جستجوی استاد راهنمای دانشگاهی

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.

• Queueing Theory
• Deadlock
• Discrete Event Simulation
• +۵ مورد دیگر

Alex Pillen is an Associate Professor in Anthropology at University College London (UCL), specializing in the anthropology of language. With a PhD from UCL (2000), she has been with the Department of Anthropology since 2004, first as a tenured Lecturer until 2018, and then as an Associate Professor from 2018 to present. She also held a mid-career Fellowship at the British Academy from 2016-2017. Her research focuses on the visual and spatial dimensions of linguistic practice, particularly examining how language functions under conditions of trauma, war, and cultural oppression. Dr. Pillen's educational background includes: Doctor of Philosophy from University College London (2000) Her research interests center on the anthropology of language, with particular focus on linguistic creativity, spatial conceptualization of language, and the translation of trauma in non-Western contexts. She has coined the term "antipodal words" for words that encapsulate their opposite, or carry out a U-turn in meaning, particularly in contexts of war, brutality, and trauma. Her work on Northern Kurdish (Kurmanji) examines visual tropes such as opaqueness and transparency, as well as "arcs of reflection" built into the language through quotation and reflexive pronouns. Pillen has also pioneered innovative approaches to language visualization, collaborating with architect and composer Emma-Kate Matthews to create 3D conceptualizations of natural language using software developed for video animation and gaming. Dr. Pillen has received recognition as a UKCGE Recognised Research Supervisor by the UK Council for Graduate Education (2023-present), acknowledging her excellence in doctoral supervision. Her work has been cited across multiple disciplines and has gained attention from news outlets and academic platforms. She is particularly known for her interdisciplinary approach, combining anthropology with digital humanities, architecture, and artistic practice to explore the complex shapes embedded in language's grammar. As an advisor and researcher, Pillen has contributed significantly to understanding linguistic diversity and the preservation of endangered languages. Her forthcoming monograph "Endurance: Speaking Kurdish in a Warped World" (Brill, 2024) represents a major contribution to Kurdish studies and linguistic anthropology. She is also active in professional associations including the Royal Anthropological Institute (Anthropology and Language Committee), Society for Linguistic Anthropology, The Association of Social Anthropologists of the UK, and The European Association of Social Anthropologists. Dr. Pillen is multilingual, with proficiency in Dutch, French, Spanish, English, and Sinhala, and the ability to understand Kurdish, Arabic, and Italian. Her work aligns with Sustainable Development Goals related to Gender Equality, Climate Action, and Reduced Inequalities.

• Linguistic Anthropology
• Anthropology of Language
• Middle Eastern Languages
• +۳ مورد دیگر

Ovidiu Șerban is a Research Fellow at the Data Science Institute, Imperial College London, leading the Data Observatory group. His work focuses on real-time Natural Language Processing, Data Curation, and Large Scale Visualization Systems. PhD in Computer Science (2013) - Joint from INSA de Rouen Normandy and Babeș-Bolyai University MSc in Artificial Intelligence (2009) - Babeș-Bolyai University BSc in Computer Science (2008) - Babeș-Bolyai University Research interests span Artifical Intelligence, Natural Language Processing, Interactive Systems, Affective Computing, and Deep Learning. Recent publications emphasize knowledge graph completion, temporal graph analysis, and multimodal data processing frameworks. Contributed to development of OVE (Open Visualization Environment) for scalable data rendering Created TKGQA dataset for temporal knowledge graph validation Advanced conflict-aware multilingual knowledge graph techniques Projects include SENTINEL for real-time event detection, Watchme for workplace analytics, Intuitel for e-learning enhancement, and Agentslang for distributed interactive systems. Affiliations include Imperial College London, University of Cambridge, and University of Reading.

• Artificial Intelligence
• Natural Language Processing
• Interactive Systems
• +۶ مورد دیگر

Dr. Md Shadab Mashuk is a Lecturer in the School of Science, Engineering & Environment at the University of Salford. He brings several years of industry experience as a Data Scientist and Research Software Engineer to his academic role, which enriches his teaching and fosters industry collaboration and interdisciplinary research. His academic credentials include: Currently pursuing Postgraduate Certificate in Academic Practice (PGCAP) at University of Salford (2023-present) PhD in Computer Science from University of Nottingham (2014-2019) MSc in Advanced Computing Science from University of Nottingham (2013-2014) BSc in Computer Science and Engineering from NSU, Bangladesh (2006-2010) Dr. Mashuk's research spans multiple interdisciplinary domains with a strong focus on practical AI applications. His work bridges Machine Learning, Deep Learning, Natural Language Processing, and Agent-Based Modeling with real-world challenges in healthcare, building science, and user-centered systems. Recent projects demonstrate particular emphasis on health AI applications for Functional Neurological Disorder analysis and agent-based modeling for building occupancy and energy prediction. His publication trend shows consistent output across different domains, with a notable concentration in 2024 on computer vision for building inspection, NLP for healthcare communication analysis, and agent-based modeling for energy systems. This indicates an active research trajectory with increasing focus on applying AI techniques to solve domain-specific problems. Dr. Mashuk's research contributions span several key areas: Computer vision applications for building inspection and mold detection NLP techniques for analyzing clinical communications and terminology extraction Agent-based modeling for building occupancy patterns and energy consumption prediction Indoor positioning systems for occupancy monitoring Medical training technologies using augmented/virtual reality Character recognition systems for multilingual contexts As an educator, Dr. Mashuk teaches core computing courses including Programming, Data Structures & Algorithm Analysis, and Web Development. He supervises undergraduate final year projects and is open to PhD supervision for students whose research aligns with his expertise. His industry background provides valuable practical insights that enhance both his teaching effectiveness and student supervision approach.

• Machine Learning
• Deep Learning
• Artificial Intelligence
• +۶ مورد دیگر