Find Academic Supervisors

• Computational Linguistics
• Natural Language Processing
• Applied Linguistics
• +7 more

Pablo Gamallo Otero is a Professor in the Department of General Linguistics at the University of Santiago de Compostela (USC), Spain. He is actively engaged in teaching and research, with a strong focus on computational linguistics and applied linguistics. He contributes to multiple degree programs including Spanish, Galician, English, Classical Philology, and Modern Languages and Literatures, and is affiliated with the Research Group in Computational Linguistics at USC. His research interests center on computational approaches to language, particularly in the development and application of language technologies. Key areas include Natural Language Processing (NLP), multilingual modeling, lexical semantics, and syntax. His work bridges theoretical linguistics with practical applications in artificial intelligence and digital humanities. The trends in his academic profile indicate a deep integration of linguistic theory with technological innovation, especially in the context of Romance and minority languages. His involvement in AI and applied linguistics programs reflects a forward-looking research agenda aligned with modern computational challenges in language understanding. Scientific Awards: No specific awards mentioned in the provided text. He advises students at both undergraduate and postgraduate levels, particularly within the Master in Applied Linguistics and Master in Artificial Intelligence. While specific grants are not listed, his research group affiliation suggests ongoing project-based funding and collaborative research activity. He is a key member of the Research Group in Computational Linguistics at the University of Santiago de Compostela, which focuses on the development of NLP tools and resources for Galician, Spanish, and other languages. The group likely engages in interdisciplinary projects involving machine learning, language modeling, and linguistic resource creation.

Susana S. FernándezView profile

Professor

• Foreign Language Pedagogy
• Second Language Pedagogy
• Intercultural Semantics/Pragmatics
• +7 more

Susana S. Fernández is a Professor at the Department of German and Romance Languages, School of Communication and Culture, Aarhus University, Denmark. She holds leadership roles as head of the Study Board for Theoretical Pedagogical Education for Upper Secondary School Teachers, co-head of the research program Language and Communication , and head of the research unit Language Acquisition and Pedagogy . Her research is centered on foreign and second language pedagogy, with a strong emphasis on intercultural semantics and pragmatics, grammar teaching, teacher cognition, and Spanish linguistics. Her research interests include: Foreign and second language pedagogy Intercultural semantics and pragmatics Grammar instruction and teacher cognition Spanish language acquisition Corpus linguistics and Spanish linguistics Pragmatic competence in adult learners The recent publications (2020–2025) reflect a consistent focus on communicative language teaching, intercultural competence, and the cognitive aspects of grammar instruction. Her work bridges theoretical linguistics with practical classroom applications, particularly in Danish as a second language for adult migrants and teacher training contexts. She frequently engages in national discourse on language education policy. Her scientific awards include: To-årigt post-doc stipendium (2007) for research on cognitive-based grammar teaching Velux Foundation stipendium (2022) Susana S. Fernández actively supervises and mentors through her leadership in research programs and projects. She has led or participated in numerous research projects, including the Velux-funded Danish in the Making , and contributes to academic service through peer review, editorial work, and organizing workshops and conferences. Her work is supported by external grants and institutional collaboration. She is actively involved in research networks and collaborative projects such as Emancipatory Ethnopragmatics and Ethnopragmatics for Intercultural Competence (EPIC) , which aim to integrate cultural values and communicative styles into language education. Her current projects extend into 2027, indicating sustained research activity.

Michael WhiteView profile

Professor

• Computational Linguistics
• Natural Language Generation
• Spoken Language Dialogue Systems
• +3 more

Michael White is a Professor in the Department of Linguistics at The Ohio State University, specializing in computational linguistics, natural language generation, and spoken language dialogue systems. He holds a Ph.D. in Computer Science from the University of Pennsylvania and has collaborated with interdisciplinary teams in both academia and industry, including roles at CoGenTex, Inc., and visiting positions at Facebook/Meta and Australian universities. His research emphasizes controllable and ethical AI, with a focus on neural language models and their applications in healthcare and conversational systems. Education: Ph.D. in Computer Science, University of Pennsylvania. Professional Background: Former Research Fellow at the University of Edinburgh School of Informatics, and founder of CoGenTex, Inc. Collaborations include researchers in Computer Science and Linguistics at Ohio State, such as Eric Fosler-Lussier and William Schuler. Research Interests: Neural language generation controllability, ethical AI alignment, discourse processing, and conversational systems. Recent projects include developing virtual patient simulators for medical education and exploring knowledge distillation to mitigate AI-generated harm. Articles Trends: Focused on advancing neural NLG techniques, improving dialogue system safety, and leveraging large language models for domain-specific tasks (e.g., healthcare, KBQA). Recent work addresses transparency, data efficiency, and ethical implications in AI. Scientific Awards: Lumley Interdisciplinary Research Award (2023), PRE Accelerator Award. Grants: Supported by interdisciplinary initiatives such as the virtual patient project collaboration with Eric Fosler-Lussier and Laura Wagner. Advising and Grants: Mentors students in computational linguistics and leads projects funded by Ohio State’s interdisciplinary programs. Current work involves neuro-symbolic approaches for patient preparation assistants and data-efficient conversational AI. Labs/Teams: Collaborates with the Ohio State Computational Linguistics Group and industry partners. Active in organizing workshops on discourse-driven NLG and ethical AI challenges.

Ekaterina ShutovaView profile

Associate Professor

• Natural Language Processing
• Machine Learning
• Multimodal Learning
• +3 more

Ekaterina Shutova is an Associate Professor at the Institute for Logic, Language and Computation (ILLC) within the Faculty of Science at the University of Amsterdam and a Visiting Associate Professor in Stanford University's Computer Science Department. She leads the Amsterdam Natural Language Understanding Lab and the NLP & Digital Humanities research unit while serving as an ELLIS Scholar. Her educational background includes a PhD from the University of Cambridge Computer Laboratory and Pembroke College, preceded by positions as a Leverhulme Early Career Fellow at Cambridge and Research Scientist at UC Berkeley's International Computer Science Institute. Shutova's research centers on natural language processing with machine learning from linguistic and multimodal data. Key interests include few-shot learning for NLP, multilingual systems, language-vision joint modeling, cognitive semantic representation, figurative language processing, and computational social science applications. Her work bridges computational linguistics, cognitive neuroscience, and AI ethics to develop culturally sensitive language technologies. Recent publications reveal strong trends toward multimodal cultural value alignment, metaphor understanding in LLMs, and cognitive modeling of language processing. Her research increasingly addresses societal implications through hate speech detection frameworks and cultural bias mitigation in vision-language systems. Major recognitions include: ERC Consolidator grant for "Towards globally accessible language technology and its alignment to cultural contexts" Outstanding Paper Award at ACL 2023 for work on NLP superhuman performance claims Finalist for TMLR Outstanding Certification for "Beyond the Imitation Game" AI Democratization grant from UvA RPA Human(e) AI for "AI clinics against hate speech" ELLIS Scholar designation Her research program is supported by ERC, Innovate UK, British Academy, and Leverhulme Trust grants alongside industrial funding from Google, Meta, and Deloitte. Current projects include benchmark development for abusive language detection and emotion-inducing communication strategies for misinformation identification. As leader of the Amsterdam Natural Language Understanding Lab, she directs interdisciplinary teams developing culturally aware language technologies while serving as ACL 2025 program co-chair to shape NLP research directions.

Ielka van der SluisView profile

Senior Lecturer

• Human Communication
• Information Presentation
• Human-Computer Interaction
• +3 more

Dr. Ielka van der Sluis is a Senior Lecturer at the Department of Communication and Information Science, Faculty of Arts at the University of Groningen since 2011. She holds a PhD in Computational Linguistics from Tilburg University (2005) and has held research positions at Trinity College Dublin (2008–2011), the University of Aberdeen (UK), and the University of Twente. Her research focuses on human communication, multimodal interaction, natural language generation, and affective computing. She is a member of the Center for Language and Cognition Groningen and has contributed to projects like TUNA (EPSRC-funded), the OLIVE EC project, and the PAT framework for multimodal instruction analysis. Her work bridges computational linguistics and human-computer interaction, emphasizing the design and evaluation of multimodal systems. She has explored topics such as cross-linguistic referring expression generation, affective text impact, and procedural instruction design. Key contributions include developing the PAT annotation model for multimodal instructions and investigating cross-cultural assessment of automated referring expressions in virtual environments. Her research history spans over two decades, with impactful contributions to the understanding of text-picture alignment in procedural instructions, action categorization in multimedia, and user-centric evaluation frameworks. She collaborates internationally, particularly in computational linguistics and next-generation localization technologies.

Nina VyatkinaView profile

Professor

• Second Language Acquisition
• Corpus Linguistics
• Data-Driven Learning (DDL)
• +3 more

Nina Vyatkina is a Professor of German Studies at the University of Kansas, specializing in second language acquisition and corpus linguistics. Her research focuses on data-driven learning (DDL) methodologies, incorporating corpus analysis into language teaching, and leveraging technology for improved L2 proficiency. She has contributed extensively to understanding how learners develop grammatical and pragmatic competence through corpus-informed pedagogy. Her work spans multiple aspects of language education, including the design of digital tools for vocabulary and writing instruction, the integration of corpus resources into classroom activities, and the evaluation of written corrective feedback strategies. Key areas of interest include learner corpus analysis, multilingual corpus applications, and the theoretical foundations of DDL frameworks. Dr. Vyatkina’s publications reflect a strong emphasis on empirical research methods, often combining quantitative and qualitative approaches to examine learning outcomes. Her studies frequently address under-researched areas such as data-driven learning in non-English languages and the longitudinal development of syntactic and pragmatic competence in L2 German. While no specific awards or grants are listed, her prolific publication record highlights sustained engagement with cutting-edge issues in language education. She maintains an active role in curriculum development at the University of Kansas, focusing on innovative approaches to German language instruction and materials design.

Gullal Singh CheemaView profile

Researcher

• Multimodal Learning
• Natural Language Processing
• Computer Vision
• +3 more

Gullal Singh Cheema is a Researcher at the Leibniz Information Centre for Science and Technology (TIB) within the Visual Analytics research group (Program Area C - Research and Development). His work bridges computer vision and natural language processing to advance multimodal analysis in digital media contexts. His research spans multimodal learning, natural language processing, and computer vision with emphasis on fact-checking systems, claim detection, and social media analytics. Key contributions include the MM-Claims dataset for multimodal verification and leadership in the CLEF CheckThat! lab series addressing political bias and news source authority. His work integrates visual and textual evidence for applications in news analysis, event-centric knowledge graphs, and wildlife conservation. Recent publications (2021-2023) reveal a concentrated focus on multimodal news verification, with significant output in CLEF and SemEval evaluation campaigns. His research demonstrates consistent innovation in fusing transformer architectures with syntactic features while expanding into multilingual sentiment analysis and misogynistic meme detection. Cheema actively shapes the research community through workshop organization (MUWS'22) and dataset development. His Visual Analytics group at TIB drives methodological advances in multimodal understanding with direct applications for social media monitoring and digital humanities.

Marta Ruiz Costa-JussàView profile

Professor

• Machine Translation
• Natural Language Processing
• Artificial Intelligence
• +6 more

Marta Ruiz Costa-Jussà is a Professor at the Faculty of Informatics of Barcelona (FIB), part of the Universitat Politècnica de Catalunya · BarcelonaTech (UPC). She is affiliated with the Department of Computer Science and holds additional teaching roles at the Escola Tècnica Superior d'Enginyeria de Telecomunicació de Barcelona (ETSETB). She is also the academic co-director of the postgraduate program Artificial Intelligence with Deep Learning at UPC School. Her research is conducted through key UPC research groups: Intelligent Data Science and Artificial Intelligence (IDEAI), the Center for Technologies and Applications of Language and Speech (TALP), and the Speech Processing Group (VEU). Her research focuses on advancing machine translation through deep learning, particularly in multilingual and low-resource settings. She investigates neural machine translation (NMT) systems that use intermediate mathematical representations (interlingua) to improve efficiency and inclusivity across majority and minority languages. A significant emphasis of her work is on ethical AI, aiming to detect and mitigate biases in translation systems. She is also pioneering research in automatic speech translation, a domain not yet fully mastered by major tech companies. Her recent publications reflect a strong trajectory in neural machine translation, multilingual representation learning, speech-to-speech translation, and ethical considerations in AI. The research trends show a consistent focus on inclusivity, efficiency, and robustness in language technologies, with applications spanning text, voice, and cross-lingual understanding. Scientific Awards: ERC Starting Grant (€1.5 million) for the LUNAR project Google Faculty Research Award (2019) Google Faculty Research Award (2020) She has secured significant research funding, notably the ERC Starting Grant, which supports her vision for lifelong universal language representation. Her advising likely includes graduate students in AI and NLP, though specific names are not listed. She has collaborated internationally with institutions such as LIMSI-CNRS (France), University of São Paulo (Brazil), Infocomm Research Institute (Singapore), National Polytechnic Institute of Mexico, and the University of Edinburgh (UK). She is a core member of several research teams: the IDEAI research center, TALP, and the VEU group. These labs focus on cutting-edge AI, data science, language technologies, and speech processing, providing a rich interdisciplinary environment for her work on inclusive and ethical machine translation systems.

Mounika MarreddyView profile

Researcher

• Natural Language Processing
• Machine Learning
• Human-AI Alignment
• +5 more

Mounika Marreddy is a Postdoctoral Researcher at Goethe-Universität Frankfurt am Main, focusing on advancing Natural Language Processing (NLP) through interdisciplinary research that bridges machine learning, cognitive science, and multilingual language modeling. Her work explores the alignment between human and AI annotations, brain activity prediction using language models, and addressing challenges in low-resource languages like Telugu. Research Focus : Human-AI annotator alignment across NLP tasks (e.g., sentiment analysis, stance detection) Task effects on concept representation in neural models Development of Telugu-specific NLP datasets and pretrained models (ELMo-Te, BERT-Te) Neuroimaging studies linking syntactic processing to brain activity Publications : Her research has been published in top-tier venues such as the European Conference on Information Retrieval (ECIR), ACL Findings, IEEE ICASSP, and ACM Transactions, with recent work on the USDC dataset for dogmatism analysis and robustness in transformer models. She actively collaborates with researchers like Alexander Mehler and Manish Gupta.

Ian LaneView profile

Associate Professor

• Natural Language Processing
• Speech Recognition
• Machine Translation
• +5 more

Ian Lane is an Associate Professor in the Computer Science and Engineering Department at the University of California, Santa Cruz's Baskin Engineering school, serving as Program Director for the Natural Language Processing Professional Master's Degree Program. He joined UCSC in Fall 2022 after an extensive career spanning academia and industry. His research centers on computational systems that understand spoken human language, spanning speech recognition, transcription, meaning interpretation, and contextually appropriate responses. Key research areas include: Natural Language Processing for real-world applications Conversational AI systems development Speech-to-speech translation technologies Multimodal interaction (audio-visual integration) Language technologies that learn through real-world interaction His recent publications demonstrate strong focus on hallucination detection in LLMs, tabular data understanding, explainable AI, and robust speech recognition systems. Current work emphasizes "in the wild" language technologies that adapt through user interaction. Dr. Lane has received recognition through impactful industry applications including Jibbigo (the first mobile speech translation app) and military translation systems deployed in Iraq and Afghanistan. He actively mentors students and collaborates across UCSC's Silicon Valley Campus programs including Games and Playable Media and Human-Computer Interaction. His vision includes integrating NLP with virtual environments for language learning and skill acquisition.

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

Dietrich Klakow is a prominent researcher at Saarland University in Saarbrücken, Germany, with an extensive publication record spanning from 1997 to 2025. His work primarily focuses on natural language processing, speech recognition, and machine learning with significant contributions to multilingual models and African language processing. His research interests span a wide range of topics within computational linguistics and artificial intelligence. Klakow has made substantial contributions to Natural Language Processing , particularly in multilingual contexts and low-resource languages. His work on African language technologies has been particularly impactful, developing resources and models for languages that are often neglected in mainstream NLP research. He has also conducted significant research in speech recognition , transformer models , and computational linguistics , with a focus on practical applications and theoretical foundations. Klakow's recent publications demonstrate a strong focus on large language models, their capabilities, limitations, and applications across diverse linguistic contexts. His work spans both theoretical investigations of model architectures and practical applications addressing real-world challenges in language technology. His collaborative work spans numerous international partnerships, particularly with researchers working on African language technologies and multilingual NLP systems.

• Artificial Intelligence
• Natural Language Processing
• Knowledge Management
• +7 more

Jorjeta Jetcheva is an Assistant Professor in the Computer Engineering Department at San José State University, part of the Charles W. Davidson College of Engineering. She brings extensive industry experience from leadership roles at Accenture, Fujitsu Laboratories of America, Itron, and Firetide, where she led innovations in AI, smart grids, and wireless networking. Her research focuses on Artificial Intelligence-based Personal Assistants, Natural Language Processing, and Knowledge Management . Her work bridges human-centered AI and enterprise applications, with emphasis on intelligent agents, knowledge platforms, and ethical AI systems. She explores how AI can enhance user productivity, decision-making, and system security across domains such as healthcare, energy, and customer service. The recent publications highlight a strong trend in Natural Language Processing applied to real-world problems like fake health news detection, agent assist systems, and knowledge graph integration. Her research also spans Smart Grid analytics, cybersecurity, and AI ethics , reflecting a multidisciplinary approach grounded in both theoretical rigor and practical deployment. Scientific Awards: Best Application Paper Award at IEEE Big Data Service 2022 Best Paper Award at SmartGridComm 2014 Top 10 Finalist, Fujitsu Next Generation Product Idea Contest 2016 ('Robo Butler') CSU STEM-NET Faculty Fellow (2023) Advising and Grants: Professor Jetcheva is the Principal Investigator of a $2.5 million NSF S-STEM grant titled 'Empowering Students to Succeed in Engineering and Computer Science'. She actively mentors graduate students, including Master’s student Garima Chaphekar, with whom she co-authored an award-winning paper on fake health news detection. She serves on the SJSU AI Advisory Committee and leads the AI Research Cluster, fostering interdisciplinary collaboration and student success. Labs and Teams: She leads the AI Research Cluster at SJSU, promoting innovation in artificial intelligence across departments. Her work involves close collaboration with students, industry partners, and interdisciplinary teams focused on deploying scalable, ethical AI solutions.

• Natural Language Processing
• Dialogue Systems
• Machine Translation
• +2 more

Luísa Coheur is an Associate Professor at the Department of Computer Science , Instituto Superior Técnico (University of Lisbon), and a researcher at INESC-ID 's Human Language Technologies group. She served on the Management Committee of IST-Taguspark (2020-2023), overseeing pedagogical organization and library services. Education: Ph.D. in Natural Language Processing (IST/Université Blaise-Pascal) Postgraduate in Higher Education Pedagogy (University of Lisbon, 2023) Degree in Applied Mathematics and Computer Science (IST) Research Interests: Specializes in NLP with focus areas in: Dialogue systems and conversational AI Machine translation (including Portuguese Sign Language) Question answering architectures Educational technology and accessibility Cyberbullying detection in social media Her work integrates linguistic theory with machine learning for real-world applications. Publication Trends: Over 120 publications emphasizing machine translation evaluation (e.g., fine-grained error detection), NLP for social good (cyberbullying datasets), sign language processing, and educational tools. Recent works leverage active learning and transformer models for low-resource scenarios. Awards: IST Outstanding Teaching Award (2023) Recognized as 'Excellent Professor' >20 times via IST QUC Advising & Projects: Supervised 10+ PhD and 80+ Master's students. Secured participation in 17 national/international projects (e.g., EU-funded initiatives in NLP). Leads pedagogical innovation like educational escape games for STEM courses. Labs/Teams: Core member of INESC-ID's Human Language Technologies group , developing resources for Portuguese NLP. Collaborates with clinicians on assistive tech (e.g., VITHEA-Kids for autism language skills).

Jens NirmeView profile

Associate Professor

• Gesture Psychology
• Comprehension Psychology
• Children Psychology
• +5 more

Jens Nirme is an Associate senior lecturer and researcher in Cognitive Science at the Department of Philosophy, Lund University. He is affiliated with multiple research groups including The Educational Technology Group, LAMiNATE (Language Acquisition, Multilingualism, and Teaching), and the LU Profile Area: Natural and Artificial Cognition. His primary research location is at the VR Lab in the LUX building (Room B467) at Helgonavägen 3, Lund. His research focuses on gesture psychology, comprehension, children's cognition, virtual reality applications, speech perception, and metaphor. His work explores how nonverbal communication, particularly gestures, influences language processing, memory, and learning. He investigates these phenomena through both traditional experimental methods and innovative virtual reality environments. Nirme's publication record shows consistent output with 18 research outputs including 10 articles, 3 abstracts, 2 conference papers, and edited volumes. His recent work (2022-2024) demonstrates a strong focus on virtual reality learning environments, gesture-speech interactions, and educational applications of cognitive science. His research shows interdisciplinary collaboration across psychology, linguistics, education, and technology fields. Nirme has been actively involved in supervising master's students and engaging with schools through educational technology projects. His research has been supported by multiple projects including VEER (2019-2023), Teaching and learning in diverse classrooms (2016-2020), and Virtuellt klassrum som forskningsplattform (2016-2021). He is part of the Cognition & Philosophy VR Lab at Lund University, where he conducts research on human-computer interaction, virtual learning environments, and multimodal communication. His work bridges theoretical cognitive science with practical educational applications, particularly in understanding how nonverbal factors influence language comprehension and learning.

Leo LeppänenView profile

Researcher

• Natural Language Generation
• Educational Data Mining
• Learning Analytics
• +3 more

Leo Leppänen is a Postdoctoral Researcher at the University of Helsinki's Department of Computer Science, currently working at the MOOC Center. His research spans automated natural language generation, educational data mining, learning analytics, and computer science education. PhD in Computer Science (2023) MSc in Computer Science (2017) BA in Language Technology (2015) His work investigates AI-generated content applications, particularly LLMs' impact on education and journalism. Recent projects include analyzing student confidence gaps, studying AI ethics in MOOCs, and developing cross-lingual embeddings for news media. Research trends show increasing focus on Large Language Models (LLMs), with studies comparing pre- and post-LLM student responses, analyzing LLM integration in classrooms, and exploring AI's role in journalism. His publications span conferences like AIED, ITiCSE, and Koli Calling. Pro Gradu Award for Exceptional Master's Thesis (2017) Researcher of the Year Award (2018) Active in academic service, Leppänen serves as Programme Committee Member for ACM conferences and peer-reviewer for Journalism Practice journal. His projects include RAPHAEL (Planetary Health Education) and Generative AI in Journalism (2025-2028).