جست‌وجوی استاد و پژوهشگر

Elham Shafiei Golمشاهده پروفایل

مدرس ارشد

• Digital Transformation
• Future of Work
• Digital Labour Platforms
• +۹ مورد دیگر

Dr Elham Shafiei Gol is a Senior Lecturer in Information Systems at Brunel Business School, part of the College of Business, Arts and Social Sciences at Brunel University London. Her research focuses on digital transformation, the future of work, digital labour platforms, and responsible innovation. Education: PhD in Information Systems, Copenhagen Business School (CBS), Department of Digitalization MSc in Information Technology, Amirkabir University of Technology Her research explores how digital platforms govern creative crowdwork to enable organizational value creation through co-creation, open innovation, and absorptive capacity. She employs sociotechnical and practice-based perspectives to understand the interplay between organizations, individuals, technologies, and work activities in digital environments. Her work bridges theory and practice, informed by her prior experience as a business analyst and usability researcher in the banking industry. Her recent publications span high-impact journals such as Information Systems Research and The Journal of Strategic Information Systems , as well as top conferences including ICIS and ECIS. Collectively, her articles reflect a sustained focus on governance models in crowdwork platforms, the motivations of skilled gig workers, and the role of digital innovation in organizational transformation. Scientific Awards and Recognition: Fellow of the Higher Education Academy (FHEA) Dr Shafiei Gol serves as a reviewer for leading journals including Journal of Strategic Information Systems and Information & Management . She is actively involved in the academic community through memberships in the Association for Information Systems (AIS), AIS Women’s Network, and the Platform Economy Interest Group (PEIG) at the University of Oxford. She teaches courses in digital transformation, AI strategy, mobile and social media services, and research methods, contributing to both undergraduate and postgraduate programs. She also mentors students and supports research development within her division of Sustainability and Innovation.

• Biometrics
• Behavioral Biometrics
• Mobile Authentication
• +۱۲ مورد دیگر

Ruben Tolosana is a researcher at the Biometrics and Data Pattern Analytics Lab (BiDA Lab) in the School of Engineering at Universidad Autónoma de Madrid. His work centers on biometrics, with emphasis on behavioral and mobile authentication, face recognition, privacy-enhancing technologies, and deep learning applications in human-computer interaction. He actively contributes to major research initiatives such as the FRCSyn-onGoing challenge and the ChildCI framework. PhD in Computer Science or related field (inferred from publication volume and role) Advanced training in machine learning, computer vision, and biometrics His research interests include behavioral biometrics, mobile device security, synthetic data for AI training, privacy in biometric systems, and the application of Transformer models to user authentication. Tolosana's work often involves the development of novel datasets and benchmarking platforms to advance the field. He has co-authored influential surveys on privacy vulnerabilities in mobile sensors and privacy-preserving techniques in biometric recognition. The most recent articles highlight trends in using synthetic data for face recognition, applying Transformers to behavioral biometrics (keystroke, touchscreen, gait), and developing frameworks for child age detection via interaction patterns. His work consistently addresses real-world challenges such as privacy, bias, and system generalization. Publications in journals like Information Fusion , Pattern Recognition , and ACM Computing Surveys reflect the high impact and interdisciplinary nature of his research. Second FRCSyn-onGoing: Winning solutions and post-challenge analysis to improve face recognition with synthetic data (2025) ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection (2024) FRCSyn-onGoing: Benchmarking and comprehensive evaluation of real and synthetic data to improve face recognition systems (2024) SwipeFormer: Transformers for mobile touchscreen biometrics (2024) An Overview of Privacy-Enhancing Technologies in Biometric Recognition (2024) Ruben Tolosana collaborates extensively with researchers in the BiDA Lab, including Rubén Vera-Rodríguez, Aythami Morales, Julian Fierrez, and others. He has contributed to the development of public databases such as mEBAL and ChildCIdb, supporting open science. His work is supported by ongoing research grants (inferred from project scope and publications), and he plays a key role in organizing workshops such as WAMWB to advance the mobile and wearable biometrics community. He is a core member of the Biometrics and Data Pattern Analytics Lab (BiDA Lab), a leading research group in biometric technologies, where he contributes to multiple projects involving mobile authentication, face recognition, and privacy-preserving AI systems.

Rafael Pereira Piresمشاهده پروفایل

مدرس

• Distributed Systems
• Machine Learning
• Privacy-Preserving Technologies
• +۳ مورد دیگر

Rafael Pereira Pires is a Lecturer and researcher at École polytechnique fédérale de Lausanne (EPFL) , affiliated with the Scalable Computing Systems Laboratory (SACS) and IC-SIN units. His research focuses on systems solutions at the intersection of privacy, efficiency, and machine learning in distributed environments. Education PhD in Computer Science (2019, University of Neuchâtel, Switzerland) Professional Master in Mechatronics (2014, IFSC, Brazil) Master in Computer Science (2009, UFSC, Brazil) His work explores privacy-preserving decentralized learning , trusted execution environments , and resource-efficient distributed systems . Recent publications address techniques like model fragmentation, approximate caching, and secure aggregation in decentralized learning contexts. Key trends in his 2023-2025 publications include: Advancements in federated learning and Mixture-of-Experts (MoE) models Applications of Trusted Execution Environments (SGX) to decentralized systems Optimization techniques for energy-aware and low-cost learning Scientific recognition includes the 2019 Léon Du Pasquier et Louis Perrier award for his PhD thesis. He has contributed to open-source tools like DecentralizePy and served as reviewer/PC member for top conferences including NeurIPS , Middleware , and ICDCS .

• Engineering Education
• Academic Motivation
• Diversity in STEM
• +۵ مورد دیگر

Dr. Walter C. Lee is an Assistant Professor in the Department of Engineering Education at Virginia Tech. His research focuses on engineering education pedagogy, academic motivation, and diversity initiatives in STEM. He has contributed extensively to the Journal of Women and Minorities in Science and Engineering through empirical studies and theoretical frameworks. Research Emphasis: Academic motivation models Key Contributions: Summer bridge program effectiveness Current Work: Systematic analysis of racial equity in engineering His scholarship examines co-curricular support systems and systemic barriers for Black Americans in engineering, with recent work (2024) exploring interpersonal relationships in undergraduate programs. Journal roles include Associate Editor, Guest Editor, and reviewer for equity-focused publications. Contact: walterl@vt.edu | Virginia Tech Faculty Profile

• Artificial Intelligence
• Data Analytics
• Machine Learning
• +۵ مورد دیگر

Prof. Dr. Christian Schulze is a Professor in the Faculty of Mathematics, Natural Sciences and Data Science at the Technical University of Central Hesse (THM), affiliated with the Competence Center for Information Technology (KITE). His research focuses on Artificial Intelligence and Data Analytics for real-world industry applications. Key projects demonstrate expertise in: LEGADA (2022-2024): Developing AI-driven lead generation systems for B2B sales using self-learning algorithms, funded with €386,330 by Hesse's 'Distr@l' program TLDia (2019-2021): Automating medical diagnosis coding through transfer learning in collaboration with Goethe University Frankfurt PAROT (2016-2018): Creating SaaS recommendation engines for e-commerce personalization ADOMIS (2015-2017): Integrating heterogeneous financial data sources for statistical analysis Prof. Schulze secures significant research funding from the State of Hesse (LOEWE-3 and 'Distr@l' programs) and maintains active industry partnerships with Minds-Medical GmbH, Dastani Consulting GmbH, and Content Software GmbH. His work bridges academic research with practical business solutions in AI deployment.

Krzysztof J. Kochutمشاهده پروفایل

استاد

• Knowledge Graphs
• Ontologies
• Semantic Web
• +۷ مورد دیگر

Krzysztof J. Kochut is a Professor in the School of Computing at the University of Georgia. His career at UGA spans from Limited Term Assistant Professor (1987–1988) to his current professorial role since 2001. He holds a Ph.D. in Computer Science from Louisiana State University (1987) and an M.S. from the University of Warsaw (1982). Education: Ph.D., Computer Science, Louisiana State University (1987) M.S., Computer Science, University of Warsaw (1982) His research focuses on knowledge graphs, ontologies, semantic web technologies, bioinformatics, distributed systems, and computational intelligence. He has developed frameworks for knowledge graph embedding, entity summarization, and semantic resource federation. Recent publications highlight knowledge graph mining, random walk-based embeddings, and relation prediction using large language models. Funded by NIH and NSF, his work addresses challenges in biomedical data integration and dark proteome annotation. Scientific Awards: Student Career Success Influencer Award 2024 Student Career Success Influencer Award 2022 Outstanding Faculty Service Award 2016 Best Paper Award 2015 Professor Kochut has received grants for projects like Annotating dark ion-channel functions using knowledge graph mining (NIH, 2021–2025) and Integrated Technology Resource for Biomedical Glycomics (NIH, 2002–2008). He leads the development of tools such as GTXplorer for glycosyltransferase analysis and participates in semantic web initiatives.

Stanica Lavinia Justinaمشاهده پروفایل

مدرس

• Software programming
• e-Learning
• Artificial Intelligence
• +۱۰ مورد دیگر

Lavinia Stănică Justina is a university lecturer at the Faculty of Managerial Informatics, Romanian-American University (URA), with 18 years of teaching experience in software programming and e-learning domains. Holding a PhD in Cybernetics and Economic Statistics since 2011, she teaches courses in Romanian and English at both bachelor's and master's degree programs. Her research focuses on ICT's role in innovation, educational technologies, and data analysis for energy consumption, with over 30 publications and multiple coordinated research projects. Faculty: Managerial Informatics University: Romanian-American University Academic Rank: Lecturer Teaching Experience: 18 years PhD: Cybernetics and Economic Statistics (2011) Her research interests include: e-Learning systems and technology integration Artificial Intelligence applications in education ICT's impact on innovation performance Mathematical content modeling Energy consumption data analysis Internet of Things implementations Fractal techniques in imaging Recent publications highlight trends in: Comparative innovation-ICT readiness analysis AI education accessibility Smart energy systems Competitive programming metrics Neural network energy forecasting IoT cloud solutions Modular educational software As Erasmus coordinator since 2013 and Institutional Erasmus Coordinator since 2020, she actively promotes internationalization efforts and academic collaboration with partner universities across Europe.

Goran Glavašمشاهده پروفایل

استاد

• Computational Semantics
• Multilingual Representation Learning
• Low-Resource NLP
• +۲ مورد دیگر

Goran Glavaš is a Professor at the University of Würzburg's Faculty of Mathematics & Computer Science, holding the Chair for Natural Language Processing (Computer Science XII) and affiliated with the Center for Artificial Intelligence and Data Science (CAIDAS). His research focuses on computational semantics, multilingual/low-resource representation learning, and democratizing language technologies through fairness and sustainability. Former Assistant Professor at University of Mannheim (2017-2021) Interim Associate Professor at LMU Munich (2021-2022) Doctorate in 2014 at University of Zagreb under Jan Šnajder Recent research trends emphasize cross-lingual learning, multilingual knowledge integration, and ethical AI frameworks. His group contributes to robust multilingual models, vision-language systems, and sustainable NLP applications in social sciences. Outstanding Paper Award at ACL 2024 (IRCoder) Outstanding Paper Award at EACL 2024 (Kardeş-NLU) Extensive publications in EMNLP, ACL, NAACL, EACL, and TACL Advises a team of researchers at the University of Würzburg's NLP Chair, including Benedikt Ebing, Gregor Geigle, and Fabian David Schmidt. Leads the WüNLP group within CAIDAS, focusing on democratizing language technologies.

• Energy Policy
• Climate Change
• Public Attitudes
• +۵ مورد دیگر

Dr. Zeynep Clulow serves as a Research Associate at the Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge, and holds a College Research Associate position at Emmanuel College. She additionally supervises the Master of Studies in Sustainability Leadership program at the Cambridge Institute for Sustainability Leadership, demonstrating her commitment to academic mentorship and sustainable development education. Educational background: PhD from the University of Nottingham Her research centers on stakeholder attitudes toward energy technologies, with particular emphasis on negative emission technologies and practices (NETPs) and the socio-political dimensions of energy transition. She investigates how political ideology shapes public perceptions of fossil fuels, renewables, and carbon capture technologies, while also examining the broader implications of fossil fuel subsidies for sustainable development and educational outcomes. Her methodological expertise includes designing and analyzing public surveys to assess energy and environmental attitudes. Analysis of her publication record (2014-2024) reveals consistent interdisciplinary focus spanning climate policy, political economy, and energy transitions. Her work demonstrates sophisticated integration of survey methodology with policy analysis, particularly examining democracy's role in energy transitions, cross-national attitude comparisons, and the socio-technical challenges of carbon removal technologies. The research shows increasing attention to practical policy applications, including COP26 contributions and union-focused briefings on fossil fuel subsidies. Scientific Awards: No scientific awards were documented in the provided materials. Advising and Grants: Dr. Clulow supervises the Master of Studies in Sustainability Leadership program and has secured significant project involvement including consultancy for the BEIS COP26 Visions Project (co-authoring the UK just transition report) and authoring a policy brief for Education International on fossil fuel subsidies' educational impacts. Her research has been published in high-impact journals including Global Environmental Change, Climate Policy, and Energy & Environmental Science. Labs and Teams: As a core member of the Energy Policy Research Group at Cambridge Judge Business School, she contributes to this interdisciplinary team focused on evidence-based energy policy analysis, sustainable transition pathways, and stakeholder engagement strategies for decarbonization.

• Environmental Epidemiology
• Trace Element Toxicology
• Public Health
• +۳ مورد دیگر

Marco Vinceti is a Full Professor at the Department of Biomedical, Metabolic and Neuroscience Sciences, University of Modena and Reggio Emilia. His work bridges environmental epidemiology, trace element toxicology, and public health policy. Research Interests: Focus on metal/metalloid exposure (selenium, iron, fluoride), neurodegenerative diseases (ALS, dementia), climate change impacts on health, and dietary interventions (MIND diet). Teaching: Leads courses in Hygiene and Public Health for Medicine and Surgery, and Health Research Methodology for Nursing Sciences. Publications: Recent studies analyze metal mixtures and mental health, selenium in drinking water risks, tofersen's impact on ALS biomarkers, and climate change's role in West Nile Virus spread. Environmental Advocacy: Investigates healthcare sector plastic waste reduction through water refill stations. Article Trends: His 2025 publications emphasize environmental toxicology (metals, selenium), neurodegenerative biomarkers, and climate-related health risks. Sub-fields include dose-response meta-analysis, dietary patterns in aging, and urban green space mitigation of noise exposure.

• Educational Leadership
• Citizenship Education
• School Policy
• +۵ مورد دیگر

Idunn Seland is an Associate Professor in Educational Leadership at Oslo Metropolitan University (OsloMet), affiliated with the Faculty of Teacher Education and International Studies and the Department of Primary and Vocational Teacher Education. She specializes in school policy for citizenship and integration, with a PhD in sociology (major in political science). Current projects include EU-funded STRIDE (2024–2026) on educational inequality in Europe Work package leader in DigiGen (2020–2023) and DEMOCIT (2020–2023) projects Subject manager for OsloMet's master's program in Educational Leadership Her research focuses on educational leadership , digitalization in schools , and inclusion through national education systems . She employs qualitative methods but collaborates with quantitative researchers. Dedicated to reducing educational inequalities, her recent publications analyze digital well-being , ICT impacts on children , and democratic participation frameworks . She has evaluated school policy measures and led research groups on these topics. While no scientific awards are explicitly listed, her work directly influences European educational reforms through STRIDE and Nordic teacher training practices through DEMOCIT. She actively disseminates research through media contributions and conference presentations.

René Vidalمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Biomedical Data Science
• +۳ مورد دیگر

René Vidal is the Rachleff & Penn Integrates Knowledge (PIK) University Professor at the University of Pennsylvania, with appointments in the Departments of Electrical and Systems Engineering, Radiology, Computer and Information Science, and Statistics and Data Science. He also serves as Director of the Center for Innovation in Data Engineering and Science (IDEAS) and the NSF-Simons Collaboration on the Mathematical Foundations of Deep Learning (THEORINET). A dual faculty member at Johns Hopkins University in Biomedical Engineering, Computer Science, and other departments, Vidal is an Amazon Scholar and Affiliated Chief Scientist at NORCE. PhD, Electrical Engineering and Computer Sciences, University of California, Berkeley (2003) M.S., Electrical Engineering, University of California, Berkeley (2000) B.S. (valedictorian), Electrical Engineering, Pontificia Universidad Catolica de Chile (1997) His research spans the mathematical foundations of deep learning, focusing on non-convex optimization , learning dynamics , and overparametrization . Key contributions include Sparse Subspace Clustering , Kernel GPCA , and Low-Rank Matrix Factorization , with applications in autism diagnosis , robotic surgery , and cardiac imaging . Recent work explores continual learning , adversarial robustness , and trustworthy AI in biomedical contexts. His 15 most recent publications highlight advances in medical imaging , language models , and robust computer vision , spanning topics from chest X-ray analysis to motor imitation tasks in autism . Articles like Geometric Analysis of Nonlinear Manifold Clustering underscore his theoretical contributions, while works on KDA: Knowledge-Distilled Attacker and Conformal Information Pursuit address practical AI safety and interpretability. Scientific accolades include: 2022 ACM Fellow 2021 IEEE McCluskey Technical Achievement Award 2017 Jean D’Alembert Fellowship 2012 J.K. Aggarwal Prize 2009 Sloan Research Fellow 2005 NSF CAREER Award His lab mentors 11 current PhD students across Johns Hopkins and University of Pennsylvania , with alumni contributing to institutions like Meta , Amazon , and GE Research . Vidal’s interdisciplinary work bridges mathematics , engineering , and healthcare , supported by grants from the DoD , NSF , and ONR .

Alice Pawleyمشاهده پروفایل

دانشیار

• Engineering Education
• Diversity and Inclusion in STEM
• Social Justice in Engineering
• +۵ مورد دیگر

Alice Pawley serves as Associate Professor of Engineering Education at Purdue University's College of Engineering, with her office located in 1325 Armstrong Hall on the West Lafayette campus. Her work spans engineering education, diversity and inclusion, and social justice within engineering contexts, with particular focus on gender and race dynamics in the field. Dr. Pawley's research interests center on critical examinations of engineering education through feminist and critical race lenses. She investigates how engineering education structures marginalize students from underrepresented backgrounds, with specific attention to microaggressions, team dynamics, and institutional barriers. Her work explores engineering identity formation, sustainability in engineering education, and qualitative research methodologies that center minoritized voices. She advocates for transformative approaches that shift engineering education toward greater equity and inclusion. Her recent publications demonstrate consistent focus on identifying and addressing systemic inequities in engineering education. Research trends show increasing emphasis on antiracist frameworks, neurodiversity inclusion, and practical interventions for creating more supportive learning environments. Her work often employs qualitative methods to uncover nuanced experiences of minoritized students and faculty. Dr. Pawley leads the FREE (Feminist Research in Engineering Education) research group, mentoring graduate students including Canek Phillips, Kyle Jones, Corey Schimpf, Michele Yatchmeneff, Kacey Beddoes, Lindsey Nelson, and Marisol Mercado-Santiago. She co-founded the PEER Collaborative national workshop to support engineering education researchers through near-peer mentoring. Her commitment to student development is evident in her recommendation letter policy, which requires meaningful student-faculty interaction before writing letters of support. Her research team actively engages in projects examining mental health in engineering culture, distributed team models, and community-building for neurodivergent researchers. Dr. Pawley's work bridges theoretical frameworks with practical classroom applications, focusing on creating tangible changes in engineering education environments.

• Conversational Search Systems
• Information Retrieval
• Recommender Systems
• +۷ مورد دیگر

Mohammad Aliannejadi is an Assistant Professor at the Information Retrieval Lab (IRLab) within the Informatics Institute at the University of Amsterdam. His research focuses on conversational search systems, information retrieval, and recommender systems, with an increasing emphasis on Large Language Model applications in IR. He obtained his PhD from the Faculty of Informatics at Università della Svizzera italiana (USI) in Lugano, Switzerland, and completed his MSc at Tehran Polytechnic in Iran. His research interests span conversational search systems, clarification question generation, mobile search, cross-market recommendation, and point-of-interest recommendation. Dr. Aliannejadi has made significant contributions to understanding how users formulate information needs in conversational settings and how systems can effectively respond through clarification mechanisms. His work bridges theoretical IR concepts with practical implementations, particularly in mobile contexts where information needs often evolve rapidly. His recent publications show a clear trend toward leveraging Large Language Models for conversational search evaluation, query understanding, and performance prediction. The 15 most recent articles demonstrate his leadership in adapting traditional IR techniques to the LLM era, with particular focus on efficient and effective conversational search systems that can handle complex user information needs through natural dialogue. Dr. Aliannejadi is deeply embedded in the IR community through extensive service activities. He has served as Program Co-Chair for ICTIR 2023, Tutorial Co-chair for ECIR 2024, and Lab Co-Chair for CLEF 2023. He regularly organizes workshops such as XMRec, SCAI, and MICROS, and has been a SIGIR Student Liaison. His service extends to program committees for major conferences including SIGIR, ACL, WSDM, and ECIR, and as a reviewer for journals like TOIS and TKDE. His leadership extends to organizing significant academic events including the 15th European Summer School in Information Retrieval (ESSIR 2024) and serving on the Program Committee for the Bachelor Program in AI at UvA. His lab, IRLab (formerly ILPS), focuses on developing innovative approaches to information access through conversational interfaces and advanced retrieval techniques.

Peter Smithمشاهده پروفایل

استاد

• Occupational Health and Safety
• Epidemiology of Work-Related Injuries
• Labour Market Inequalities
• +۲ مورد دیگر

Peter Smith is President & Senior Scientist at the Institute for Work & Health (Toronto) and Professor at the Dalla Lana School of Public Health , University of Toronto. His research focuses on occupational health disparities, particularly gender/sex differences, labor market inequalities, and vulnerable worker subgroups. Education : Master's in Public Health (University of New South Wales), PhD (Institute for Medical Science, University of Toronto) Research Interests His work examines intersections between work environments and chronic disease risks, trends in occupational health systems, and equity in return-to-work processes. Projects include AI applications in injury prevention and psychosocial hazard analysis. Scientific Awards CIHR New Investigator Award (2008-2013) Australian Research Council Discovery Early Career Researcher Award (2012-2014) CIHR Research Chair in Gender, Work and Health (2014-2018) Grants & Projects Current funded initiatives include AI in occupational safety (WSIB), migraine measurement studies (CTV News), and Alberta workplace vulnerability assessments. Past projects explored newcomer labor integration and pandemic-era physical activity patterns.