientist at Columbia University, where she completed her PhD in Computer Science in 2019 under Dr. Julia Hirschberg. Research Focus: Spoken Language Processing Natural Language Processing Paralinguistic Analysis Trustworthiness and Deception Detection Acoustic-Procedic and Lexical Feature Extraction Online Radicalization and Misinformation Recent Publications demonstrate expertise in analyzing speech and text for trust cues, deception detection, and mental health prediction. Her awards include grants from NSF, Google, and Columbia University fellowships. She leads the Hunter Speech Lab , mentoring PhD, MS, and undergraduate students in computational linguistics research. Scientific Awards and Grants: NSF EAGER Grant (2023) Google Cyber NYC Grant (2023) NSF AI Institute Grant (2023) Air Force Office of Scientific Research Grant (2020) Brown Institute Seed Grant (2020) Knight News Innovation Fellowship (2018) Teaching: Courses include Natural Language Processing (undergraduate/graduate), Computational Linguistics, Computer Theory, and advanced topics in spoken language processing at both Hunter College and Columbia University.

• Adult second language acquisition
• Phonetics
• Phonology
• +6 more

Shannon Barrios is an Associate Professor in the Department of Linguistics at the University of Utah, where she has served since 2022. She co-directs the Speech Acquisition Lab and specializes in second language acquisition, phonetics/phonology, and psycholinguistics. Her research explores how adult learners develop perceptual and lexical representations of novel phonological contrasts, with a focus on cross-language speech perception, orthographic effects, and social factors in input processing. BA, Spanish (SUNY Geneseo, 2004) MA, Linguistics (Syracuse University, 2007) PhD, Linguistics (University of Maryland, 2013) Her research interests span adult second language acquisition , phonolexical development , and accent bias . She investigates how learners process phonological contrasts, the role of orthography in speech perception, and the influence of social roles (e.g., teachers vs. peers) on language learning. Her work combines behavioral experiments, ERP/MEG neuroimaging, and computational modeling. Barrios’ recent publications (2024–2020) focus on representational fuzziness , talker variability , and lexical contrast mechanisms . Her 2024 Languages paper proposes a factorial typology for evaluating auditory word recognition scenarios, while her 2024 JASA Express study highlights individual listener variation in cross-language speech perception. Earlier works examine allophone acquisition, orthographic input effects, and neural correlates of phonological mapping. She has received two teaching awards from the University of Maryland (2013). Her teaching portfolio includes undergraduate and graduate courses in phonetics , psycholinguistics , and second language acquisition theory . She also leads workshops on research ethics, mentee development, and academic literacies.

Karen LivescuView profile

Professor

• Speech Processing
• Language Processing
• Machine Learning
• +5 more

Karen Livescu is a Professor at the Toyota Technological Institute at Chicago (TTIC), a philanthropically endowed graduate institute for computer science located on the University of Chicago campus. She also serves as a courtesy faculty member in the Department of Computer Science at the University of Chicago and is an Affiliated Scholar at the Data Science Institute there. Her research focuses on advancing speech and language processing through innovative machine learning approaches. Education: PhD in Electrical Engineering and Computer Science from MIT (2005) S.M. from MIT Department of Electrical Engineering and Computer Science (1999) A.B. in Physics from Princeton University (1996) Karen's research spans multiple dimensions of speech and language processing with particular emphasis on speech recognition, spoken language understanding, and multimodal processing. She has made significant contributions to articulatory feature-based speech recognition, self-supervised learning for speech representation, and sign language processing. Her work consistently bridges machine learning techniques with linguistic and speech science knowledge, focusing on creating more robust, interpretable, and inclusive speech processing systems that can handle diverse languages and modalities. Her recent publication trajectory reveals a strong focus on self-supervised learning for speech representation, multilingual speech processing, and sign language understanding. She has been instrumental in developing benchmark frameworks like SUPERB and ML-SUPERB that have become standard evaluation tools in the speech community. Her work increasingly addresses critical challenges in low-resource language scenarios, language disparities in speech technology, and ethical considerations in real-world deployment. Scientific Awards: Best Paper award at EMNLP 2024 for 'Towards robust speech representation learning for thousands of languages' Best Student Paper Award at ASRU 2023 Best Short Paper Award at CRAC 2021 Top system at WMT-SLT 2023 Karen has successfully advised numerous PhD students and postdoctoral researchers who have gone on to faculty positions at institutions like University of Waterloo, University of Edinburgh, and Stellenbosch University, as well as industry roles at major technology companies including Google, Meta, and NVIDIA. Her research group has secured significant funding for projects including the development of the SLUE benchmark for spoken language understanding and the SUPERB framework for evaluating self-supervised speech models. She has been actively involved in organizing workshops and symposia that bring together researchers in speech and language processing. Karen leads the Speech and Language at TTIC (SL@TTIC) research group, which maintains a strong collaborative relationship with researchers at the University of Chicago and other institutions. The group has been particularly active in advancing sign language processing through projects like ChicagoFSWild and OpenASL, while also making significant contributions to spoken language understanding and multilingual speech recognition. Her team regularly participates in community challenges and benchmarks, helping to push the field forward through open science and collaborative evaluation frameworks.

Stefanie JannedyView profile

Researcher

• Sociophonetics
• Language Register
• Phonetic Variation
• +4 more

Dr. Stefanie Jannedy is a senior researcher at the Leibniz-Zentrum Allgemeine Sprachwissenschaft (ZAS) in Berlin, where she has been employed since 2008. She is a Principal Investigator of the DFG project C02 "Variation in Situated Interaction" within the Collaborative Research Center 1412 (CRC 1412) on "Register: Language-Users' Knowledge of Situational-Functional Variation." As a member of the Laboratory Phonology Group, her work focuses on sociophonetic aspects of language variation. Dr. Jannedy's research centers on language register, phonetic variation, and sociolinguistic patterns in speech. Her work particularly examines how situational contexts influence phonetic detail in speech production, with a focus on intra-individual variation. She has developed innovative experimental methods, including smartphone applications like "Plapper" for self-recording speech data in controlled conditions. Her research spans formal and informal speech contexts, examining speech rate, vowel dispersion, filler particles, and other phonetic features that vary systematically across different communicative situations. Analysis of her publication record shows a strong focus on register variation, particularly how speakers systematically adjust their speech across different social contexts. Her work combines experimental methods with corpus-based approaches to investigate fine phonetic detail in relation to situational factors. Recent publications demonstrate increasing interdisciplinary connections between phonetics, sociolinguistics, and cognitive science in understanding register knowledge. Dr. Jannedy has advised several students including Schüppenhauer, Gediminas, Witt, Johannes, and Hong, Nhung-Le. Her research is primarily supported through the CRC 1412 framework, which represents a major collaborative effort in register studies. Her laboratory work involves experimental setups that simulate tele-conference interactions to systematically manipulate social contexts while measuring subtle phonetic differences. This methodological innovation allows for controlled examination of register variation that would be difficult to capture in naturalistic settings.

Alexander KollerView profile

Professor

• Computational Linguistics
• Neural-Symbolic Models
• Semantic Parsing
• +5 more

Professor Alexander Koller is a leading academic in Computational Linguistics at Saarland University's Department of Language Science and Technology. He holds a courtesy appointment in Computer Science and contributes to the Saarland Informatics Campus - one of Europe's premier computer science research centers. He leads the Computational Linguistics group and serves as speaker for the DFG-funded Research Training Group 'Neuroexplicit Models of Language, Vision, and Action'. PhD in Computer Science (Saarland University) Former positions: University of Potsdam, Columbia University, University of Edinburgh Sabbatical experiences: Meta AI (Paris), Allen Institute for AI (Seattle) His research focuses on computational modeling of meaning and reasoning in NLP, combining neural and symbolic approaches. Key contributions include semantic parsing systems like the AM parser and Alto, neurosymbolic models, and the GIVE Challenge for NLG evaluation. His recent work explores LLMs' limitations in problem-solving and compositional generalization. Recent publications highlight diverse applications across semantic parsing, dialogue systems, and LLM evaluation. Awards include ACL 2020 Best Theme Paper and multiple Outstanding Paper recognitions at ACL conferences. 2025 - AI Action Summit keynote speaker 2023 - ACL Outstanding Paper Awards 2022 - ELLIS Faculty appointment He maintains the DialogOS system for spoken dialogue development and teaches advanced computational linguistics topics. His group includes multiple postdocs and PhD students working across LLMs, dialogue systems, and semantic modeling.

Kwantae KimView profile

Assistant Professor

• Power-Efficient Analog/Mixed-Signal Integrated Circuits
• Biomedical Sensor Systems
• Neuromorphic Sensor ICs
• +3 more

Kwantae Kim is an Assistant Professor at the Department of Electronics and Nanoengineering within Aalto University's School of Electrical Engineering . He leads the Tiny Systems and Circuits (TSirc) Group , focusing on power-efficient analog/mixed-signal ICs for biomedical and neuromorphic sensor systems. IEEE Senior Member (2025) Collaborates with institutions across Europe, Asia, and America Specializes in ultra-low-power AI-embedded IoT platforms His research emphasizes Tiny, Sensory, Intelligent, and Wireless IoT systems through: Development of energy-efficient IC architectures Democratizing access to advanced chip design Hardware-software co-design for edge computing Recent publications highlight innovations in: Spoken-language-understanding SoCs Temporal-sparsity-aware keyword spotting Open-source silicon frameworks Awards include: 2025 IEEE Senior Member 2023 Best Poster Award (AICAS) 2019 Samsung HumanTech Silver Award Research partnerships span: Prof. Tobi Delbruck (UZH/ETH Zurich) Prof. Hoi-Jun Yoo (KAIST) Prof. Shih-Chii Liu (UZH) Prof. Sohmyung Ha (NYU Abu Dhabi)

• Neuromorphic Engineering
• Neural Networks
• Edge Computing
• +3 more

Shih-Chii Liu holds the rank of Privatdozent (Associate Professor) in the Department of Information Technology and Electrical Engineering at ETH Zürich. He is affiliated with the Institute of Neuroinformatics , a joint institute between the University of Zurich and ETH Zurich. His research focuses on neuromorphic engineering, bio-inspired neural hardware, and edge computing systems, emphasizing energy-efficient algorithms and sensor technologies. Key research areas include neuromorphic sensors for real-time data processing, sparsity-aware neural networks, and adaptive computing architectures for edge devices. His work spans applications such as speech enhancement, wearable health monitoring, and bio-inspired keyword spotting systems. He leads the Sensors Research Group, which develops neuromorphic systems integrating novel sensors, spiking neural networks, and low-power hardware accelerators. Recent projects include the DeltaKWS low-power keyword spotting IC, EFLOP computational cost metrics for spiking networks, and NeuroBench benchmarking frameworks for neuromorphic systems. His contributions emphasize bridging biological neural principles with practical engineering solutions for IoT and embedded systems. Liu teaches courses such as Neuromorphic Engineering I and collaborates on cross-disciplinary projects involving neuroprosthetics, smart wearables, and multimodal sensor fusion. His work is characterized by hardware-software co-design approaches to tackle challenges in real-time, low-latency, and energy-constrained computing environments.

Benoît SagotView profile

Researcher

• Natural Language Processing
• Computational Linguistics
• Machine Translation
• +7 more

Benoît Sagot is a Senior Researcher in Natural Language Processing and Computational Linguistics at Inria , currently holding the 2023-2024 Informatics and Digital Sciences Annual Chair at Collège de France. He directs the ALMAnaCH research team and contributes to the PRAIRIE Institute for AI research. Research Focus: His work spans neural language models, machine translation, text simplification, multimodal NLP, and lexical resource development for French and low-resource languages. He explores computational morphology, etymology, and historical linguistics, with applications in opinion mining and computational oenology. Recent Articles emphasize language model interpretability, cross-lingual transfer, and multimodal integration (speech, image). Tools & Resources: He has developed morphological lexicons (Le fff, Alexina), corpora (OSCAR, CAMEMBERT), and parsing pipelines (SxPipe). Projects: Involved in initiatives like ANR BASNUM (Furetière's dictionary digitization) and 3IA PRAIRIE (AI research). His career combines foundational work in syntactic analysis with evolving deep learning approaches.

• Deep Learning
• Automatic Speech Recognition (ASR)
• Spoken Language Modeling
• +3 more

Mikko Kurimo is a Full Professor at Aalto University's Department of Information and Communications Engineering, School of Electrical Engineering. He earned his M.Sc., Lic.Tech., and D.Sc.(Tech.) from Helsinki University of Technology (1992, 1994, 1997) and pioneered neural networks for automatic speech recognition (ASR) in his PhD thesis. After research roles at IDIAP (Swiss AI center) and visiting positions at University of Colorado, Edinburgh, SRI, ICSI, and Nitech, he leads Aalto's ASR group since 2000. His work focuses on unsupervised subword modeling for morphologically complex languages (Finnish, Estonian, Turkish, Arabic) and large speech foundation models. PhD in Neural ASR (Helsinki University of Technology, 1997) Research Scientist at IDIAP (Switzerland) Visiting Fellow at University of Colorado, Edinburgh, SRI, ICSI, Nitech Head of Aalto ASR Group (2000-present) His research spans deep learning for ASR, spoken language modeling , and low-resource language solutions . Recent work explores continued pre-training of self-supervised models, multimodal emotion recognition, and pronunciation assessment using LLMs. He led the winning team in the 2017 Multi-Genre Broadcast challenge and secured competitive funding in Tekes Challenge Finland and EC's H2020-ICT-2017. Key article trends include: Advancements in children's speech recognition and dysarthric speech processing Integration of generative AI for language learning feedback Specialization in low-resource Uralic languages (Finnish, Northern Sámi) Development of robust ASR systems for complex phonetic environments Scientific Awards ACM Multimedia 2023 Computational Paralinguistics Challenge Prize First place in MGB3 2017 Arabic ASR Challenge ISCA Best Student Paper Award (2011) Professeur Invité at Université de Saint-Etienne (2005-2006) Royal Society International Short Visit Fellowship (2004) Professor Kurimo leads the Speech Recognition Group at Aalto, collaborating with COIN (Centre of Excellence in Computational Inference) and AIRC (Adaptive Informatics Research Centre). His projects like CaptainA mobile app demonstrate practical applications of ASR in language education. He has supervised numerous publications with co-authors in domains spanning bandwidth extension, stuttering detection, and speech sound disorder assessment.

• World Englishes
• Corpus Linguistics
• Gender and Language
• +7 more

Prof. Robert Fuchs holds the Frommann Professorship of Applied English Linguistics at the University of Bonn, leading the Chair of Bonn Applied English Linguistics (BAEL) within the Department of English, American and Celtic Studies. His research focuses on World Englishes, corpus linguistics, sociolinguistics, and the impact of artificial intelligence on linguistic analysis. He actively supervises PhD students in topics aligned with his research group's interests, emphasizing empirical work and data science. Recent research explores language change in varieties like Hong Kong English, Trinidadian prosody, and intensifier usage across cultures. Fuchs frequently presents at international conferences, including ISLE, ICAME, and Sociolinguistics Symposium, and publishes extensively in journals like World Englishes and Language and Speech . His teaching includes advanced courses on corpus linguistics and language in culture, with a focus on climate change discourse analysis. He maintains an active academic presence through ResearchGate, Academia.edu, and LinkedIn. Research Interests: Fuchs investigates sociolinguistic variation, AI applications in linguistics, and the structural features of postcolonial Englishes. His work addresses topics such as vowel mergers in Hong Kong English, lexical stress perception in Indian English, and the role of gender in language use. He also explores diachronic changes in aspects like stative progressives and the perfect-past alternation across Asian Englishes. Advising & Grants: Fuchs oversees PhD student recruitment through research associate positions and self-funded scholarships, prioritizing applicants with strong empirical and analytical skills. His funded projects include studies on pandemic discourse (DisCOVIndUK) and linguistic trends in Caribbean English. His lab, BAEL, collaborates internationally, with ongoing work on Trinidadian prosody and Northeast Indian linguistic ecology. Labs/Teams: The Bonn Applied English Linguistics (BAEL) group, part of the University of Bonn's IAAK institute, focuses on cutting-edge research in global Englishes and computational linguistics, hosting international workshops and fostering interdisciplinary collaboration.

• Artificial Intelligence
• Natural Language Processing
• Human-AI Interaction
• +4 more

Khiet P. Truong is an Associate Professor affiliated with the Digital Society Institute and the Human Media Interaction group. Their research focuses on the intersection of artificial intelligence, robotics, and human-computer interaction, with particular emphasis on speech emotion recognition, conversational agents for children, and multimodal interaction analysis. Recent work includes exploring how robots can restore trust through apologies, benchmarking Dutch automatic speech recognition systems, and developing child-friendly interfaces for cultural heritage archives. Truong has also investigated physiological signals like laughter and stress markers in speech across diverse contexts. Scientific Awards : Best Functional Design Award (2019) Research Trends : Analysis of speech patterns, emotion recognition, robot-human dialogue, and multimodal behavioral cues dominate their recent publications. Key subfields include Dutch language processing, laughter classification, trust indicators in child-robot interactions, and healthcare applications of speech technology. Academic Activities : Chair of the 26th ACM International Conference on Multimodal Interaction (2024) Examiner roles for PhD defenses and research evaluations (2024–2023) Contributions to workshops on emotion representation and social signal processing

John W. Du BoisView profile

Professor

• Discourse and Grammar
• Sociocultural Linguistics
• Referential Pragmatics
• +6 more

John W. Du Bois is a Professor in the Department of Linguistics at the University of California, Santa Barbara (UCSB), within the College of Letters and Science. His work focuses on the interplay between discourse, grammar, and sociocultural contexts. Specializing in dialogic syntax, he explores how linguistic structures emerge from interactional dynamics, particularly in conversational coherence and stance-taking mechanisms. His research integrates corpus linguistics, computational methods, and ethnographic approaches to study languages like Mayan and Kazakh. Key research areas include: Discourse and grammar integration Dialogic resonance and affective alignment Corpus design and analysis Ritual language and cognitive models Mayan linguistic systems Recent studies emphasize computational tools like Rezonator for dialogue coherence visualization and remote corpus development methodologies. His work bridges theoretical linguistics with applied research in language documentation and education. Du Bois has contributed to foundational texts on discourse transcription standards and maintains active involvement in the Santa Barbara Corpus of Spoken American English project. His publications span over four decades, reflecting sustained engagement with linguistic complexity across multiple levels—from micro-level syntactic interactions to macro-level sociocultural frameworks. Current projects investigate dialogic syntax in autism and the evolutionary niche of language within social interaction.

Margaret E. L. RenwickView profile

Academic

• Sociophonetics
• Laboratory Phonology
• Phonetics
• +5 more

Margaret E. L. Renwick serves as Associate Research Professor and Director of Undergraduate Studies in the Department of Cognitive Science at Johns Hopkins University's Krieger School of Arts and Sciences. Previously holding a tenured position in Linguistics at the University of Georgia, she brings extensive expertise in speech variation and phonological systems to her current role. Her academic journey includes affiliation with the Phonetics Laboratory at the University of Oxford. Dr. Renwick's research focuses on sociophonetics and laboratory phonology, examining how speakers manipulate phonetic detail in patterned ways while listeners extract linguistic and social meaning from speech. Her work investigates phonological contrast, regional accents of US English (particularly Southern accents), and linguistic change across generations. A significant portion of her research explores African American vowel systems in Georgia and Italian mid-vowel systems, bridging theoretical linguistics with empirical acoustic analysis. Analysis of her recent publications reveals a strong trend toward computational approaches in phonetics, with increasing use of machine learning techniques like the Phonet library for vowel variation analysis. Her work consistently bridges theoretical phonology with empirical acoustic data, showing particular strength in regional variation studies across multiple language systems including English and Romance languages. Dr. Renwick actively mentors students through the Renwick Lab, welcoming advisees at all levels including PhD and MA candidates in Cognitive Science at JHU. Her teaching portfolio includes courses in Acoustic Phonetics, Sociophonetics, and her First-Year Seminar 'Who Has an Accent?' examines sociolinguistic perceptions of speech variation. The Renwick Lab functions as a comprehensive research environment focused on spoken language analysis, providing resources for phonetic research including tools for IPA transcription, acoustic analysis with Praat, and computational approaches to speech data. The lab supports both theoretical investigations of phonological systems and practical applications of speech technology.

Dmitri TymoczkoView profile

Professor

• Composition
• Music Theory
• Geometry of Music
• +5 more

Dmitri Tymoczko is a Professor of Music at Princeton University, where he has taught composition and theory since 2002. His work bridges the gap between academic music theory and contemporary composition, creating a unique interdisciplinary approach that has earned him recognition as a leading figure in modern music scholarship and creation. Tymoczko's research interests focus on the geometric modeling of musical structures, polystylistic composition that draws from genres spanning Renaissance to rock, and the mathematical foundations of tonality. His theoretical work explores how harmonic structures can be represented geometrically, revealing fundamental patterns that connect diverse musical traditions. He approaches composition as 'a logical deduction from absurd premises,' blending rigorous structural thinking with playful musical exploration. His scholarly publications and compositions reveal a consistent interest in the intersection of mathematical precision and expressive freedom. The articles demonstrate expertise across music theory, composition, and the cognitive aspects of musical perception, with recurring themes of geometric modeling, tonal structure, and genre hybridization. His work often challenges traditional boundaries between academic and popular music forms. Guggenheim fellowship Rhodes Scholarship Leonard Bernstein fellowship from Tanglewood Fellowship from the Radcliffe Institute for Advanced Study Block lectureship from the Society for Industrial and Applied Mathematics First music-theory article published in Science magazine Tymoczko maintains an active performance career alongside his academic work, with his compositions performed by leading ensembles including the Brentano Quartet, Newspeak, and Roomful of Teeth. His teaching integrates theoretical insights with practical composition, fostering a generation of musicians who understand music's structural foundations while embracing creative freedom. He has developed innovative tools like the musical programming language 'arca' to explore new compositional possibilities.