Find Academic Supervisors

• Medical Translation
• Speech-to-Sign Translation
• Pictograph Communication Systems
• +7 more

Johanna Gerlach is a Professor at the Faculty of Translation and Interpretation at the University of Geneva, affiliated with the TIM/ISSCO research group. With an extensive publication record spanning from 2010 to 2025, she has established herself as a leading researcher in the field of medical translation technology and accessible healthcare communication. Her research focuses on developing innovative translation systems that bridge communication gaps in medical settings, particularly through her work on the BabelDr platform and PROPICTO project. Dr. Gerlach's work spans multiple dimensions of accessible communication including speech-to-pictograph translation systems, sign language production for healthcare, and multilingual medical communication solutions for emergency departments. Her research demonstrates a strong commitment to improving healthcare accessibility for non-native speakers and people with communication difficulties. Analysis of her recent publications (2023-2025) reveals a clear trend toward practical implementation of translation technologies in real-world healthcare settings, with particular emphasis on emergency medicine contexts. Her work integrates computational linguistics, machine learning, and human-centered design to create accessible communication tools that address critical gaps in multilingual healthcare delivery. The research spans both contemporary medical communication challenges and historical text processing applications. Dr. Gerlach has supervised 3 academic works and maintains an active research program with numerous ongoing projects including UNI-ACCESS (focusing on web accessibility for higher education institutions) and PASSAGE (addressing Swiss German TV content subtitling). Her collaborations span multiple disciplines including medical informatics, computational linguistics, and accessibility studies.

• Applied Linguistics
• Syntax
• English Language Syntax
• +5 more

Brett Reynolds is an Adjunct Professor at the University of Toronto (St. George Campus). His research focuses on English syntax, particularly determiners, pronouns, and syntactic annotation. He explores intersections between cognitive and functional linguistics, and questions regarding the philosophy of grammaticality. Fields: Applied Linguistics, Syntax, Syntactic Annotation Key Interests: Determiner systems, functional syntax, cross-disciplinary grammatical theory His recent publications (2021-2025) analyze negation structures across languages, adverbial categorization debates, and introductory syntax pedagogy. No major awards are listed, though his work contributes to foundational linguistic theory. No advising/grants information available. Research activities include treebanking projects and theoretical syntax development.

Olac FuentesView profile

Associate Professor

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

Olac Fuentes is an Associate Professor in the Computer Science Department at the University of Texas at El Paso. His primary research focuses on developing machine learning systems for scientific data analysis, with applications in astronomy, geology, biology, and optics. He specializes in leveraging unlabeled data, active learning, feature selection, and noise-aware algorithms to extract insights from complex datasets. Education: B.S. in Industrial Engineering from Instituto Tecnológico de Chihuahua M.S. in Computer Science from University of Texas at El Paso Ph.D. in Computer Science from University of Rochester Research Focus: Dr. Fuentes develops intelligent systems for interdisciplinary scientific challenges. His work spans machine learning theory (optimization, noise handling) and applied domains including: computer vision for environmental monitoring (Arctic change detection, glacier segmentation), neuroinformatics (brain mapping), and multimodal data fusion (prosodic analysis for communication disorders). He frequently employs deep neural networks, active learning, and novel regularization techniques. Publication Trends: Recent works demonstrate strong cross-disciplinary focus on climate science (satellite image analysis for coastal erosion), biomedical applications (neuroanatomy mapping, histology), and fundamental ML theory. His publications consistently integrate advanced neural architectures (CNNs, LSTMs) with domain-specific challenges in geosciences, neuroscience, and linguistics.

Aleksandra ĆwiekView profile

Researcher

• Linguistics
• Phonetics
• Phonology
• +7 more

Aleksandra Ćwiek is a Researcher at the Leibniz Centre General Linguistics (ZAS), Berlin, where she leads the DFG project FLESH (On the Flexibility and Stability of gesture-speech coordination). She holds a Ph.D. in General Linguistics from Humboldt-Universität zu Berlin (2022) and has held roles such as Deputy Equal Opportunities Officer at ZAS and Mentee in the Leibniz Mentoring Program. Her research focuses on acoustic/prosodic iconicity, sound symbolism, and multimodal communication, with cross-linguistic studies exploring gesture-speech coordination and language evolution. Education includes a Master's in Linguistics from Bielefeld University (2016) and a Bachelor's in Linguistics/German as a Foreign Language (2015). She co-initiated envisionBOX , a platform for multimodal data analysis. Research interests span linguistic prominence, kinematic properties of gestures, and the evolution of language. Awards include the 2024 DGfS Wilhelm von Humboldt Young Talent Award. Her work bridges experimental phonetics, cognitive linguistics, and computational methods, with recent contributions to special issues on iconicity and sound symbolism.

Kazuhiro AokiView profile

Associate Professor

• Analytical Methodologies
• Multi-Omics Analysis
• Mass Spectrometry
• +3 more

Kazuhiro Aoki, PhD, is an Associate Professor at the Medical College of Wisconsin (MCW) and Technical Director of the Translational Metabolomics Shared Resource at the MCW Cancer Center. Previously, he served as faculty at the University of Georgia (2008-2022) and as an invited professor at Lille University of Science and Technology, France (2017). His expertise spans analytical methodologies for multi-Omics studies, mass spectrometry-based technologies, and glycomics research. Dr. Aoki holds a PhD in Life Science from Kyoto University (2001) and advanced training in glycobiology and pharmaceutical assessment. Education: PhD in Life Science, Kyoto University, Japan (2001) MS in Science Pedagogy, Shiga University, Japan (2000) BS in Science, Shiga University, Japan (1995) Research Focus: Dr. Aoki develops and applies cutting-edge glycomics tools to study biomolecule structure-function relationships across organisms, including embryonic stem cells, cancer tissues, and microbial systems. His work emphasizes multi-Omics integration, with applications in drug metabolism, disease progression (e.g., Fabry disease), and cell differentiation mechanisms. Key techniques include mass spectrometry-based glycoproteomics and linked-Omics approaches. Grants & Labs: Led development of MicroGlycoDB, a microbial glycan database Pioneered tools like DANGO for glycolipidomics analysis Collaborates internationally on glycobiology projects Labs/Teams: Directs the Translational Metabolomics Shared Resource, supporting metabolomic and glycomic analyses for cancer research.

Yu LiuView profile

Professor

• Sustainable Computing
• Energy-Efficient Software
• Programming Languages
• +3 more

Yu Liu is a Professor at the School of Computing, Binghamton University, where he has been a faculty member since 2008. His research focuses on sustainable computing, energy efficiency, and security in emerging software systems, with significant contributions to programming languages, robotics, and software-hardware interfaces. Education: MSE, Johns Hopkins University PhD, Johns Hopkins University Professor Liu's research centers on sustainable computing and energy-aware software systems. He investigates programming language designs for energy prediction, develops reliable robotics software through managed languages, and creates secure software-hardware interfaces. His work bridges theoretical foundations with practical applications in data centers, UAV systems, and multi-threaded environments, emphasizing verifiable sustainability metrics and energy-efficient resource management. His publication trends reveal a consistent focus on sustainable computing evolution, with recent work advancing verifiable sustainability frameworks in data centers (2023-2024), energy accounting for multi-threaded applications (2020), and secure cache management techniques (2022). The research spans programming language theory, robotics safety, and hardware security, demonstrating interdisciplinary integration across computer science subfields. Scientific Awards: NSF CAREER Award Google Faculty Research Award Fulbright Scholarship Professor Liu has secured significant research funding through his NSF CAREER Award and Google Faculty Research Award, supporting innovations in sustainable computing infrastructure. His Fulbright Scholarship enabled international collaboration in Slovenia, advancing global research in energy-efficient software systems. He regularly teaches core courses including Programming Languages (CS471/571) and Sustainable Computing (CS680G), mentoring the next generation of computer scientists. While specific lab affiliations aren't detailed in the source text, his research on UAV software (Jcopter) and cache security (Composable cachelets) suggests active involvement in robotics and systems security research groups at Binghamton University.

Jan Milan DeriuView profile

Researcher

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +3 more

Jan Milan Deriu is affiliated with the ZHAW School of Engineering, where he is part of the Centre for Artificial Intelligence. He holds the role of Researcher and has been actively involved in multiple research projects, serving as Project Leader and Deputy Project Leader in areas such as dialogue systems evaluation, speech translation, and misinformation analysis. His work spans academic publications in top conferences and journals, focusing on AI-driven solutions in natural language processing and related fields. His research interests are centered around Natural Language Processing (NLP), including dialogue systems, text generation, and sentiment analysis; Artificial Intelligence evaluation methodologies; Speech technology, particularly dialect recognition and speech-to-text systems; Analysis of organized misinformation in social networks; Machine learning applications for data-centric AI development. Deriu has led or co-led several significant projects, including: Unified Model for Evaluation of Text Generation Systems (UniVal) – Deputy Project Leader (ongoing) Holistic Analysis of Organised Misinformation Activity in Social Networks – Project Leader (ongoing) End-to-End Low-Resource Speech Translation for Swiss German Dialects – Deputy Project Leader (completed) Pre-Study on Generation of Hockey News – Deputy Project Leader (completed) Call-E – Virtual Call Agent – Team Member (completed) DeepText: Intelligent Text Analysis with Deep Learning – Deputy Project Leader (completed) He collaborates extensively with international researchers and institutions, contributing to advancements in dialogue systems, speech technology, and AI evaluation frameworks. His publications emphasize practical applications, such as Swiss German dialect processing and misinformation detection in social media.

• Artificial Intelligence
• Bioinformatics
• Natural Language Processing
• +3 more

Dr. Ahmad Aghaebrahimian is a researcher at the ZHAW School of Life Sciences and Facility Management, affiliated with the Institute of Computational Life Sciences. He specializes in computational methods applied to healthcare, natural language processing (NLP), and bioinformatics. His work integrates deep learning, ontology-based systems, and signal processing to address challenges in healthcare informatics, biomedical research, and security systems. Research Projects: Project Leader: Advancing Information Accessibility in Hospitals (LLMs) Project Leader: Multi-document Patient Records Summarization Project Leader: Plant Cell Cultures with Deep Learning Deputy Leader: Automatic Supply Chain Monitoring Research Interests: His research focuses on AI-driven solutions for healthcare, including ontology-aware relation extraction, medical text mining, and robust signal processing systems. He also explores NLP applications in question answering, entity disambiguation, and parallel corpus creation. Recent work includes drone detection using CNNs in low SNR environments and computational methods for natural products discovery. Publications Trends: Over the past decade, his publications emphasize interdisciplinary approaches combining machine learning with bioinformatics and medical informatics. Key themes include deep learning model optimization, biomedical knowledge graph construction, and practical applications of NLP in healthcare systems. Grants & Collaboration: Leads research initiatives on AI in colorectal cancer classification and supply chain monitoring, demonstrating expertise in securing project leadership roles within academic-industry collaborations.

• Bioinformatics
• Computational Biology
• Genomics
• +4 more

Prof. Dr. Maria Anisimova is a Professor at the Institute of Computational Life Sciences within the ZHAW School of Life Sciences and Facility Management. Her research focuses on computational methods in evolutionary genomics, bioinformatics, and molecular evolution. Key areas include tandem repeat analysis, ancestral sequence reconstruction, and cancer genomics. She leads multiple projects on colorectal cancer mechanisms, computational drug discovery, and evolutionary biology. Her work integrates statistical models and algorithms to address challenges in genome analysis, including indel evolution, phylogenetics, and natural language-based database querying. Notable contributions include tools like ARPIP, ProPIP, and TRAL, advancing sequence alignment and tandem repeat detection. She also explores the role of protein intrinsic disorder and tandem repeats in cancer biology. Prof. Anisimova’s interdisciplinary approach spans bioinformatics, computational biology, and clinical applications, with publications in journals like *Nature*, *Genome Biology*, and *Molecular Biology and Evolution*. She has authored a textbook on evolutionary genomics and contributed to major conferences and workshops in the field.

Barbara PlankView profile

Visiting Professor

• Natural Language Processing
• Machine Learning
• Computational Linguistics
• +3 more

Barbara Plank is a Visiting Professor at the IT-University of Copenhagen, affiliated with the NLPnorth research group. She specializes in Natural Language Processing (NLP), focusing on multilingual language understanding, computational job market analysis, and annotation tools. Her work bridges machine learning techniques with practical applications in domains like skill extraction and cross-lingual systems. Affiliations: NLPnorth, IT University of Copenhagen Key Research Areas: Multitask learning, domain adaptation, entity linking Education: Not explicitly listed in text. Research Interests: Barbara’s research emphasizes advancing NLP through robust models for under-resourced languages and real-world applications. She explores techniques like nearest neighbor methods for occupational analysis, domain-aware relation classification, and easy-to-use annotation tools (e.g., EEVEE) to democratize NLP tasks. Her work often addresses challenges in multilingual systems and ethical AI deployment. Grants & Projects: MultiSkill : Multilingual information extraction for job market analysis (2020–2024) MultiVaLUe : Multilingual variety-aware language understanding (2020–2024) Pioneer Centre for Artificial Intelligence : Focus on pre-registered replication and ethical AI (2021–2034) Awards: Amazon Research Award (2019) Outstanding paper awards at EACL 2021 and ML Evaluation Standards Workshop 2022 Labs/Teams: Active in the NLPnorth group, collaborating on projects like the 18th Linguistic Annotation Workshop and SemEval tasks.

Sina ZarrießView profile

Professor

• Computational Linguistics
• Natural Language Processing
• Dialogue Systems
• +5 more

Sina Zarrieß is a Professor of Computational Linguistics at the University of Bielefeld, affiliated with the Faculty for Linguistics and Literature Studies. His research focuses on computational models of language use, with applications in natural language generation, dialogue systems, and language-vision integration. He leads the Computational Linguistics Bielefeld group and collaborates on interdisciplinary projects in ecology, hate speech analysis, and multimodal interaction. Research interests include language model architecture optimization, pragmatic reasoning in generation, and ethical NLP. He actively contributes to workshops such as ACL, EMNLP, and NLP4Ecology, publishing on topics like character-based LMs, gaze-driven hate speech detection, and visualization-oriented dialog systems. His work bridges theoretical linguistics with applied machine learning, emphasizing interpretability and real-world impact. Notable projects include developing BabyLM character-based models, studying gender-inclusive language benchmarks (SlayQA), and creating tools like VIST5 for adaptive visualization dialog. He explores how LMs encode linguistic principles like Maximize Presupposition! and investigates zero-shot learning for novel object categories. Current research trends show a focus on model efficiency (e.g., sentence selection for classification), multimodal grounding (e.g., scene context in visual tasks), and human-AI interaction dynamics (e.g., explanation effects on user perception). Despite prolific publishing, no specific scientific awards are mentioned in the provided materials. Advising and grants are not explicitly detailed, though his extensive co-authorship network indicates active mentoring. The Computational Linguistics Bielefeld group maintains open research directions in visual question answering, poetry generation diversity, and historical hate speech evolution studies.

Ernesto Jimenez-RuizView profile

Researcher

• Semantic Web Technologies
• Ontology Alignment
• Knowledge Graph Integration
• +2 more

Ernesto Jimenez-Ruiz is a Researcher at the University of Oslo affiliated with the Centre for Scalable Data Access (SIRIUS) and Logic and Intelligent Data group. He holds a PhD in Computer Science from University Jaume I of Castellon and specializes in semantic technologies and ontology engineering. His research spans bio-medical information processing, ontology reuse/alignment, and semantic web technologies for data analytics. Current projects include Artificial Intelligence for Data Analytics (AIDA) at The Alan Turing Institute, where he serves as Senior Research Associate. Recent publications (2024-2025) focus on neurosymbolic AI systems, knowledge graph construction from tabular data, and ontology alignment techniques. His work demonstrates strong emphasis on practical applications of semantic technologies. Dr. Jimenez-Ruiz has developed several tools including LogMap for ontology matching and BootOX for relational-to-ontology mapping. He teaches Semantic Technologies (INF3580/INF4580) and supervises PhD students in ecotoxicological effect prediction using knowledge graphs.

Bogdan VrusiasView profile

Visiting Professor

• Generative AI
• Large Language Models
• Foundation Models
• +6 more

Bogdan Vrusias is a Visiting Professor at the University of Surrey's School of Computer Science and Electronic Engineering (part-time). He concurrently serves as Global Head of AI and Data Engineering at The Economist. His academic journey began at Surrey as an undergraduate (BSc Computing and Information Technology, 1998), followed by a PhD in multi-modal information retrieval (2004) and an MBA (2010). He is a Fellow of the Higher Education Academy (FHEA). Education: PhD, University of Surrey (2004) MBA, University of Surrey (2010) BSc Computing and Information Technology, University of Surrey (1998) His research spans Generative AI, Large Language Models, Foundation Models, Machine Learning, Deep Learning, Cloud Computing, Natural Language Processing, and Computer Vision . His work focuses on developing scalable AI architectures and semantic technologies for real-world applications. Publications consistently explore semantic systems, neural networks, and multimodal information retrieval . Recent articles emphasize video annotation frameworks and P2P network architectures, while earlier work established foundations in self-organizing maps and feature selection for high-dimensional data. Awards: FHEA (Fellow of the Higher Education Academy) He previously directed UG/PG programs at Surrey and created pioneering courses like Web Hacking Countermeasures. His industry leadership includes founding tech startups and heading Amazon Web Services' AI/ML Specialist Solutions Architects team for EMEA. At The Economist, he drives AI and data transformation.

• Computational Linguistics
• Portuguese Corpus Studies
• Digital Humanities
• +3 more

Dr. Diana Santos is a Professor at the University of Oslo's Department of Literature, Area Studies and European Languages. She directs projects like Linguateca and Distant Reading for European Literary History , focusing on computational linguistics, Portuguese corpus analysis, and digital humanities. Her research spans machine translation, emotion annotation, literary text mining, and statistical methods for linguistic analysis. She teaches courses on Portuguese grammar, translation, and digital methodologies. She leads international collaborations and develops resources for Portuguese language processing. Her publications emphasize cross-linguistic studies and computational tools for literary and linguistic research.

Daniel JaquetView profile

Researcher

• Medieval History
• Military History
• Digital Humanities
• +3 more

Dr. Daniel Jaquet is an Associated Researcher in the Department of Medieval History at the University of Bern's Institute of History. His work focuses on martial culture, historical European martial arts, and digital humanities applications in cultural heritage preservation. He leads projects such as the digital reconstruction of the Murten Panorama and studies late medieval fight books. His research bridges textual analysis, material culture, and experimental archaeology, exploring topics like urban warfare traditions, gender roles in martial practices, and cross-cultural martial exchanges between Europe and Asia. Key research areas include: Analysis of medieval combat manuals (Fight Books) Historical martial practices in urban contexts Digitization of cultural heritage artifacts Material culture of weapons and armor His work frequently intersects with digital humanities, producing innovative visualizations and semantic annotation frameworks for historical artifacts. He collaborates internationally on projects combining academic research with experimental martial arts reconstruction. No formal awards are listed in the provided materials, though his contributions to digital heritage have likely impacted academic and museum practices. Current initiatives include the 'Martial Culture in Medieval Towns' research project (2018–2022) and ongoing studies on gender representation in fight books. He actively publishes in journals like Acta Periodica Duellatorum and contributes to museum exhibitions interpreting historical martial arts.