جست‌وجوی استاد و پژوهشگر

• Law and Forensic
• Psychology and Law
• Eyewitness Identification
• +۳ مورد دیگر

Ryan Fitzgerald is an Associate Professor (on leave) in the Department of Psychology at Simon Fraser University. His research focuses on law and forensic psychology, particularly eyewitness identification, face recognition, memory, and meta-analysis. He directs the EyeWitnessLab (www.eyewitnesslab.com/) and has contributed to advancing understanding of how social media, lineup procedures, and stress affect eyewitness accuracy. His work bridges psychological science with legal practice through police training initiatives and evidence-based policy reforms. Research Interests: Psychology and Law Eyewitness Identification Mechanisms Face Recognition Technologies Memory Distortion Factors Cross-Cultural Forensic Practices Meta-Analytic Methodology Recent work highlights innovations like the Eyewitness Lineup Identity (ELI) database and augmented reality lineup applications. Fitzgerald emphasizes practical implications of his research, aiming to reduce wrongful convictions through evidence-based practices.

• Artificial Intelligence
• Machine Learning
• Medical Imaging
• +۴ مورد دیگر

Prof Noel O'Connor is a Full Professor at Dublin City University's School of Electronic Engineering, specializing in cutting-edge research at the intersection of artificial intelligence (AI), medical imaging, robotics, and smart city technologies. His work spans applications such as cardiac MRI reconstruction, robotic manipulation using reinforcement learning, and the development of the Smart DCU Digital Twin for autism-friendly university environments. Research interests include AI-driven medical diagnostics, multimodal data fusion, and adaptive systems. His contributions to cardiac MRI reconstruction and transformer-based medical imaging analysis reflect a strong focus on healthcare innovation. He also explores ethical AI practices to reduce social bias in foundation models. Recent work emphasizes smart infrastructure projects, such as optimizing parking recommendations for electric vehicles and enhancing accessibility through digital twin frameworks. His research often integrates real-time sensor data and multi-agent systems to address complex urban challenges. No scientific awards are listed. Collaborations include the ASU-DCU International Research Program on Sensors and Machine Learning. Advising details and grant information are not explicitly provided.

Maryam Aldossariمشاهده پروفایل

مدرس ارشد

• Gender and Equality Studies
• Cross-Cultural Management
• Psychological Contracts
• +۵ مورد دیگر

Maryam Aldossari is a Senior Lecturer in the Department of Human Resource Management and Organisation Studies at Royal Holloway, University of London. Her research focuses on gender equality, cross-cultural management, and the applicability of Western theories in Middle Eastern contexts. She holds a PhD from Queen Mary University of London, an MSc in HRM from Brunel University, and a BA in English Literature from King Faisal University. Dr. Aldossari’s work bridges Eastern and Western perspectives, particularly exploring gendered precarity in Saudi Arabia, psychological contracts, and expatriation/repatriation dynamics. She is an Associate Editor of Gender, Work & Organization and has contributed to high-impact journals addressing issues like Palestinian rights and decolonial feminism. Her editorial roles include serving on panels for Group & Organization Management and Work, Employment and Society . Her recent research highlights include analyzing socio-institutional factors in Pakistan’s labor market and critiquing Western feminism’s silence on Palestinian genocide. She supervises PhD students at the University of Edinburgh Business School and actively engages in public discourse on topics such as Saudi Arabian labor policies and global feminist accountability. Dr. Aldossari’s work aligns with UN Sustainable Development Goals focused on gender equality and decent work. Her collaborations span international scholars and institutions, reflecting her commitment to global academic and societal impact.

Seth Polsleyمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Intelligent Systems
• Educational Technology
• +۴ مورد دیگر

Seth Polsley is an Assistant Professor in the Jeffrey S. Raikes School of Computer Science and Management at the University of Nebraska-Lincoln. His academic home resides in the School of Computing, where he bridges intelligent systems design with human-computer interaction to enhance educational and universal computing experiences. BS in Computer Engineering (2014) - University of Kansas MS (2017) & PhD (2023) in Computer Engineering - Texas A&M University His research explores: Intelligent tutoring systems Brain-computer interfaces Accessible educational technologies Machine learning for child development assessment Sketch recognition in STEM learning Recent publications demonstrate expertise in tactile learning interfaces, sketch-based developmental assessment, and equitable AI systems. Key disciplines span Human-Computer Interaction, Machine Learning, and Educational Technology. Scientific recognition includes: James Blackiston Memorial Graduate Fellowship Sigma Xi Research Award With professional experience at Lexmark International and MIT Lincoln Lab, Polsley combines practical engineering with educational innovation. His work on sketch-based tools and wearable systems addresses both technical and societal challenges in computing.

Andrea Crovettoمشاهده پروفایل

دانشیار

• Photovoltaics
• Solar Energy Conversion
• Thin Film Technology
• +۳ مورد دیگر

Andrea Crovetto is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the National Centre for Nano Fabrication and Characterization and the Department of Nanofabrication. His research focuses on advanced materials for photovoltaic applications, including solar cell technologies, thin films, and semiconductor materials. His work contributes to UN Sustainable Development Goals related to affordable and clean energy. Key research interests include photovoltaic materials discovery, tandem solar cell design, and semiconductor characterization. Notable achievements include developing monolithic selenium/silicon tandem solar cells and pioneering studies on phosphosulfide semiconductors. He has authored over 90 publications and datasets, including high-impact articles in journals like JPhys Energy and PRX Energy . Dr. Crovetto has received the Young Scientist Award (2016) and actively supervises PhD students in projects such as Experimental Discovery of Phosphosulfide Materials for Solar Cells and Thiophosphate Thin Films for Quantum Technology . His research also involves collaborations on material synthesis, computational modeling, and device fabrication. He has presented at international conferences, including talks on monolithic tandem solar cells and materials discovery methodologies. His lab, based at DTU’s Produktionstorvet , integrates experimental and theoretical approaches to advance sustainable energy technologies.

Giulia Totiمشاهده پروفایل

استادیار

• Computer Science Education
• Ethics in Data Science
• Machine Learning
• +۳ مورد دیگر

Giulia Toti is an Assistant Professor of Teaching in the Department of Computer Science at the University of British Columbia (UBC), part of the Faculty of Science. Her work focuses on computer science education, equity in curriculum design, and fostering inclusive learning environments. She teaches courses such as Applied Machine Learning (CPSC 330), Fairness, Accountability, Transparency, and Ethics (FATE) in Data Science (DSCI 430), and Computers and Society (CPSC 430). Her research explores diversity initiatives in CS education, mastery learning frameworks, and equitable grading practices. Notable contributions include studies on pandemic-era remote teaching impacts and the development of Agora, a tool for enhancing large-classroom engagement. Toti has received UBC Faculty Teaching Awards for her pedagogical innovations. Her interdisciplinary work spans machine learning applications in industry and healthcare, including semantic search systems for clinical data (SemEHR) and predictive analytics for energy production. She is affiliated with the ACE Lab and actively contributes to curriculum reforms addressing DEI (Diversity, Equity, Inclusion) challenges in STEM education. Grants/Awards: Faculty Teaching Awards Labs/Teams: ACE Lab (Advancing Computing Education) Advising: No explicit advisee listings found, but contributes to pedagogical research impacting teaching practices.

Skyler Wangمشاهده پروفایل

استادیار

• AI
• Technology
• Human-Computer Interaction
• +۷ مورد دیگر

Skyler Wang is an Assistant Professor of Sociology at McGill University, specializing in AI, technology, and human-computer interaction. He holds a Ph.D. from UC Berkeley and previously served as a Sociologist at Meta’s FAIR lab. His research critically examines sociotechnical systems' epistemic cultures and social impacts, focusing on AI-driven human-machine interactions in health, relational contexts, and digital platforms. His research interests include AI ethics, platform societies, digital intimacy, and multilingual systems. Notable works include the book project Sharing Bodies in the Sharing Economy , exploring Couchsurfing’s sociosexual dynamics, and applied AI projects like No Language Left Behind (doubling machine translation languages) and SeamlessM4T (awarded TIME’s 2023 Best Inventions). Teaching focuses on Technology & Society, Artificial Intelligence & Society, and Digital Intimacy. Advising roles include Major/Minor and Honours Sociology students. Active in interdisciplinary collaborations through McGill’s Quebec Inter-University Centre for Social Statistics and global AI ethics initiatives. Education: Ph.D. Sociology, UC Berkeley (2023) Key Affiliations: Meta FAIR Lab (prior), McGill Department of Sociology Publications in Nature , CSCW , Big Data & Society , and media features in WIRED, CNN, and NPR

Archie Chapmanمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Game Theory
• Optimization
• +۸ مورد دیگر

Associate Professor Archie Chapman is an Associate Professor in Computer Science and Deputy Director (Teaching and Learning) at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on applying artificial intelligence, game theory, optimization, and machine learning to address challenges in future power systems, including renewable energy integration and battery storage optimization. Prior to UQ, he held roles as a Research Fellow in Smart Grids at the University of Sydney (2011-2019) and a postdoc at the University of Southampton (2009-2010), where he completed his PhD in 2004. Research interests include: - Large-scale optimization for energy systems - Demand response and peer-to-peer energy trading - Renewable energy integration and grid stability - Battery storage strategies for smart grids - Algorithmic game theory for energy market design Notable projects: - Bruny Island battery trial for network congestion management - Analysis of tariff impacts on solar households - Development of decentralized energy management frameworks Publications span over 100 articles, with recent work focusing on: - Prosumer battery systems and capacity firming (2025) - Unbalanced optimal power flow benchmarks (2024) - P2P energy trading mechanisms (2021-2023) Expertise includes: - Techno-economic analysis of energy systems - Distributed optimization algorithms - Policy and market design for renewable integration

Christoph T. Kochمشاهده پروفایل

استاد

• Electron Microscopy
• Materials Science
• Condensed Matter Physics
• +۳ مورد دیگر

Christoph T. Koch is a Professor of Physics at Humboldt-Universität zu Berlin, where he has held the W3 Chair since 2015. Previously, he held a similar position at Ulm University (2011–2015), supported by the Carl Zeiss Foundation. His research focuses on advanced electron microscopy techniques, including quantitative transmission electron microscopy (TEM), electron holography, and strain mapping. He leads the AG Strukturforschung/Elektronenmikroskopie group, advancing materials science through innovations in imaging and spectroscopy. Education: B.Sc./M.Sc. in Physics at Heidelberg University (1996–1998), followed by an exchange at Arizona State University (1997–1998). PhD in Physics from Arizona State University (2002, advisor: Prof. John C.H. Spence). Postdoctoral research at the Max Planck Institute for Metals Research, Stuttgart (2002–2011). Research interests include: Electron diffraction and phase retrieval Nanometer-scale strain and defect analysis Electron energy-loss spectroscopy (EELS) for plasmonics and bandgap mapping Development of FAIR data infrastructure for materials science Leadership: Managed the Department of Physics at Humboldt University (2020–2024). Collaborates widely, with key co-authors including P.A. van Aken, W. Sigle, and C. Felser. His work bridges experimental microscopy and computational modeling, addressing challenges in semiconductors, ceramics, and 2D materials. Notable contributions include pioneering methods for 3D reconstruction via electron ptychography, dynamic electron diffraction analysis, and strain mapping in advanced CMOS technologies. Current efforts emphasize real-time imaging and AI-driven data analysis in materials research.

Svetlana Yanushkevichمشاهده پروفایل

استاد

• Biometric Technologies
• Machine Learning
• Signal Processing
• +۳ مورد دیگر

Dr. Svetlana Yanushkevich is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. She is also a Full Member of the Hotchkiss Brain Institute and the Mathison Centre for Mental Health Research and Education. Her research focuses on biometric technologies, decision support systems, biomedical applications, and computational intelligence. She leads the Biometric Technologies Laboratory, developing strategies for risk assessment in biometric systems and healthcare monitoring through machine reasoning and signal processing. Education : BSc/MSc in Electrical Engineering (1989), State University of Informatics and Radioelectronics, Minsk PhD in Electrical Engineering (1992), same institution Dr. Habilitated in Technical Sciences (1999), Warsaw University of Technology Research Interests : Dr. Yanushkevich’s work spans biometric system design (e.g., gait analysis, facial attributes), decision support via probabilistic models (Bayesian networks, causal inference), biomedical applications (stroke rehabilitation, wearable sensors), and computational intelligence for data science. She emphasizes fairness, bias mitigation, and trustworthiness in AI systems, particularly in healthcare and accessibility contexts. Recent Research Trends : Her recent publications address causal modeling for accessibility barriers, UAV operator cognitive workload, and medical device optimization in radiation therapy. She explores AI ethics, stress contagion in human-robot teams, and cross-spectral biometric systems. Awards & Recognition : 2024 FEIC Fellow (Engineering Institute of Canada) 2019 Research Excellence Award (Schulich School of Engineering) 2001 Senior IEEE Membership Advising & Grants : She coordinates courses like ENCM 509 (Biometric Systems Design) and ENEL 610 (Biometric Technologies). Her research is supported by grants focusing on healthcare AI, accessibility technologies, and computational epidemiology. Labs & Collaborations : Her Biometric Technologies Lab collaborates with institutions like Hokkaido University and the IEEE Computational Intelligence Society. Projects include wearable health monitoring, decision support platforms, and AI-driven epidemiological modeling.

• Artificial Intelligence
• Natural Language Processing
• Computational Semantics
• +۵ مورد دیگر

Luis Espinosa-Anke is a Senior Lecturer at Cardiff University's School of Computer Science and Informatics. His academic journey includes working as a Natural Language Processing (NLP) scientist at Savana Médica, a Madrid-based healthcare AI company, prior to joining Cardiff. He completed his PhD at Pompeu Fabra University in Barcelona while working at Savana. Dr. Espinosa-Anke's research focuses on Artificial Intelligence and NLP, with particular emphasis on meaning representation, computational semantics, multilingual NLP, and computational lexicography. His work spans theoretical and applied aspects of language technology, with applications in healthcare, social media analysis, and multilingual systems. His recent publications reveal a strong trend toward analyzing language model behavior, bias detection in AI systems, and creating resources for semantic analysis. The publications show increasing focus on practical applications of NLP in healthcare, social media, and cross-lingual settings, with notable contributions to datasets like WIKITIDE and 3D-EX that support definition extraction and semantic understanding. laCaixa Fellow Fulbright scholarship recipient Erasmus Mundus program participant Dr. Espinosa-Anke has secured research funding including a Kaggle Open Research grant ($2,000 USD) as PI for the 'Don't Patronize Me!' project, a Snap Inc. grant ($10,000 USD) as CO-I for modeling meaning shift in social media, and a £90,000 Welsh Government grant for English-Welsh bilingual embeddings research. He currently supervises five PhD students working on meaning representations, contextual word embeddings, NLP for healthcare applications, and metaphor identification.

Jerrell D. Coggburnمشاهده پروفایل

استاد

• Public Human Resources Management
• Public Management
• Government Procurement
• +۳ مورد دیگر

Jerrell D. Coggburn is a Professor and Chair of the Department of Public Administration at NC State University’s School of Public and International Affairs (SPIA). He also serves as the PhD Program Director. His research focuses on public human resources management and public management, with notable contributions to organizational justice, employee benefits, and public pension systems. Coggburn holds a B.A. in Political Science from Oklahoma State University and an MPA and Ph.D. from the University of South Carolina. He has held leadership roles including MPA Director and Department Chair at the University of Texas at San Antonio (1999–2007). Coggburn’s awards include the 2022 Jonathan West Outstanding Scholar Award and the 2018 Jesse Burkhead Award. He serves on editorial boards for journals like the Review of Public Personnel Administration and chairs NASPAA’s Commission on Peer Review and Accreditation (COPRA). His research spans topics such as mediation effectiveness, green procurement, and retirement benefits for public employees. He teaches courses like PA 510 (PA Institutions and Values) and PA 714 (PA Research Methods), emphasizing ethical and strategic dimensions of public administration.

Desmond Upton Pattonمشاهده پروفایل

استاد

• Social Media Impact
• Public Health
• AI Bias
• +۷ مورد دیگر

Desmond Upton Patton is the Brian and Randi Schwartz University Professor at the University of Pennsylvania, with joint appointments in the School of Social Policy & Practice and Annenberg School for Communication, and a secondary appointment in the Department of Psychiatry at the Perelman School of Medicine. His work bridges social work, data science, and digital sociology to address issues like social media's impact on marginalized communities, AI bias, and violence prevention. Education: B.A., University of North Carolina at Greensboro (2004); M.S.W., University of Michigan (2006); Ph.D., University of Chicago (2012). Research focuses on social media's role in trauma, grief, and violence among Black and Hispanic youth. He developed the Contextual Analysis of Social Media (CASM) methodology to address cultural biases in AI. Key projects include studying grief pathways on Twitter, digital mourning practices, and algorithmic equity in child welfare systems. Notable awards include the Deborah K. Padgett Early Career Achievement Award (2018) and fellowships at Harvard's Berkman Klein Center and the Harvard Kennedy School. He advises platforms like Twitter and Spotify on safety and bias. Grants include an NSF-funded program supporting STEM researchers from underrepresented backgrounds. He directs SAFELab, which explores digital safety and equity. Courses taught include 'Advocacy in Emergent Technology' and 'Journey to Joy: Designing a Happier Life.' Future work emphasizes AI ethics, inclusive tech policy, and leveraging community insights to shape equitable digital tools.

Viktoria Spaiserمشاهده پروفایل

استاد

• Climate Politics
• Sustainability Research
• Computational Social Science
• +۵ مورد دیگر

Professor Viktoria Spaiser is a Professor of Climate Politics and Computational Social Science at the University of Leeds' School of Politics and International Studies (POLIS), holding this position since March 2025. Previously, she served as an Associate Professor (2020–2025) and a University Academic Fellow (2015–2020). She is affiliated with the Priestley Centre for Climate Futures and the Leeds Institute for Data Analytics (LIDA). Her research focuses on societal transitions to sustainability, climate governance, and computational social science methods. Education: PhD in Sociology (Bielefeld University, 2012), MA in Conflict, Security and Development (King’s College London, 2008), German Diploma in Computer Science (University of Applied Sciences Trier, 2013). Postdoctoral research included roles at ETH Zurich, the Institute for Futures Studies Stockholm, and Uppsala University. Research interests emphasize rapid, fair transitions to zero-emissions societies, leveraging mathematical and computational tools. Current projects include a UKRI Future Leaders Fellowship on 'Understanding normative change to address the climate emergency.' She explores topics like climate narratives, behavioral change, tipping points governance, and AI applications in social science. Methodological expertise spans agent-based modeling, big data analysis, and Bayesian statistics. Teaching focuses on quantitative and computational methods, including modules on programming for social science, statistical analysis, and climate justice. She supervises PhD students in climate politics, AI ethics, and advanced quantitative methods. Her work bridges academia and policy, addressing global challenges such as disinformation, democratic engagement, and socio-ecological system dynamics. Recent projects include studies on climate protests' impact on policy, smartphone-based behavioral interventions, and EU governance of tipping points.

• Data Mining
• Machine Learning
• Clustering Algorithms
• +۳ مورد دیگر

Anna Beer is a researcher in the Faculty of Computer Science, specializing in data mining and machine learning with a focus on density-based clustering, spectral clustering, and interactive clustering frameworks. She holds a BSc and MSc in computer science and maintains an ORCID profile (https://orcid.org/0000-0002-6890-997X) for her research contributions. Research Themes: Development of clustering algorithms (e.g., DISCO, Scar, LUCKe), fairness in density-based clustering (FairDen), and applications to molecular dynamics and climate research (DROPP). Collaborations: Works with colleagues like Ira Assent, Christian Plant, and Lars Krieger, with recent contributions to conferences like ICLR 2025. Activities: Presented research on density-connectivity distance at a 2023 oral contribution. Publications: 9 publications since 2019, including 3 in 2025 and 6 in 2024, covering topics from cluster evaluation to deep active learning strategies.