جست‌وجوی استاد و پژوهشگر

Jim Whiteheadمشاهده پروفایل

استاد

• Artificial Intelligence
• Software Engineering
• Computer Games
• +۶ مورد دیگر

Jim Whitehead is a Professor of Computational Media in the Baskin School of Engineering at the University of California, Santa Cruz. His research bridges artificial intelligence, software engineering, and computer games, with notable contributions to procedural content generation, software bug prediction, and serious games. He serves as Associate Dean for Undergraduate Affairs, focusing on student success initiatives including equity gap reduction, retention strategies, and experiential learning programs like first-year engineering design and senior capstone sequences. Academic Leadership: Former Chair of Computer Science (2000-2014) and Computational Media (2017-2019) Community Building: Founder of Society for the Advancement of Science of Digital Games (SASDG), procedural content generation communities, and games/software engineering collaborations Research interests span AI for games , software evolution , and human-AI collaboration in creative domains. Articles highlight trends in procedural generation (2020), music sentiment modeling (2019), and code change analysis (2008-2015). Administrative expertise includes UC faculty search committees, personnel case management, and curriculum development. He pioneered UCSC's computer games major (ranked top in the US) and masters program in games/playable media. GitHub activity shows active involvement in open-source projects like smt_dungeon (SMT solver-based dungeon generator) and MovementLab (interactive media tools). His website template is based on the al-folio Jekyll theme.

Rahul Mouryaمشاهده پروفایل

مدرس

• Machine Learning
• Computer Vision
• Inverse Problems
• +۶ مورد دیگر

Rahul Mourya is a Lecturer in Computer Science at the Faculty of Science and Engineering , University of Wolverhampton, UK. He joined in October 2023 and is affiliated with the Digital Innovations and Solution Centre (DISC) , which focuses on fundamental and applied research with societal and economic impact. PhD & MSc in Computer Science (Signal/Image/Vision) from Université Jean Monnet Saint-Etienne, France BEng in Electronics & Telecommunications from University of Pune, India His research develops foundational tools for machine learning, computer vision, inverse problems , and signal/image processing , with applications in autonomous systems, robotics, and sensor networks . Teaching includes computational mathematics, robotics engineering, and deep learning modules. Collaborations span institutions like Heriot-Watt University, Telecom ParisTech, and interdisciplinary projects in underwater acoustics and astronomical imaging. Current research explores measurement-consistent neural networks and optimization algorithms for inverse problems.

• Artificial Intelligence
• Machine Learning
• Biomedical Engineering
• +۱ مورد دیگر

Dr. Sahil Sharma is a Research Fellow at the School of Computing, Engineering and Intelligent Systems, Ulster University, Derry~Londonderry campus. His interdisciplinary research bridges artificial intelligence, biomedical engineering, and agricultural science, with significant contributions to medical diagnostics and sustainable agricultural practices through advanced computational techniques. Sharma's primary research domains include artificial intelligence (particularly deep learning and large language models), biomedical engineering (focusing on cardiac biomarker detection and medical data analysis), and agricultural science (specializing in plant biostimulants and sustainable farming). His work demonstrates consistent innovation in applying machine learning to solve real-world problems across healthcare and agriculture, with recent emphasis on explainable AI for medical visualization and anime recommendation systems. Analysis of Sharma's 15 most recent publications (2023-2025) reveals a dominant trend toward AI-driven healthcare solutions, including cardiac troponin I detection assays, XAI-based medical data visualization, and synthetic data generation for diagnostics. Parallel work explores agricultural applications through deep learning-based crop monitoring systems. His research outputs show strong translational impact, with significant citations (h-index 86) and practical implementations referenced in patents, particularly in the biomedical domain where his 2012 agricultural paper accumulated 85 Scopus citations.

• Disability Sport
• Sport Management
• Gambling Marketing
• +۴ مورد دیگر

Paul Kitchin is a Senior Lecturer in the School of Sport at Ulster University, affiliated with the Faculty of Life & Health Sciences. His research focuses on disability sport, gambling marketing, youth development, and organizational change in sport. He holds a PhD from Loughborough University on disability cricket's organizational dynamics. His work emphasizes health and social outcomes through sport, with notable contributions to disability inclusion, gambling's societal impacts, and sport management practices. Education: PhD (Loughborough University, 2014), specializing in disability cricket’s organizational change. Research interests span disability sport policy, gambling’s influence on youth, media marketing in sport, and equity in sports venues. Recent studies include a landmark report on gambling exposure among Irish youth (CODE RED, 2024) and analyses of disabled fans’ inclusion in English football (2025). Articles collectively highlight trends in accessibility challenges, gambling’s societal role, and disability advocacy in sport governance. Key themes include institutional barriers to inclusion, marketing ethics, and participatory equity. Awards: Sustained Educational Excellence Award (2021), Outstanding Paper Award (2021), Inter-Disciplinary PhD Competition Winner (2018). Advising and grants include supervising over 10 PhD students and securing grants like the North-South Research Programme (€199,962, 2022). He has led the Ulster University Research Seed Funding (2025) and ESRC initiatives on gambling-related harms. He leads the School of Sport’s research on sport management and disability inclusion, contributing to the Centre for Sport in Society. His work bridges academia and practice through external examiner roles at multiple institutions and editorial positions in journals like Managing Sport & Leisure .

Nicolas Louvetonمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Cognitive Ergonomics
• Virtual Reality
• +۴ مورد دیگر

Nicolas Louveton is an Associate Professor at the University of Poitiers, affiliated with the Center for Research on Cognition and Learning (CeRCA) within the School of Humanities and Social Sciences. His work bridges cognitive science and practical interface design across automotive, cybersecurity, and industrial contexts. His research focuses on Human-Computer Interaction , Cognitive Ergonomics , and Virtual Reality , with specific expertise in visual attention, multitasking performance, and driver behavior. Current projects include the RESISTECC initiative for cyber crisis management training, industrial VR maintenance scenarios (INTEROPS project), and autonomous vehicle trust studies (CMI project). Louveton's recent publications reveal a strong trend toward applied VR solutions for high-stakes environments, particularly in cybersecurity training effectiveness and driver-AI interaction. His work consistently applies cognitive ergonomics principles to measure mental workload, situational awareness, and usability in complex systems. As an educator, he leads the UX/UI Ergonomics Master's program and teaches courses on interface usability, visual perception, and UX research methodology. He also serves as Carnot Cognition correspondent for CeRCA laboratory. Supervises PhD candidates Marine Desvergnes and Deslande Liboutchi Pepe Formerly co-supervised Clarisse Lawson-Guidigbe (now Head of Web Editorial) Member of CNU 16 (Psychology and Ergonomics) 2019-2023 Co-head of Digital Interactive Games and Media Master's program 2018-2022

• Geomechanics
• Granular Materials
• Foundation Engineering
• +۶ مورد دیگر

Prof. Wu, Wei is a Professor and Director at Institute of Geotechnical Engineering , Department of Structural Engineering and Natural Hazards, BOKU University, Vienna, Austria. With over two decades of academic and industry experience, his work bridges geotechnical research and engineering practice. Education: Dr.-Ing. in Geotechnical Engineering (Karlsruhe University, Germany, 1986–1993), MSc in Geotechnical Engineering (Xian University of Technology, China, 1982–1985), Bachelor in Civil Engineering (Wuhan University, China, 1978–1982). Research Interests span geomechanics, granular materials, and computational geotechnical engineering. His expertise includes: Constitutive modeling of soils and granular media Numerical simulation of landslides and debris flows Soil bioengineering and root reinforcement Geo-energy systems and energy storage Advanced computational methods (SPH, DEM, FE) Selected Google Scholar Articles (2025–2024) highlight innovations in hypoplastic models for climate-affected soils, machine learning applications for slope stability, and multiscale simulations of geohazards. His work emphasizes both theoretical advancements (e.g., phase-field fracture models) and practical solutions (e.g., centrifuge testing for tunnel design). Scientific Awards include: Advanced Grant, European Research Council (2024) Gold Medal, Technical University of Brno (2024) Teaching & Supervision covers soil mechanics, tunneling, and advanced geotechnical courses. He has supervised over 30 PhD and 100 MSc theses, mentoring future engineers in numerical methods and geohazard mitigation. Leadership Roles : Editor-in-Chief of Acta Geotechnica , founder of Springer Series in Geomechanics, and Chairman of the Otto Pregl Foundation (€3M endowment). He organized key conferences like the China-Europe Conference on Geotechnical Engineering (2018) and International Symposium on Particle-Based Continuum Methods (2019).

Derek Lomasمشاهده پروفایل

پژوهشگر

• Human-Centered Design
• Artificial Intelligence
• Health Technology
• +۳ مورد دیگر

Derek Lomas is a researcher at Delft University of Technology’s Faculty of Industrial Design Engineering, specializing in Human-Centered Design and Human Technology Relations. He holds a PhD in Human-Computer Interaction from Carnegie Mellon University, an MFA in Social Design from UC San Diego, and a BA in Cognitive Science from Yale University. His research focuses on AI-driven wellbeing solutions, neurodesign, and educational technology. He leads projects like NeuroUX (mobile cognitive assessment software) and Zensus (patient wellness tracking), and has developed over 40 learning/assessment games. Key areas include music perception via EEG, AI alignment with human emotions, and design methodologies for positive AI. Education: B.A. Cognitive Science, Yale University, 2003 MFA Social Design, UC San Diego, 2009 PhD Human-Computer Interaction, Carnegie Mellon University, 2014 Research Interests: AI for wellbeing and mental health Neuroscience-driven design (EEG, brain-computer interfaces) AI ethics and human-AI interaction Game-based learning and assessment Key Projects: NeuroUX : Cognitive assessment software used in psychiatric research Zensus : AI-driven patient wellness monitoring system FactFlow : AI math fluency tool for children Vibe Research Labs : Exploring AI and positive human experiences Awards: Social Innovation Fellowship (PopTech) MacArthur Foundation Digital Media Learning Grant White House National STEM Game Competition McGinnis Business Plan Competition Winner Grants & Collaborations: Consultancy: Playpower Labs (UX, data science, software) Partnerships with UC San Diego, Brown University, and UT Austin

Sheree Bekkerمشاهده پروفایل

مدرس ارشد

• Injury Prevention
• Sport Medicine
• Gender in Sports
• +۳ مورد دیگر

Sheree Bekker is a Senior Lecturer at the University of Bath's Department for Health. Her research focuses on injury prevention, gender equity in sports, and qualitative methodologies. She holds a PhD in Sport Medicine from Federation University (2018). She contributes to UN Sustainable Development Goals related to education and health equity. Research Interests: Injury prevention strategies, gender inclusion in sports, policy analysis, and qualitative research methods. Affiliations: Centre for Qualitative Research, Centre for Health and Injury Prevention in Sport, and SPHERE (Sport, Physical Activity, and Health Equality). Her work emphasizes bridging research and practice, particularly in translating injury prevention knowledge and advocating for gender-expansive policies. Notable projects include the Qualitative Research Seminar Series (2021-2022), fostering interdisciplinary collaboration. Publications highlight themes like sport safety resource analysis, athlete rights, and systemic barriers in sport governance. She has collaborated internationally on topics ranging from rugby injury prevention to trans-inclusive policies. Grants/Projects: Funded initiatives focused on qualitative research capacity-building and sport safety policy development. Labs/Teams: Active in multi-disciplinary teams addressing sport health equity and emergency preparedness in community settings.

Chuncheng Liuمشاهده پروفایل

استادیار

• Science and Technology Studies
• Political Sociology
• Economic Sociology
• +۱۰ مورد دیگر

Chuncheng Liu is an Assistant Professor of Communication and Sociology at Northeastern University, with a PhD in Sociology and Science Studies from UC San Diego and postdoctoral research at Microsoft Research New England. His work bridges science and technology studies, political sociology, and global health, focusing on the politics of algorithms, surveillance systems, and public health classification practices. Education: MA (2019) and BA (2015) in Sociology from UC San Diego and Sun Yat-sen University, respectively. His research investigates how sociotechnical systems surveil and classify citizens, particularly in China’s Social Credit Systems and pandemic contact tracing. He employs mixed methods to analyze algorithmic governance, public perception, and institutional power dynamics. Article Trends: Recent publications address algorithmic surveillance in China, pandemic response frameworks, and long-term studies on HIV stigma, testing behaviors, and sexual health interventions among Chinese men who have sex with men (MSM). Key subfields include sociotechnical systems, health communication, and data politics. Scientific Awards: Hacker-Mullins Graduate Student Paper Award (2022) Martin Levine Student Paper Award (2020) Best Paper Award, Lancet-CAMS Health Summit (2017) Multiple internal and external fellowships from UC San Diego, ASA, and AAS He has guest-lectured at the University of Milan, Boston University, and Arizona State University and served as a teaching assistant at UC San Diego for courses on health sociology, law, and future prediction. His work is supported by grants from the Chiang Ching-kuo Foundation, Horowitz Foundation, and Microsoft Research.

Teresa Brunsdonمشاهده پروفایل

مدرس ارشد

• Time Series Analysis
• Compositional Data
• Data Science
• +۳ مورد دیگر

Dr. Teresa Brunsdon is a Senior Lecturer in the Department of Statistics at the University of Warwick, part of the Faculty of Science. She holds a PhD in Time Series Analysis of Compositional Data from the University of Southampton (1997) and has over three decades of academic experience, including 31 years at Sheffield Hallam University before joining Warwick in 2019. Education: BSc in Mathematics Sciences, Loughborough University MSc in Applied Statistics, University of Southampton PhD in Time Series Analysis of Compositional Data, University of Southampton Research Interests: Time Series Analysis Compositional Data Analysis Machine Learning Applications (e.g., interpretable classifiers) Statistical Methodology Education Technology in Data Science Teaching: Delivers core modules such as Introduction to Statistical Practice (ST952) and Designed Experiments (with Advanced Topics) (ST305/ST410) at Warwick. Publications: Focuses on time series methodologies, compositional data, and applications in social media and language processing (e.g., Sinhala documents). Recent work explores ethical AI and interpretable machine learning. Affiliations: Office: MSB 2.11 Email: teresa.brunsdon@warwick.ac.uk Office Hours: Monday 16:30–17:30 and Thursday 11:30–12:30

Sharif Ullahمشاهده پروفایل

استادیار

• Cybersecurity
• Cyber Threat Analysis
• Anomaly Detection
• +۴ مورد دیگر

Sharif Ullah is an Assistant Professor in the Department of Computer Science and Engineering at the University of Central Arkansas (UCA). He holds a Ph.D. in Electrical and Computer Engineering from Old Dominion University, along with M.Sc. and B.Sc. degrees in Applied Physics, Electronics & Communication Engineering from the University of Dhaka, Bangladesh. His research focuses on cybersecurity, including cyber threat analysis, anomaly detection, adversarial behavior analysis, and industrial internet of things (IIoT). He explores AI-driven solutions for intrusion detection, secure data sharing, and enhancing cybersecurity in critical infrastructure like energy delivery systems. Recent work highlights include adaptive intrusion detection systems leveraging reinforcement learning, privacy-preserving medical data sharing, and automated attack pattern analysis. His research also intersects interdisciplinary areas, such as analyzing social media discourse on immigration using mixed-methods approaches. Dr. Ullah’s publications span topics from cyber defense remediation in energy systems to cognitive radio network optimization. His work emphasizes practical applications of cybersecurity principles in real-world scenarios, particularly in industrial and healthcare domains.

• Biometric Recognition
• Presentation Attack Detection
• Deepfake Forensics
• +۵ مورد دیگر

Giulia Orrù is an Assistant Professor of Computer Engineering at the University of Cagliari, Italy, affiliated with the Department of Electrical and Electronic Engineering. She holds an M.S. and Ph.D. in Electronic Engineering and Computer Science from the same institution. Her research focuses on biometric recognition, presentation attack detection, deepfake forensics, and cybersecurity. She is a core member of the Pattern Recognition and Applications Laboratory (PRA lab), contributing to projects like BullyBuster (anti-bullying detection systems) and LivDet competitions (fingerprint liveness detection). Dr. Orrù has authored numerous publications in top-tier conferences and journals, with a strong emphasis on advancing secure authentication systems and combating adversarial attacks in biometrics. She actively serves as a referee for pattern recognition and cybersecurity venues. Teaching activities include courses such as Technologies for Information Security and Artificial Intelligence and Security . Research interests span multimodal biometrics, 3D face reconstruction for surveillance, AI-driven anti-bullying systems, and deepfake detection algorithms. Her work bridges theoretical advancements (e.g., diffusion models for anomaly detection) with real-world applications like forensic recognition and crowd analysis. Notable projects include the Synthetic Data for Face Recognition (SdFR) initiative and contributions to the Face Deepfake Detection Challenge. Dr. Orrù's lab explores cutting-edge techniques in EEG-based personal recognition and vulnerability analysis of medical AI systems. She maintains active participation in international research networks and has developed open-source tools for evaluating biometric system resilience against spoofing attacks.

• Spatial Data Infrastructure (SDI)
• GIS Applications
• Machine Learning in Geoinformatics
• +۳ مورد دیگر

Iwona Kaczmarek is a Professor in the Department of Systems Research at the Wrocław University of Science and Technology's Faculty of Spatial Management and Landscape Architecture. Her work focuses on advancing spatial data infrastructure (SDI), geoinformatics, and machine learning applications in urban and regional planning. She leads interdisciplinary research integrating GIS, natural language processing (NLP), and graph neural networks to address challenges in spatial planning, policy analysis, and socio-economic modeling. Research interests include: Spatial data integration and interoperability Machine learning for geospatial analysis Semantic web technologies for open data Urban sustainability and transit-oriented development Policy text mining and stakeholder analysis Recent work emphasizes: 1. Combining media sentiment analysis with economic indicators during crises (2025) 2. GeoAI-driven quality of life predictions using graph neural networks (2023) 3. Knowledge graph extraction from spatial development plans (2023) 4. Harmonizing local planning documents via NLP (2022) Collaborations include projects like the EYE initiative analyzing remote sensing for economic trends and SDI implementations in academic contexts. Over 75 documented outputs highlight her contributions to geospatial innovation and policy-relevant research.

• Chronic Obstructive Pulmonary Disease (COPD)
• Immunology
• Respiratory Medicine
• +۵ مورد دیگر

Andrew Higham is a Research Fellow in the Division of Immunology, Immunity to Infection and Respiratory Medicine. His work focuses on Chronic Obstructive Pulmonary Disease (COPD), inflammation, and respiratory medicine. He completed his PhD in 2014 under Dr. D. Singh, investigating the role of the Liver X Receptor in COPD. His research spans COPD pathophysiology, smoking effects, neutrophil/eosinophil dynamics, and therapeutic strategies. Key research interests include COPD pharmacology, small airway remodeling, electronic cigarette impacts, and type 2 inflammation mechanisms. He has contributed to high-impact studies like the FLAME trial and RECOVERY trial on corticosteroid use in severe COVID-19 cases. His work has been featured in media outlets like COPD News Today and The Express. Higham has published over 40 articles since 2011, with recent focus on COPD subphenotypes, exhaled nitric oxide biomarkers, and long-term smoking effects. He received the British Thoracic Society Early Career Investigator Award in 2014. Education: PhD in Chronic Obstructive Pulmonary Disease (2014) Awards: British Thoracic Society Early Career Investigator Award (2014) Media Coverage: Over 7 media mentions on COPD, e-cigarettes, and lung disease Collaborations: Global networks on COPD and respiratory medicine

• Bioinformatics
• Health Informatics
• Affective Computing
• +۳ مورد دیگر

Dr. Stamos Katsigiannis is an Associate Professor in the Department of Computer Science at Durham University. His research focuses on bioinformatics, health informatics, affective computing, and GPU computing. He holds a BSc, MSc, and PhD in Computer Science from the University of Athens and the Athens University of Economics and Business. Before Durham, he was a Postdoctoral Research Fellow and Lecturer at the University of the West of Scotland (2016–2020). His work spans biometric identification via EEG signals, medical image analysis, and deep learning applications in healthcare. Education: BSc (Hons.) in Informatics and Telecommunications from National and Kapodistrian University of Athens MSc in Computer Science from Athens University of Economics and Business PhD in Computer Science from National and Kapodistrian University of Athens Research interests include bioinformatics (e.g., microarray analysis), health informatics (e.g., ECG-based emotion modeling), and GPU computing for real-time applications. He has pioneered studies on EEG-based biometrics and affect recognition in human-horse interaction. Recent articles explore chest X-ray classification using deep learning , AI-generated content detection , and trajectory prediction with graph networks . His research emphasizes interdisciplinary applications of machine learning in healthcare and education. He advises six postgraduate students and collaborates on UK parliamentary AI governance reports. Notable contributions include the BED EEG dataset and the DREAMER emotion recognition database.