Find Academic Supervisors

• Linguistics
• Computational Linguistics
• Cognitive Science
• +7 more

Aniello De Santo is an Assistant Professor in the Department of Linguistics at the University of Utah, where he has been serving since July 2020. He earned his PhD in Linguistics from Stony Brook University in 2020 and is fluent in Italian, which informs his research on Italian syntax and processing. His research spans multiple disciplines with key interests in: Computational Linguistics and Syntax Cognitive Science and Theoretical Frameworks Artificial Intelligence and Machine Learning Applications Formal Language Theory and Complexity Psycholinguistic Processing Models De Santo's scholarly work demonstrates remarkable interdisciplinary integration, with publications in top journals across linguistics, cognitive science, and computer science. His recent work focuses on theoretical foundations in cognitive science (2024 publications on plausibility criteria and theoretical virtues), empirical investigations of Italian relative clause processing (2024), and innovative applications of machine learning techniques to linguistic problems. His research often bridges formal theoretical analysis with computational modeling and empirical validation. He has developed innovative educational approaches including an asynchronous general-education course "Language in the United States" (2023) and teaches a diverse range of courses in computational linguistics, syntax, and language studies. His extensive teaching portfolio includes Computers & Language, Introduction to Syntax, Computational Linguistics, and various research/thesis courses at both undergraduate and graduate levels. De Santo is actively engaged in community outreach as an organizer of the North American Computational Linguistics Open Competition (NACLO) for high school students, conducting practice sessions and hosting competition rounds since 2022. This work connects academic linguistics with pre-college education and demonstrates his commitment to promoting computational thinking in language studies.

Michael J. SchniedersView profile

Professor

• Biomolecular Simulation
• X-ray Crystallography
• Drug Design
• +5 more

Michael J. Schnieders is a Professor in the Roy J. Carver Department of Biomedical Engineering and the Department of Biochemistry at the University of Iowa. He directs the Computational Biomolecular Engineering Lab and holds research appointments at the Iowa Technology Institute, Center for Bioinformatics and Computational Biology, Institute for Vision Research, and Holden Comprehensive Cancer Center. He is also an affiliate of the University of Iowa Genetics Cluster Initiative and Iowa Informatics Initiative, with professional memberships in the Biophysical Society and American Chemical Society. His academic credentials include: PhD in Biomedical Engineering from Washington University, St. Louis BSE in Biomedical Engineering from the University of Iowa Dr. Schnieders' research program focuses on computational biomolecular engineering through four interconnected pillars: developing next-generation theory for biomolecular x-ray crystallography, predicting drug tablet structure/thermodynamics/solubility, advancing personalized medicine from genome sequencing to molecular phenotypes, and studying biomolecular electrostatics. His work integrates polarizable force fields (notably AMOEBA) and molecular dynamics to address challenges in drug design and genetic disorder mechanisms. Analysis of his 2022-2025 publications reveals dominant themes in computational structural biology applied to human disease. Approximately 40% of recent work targets genetic eye disorders (glaucoma, cataracts), using molecular modeling to interpret variants in genes like EFEMP1 and METTL23. Another 30% advances force field methodology (AMOEBA) and crystal structure prediction, while the remainder addresses hearing loss genetics and pharmaceutical crystal engineering through computational-experimental hybrid approaches. No specific scientific awards were documented in the source material. Information regarding graduate student advising and research grant funding was not provided in the available texts. He leads the Computational Biomolecular Engineering Lab, which develops the Force Field X software platform for biomolecular simulation. The lab maintains active collaborations with the Institute for Vision Research and Holden Comprehensive Cancer Center, focusing on structural impacts of disease-associated mutations. Current projects include developing predictive tools for pharmaceutical cocrystals, simulating genetic variants in ophthalmic disorders, and refining polarizable electrostatics models for biomolecular systems.

Jochen StaigerView profile

Professor

• Neuroanatomy
• Cortical Microcircuits
• Thalamo-Cortical Interactions
• +12 more

Jochen Staiger is a Full Professor and Director of the Department of Neuroanatomy at the University Medical Center Göttingen, University of Göttingen, where he leads research on cortical microcircuits and thalamo-cortical interactions. He is affiliated with multiple graduate programs under the Göttingen Graduate Center for Neurosciences (GGNB), including Neurosciences (IMPRS), Sensory and Motor Neuroscience, Cellular and Molecular Physiology of the Brain (CMPB), and Molecular Biology of Cells (GZMB). Dr. med., Justus Liebig University Giessen (1993), summa cum laude Habilitation in Anatomy, Heinrich Heine University Düsseldorf (2000) W3 Professor of Cell Biology, Albert-Ludwigs-University Freiburg (2006) His research focuses on the synaptic architecture of neocortical microcircuits, particularly in the barrel cortex, examining how thalamo-cortical inputs shape cortical processing, how inhibitory interneurons organize layer-specific circuits, and how sensory experience drives genomic and structural plasticity. He uses transgenic mouse models, including the reeler mutant, to study cortical function in both normally laminated and dysplastic cortices. The recent publications (2015–2020) reflect a strong focus on VIP and parvalbumin-expressing interneurons, neuromodulation, layer-specific connectivity, and functional organization of cortical columns. Key themes include synaptic targeting, burst-tonic transitions, brain-wide connectivity mapping, and compensation in malformed cortices. No scientific awards were mentioned in the provided text. Prof. Staiger leads an active research group with a focus on fundamental neuroscience questions. His lab investigates how cortical circuits develop, function, and adapt, with implications for understanding neurodevelopmental disorders. The team employs advanced neuroanatomical, genetic, and imaging techniques to dissect circuit motifs. While no formal students are listed, his collaborative publications suggest mentorship of junior researchers. His research group maintains a dedicated homepage: http://www.neuroanatomie.uni-goettingen.de/ and a specialized site on barrel cortex research: http://neuro.ukat.gwdg.de/barrels/ .

• Natural Language Processing
• Artificial Intelligence
• Data Science
• +3 more

Jorge Turmo Borras es profesor del Departament de Ciències de la Computació en la Universitat Politècnica de Catalunya. Forma part del Grup de Processament del Llenguatge Natural (GPLN) i del Centre de Tecnologies i Aplicacions del Llenguatge i la Parla (TALP). Su investigación se centra en procesamiento del lenguaje natural, inteligencia artificial y minería de datos clínicos. Investigación: NLP, Deep Learning, Salud Digital Colaboraciones: IDEAI-UPC, XarTEC Salut Sus intereses principales incluyen extracción de información de documentos médicos, resolución de anáforas mediante hipergrafos, y normalización léxica de microtextos. Ha publicado sobre modelado de temas para enlazado de entidades y detección de negaciones en textos clínicos. En los últimos 5 años ha trabajado en sistemas de asistencia para diagnóstico , procesamiento de tweets médicos , y redes neuronales para historiales de salud . Sus artículos destacan aplicaciones de Transformers, CRF y modelos híbridos. Patrocinadores: HORIZON 2020, Plan Estatal de Investigación 2021-2023, RIS3CAT. Colabora con investigadores como Alicia Ageno, Lluís Padró y Horacio Rodríguez-Hontoria.

• Actuarial mathematics
• Financial mathematics
• Bioinformatics
• +9 more

Jing Qin is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where she contributes to research and teaching in mathematical statistics and applied probability. She is also affiliated with the SDU Climate Cluster, reflecting her interdisciplinary engagement in climate and health modeling. Research Interests: Her work spans actuarial mathematics, financial mathematics, bioinformatics, and mathematical modeling. She specializes in extreme value theory, conditional risk measures, tail dependence, and statistical methods for RNA folding. Her research integrates rigorous theoretical development with practical applications in insurance, finance, and biomedical data analysis. The recent publications indicate a strong trend in developing robust, nonparametric estimators for conditional extremes, particularly in bivariate and covariate-adjusted settings. Her work often involves asymptotic analysis and simulation studies, with applications in reinsurance, epidemiology, and genomics. Collaborative research with Y. Goegebeur and A. Guillou is prominent. Scientific Awards: No specific awards listed in the provided text. Advising and Grants: Jing Qin supervises BA, MA, and PhD students in mathematical and statistical research. She is actively involved in externally funded projects, including as Principal Investigator (PI) on a research project analyzing the impact of extreme weather on emergency hospital demand. She has participated in projects funded by the Novo Nordisk Foundation, Carlsberg Foundation, and the Danish Research Council, covering areas from intellectual disability genetics to RNA bioinformatics. Labs and Teams: She is part of collaborative networks in statistical extremes and bioinformatics, and contributes to the SDU Climate Cluster, suggesting active participation in interdisciplinary research teams focused on climate, health, and data science.

• Neural Machine Translation
• Computational Linguistics
• Natural Language Processing
• +6 more

Antonio Toral is a leading researcher at the University of Groningen, focusing on Neural Machine Translation (NMT) , human evaluation , and parallel corpus curation . His work spans low-resource language modeling, lexical diversity enhancement, and multilingual figurative language detection. Affiliations: University of Groningen, MaCoCu Project, CREAMT Consortium Key projects: MaCoCu (Massive collection of under-resourced language data) CREAMT (Creativity in literary translation) Research interests include: Improving NMT naturalness and lexical richness Document-level evaluation of machine translations Character-level modeling and downsampling techniques Reproducibility challenges in human NLP evaluation Cross-lingual formality transfer without parallel data His recent articles (2021–2025) demonstrate expertise in: Reinforcement learning for naturalness preservation Statistical analysis of translationese effects Dependency-based reordering models Pivot translation for Catalan→Chinese Domain-specific corpus creation for EU Digital Service Infrastructures

• Classical Philology
• Greek Language and Linguistics
• Greek Metrics
• +7 more

Ruggiero LIONETTI is a Contract Lecturer in the Department of Asian and North African Studies at Ca' Foscari University of Venice and concurrently serves as a Research Fellow and Contract Professor of Greek Language at the University of Urbino Carlo Bo. His academic work bridges classical philology, Greek linguistics, and the reception of antiquity in Byzantium. Research Interests: His primary research areas include Classical Philology, Greek Language and Linguistics, Greek Metrics, and Attic Tragedy—especially the works of Aeschylus and Euripides. He also investigates the role of the Ancient Chorus and the reception of classical poetry in Byzantine literature. The recent publications reflect a consistent focus on textual criticism, choral dynamics in tragedy, and Byzantine interpretations of ancient texts. His work spans journals like Classical Philology , Medioevo Greco , and Rheinisches Museum , demonstrating expertise in both philological analysis and historical context. Academic Background: Ph.D. in Ancient History (with honors), Scuola Normale Superiore, Pisa (2021) Master’s in Philology and History of Antiquity, University of Pisa (2015, cum laude) Bachelor’s in Literature, University of Bari Aldo Moro (2011, cum laude) Visiting Researcher, University of California, Berkeley (2016–2017) Teaching Experience: Greek Language courses at University of Urbino (2022–2025) Workshops on Ancient Greek for high school teachers Supplementary teachings on Greek prose and Hellenistic texts Language Skills: Native Italian, fluent English, advanced reading in German and French.

Gerard KeubeungView profile

Assistant Professor

• Francophone Studies
• Postcolonial Theory
• African Literature
• +9 more

Gerard Keubeung is an Assistant Professor in the Department of World Languages, Literatures, & Cultures at McDaniel College, where he teaches French language and courses on Francophone cultures, African diaspora, and postcolonial literature. His academic background includes a Ph.D. from the University of Tennessee-Knoxville and an M.A. from the University of Oregon, with prior teaching experience in Cameroon and at Bowdoin College. Ph.D., University of Tennessee-Knoxville (2018) M.A. in Francophone Studies, University of Oregon (2013) Maitrise (M.A), University of Yaoundé I (2008) Licence (B.A.), University of Yaoundé I (2005) DIPES (High School Teacher Diploma), Ecole Normale Supérieure du Cameroun (2004) His research focuses on postcolonial African literature, the construction of African identity in the French imaginary, colonial education, and representations of alterity in Francophone novels. He explores themes such as immigration, gender, diaspora, and Francophone cinema from West Africa, Central Africa, and the Caribbean. His teaching reflects his interdisciplinary and culturally empathetic approach. The recent publications of Gerard Keubeung reveal a consistent intellectual trajectory centered on the postcolonial condition of African subjects. His works analyze literary representations of alienation, exile, urban marginality, and national identity, primarily through Francophone African novels. These articles span disciplines including literary theory, postcolonial studies, migration, and education, with a strong emphasis on socio-political critique and identity formation in the wake of colonialism. Gerard Keubeung has not been publicly recognized with any scientific awards based on the available information. He is actively engaged in mentoring students through language and cultural instruction, though no specific advisees are listed. His scholarly work is supported by a deep engagement with postcolonial theory and Francophone literary analysis, though no grants are mentioned. His academic mission emphasizes cultural empathy, critical thinking, and the transformative power of language education. There is no mention of specific research labs or collaborative teams in the provided text, but his work aligns with interdisciplinary groups focused on postcolonial studies, Francophone literatures, and diaspora research.

• Computer Vision
• Computer Graphics
• Artificial Intelligence
• +4 more

Alexei Efros is a Professor in the Electrical Engineering and Computer Sciences Department at UC Berkeley's College of Engineering, where he holds the Howard Friesen Professorship. He is a leading researcher in computer vision and computer graphics, with a focus on data-driven techniques and self-supervised learning. His work bridges the intersection of vision and graphics, leveraging large quantities of unlabeled visual data to tackle complex problems. Dr. Efros received his PhD from UC Berkeley in 2003 and joined the Berkeley faculty in 2013 after spending a decade at Carnegie Mellon University. He has also held affiliations with École Normale Supérieure/INRIA and the University of Oxford. His research group is part of the Berkeley Artificial Intelligence Research Lab (BAIR). His research interests span computer vision, computer graphics, artificial intelligence, and machine learning, with particular emphasis on data-driven approaches, self-supervised learning, computational photography, and visual data mining. Efros has pioneered numerous techniques in image synthesis, scene understanding, and visual representation learning that have shaped modern computer vision research. An analysis of his recent publications reveals a strong focus on generative models, particularly diffusion models and their applications; interpretability of vision-language models like CLIP; 3D scene understanding and reconstruction; and the application of self-supervised techniques to video and spatial reasoning problems. His work continues to push boundaries in how machines understand and generate visual content. Among his numerous accolades are the ACM Prize in Computing (2016), multiple Helmholtz Test-of-Time Prizes, the SIGGRAPH Significant New Researcher Award, Sloan and Guggenheim Fellowships, and teaching awards including the Jim and Donna Gray Award for Excellence in Undergraduate Teaching (2023). Professor Efros has mentored an impressive cohort of students who have gone on to prominent positions in academia and industry, including faculty positions at CMU, TTIC, Stanford, and research scientist roles at OpenAI, Google DeepMind, and Anthropic. His teaching includes core computer vision courses at both undergraduate and graduate levels.

• Solid State Chemistry
• Nanomaterials Synthesis
• Nanostructured Thin Films
• +7 more

Delacroix Simon is an Assistant Professor in the Chemistry Department at Ecole Polytechnique and IP Paris, affiliated with the Laboratoire de Physique de la Matière Condensée (PMC). He has been serving in this role since December 2023, focusing on innovative materials synthesis and nanomaterial discovery. His educational background includes a Master of Science from both Ecole Normale Supérieure de Cachan and Sorbonne University (2016), and he is a laureate of the chemistry agrégation (2015). He completed his PhD in 2019 under the supervision of Clément Sanchez, David Porthault, and Yann Le Godec, working on the synthesis of boron-rich nanoparticles at high temperature and pressure. Subsequently, he conducted postdoctoral research at the Max Planck Institute of Colloids and Interfaces in Potsdam under Markus Antonietti, where he developed ultrafast laser carbonization techniques for sensor applications. Ecole Normale Supérieure de Cachan – MSc Sorbonne University – MSc Chemistry Agrégation – 2015 PhD – 2019, Collège de France / Sorbonne University / IMPMC Simon Delacroix's research is centered on the synthesis of nanostructured thin films using methods such as molten salts and laser irradiation. He is pioneering a high-throughput laser synthesis approach integrated with machine learning to accelerate the discovery of novel nanomaterials. His work spans functional nano-objects, photoactive materials, and advanced characterization techniques. His research group, part of the Solid State Chemistry team at PMC, contributes to interdisciplinary efforts in materials science and condensed matter physics. Although no publications are listed in the scraped text, his research trajectory indicates a strong focus on experimental physical chemistry, materials innovation, and the development of smart synthesis platforms combining laser processing and data-driven discovery. He has received research support through the Saint-Gobain chair on innovative materials (2022), which enabled his transition to an independent research position. While no formal advisees are listed, he is embedded in a vibrant research environment with doctoral and postdoctoral researchers in the Solid State Chemistry group. Delacroix is based at the PMC laboratory, located at Ecole Polytechnique in Palaiseau, France, with office 05-3067A in aisle 5, 2nd floor. His work contributes to the broader mission of Ecole Polytechnique and IP Paris in advancing cutting-edge materials science through interdisciplinary collaboration and technological innovation.

• Queueing Theory
• Deadlock
• Discrete Event Simulation
• +5 more

Geraint Palmer is a Welsh Medium Lecturer at Cardiff University's School of Mathematics, where he teaches mathematics courses primarily in Welsh. His academic journey includes a BSc in Mathematics from Aberystwyth University (2013), followed by an MSc in Operational Research and Applied Statistics (2014) and a PhD in Applied Stochastic Modelling (2018), both from Cardiff University. His educational background includes: BSc in Mathematics, Aberystwyth University (2013) MSc in Operational Research and Applied Statistics, Cardiff University (2014) PhD in Applied Stochastic Modelling, Cardiff University (2018) Dr. Palmer's research spans several interconnected areas within operational research and applied mathematics. His primary focus is on queueing theory and stochastic modeling , with applications in healthcare systems and emergency services. He has made significant contributions to discrete event simulation , notably through the development of the open-source Ciw library. Additionally, his work extends to Welsh language processing, where he has contributed to computational linguistics projects including Welsh word embeddings and stemmers. His interdisciplinary approach combines theoretical mathematical modeling with practical software implementation, often using Python and R. His recent publications demonstrate a strong trend toward applying operational research methods to healthcare challenges, particularly emergency services optimization. His work on ambulance fleet allocation, emergency care transformation, and orthopaedic care systems shows a consistent focus on improving healthcare delivery through mathematical modeling. Simultaneously, his research in Welsh language processing represents a unique interdisciplinary contribution at the intersection of mathematics, computer science, and linguistics. His publication record also highlights his commitment to open-source software development, with contributions to libraries like Ciw (for discrete event simulation) and GCol (for graph coloring). His scientific contributions include: Development of Ciw, an open-source discrete event simulation library Development of GCol, a high-performance Python library for graph coloring Contributions to Welsh language processing tools and resources Co-authorship of "Applied Mathematics with Open-Source Software: Operational Research Problems with Python and R" (2022) Dr. Palmer is actively involved in teaching mathematics at Cardiff University, delivering modules including Preliminary Mathematics II, Problem Solving, and Computational Methods. His bilingual capabilities enable him to provide Welsh-medium instruction, supporting linguistic diversity in higher education. His research projects often involve collaboration with healthcare professionals, operational research specialists, and language technologists, reflecting the interdisciplinary nature of his work. Notably, he has contributed to standardized Welsh language assessment tools, demonstrating his commitment to both academic research and practical community applications.

• Computer Vision
• Image Processing
• Biometrics
• +12 more

Pankaj Kumar Sa is an active academic researcher in computer science, specializing in computer vision, biometrics, and artificial intelligence. He has published extensively from 2006 to 2025 in top-tier journals and conferences, with a strong focus on person re-identification, deep learning, image processing, and low-resource language technologies. His collaborative work with researchers like Sambit Bakshi and Banshidhar Majhi highlights his role in a vibrant research community, likely within an Indian academic institution. His research interests span a wide range of topics, including: Computer Vision and Image Processing Biometrics (Iris, Ear, Periocular) Person Re-identification and Surveillance Deep Learning and Neural Networks Natural Language Processing for Indian Languages (e.g., Odia) UAV and Satellite-based Aerial Imaging Video Anomaly Detection His recent publications from 2023 to 2025 showcase a trend toward practical and socially relevant applications, such as emergency crowd monitoring, agricultural prediction, and low-resource language support. These works leverage advanced deep learning models and contribute valuable datasets like RGBT-1K and NITRDrone. The primary themes include multimodal sensing, robustness under real-world conditions, and efficient model design. Pankaj Kumar Sa has mentored and collaborated with several researchers, including Nayan Kumar Subhashis Behera, Tanmay Kumar Behera, and Tusarkanta Dalai, indicating an advisory or supervisory role. His work often addresses challenges in smart cities, security, and healthcare, demonstrating a commitment to impactful research.

• Computer Vision
• Biometrics
• Deep Learning
• +12 more

Sambit Bakshi is an active academic researcher in the field of computer science, affiliated with the Department of Computer Science and Engineering at the National Institute of Technology Rourkela, India. His research spans computer vision, biometrics, deep learning, and intelligent systems, with a strong emphasis on real-world applications in surveillance, healthcare, agriculture, and IoT. His primary research interests include biometrics (especially ear and periocular recognition), person re-identification , UAV-based image analysis , multimedia forensics , and fog/edge computing . He has contributed significantly to the development of deep learning models for object segmentation, anomaly detection, and secure biometric systems. The recent publications demonstrate a consistent trend in applying deep neural networks , attention mechanisms , and lightweight architectures to solve complex problems in visual recognition and data analytics. His work often appears in high-impact IEEE and ACM journals, reflecting strong technical rigor and relevance. Scientific Contributions: Co-edited special issues in IEEE Access and Image and Vision Computing Contributed to benchmark challenges such as the Unconstrained Ear Recognition Challenge 2019 Developed novel methods in ear biometrics, periocular recognition, and UAV-based segmentation Active in editorial roles and collaborative research across international teams Advising and Collaborative Research: Frequent collaborator with researchers from NIT Rourkela, University of Beira Interior (Portugal), and other international institutions Co-authored over 120 publications, indicating active supervision and mentoring of students Involved in interdisciplinary projects spanning AI, security, and healthcare Labs and Research Groups: Though not explicitly stated, his work suggests involvement in a computer vision and biometrics lab at NIT Rourkela, focusing on AI-driven solutions for societal and industrial applications.

Cindy BrantmeierView profile

Professor

• Second Language Acquisition
• Health Literacy
• Linguistic Diversity
• +5 more

Cindy Brantmeier is Professor of Applied Linguistics with a primary appointment in Global Studies at Washington University in St. Louis. She serves as Director of Applied Linguistics, overseeing the interdisciplinary PhD program and undergraduate minor. Her academic affiliations include courtesy appointments in the Department of Romance Languages and Literatures and the Department of Psychological and Brain Sciences. As Faculty Scholar at the Institute for Public Health and Faculty Fellow for International Research with Human Subjects in the Office of the Vice Chancellor for Research, she bridges academic research with practical healthcare applications. Dr. Brantmeier's research spans interdisciplinary domains connecting applied linguistics, social psychology, and public health. Her work focuses on language acquisition, second language reading across cultures, health literacy, and linguistic diversity in healthcare settings. She has conducted extensive research on self-assessment methodologies, reading strategies, and individual learner differences. Her laboratory research connects to practical applications with refugee and immigrant communities in St. Louis, particularly examining communication challenges in healthcare contexts for linguistically diverse populations. Her publications reveal a strong emphasis on cross-cultural language research, with significant focus on Chinese EFL learners and Spanish language acquisition. The research demonstrates consistent exploration of how working memory, self-assessment, and individual differences impact second language reading comprehension. Recent work increasingly addresses healthcare communication challenges during the pandemic, showing evolution from theoretical language acquisition research toward practical public health applications. Washington University's 2012 Emerson Excellence in Teaching Award Five-time winner of outstanding graduate student mentoring award 2019 Merle E Simmons Distinguished Alumna (Indiana University) Distinguished Visiting Professor at Northeast Normal University, China (2016-2021) Keynote speaker at UNESCO International Conference on Literacy Professor Brantmeier has secured research funding from diverse sources including the US State Department, National Strategic Language Initiative, Africa Initiative Pilot Grant Program, Educational Testing Service, and American Council on the Teaching of Foreign Languages. She has mentored numerous graduate students, with recent PhD graduates securing tenure-track positions at prestigious institutions including the United States Air Force Academy and the Defense Language Institute. As Director of the Language Research Laboratory, she leads interdisciplinary research teams examining language use in healthcare settings and second language acquisition processes. Her international engagement includes delivering plenary addresses across five continents and serving as Co-Editor of Reading in a Foreign Language journal. Current initiatives focus on patient-provider communication in obstetrics and gynecology, funded by the Maimonides Research and Development Foundation, demonstrating continued relevance of her work to critical healthcare communication challenges.

Mark HeppleView profile

Associate Professor

• Natural Language Processing
• Computational Linguistics
• Formal Grammar and Parsing
• +5 more

Dr. Mark Hepple is a Reader (Associate Professor) at the University of Sheffield's School of Computer Science, affiliated with the Natural Language Processing (NLP) research group. With a BSc in Psychology from Sheffield (1986) and MSc/PhD in Cognitive Science from the University of Edinburgh (1987, 1990), he joined Sheffield in 1993 following research positions at Cambridge and the University of Pennsylvania. His research spans: Core NLP : Formal grammar, parsing algorithms, and efficient linguistic data storage Applied NLP : Clinical text mining, temporal information extraction, and dialogue systems Low-resource languages : Igbo language tooling (POS taggers, diacritic restoration) Social media analysis : Comment clustering, sub-story detection, and summarization Recent publication trends (2016-2020) show concentrated work on: Igbo NLP resources (tagging, diacritics, embeddings) Social media comment analysis using clustering and summarization Event detection via temporal word co-occurrence models He has led significant grants including: SENSEI (EU FP7, £459K): Human conversation analysis uComp (EPSRC, £375K): Human computation for knowledge extraction CLEF (MRC, £401K): Clinical text mining frameworks