جست‌وجوی استاد و پژوهشگر

Mary Harrisonمشاهده پروفایل

دانشیار مهمان

• Marketing
• Consumer Behavior
• Services Marketing
• +۴ مورد دیگر

Mary Harrison is a Visiting Associate Professor of Marketing in the Department of Entrepreneurship, Management and Marketing at Samford University’s Brock School of Business. She brings more than a decade of prior experience from Birmingham-Southern College (BSC), where she served from 2011 to 2024 as faculty member, department chair, and program leader. Education Ph.D. in Marketing (concentration in Social Psychology) – University of Alabama MBA – University of Alabama B.S. in Business Administration – Mississippi College (including a semester of study in London) Research Interests Harrison’s scholarship centers on consumer behavior and services marketing, with particular emphasis on customer–firm relationships, service employee behavior, and the emotional dynamics of service encounters. She investigates how consumers react to service failures, penalties, and special requests, and explores factors that create “lock-in” and long-term loyalty. More recently, her work examines the intersection of artificial intelligence and personal branding in higher-education contexts. Across her publications, three consistent themes emerge: (1) understanding and managing customer emotions during and after service experiences; (2) frontline employee decision-making when faced with ethically or operationally “gray” customer requests; and (3) mechanisms—psychological, relational, and technological—that deepen or dissolve customer–brand relationships over time. Scientific Awards & Honors Omicron Delta Kappa Excellence in Teaching Award – Birmingham-Southern College Bob Whetstone Faculty Development Award – Birmingham-Southern College ACS Career Advancement Pathways Program Fellow – Associated Colleges of the South ACS Summer Teaching & Learning Experience Fellow – Associated Colleges of the South Service & Professional Engagement Harrison currently serves on the Editorial Review Board of the Journal of Marketing Theory and Practice and previously acted as Co-Associate Editor for Services Marketing at the Journal of Global Scholars of Marketing Science . She has delivered more than 25 conference presentations or panel discussions at leading marketing academic conferences, and advises Samford’s student chapter of the American Marketing Association.

John Pillمشاهده پروفایل

مدرس

• Language Testing for Specific Purposes
• Language Assessment Literacy
• Speaking Assessment
• +۵ مورد دیگر

Dr John Pill is a Lecturer in Language Testing at Lancaster University’s School of Social Sciences, holding the Trinity College London Lectureship in Language Testing . His research focuses on testing language for specific purposes, speaking assessment, language assessment literacy, and test impact across academic and healthcare domains. He actively collaborates with Trinity College London on research and development projects. Current Teaching (2025-26): MA in Language Testing by distance (LING504, LING506) PhD Supervision: All aspects of language testing, particularly test constructs and stakeholder perspectives Research Groups: Language Testing Research Group (LTRG) Research Interests span technical and social dimensions of language testing. Technically, he examines test development for domain-specific language use (e.g., medical contexts) and construct validity. Socially, he investigates test impact through stakeholder views, including professional registration bodies and multilingual faculty at the American University of Beirut. His work bridges discourse community analysis with practical testing frameworks. Recent publications (2025) address societal implications of language testing, comparative judgment methodologies in EFL writing assessment, and fairness in testing legacy. Earlier work (2016-2024) includes healthcare communication standards, academic-to-workplace writing transitions, and Trinity College London Graded Examinations alignment with China’s English standards.

Alvaro Fernandez Quilezمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Responsible AI
• AI Ethics
• +۱۳ مورد دیگر

Alvaro Fernandez Quilez is an Associate Professor in Artificial Intelligence at the Department of Electrical Engineering and Computer Science, Faculty of Science and Technology, University of Stavanger. He leads the Stavanger AI Laboratory (SAIL), fostering interdisciplinary AI research with a focus on healthcare and education applications. Research Interests: His work centers on responsible AI, emphasizing ethics, fairness, transparency, and uncertainty in AI systems. He applies deep learning and machine learning techniques to medical imaging, particularly in prostate cancer and neurodegenerative diseases like Alzheimer’s and Parkinson’s. His research integrates algorithmic innovation with clinical relevance, addressing challenges in data scarcity, bias, and model interpretability. The recent publications highlight a strong trend in developing and evaluating AI models for diagnostic support in radiology and neurology. Key themes include uncertainty quantification, self-supervised learning, synthetic data generation via GANs, and fairness analysis across gender and centers. The work spans from foundational AI methods to their clinical translation in multi-center studies. Teaching and Academic Leadership: He coordinates the course DAT105 - AI for everyone and has contributed as a guest lecturer in bioinformatics, technological foundations, and PhD ethics, particularly on AI and ethics. He is also enrolled in a PhD supervisory qualification program, underscoring his growing role in graduate education. Advising and Grants: While specific students and grants are not listed in the text, his leadership of SAIL and active publication record suggest involvement in research supervision and project funding. His collaborations span multiple institutions and disciplines, indicating strong team-based research efforts. Laboratories and Teams: He leads the Stavanger AI Laboratory (SAIL), which serves as the central hub for AI research at the University of Stavanger, promoting collaboration across departments and with external partners in healthcare and technology.

Paul Ralphمشاهده پروفایل

استاد

• Software Engineering
• Empirical Software Engineering
• Human-Computer Interaction
• +۱۷ مورد دیگر

Dr. Paul Ralph is a Professor in the Faculty of Computer Science at Dalhousie University , where he leads the Dalhousie Software Engineering Lab (DalSEL) . His work bridges software engineering, human-computer interaction, and project management, with a focus on empirical research and social sustainability in software development. Education: PhD in Computer Science, University of British Columbia BSc in Computer Science, Memorial University BComm in Business, Memorial University Dr. Ralph's research centers on the sociotechnical aspects of software engineering , particularly how team dynamics, ethics, and human factors influence software success. He rejects pseudoscientific models like Waterfall and SDLC, and avoids AI/ML/data science, instead emphasizing rigorous qualitative and quantitative human-participant studies. His lab is known for its work on socially sustainable software engineering and evidence standards in computing research. His recent publications reflect a strong trend toward methodological rigor, ethical computing, and human-centered practices . Themes include empirical standards, agile methods, requirements engineering, and the social impact of technology. He publishes in top venues like IEEE TSE and ICSE , and has authored over 80 scholarly works. Scientific Awards and Recognition: Award-winning scientist (multiple unspecified awards) Editor-in-Chief, SIGSOFT Empirical Standards for Software Engineering Research Dr. Ralph is actively involved in mentoring and funding graduate students , particularly through external scholarships like NSERC, Killam, and Banting. He prioritizes applicants from underrepresented groups and emphasizes original, non-AI-generated work. His lab offers strong industry connections, professional development, and support for tenure-track aspirations among postdocs. Labs and Research Groups: Dalhousie Software Engineering Lab (DalSEL) : Focuses on empirical, human-centered software engineering research, with active projects in social sustainability and evidence standards.

• Economics
• Telecommunications
• Antitrust
• +۳ مورد دیگر

Hal J. Singer is a Managing Director at Econ One and an Adjunct Professor at the University of Utah. His career spans economics consulting and academic research, with a focus on telecommunications, antitrust, regulatory policy, and market competition. Key Affiliations: Econ One, University of Utah, Criterion Economics, LLC, Technology Policy Institute. Research Interests: Broadband regulation, wireless markets, antitrust analysis, merger impacts, and consumer welfare in high-tech industries. Recent Work Trends: Analyzes competition in telecom markets, regulatory frameworks for net neutrality, and antitrust implications in digital platforms. His publications often address policy decisions in the U.S. and international contexts. Notable Contributions: Co-author of influential studies on the Sprint/T-Mobile merger, Google/DoubleClick antitrust case, and economic impacts of broadband regulation.

Tandra R. Chakrabortyمشاهده پروفایل

استاد

• Endocrinology
• Neurobiology
• Estrogen Receptors
• +۷ مورد دیگر

Tandra R. Chakraborty is a tenured Professor in the Department of Biology at Adelphi University’s College of Arts and Sciences, where she has served since 2006. She earned her Ph.D. from Calcutta University in 2000 and completed a postdoctoral fellowship at Mount Sinai School of Medicine. She has held leadership roles including Chair of the Biology Department (2020–2024), Director of the Biology Graduate Program (2014–2020), and Interim Associate Dean of Student Success and Strategic Initiatives. Ph.D., Calcutta University, India (2000) Postdoctoral Fellow, Mount Sinai School of Medicine (2006) Her research lies at the intersection of Endocrinology and Neurobiology, focusing on the role of estrogen in neuroprotection, obesity, metabolic syndrome, and reproductive health. She investigates hormonal changes in aging and high-fat diet models, neuroprotective effects of estrogen in Alzheimer’s and hypoglycemic injury, and the impact of endocrine-disrupting chemicals on development and pregnancy. Her work combines molecular, cellular, and animal model approaches to understand the interplay between metabolism and neural function. Her recent publications reflect a strong trend in biomedical research involving hormonal regulation, neuroprotection, and metabolic disease. Key themes include estrogen’s protective role in neurodegenerative models, the effects of high-fat diets on endocrine and reproductive systems, and environmental impacts on human health. Her work spans both basic science and public health, with applications in obesity, diabetes, and neurodegenerative disorders. She has received multiple scientific recognitions, including: Frederick Bettelheim Research Award Adelphi Faculty Development Grant (2007, 2008) CASHE Award for innovative academic support (2023) Multiple ASBMB Travel Awards for student mentors Nominations for Teaching and Service Excellence Awards (2019) She has advised numerous graduate and undergraduate theses, mentoring students in research on obesity, diabetes, neuroprotection, and environmental health. Many of her students have co-authored publications, presented at national conferences, and won awards. She has secured internal funding and led curriculum development, including the BS in Neuroscience program. She is also an active journal reviewer and science fair judge, contributing significantly to academic service and community outreach. Dr. Chakraborty leads a vibrant research lab focused on endocrine and neurobiological mechanisms in disease. Her team includes undergraduate and graduate students trained in animal care, cell culture, immunocytochemistry, and molecular techniques. She is involved in the Collegiate Science and Technology Entry Program (CSTEP) and promotes diversity in STEM through mentoring and outreach.

Navid Rekab-sazمشاهده پروفایل

استادیار

• Natural Language Processing
• Information Retrieval
• Fairness and Bias in AI
• +۷ مورد دیگر

Navid Rekab-saz is an Assistant Professor at the Institute of Computational Perception, Johannes Kepler University Linz (JKU), Austria. He is actively involved in research and teaching, offering courses such as Natural Language Processing and Natural Language Processing with Deep Learning . He maintains regular office hours and is accessible via email and a dedicated booking system for meetings. His research focuses on natural language processing , information retrieval , fairness and bias in AI , and recommender systems , with applications in humanitarian action and ethical AI. He employs deep learning and machine learning techniques to address challenges in bias mitigation, explainability, and domain adaptation. His work often bridges technical innovation with societal impact, especially in developing inclusive and fair AI systems. The recent publications of Navid Rekab-saz reflect a strong trend in debiasing strategies , parameter-efficient learning , and evaluation of societal biases in search and recommendation systems. His research spans from foundational work on word embeddings and retrieval models to applied studies in humanitarian NLP and gender bias in user queries. He frequently collaborates with a broad network of researchers and contributes to the development of datasets and benchmarks. Scientific Awards: Best Student Paper Award at ISMIR 2022 for 'Traces of Globalization in Online Music Consumption Patterns and Results of Recommendation Algorithms' Advising and Grants: Navid Rekab-saz has advised and collaborated with numerous students and researchers, many of whom are co-authors on his publications. While specific grant details are not listed in the provided text, his extensive publication record in top-tier venues suggests active involvement in funded research projects, likely supported by national or European funding bodies. He is also engaged in interdisciplinary research, particularly at the intersection of technical AI and legal or social implications. Labs and Teams: He is a core member of the Institute of Computational Perception at JKU, where he contributes to research projects in computational linguistics and AI. He collaborates closely with the team led by Prof. Markus Schedl and participates in initiatives related to music information retrieval, fairness in AI, and humanitarian applications of NLP.

Li Chenمشاهده پروفایل

استاد

• Conversational AI
• Explainable AI
• Recommender Systems
• +۷ مورد دیگر

Professor Li Chen is a full Professor and Associate Head (Research) in the Department of Computer Science at Hong Kong Baptist University (HKBU), with an affiliate appointment at the Academy of Wellness and Human Development. She leads the Positive Intelligence Lab , focusing on intelligent technologies for human well-being. Her research spans conversational AI, explainable AI, recommender systems, and human-computer interaction. Education: PhD in Computer Science, Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland (Nominee for Best PhD Thesis Award) Master in Computer Software and Theory, Peking University, China Bachelor in Computer Science, Peking University, China Her research interests revolve around personalized conversational and explainable AI, with applications in entertainment, education, e-commerce, and mental well-being. She has published over 150 papers in top venues including ACM TOIS, IJHCS, CHI, SIGIR, AAAI, RecSys, and UMAP . Her work has been recognized with awards such as the RecSys Best Student Paper Award (2024), CHI Honourable Mention (2022), and multiple best paper awards at UMAP and UMUAI. The most recent publications reflect a strong trend toward fair, explainable, and user-centric recommender systems , with increasing integration of large language models , mental health applications , and conversational agents . Her research emphasizes user feedback, negative sampling techniques, and evaluation frameworks grounded in real user behavior. Scientific Awards & Recognition: President’s Award for Outstanding Performance in Teaching (Individual), HKBU (2024/25) President’s Award for Outstanding Performance in Research Supervision (2022/23) World’s Top 2% Most-Cited Scientists, Stanford University (2021–2024) ACM Senior Member (2015) RecSys’24 Best Student Paper Award CHI’22 Honourable Mention Award UMAP’20 Best Student Paper Award UMUAI 2018 Best Paper Award THE Awards Asia 2021 Excellence and Innovation in the Arts (Co-I) Professor Chen is actively involved in mentoring PhD and Master’s students such as Wanling Cai and Yuhan Zhao, who have co-authored award-winning papers. She has secured research funding through grants like the HKBU IRCMS Project. Her editorial leadership includes serving as Co-Editor-in-Chief of ACM Transactions on Recommender Systems (TORS) , Associate Editor for ACM TiiS , and Editorial Board Member for UMUAI . She has chaired major conferences including ACM RecSys’23 (General Co-Chair), RecSys’20 (Program Co-Chair), and UMAP’18 (Program Co-Chair). She leads the Positive Intelligence Lab , which conducts interdisciplinary research on AI for well-being. The lab has developed datasets like the Intent Annotation of Recommendation Dialogue (IARD) and focuses on user-centric AI design, mental health chatbots, and personalized recommendation interfaces.

• Computer Vision
• Machine Learning
• Human-Computer Interaction
• +۳ مورد دیگر

Olga Russakovsky is an Associate Professor in the Computer Science Department at Princeton University. She serves as Associate Director of the Princeton AI Lab and Chair of the Board of Directors at AI4ALL, a nonprofit dedicated to diversity in AI leadership. Her research focuses on computer vision, machine learning, human-computer interaction, and fairness in AI. She specializes in developing AI systems that reason about the visual world, emphasizing fairness, accountability, and transparency. Her work integrates computer vision with ethical AI frameworks, and she is affiliated with Princeton’s Center for Statistics and Machine Learning and Center for Information Technology Policy. Her publications address biases in datasets, explainable AI, and generative models. Her recent research trends include: Bias detection in datasets (e.g., CelebA, ImageNet) Interactive and explainable AI systems Generative models like diffusion and vision-language integration Deepfake detection and AI forensics Conceptual learning and few-shot training Scientific awards: NSF CAREER Award for fairer computer vision systems Co-founder of AI4ALL and Stanford AI4ALL outreach programs She advises students through AI4ALL initiatives and leads the Visual AI Lab, which focuses on robust, inclusive AI development. Her work bridges technical innovation with societal impact, particularly in diversity-focused education.

Eva Eberhartingerمشاهده پروفایل

استاد

• Taxation
• Business Taxation
• International Taxation
• +۵ مورد دیگر

Univ.Prof. Dr. Eva Eberhartinger is a full professor of Business Taxation and Chair of the Institute of Accounting and Auditing at WU Vienna University of Economics and Business . She previously served as Vice-Rector of Financial Affairs (2006-2011) and was a full professor at the University of Münster. She holds visiting positions at institutions including University of Exeter, HEC Paris, and McGill University.

• Sport Finance
• Football Economics
• Competitive Balance in Sports
• +۵ مورد دیگر

Daniel Plumley is a Principal Lecturer in Sport Finance at Sheffield Hallam University's Sheffield Business School, where he has been employed since November 2012. His academic career focuses on the economic and financial aspects of professional sports, with particular emphasis on football (soccer) and rugby across multiple international contexts including England, Europe, Asia, and Japan. Dr. Plumley's research spans several interconnected domains in sports economics. His primary focus is on sport finance, where he has conducted comprehensive analyses of financial health and sustainability in professional sports clubs. He has developed sophisticated frameworks for assessing competitive balance in sports leagues and examining how financial regulations like Financial Fair Play impact competitive equity. His work on governance includes developing 'The Good Governance Index for the Asian Professional Football Industry,' creating a comprehensive measurement tool for football clubs. He has also investigated emerging phenomena like sportswashing, particularly examining Saudi Arabia's involvement in elite sports through initiatives like LIV Golf. His methodological approach combines quantitative financial analysis with qualitative policy assessment, providing comprehensive insights into the complex financial ecosystems of professional sports. Dr. Plumley's research demonstrates significant implications for sports policymakers, club executives, and regulatory bodies seeking to understand and improve the financial sustainability and competitive integrity of professional sports leagues worldwide. Dr. Plumley maintains an extensive collaborative network, frequently working with researchers including Rob Wilson, Sarthak Mondal, and Leon Davis. His work appears in leading sports management journals such as Sport, Business and Management, Managing Sport and Leisure, Soccer and Society, and the Journal of Applied Accounting Research. He is also the co-author of the book 'The Economics and Finance of Professional Team Sports' (2022), establishing himself as a thought leader in sports economics education.

Haipeng Luoمشاهده پروفایل

دانشیار

• Machine Learning
• Online Learning
• Reinforcement Learning
• +۳ مورد دیگر

Haipeng Luo is an Associate Professor at the Thomas Lord Department of Computer Science, University of Southern California, holding the IBM Early Career Chair. He previously worked as a Postdoctoral Researcher at Microsoft Research, NYC, and has held visiting roles at Google and Amazon. His research focuses on developing practical machine learning algorithms with strong theoretical guarantees, particularly in online learning, bandit problems, reinforcement learning, and game theory. PhD in Computer Science, Princeton University (2011–2016) BSc in Computer Science, Peking University (2007–2011) His work spans adversarial and stochastic environments, addressing challenges in reinforcement learning, game dynamics, calibration, and omniprediction. Recent publications highlight advancements in regret minimization, game equilibrium computation, and robust optimization frameworks. Key contributions include algorithms for zero-sum games, bandit problems with feedback graphs, and theoretical analyses of convergence properties in multi-agent systems. Scientific accolades include Best Paper Awards at COLT 2021, COLT 2018, NeurIPS 2015, and ICML 2015. He has received prestigious grants such as the NSF CAREER Award (2020), Google Faculty Research Award (2020), and NSF CRII Award (2018). His students have secured academic and industry positions, and he actively teaches graduate courses in machine learning and online optimization.

Daniel Lindvallمشاهده پروفایل

پژوهشگر

• climate change
• democracy
• energy governance
• +۷ مورد دیگر

Daniel Lindvall is a Researcher at Uppsala University's Department of Geosciences, affiliated with the Natural Resources and Sustainable Development unit and Climate Leadership initiative. He holds a doctorate in sociology and specializes in democracy-climate policy intersections, with additional expertise in peacebuilding and reconciliation processes in post-conflict regions like Bosnia and Herzegovina. His research focuses on: Democratic governance challenges in climate crisis contexts Public acceptance of renewable energy policies Climate justice and intergenerational equity Political barriers to sustainability transitions Local governance of climate initiatives Lindvall leads multiple research programs including Mistra-Formas funded Fairtrans, Formas' Wicked Problem Governance, and the Swedish EPA's climate-biodiversity policy initiative. His publications consistently examine democratic institutions' capacity to address environmental crises through policy design, public engagement, and institutional innovation.

Andrew Clarkمشاهده پروفایل

استاد پژوهشی

• Labour economics
• Subjective well-being
• Health economics
• +۲ مورد دیگر

Andrew Clark is a CNRS Full Research Professor of Exceptional Class (DRCE1) based at the Paris School of Economics (PSE), France, where he has been a permanent member of the research staff since 2001. Previously he held positions at DELTA (now PSE), Université d’Orléans, OECD, CEPREMAP, the University of Essex, and Dartmouth College. Research Interests: Labour Economics: Wage determination, job satisfaction, unemployment experience. Subjective Well-Being: Measurement of utility via life and job satisfaction scores, adaptation to life events, relative income comparisons. Health Economics: Effects of income shocks and life events on physical and mental health. His empirical work relies extensively on large-scale panel datasets and interdisciplinary collaborations with psychologists. Publication Trends: Between 2013 and 2018 Clark produced a steady stream of high-impact articles and two books. Recurring themes include adaptation to income and life events, inequality attitudes, and the long-run determinants of individual well-being. The work spans theoretical modelling, experimental evidence, and policy-oriented syntheses. Grants & Awards: No specific awards or external grants are listed in the provided text. Advising & Teams: No doctoral students or research group details are supplied in the text.

• Networking and Communications
• Blockchain Technology
• Smart Grids and Energy Systems
• +۵ مورد دیگر

Roberto Rojas-Cessa is a Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT), affiliated with the School of Applied Engineering and Technology. His research focuses on networking, blockchain applications in smart cities, energy systems, wireless communications, and high-performance switching. He has led multiple National Science Foundation (NSF)-funded projects, including initiatives on controlled delivery power grids and next-generation network quality of service. Notably, his work explores blockchain for energy metering, sustainable environmental measures, and smart grid optimization. He is also a Senior Member of the National Academy of Inventors (2024). His research interests span network protocols, distributed systems, and IoT applications. Recent projects include AMI-Chain (a blockchain-based power metering system) and studies on indirect free-space optical communications for vehicular networks. He has contributed to advancements in medium access control for crowded networks and energy packet switches for digital microgrids. Rojas-Cessa’s work integrates machine learning for network management and flood impact analysis. He has developed tools for time-lapse analysis of urban data and agent-based models to evaluate electric vehicle adoption. His publications emphasize scalability, security, and efficiency in both traditional and emerging technologies. Grants: Collaborative Research on Power Grids (NSF, 2016–2018), NeTS-NR: Quality of Service Networks (NSF, 2004–2008) Awards: Senior Member of the National Academy of Inventors (2024) His lab activities include experimental evaluations of digital microgrids and blockchain implementations for carbon footprint tracking. He actively collaborates on projects addressing emergency communications and resilient energy distribution systems.