جست‌وجوی استاد و پژوهشگر

Paul D. Blieseمشاهده پروفایل

استاد

• Organizational Behavior
• Stress and Well-being
• Leadership Development
• +۳ مورد دیگر

Paul D. Bliese is the Jeff B. Bates Professor of Management and Department Chair at the University of South Carolina’s Darla Moore School of Business. He holds a Ph.D. from Texas Tech University and a B.A. from Texas Lutheran University. Before academia, he served 22 years in the U.S. Army as a research psychologist, retiring as a Colonel in 2014. His military roles included directing the Center for Military Psychiatry and Neuroscience and overseeing the Army’s Mental Health Advisory Team program in Iraq and Afghanistan. Bliese’s research focuses on stress, leadership, well-being, and performance, with a strong emphasis on multilevel statistical methodologies. He developed the multilevel package for R, advancing organizational multilevel theory. His work bridges military and civilian contexts, applying analytics to complex organizational data. Current projects include longitudinal studies on leadership transitions, team climate in tank crews, and university band dynamics. He teaches courses like Strategic HR Metrics and Leading Teams, emphasizing data-driven decision-making. His articles address topics ranging from PTSD prevention to organizational resilience. Collaborations with Army and civilian institutions ensure practical applications of his findings. Bliese advocates for methodological rigor and interdisciplinary research, serving as Editor-in-Chief for Organizational Research Methods.

• Global Health Security
• Public Health Emergency Response
• Data Science for Policy
• +۳ مورد دیگر

Ellie Graeden, Ph.D., is a Research Professor at Georgetown University's Center for Global Health Science and Security, leading health intelligence research and data architecture for global health response systems. She previously founded Talus Analytics, specializing in data-driven policy solutions at the intersection of science and strategy. Her work focuses on global health security, including pandemic preparedness, data standardization for wildlife diseases, and financing mechanisms for health resilience. Dr. Graeden holds a B.S. in Microbiology from Oregon State University and a Ph.D. in Biology from MIT. Her research emphasizes quantitative approaches to global health challenges, such as designing data platforms for vaccination coverage and emergency response during influenza and COVID-19. She has collaborated with the CDC, G20, and United Nations to develop tools for health security policy analysis, including the Global Health Security Index and investment tracking systems. Her team’s work is featured in resources like ghsidea.org and the Outbreak Activity Library. Dr. Graeden’s expertise spans interdisciplinary data systems, policy implementation frameworks, and emergency decision-making paradigms. She has pioneered methodologies for linking health data to actionable policies, particularly in high-risk contexts like pandemic response and biological event preparedness.

Joana Gaiaمشاهده پروفایل

استادیار بالینی

• Decision support systems
• Health information systems
• Design science research
• +۱ مورد دیگر

Joana Gaia is a Clinical Assistant Professor in the Management Science and Systems department at the School of Management, University at Buffalo . Her contact address is 325Q Jacobs Management Center, Buffalo, NY 14260-4000, and she can be reached at 716-645-3213. Education: PhD and MS from University at Buffalo School of Management; BS from Universidade Lusiada, Lisbon; Advanced Certificate in Information Assurance from University at Buffalo Teaching Interests: Business intelligence, Management analytics, Business statistics, and Quantitative methods. Research Focus: Decision support systems, health information systems, design science research, and emergency management. Her work explores privacy concerns in health data sharing and digital system design. Scientific Awards: Best Prototype Award at WITS 2010 Selected Publication: 2017 study on patient-centered privacy impacts in health information sharing, published in the Journal of Medical Internet Research. Professional Affiliations: PhD Project, AIS, and INFORMS. With industry experience in financial services IT migration projects, she bridges academic research with practical applications in information systems.

Kevin G. Owensمشاهده پروفایل

دانشیار

• Analytical Chemistry
• Mass Spectrometry
• MALDI TOFMS Instrumentation
• +۴ مورد دیگر

Dr. Kevin G. Owens is an Associate Professor in the Department of Chemistry at Drexel University, where he also chairs the Faculty Senate. He holds a PhD from Indiana University (1989) and a BS from the University of New Hampshire (1982). His research focuses on analytical chemistry, particularly mass spectrometry (MALDI TOFMS), laser spectroscopy, and chemometrics. Key areas include improving MALDI techniques for biological and synthetic polymer analysis, developing imaging mass spectrometry methods, and strain-level micro-organism identification via mass spectral correlation analysis. He pioneered electrospray deposition (ESD) for quantitative MALDI analysis and has contributed to detector innovations like the bipolar time-of-flight detector. His work spans fundamental MALDI process studies, instrumentation design, and applications in microbiology and polymer science. Education: PhD, Analytical Chemistry, Indiana University, 1989 BS, Chemistry, University of New Hampshire, 1982 Research Interests: Dr. Owens' lab investigates MALDI fundamentals, instrument development (e.g., TOFMS detectors), and chemometric methods like 2D correlation analysis. Recent efforts include optimizing MALDI imaging for tissue analysis, improving microbe strain identification, and advancing electrospray-based sample preparation techniques. His publications address matrix solubility, ion formation dynamics, and applications in brewing yeast analysis. Publications: Over 80 peer-reviewed articles emphasize methodological advancements in MALDI, including pioneering work on ESD and strain-level organism identification. Recent trends focus on MALDI imaging improvements and microbiological applications. Awards/Honors: Not explicitly listed in provided texts. Advising/Grants: As a graduate program faculty member, he mentors students in analytical chemistry and mass spectrometry. His research is supported by grants (details not specified). Labs/Teams: Leads the Owens Research Group, collaborating on MALDI instrumentation, microbiology, and polymer analysis projects.

Charles Kelliherمشاهده پروفایل

دانشیار

• Tax Compliance
• Tax Planning
• Social Norms
• +۲ مورد دیگر

Charles Kelliher is an Associate Professor at the Kenneth G. Dixon School of Accounting within the College of Business at the University of Central Florida. His research primarily explores tax compliance, tax planning strategies, and the impact of social norms on taxpayer behavior. He employs empirical and behavioral approaches to investigate fiscal decision-making. Kelliher's work spans interdisciplinary domains, integrating accounting with behavioral economics and public policy. His recent articles focus on modern tax administration challenges, including pre-populated tax returns and behavioral interventions to enhance compliance. Long-term research trajectories include financial modeling applications, with historical work on spreadsheet optimization for capital budgeting and investment simulations. Methodological contributions include psychometric scale development for tax compliance studies.

Charles Chi Cuiمشاهده پروفایل

استاد

• International Marketing
• Behavioral Science
• Diversity and Inclusion
• +۳ مورد دیگر

Prof. Charles Chi Cui is a Professor of Marketing at the School of Management and Marketing, Westminster Business School (WBS), University of Westminster. He leads the Research Group for Inclusive and Sustainable Business and serves on editorial boards of academic journals. Prior roles include Director of Research and Knowledge Exchange at Northumbria University and Associate Professor at Alliance Manchester Business School. He holds a PhD in International Business Management and has over 20 years of academic experience, including supervising 11 PhD and 2 DBA candidates. His research focuses on international marketing, behavioral science, diversity/inclusion, sustainability, and branding, using mixed methods like SEM, fsQCA, and qualitative analyses. Education: PhD in International Business Management (specializing in joint venture management), MA in International Business Management, Postgraduate Diploma in Development Studies, and Certificate in Mechanical Manufacture. Pre-academic career included 12 years in manufacturing, trade, and a Sino-British joint venture in China. Research interests span brand addiction, consumer social inclusion, cross-cultural values, and digital marketing. He advocates for rigorous, multidisciplinary research with practical impact. Teaching expertise includes international marketing, branding, and research methods at UG, PG, and MBA levels. He has designed doctoral training courses such as Advanced Survey Design and Critical Thinking for Scientific Research. Labs/Teams: Leads the Research Group for Inclusive and Sustainable Business, fostering collaborations on diversity-driven marketing and sustainable business practices. His work emphasizes multicultural marketplace well-being and institutionalizing inclusive strategies.

• Machine Learning
• Pain Assessment
• Neurophysiological Sensors
• +۵ مورد دیگر

Raul Fernandez Rojas is an Associate Professor in the Department of AI and Robotics at the University of Canberra. His research focuses on multimodal neurophysiological sensing, machine learning applications in healthcare, and pain assessment using technologies like fNIRS, EEG, and facial expression analysis. He leads projects integrating brain-body interactions in neurological disorders such as Parkinson's disease and dementia, and develops intelligent systems for driver distraction detection. Education: PhD (details unspecified) Research interests include cognitive workload analysis, sensor fusion for biomedical applications, and AI-driven diagnostics for mental and neurological conditions. His work spans clinical pain assessment, human-swarm interaction, and real-time monitoring systems. He has contributed to over 55 peer-reviewed publications and actively supervises PhD candidates in machine learning for neurophysiological applications. Current projects include a dementia detection initiative using machine learning and exercise interventions, funded from 2024–2026. He collaborates internationally on topics like head motion patterns for depression biomarkers and fNIRS-based pain assessment for non-verbal patients. Advising focuses on PhD projects involving neurophysiological sensors (EEG, fNIRS, etc.) and facial expression analysis for pain recognition. Grants include funding for multimodal signal fusion research and wearable sensor systems.

Aashutosh Mistryمشاهده پروفایل

استادیار

• Energy Technologies
• Electrochemistry
• Battery Science
• +۳ مورد دیگر

Aashutosh Mistry is an Assistant Professor in the Department of Mechanical Engineering at the Colorado School of Mines. His research group operates from CoorsTek 207, focusing on experimental and theoretical approaches to advance energy technologies. Contact details include the email aashutosh.mistry@mines.edu and phone number 832-730-9071. Mistry's research integrates physics-based modeling, controlled experiments, and machine learning to bridge gaps between novel materials and scalable energy devices. Key interests encompass battery science, ion transport dynamics, multiscale electrolyte behavior, and sustainable energy transitions. His work targets applications like electrified transportation, solid-state batteries, and electrochemical systems optimization. Recent publications emphasize data-driven electrochemistry, electrolyte transport mechanisms, and machine learning applications. Trends include operando characterization of battery materials, predictive modeling of ion motion, and sustainability-focused energy research. Articles frequently utilize advanced techniques like electrophoretic NMR and computational simulations to resolve transport complexities. Mistry leads an active research group developing tools for microstructure analysis and transport phenomena. The team synergizes multiscale experimentation with theoretical frameworks to address energy technology challenges.

Atanas Mihovمشاهده پروفایل

دانشیار

• International Finance
• Banking
• Operational Risk
• +۲ مورد دیگر

Atanas Mihov serves as Associate Professor of Finance and Capitol Federal Fellow at the University of Kansas School of Business, where he teaches International Finance and Commercial Credit Analysis at the undergraduate level. Since joining KU in 2020, he has maintained visiting positions with the Federal Reserve Banks of Dallas and Richmond, building on his prior role as Senior Financial Economist leading operational risk modeling for the Federal Reserve's stress-testing program. Education: Ph.D. in Finance, University of Florida Warrington College of Business (2014) B.S. in Business Administration – Finance, Ramapo College of New Jersey Research Focus: Dr. Mihov's scholarship centers on international finance, banking systems, operational risk dynamics, supply chain financial interactions, and corporate innovation mechanisms . His work bridges theoretical finance with regulatory applications, particularly examining how operational risk manifests across banking institutions and interacts with macroeconomic conditions. Current investigations explore AI's role in loss prediction, climate risk transmission, and payment timeliness effects on market returns. Publication Trends: Recent work (2023-2025) demonstrates concentrated exploration of operational risk in banking through 15 high-impact studies. Key themes include B2B payment analytics' relationship to stock returns, AI-driven operational loss modeling, climate risk quantification, workforce policy impacts on risk, and corporate espionage effects on innovation. These studies leverage unique datasets from banking institutions and regulatory filings, frequently appearing in top-tier journals like the Journal of Financial Economics . Scientific Recognition: Capitol Federal Fellow designation at University of Kansas Professional Engagement: Dr. Mihov serves as Associate Editor for Emerging Markets Review , reflecting his scholarly influence. While specific grant details aren't documented in source materials, his research trajectory indicates sustained support through Federal Reserve collaborations and university resources. His prior leadership of quantitative teams at the Richmond Fed demonstrates capacity for managing complex research initiatives. Research Infrastructure: Current work leverages KU's business school resources alongside ongoing Federal Reserve partnerships. His prior operational risk modeling team at the Richmond Fed established foundational methodologies now informing banking regulation, while KU collaborations continue advancing supply chain finance and innovation research through the Finance area's academic ecosystem.

Cory Hirschمشاهده پروفایل

دانشیار

• Plant Stress Resistance
• Abiotic Stress Biology
• Biotic Stress Responses
• +۳ مورد دیگر

Cory Hirsch is an Associate Professor & Interim Department Head in the Department of Plant Pathology at the University of Minnesota , located in the College of Food, Agriculture and Natural Resource Sciences (CFANS) . His lab focuses on Plant Stress Resistance Biology , leveraging genomic, transcriptomic, and phenomic approaches to understand plant responses to abiotic (e.g., extreme temperatures, salinity) and biotic (e.g., pathogens) stresses. Key research areas include microbiome interactions, pathogen resistance mechanisms, and precision phenotyping. He leads or collaborates on grants from USDA, Minnesota Soybean Council, and the University of Minnesota. Education: PhD and BS in Plant Breeding/Genetics and Biochemistry from the University of Wisconsin-Madison. The Hirsch Lab is based in Stakman Hall , with a focus on translational research bridging basic science and agricultural applications. Research Themes: The lab uses cutting-edge technologies to dissect genomic variation and gene expression dynamics in crops like maize, wheat, and sugar beet. Recent work includes transposable element roles in stress responses, hyperspectral imaging for disease detection, and machine learning for phenotyping. Projects emphasize understanding stress biology to enhance crop resilience. Grants & Collaborations: Notable projects include USDA-funded studies on transposable elements in maize abiotic stress, Minnesota Soybean Council support for soybean disease phenotyping, and collaboration with the Microbial and Plant Genomics Institute. These efforts aim to improve crop productivity and sustainability. Labs & Infrastructure: The lab is equipped with advanced phenotyping tools, including RGB/hyperspectral imaging systems and drone-based platforms. It collaborates with multiple departments and external institutions to advance integrative plant science.

Isaac Penceمشاهده پروفایل

استادیار

• Translational Biophotonics
• Raman Spectroscopy
• Medical Device Development
• +۳ مورد دیگر

Dr. Isaac Pence is an Assistant Professor at UT Southwestern Medical Center's Department of Biomedical Engineering, with secondary appointments in Internal Medicine and the Charles and Jane Pak Center for Mineral Metabolism. He also holds an Adjunct Assistant Professor role at UT Dallas' Bioengineering Department. His research focuses on developing optical tools for non-invasive disease characterization and therapeutic monitoring, integrating biophotonics, computational analysis, and clinical medicine. Dr. Pence's work includes advancements in Raman spectroscopy for drug distribution analysis, tissue engineering, and cryoneurolysis devices for pain management. He completed his PhD at Vanderbilt University and postdoctoral training at Imperial College London and Harvard Medical School. Research interests span label-free quantitative tissue mapping, translational biophotonics, and biomarker heterogeneity analysis. His lab develops clinical instruments such as portable Raman systems for in vivo imaging and theranostic platforms. Recent work addresses pelvic organ prolapse via ECM composition analysis and cryotherapy device innovation. Collaborations include UT Dallas and the Texas Instruments Biomedical Engineering and Sciences Building. Key projects include Raman-guided surgical tools, nanocarrier design, and extracellular vesicle biomarker detection. His contributions have led to funded grants and patents, though specific award names are not listed. The Pence lab actively trains graduate students and postdocs in biophotonics and biomedical engineering.

Bernardino Casas Fernándezمشاهده پروفایل

استاد مدعو

• Quantitative Linguistics
• Natural Language Processing
• Polysemy
• +۳ مورد دیگر

Bernardino Casas Fernández is an Adjunct Professor at the Departament de Llenguatges i Sistemes Informàtics (LSI) of Universitat Politècnica de Catalunya (UPC). He holds offices at both the Vilanova i la Geltrú campus (EPSEVG-VG1, Room 120) and the Barcelona campus (Campus Nord-Edifici Omega, Room 224). His research focuses on quantitative linguistics, natural language processing, polysemy analysis, and computational linguistics. He has contributed to open-source tools like FreeLing and projects such as CARPANTA for email summarization. Recent work explores semanticity in Catalan using large language models and ethical implications of generative AI in education. He maintains active involvement in computational linguistics and child language development studies. Education details are not explicitly listed, but his academic career spans from 2003 (earliest article) to 2024. He collaborates with initiatives like LAPPS (Language Acquisition and Processing Systems) and has participated in projects involving churn prediction systems and entropy estimation techniques.

• Dependence Modeling
• Copula Models
• Multivariate Analysis
• +۷ مورد دیگر

Harry Joe is a Professor in the Department of Statistics at the University of British Columbia (Vancouver Campus). His primary research focuses on dependence modeling, copula theory, multivariate analysis, and applications in biostatistics, finance, and psychometrics. He has advised students including Xiaoting Li, Xinyao Fan, and Pavel Krupskiy. Research Interests: - Advanced copula constructions (e.g., vine copulas) - Extreme value theory and tail dependence - Applications in financial risk, biomedical research, and educational measurement - Multivariate time series analysis and non-Gaussian models Publications highlight contributions to copula-based classification methods (2024), factor copula models (2015), and dynamic dependence modeling (2020). His work bridges theoretical developments with practical applications across disciplines. Teaching and advising emphasize methodological innovation. Current research explores high-dimensional dependence structures and computational methods for complex data. No lab/team affiliations explicitly noted in provided materials.

Shachar Karivمشاهده پروفایل

استاد

• Economic theory
• Experimental economics
• Behavioral economics
• +۷ مورد دیگر

Shachar Kariv is the Benjamin N. Ward Professor of Economics at the University of California, Berkeley. He earned his Ph.D. in Economics from New York University in 2003 and has been a faculty member at UC Berkeley since joining that year. His academic career includes leadership roles as Department Chair (2014-17, 2021-22) and Director of the UC Berkeley Experimental Social Science Laboratory (Xlab) from 2008 to 2014. He co-founded Xmobile, a smartphone-based platform for social science experiments. Ph.D., Economics, New York University (2003) M.A., Economics, New York University (2000) B.A., Economics, Tel Aviv University (1998) Kariv's research focuses on economic theory, experimental economics, and behavioral economics, with particular emphasis on social networks, personal and social preferences, decision-making under uncertainty, and network architecture. His work often combines theoretical models with laboratory experiments to analyze individual and collective economic behavior. Kariv's recent publications explore topics such as social learning , transfer performance of predictive models , and choice under risk and uncertainty . These works employ experimental data to investigate how individuals process information, make spending decisions, and interact within networked environments. UC Berkeley Haas School of Business Cheit Award for Excellence in Teaching (2012) UC Berkeley Division of Social Sciences Distinguished Teaching Award (2008) NYU College of Arts and Science Outstanding Teaching Award (Golden Dozen) (2002) Sloan Research Fellowship (2009-10) Outstanding Dissertation Award, NYU Graduate School of Arts and Science (2003) Kariv has received major grants from institutions like the Alfred P. Sloan Foundation , National Science Foundation , and Center on the Economics and Demography of Aging (CEDA) . His professional activities include editorial roles at prestigious journals such as the Review of Economics and Statistics and Games and Economic Behavior . He has also held visiting professorships at institutions including Stanford University, University of Oxford, and NHH Norwegian School of Economics.

Aneesha Bakhariaمشاهده پروفایل

مدرس ارشد

• Learning Analytics
• Educational Technology
• Artificial Intelligence in Education
• +۷ مورد دیگر

Dr. Aneesha Bakharia is a Senior Lecturer - Teaching Focussed at the School of Electrical Engineering and Computer Science within the Faculty of Engineering, Architecture and Information Technology at the University of Queensland. She has established herself as a prominent researcher in educational technology and learning analytics with numerous publications spanning over a decade. Her educational background includes a Bachelor (Honours) of Engineering, a Postgraduate Diploma, and a Masters (Coursework) of Digital Design from Griffith University, along with a Postgraduate Diploma in Open and Distance Learning from the University of Southern Queensland. These qualifications form a strong foundation for her interdisciplinary approach to educational technology research. Dr. Bakharia's research primarily focuses on learning analytics, educational technology, and the application of artificial intelligence in educational contexts. Her work explores how data-driven approaches can enhance teaching practices and student learning experiences. She has made significant contributions to the development of learning analytics dashboards, the integration of AI in education, and the design of effective online learning environments. Her recent research has particularly emphasized generative AI applications in educational settings, examining how these technologies can transform teaching and learning practices while addressing associated challenges and ethical considerations. Analysis of her recent publications reveals a clear progression toward AI-integrated educational technologies, with an increasing focus on generative AI applications in teaching and learning. Her work spans multiple domains including programming education, language learning, work-integrated learning, and medical education, demonstrating the versatility of her research approach. The consistent thread throughout her publications is the application of data analytics and technological innovation to solve practical educational challenges. Dr. Bakharia is actively engaged in supervision, as indicated by her availability for student supervision at the University of Queensland. Her collaborative approach is evident in her extensive co-authorship with researchers across various disciplines, particularly in projects involving dashboard design, learning analytics implementation, and AI in education initiatives. Her research has been implemented through various collaborative projects, including the development of tools like PerspectivesX for collaborative learning activities and SNAPP (Social Networks Adapting Pedagogical Practice), which provides visualizations of student interaction networks. These projects often involve interdisciplinary teams working at the intersection of computer science, education, and domain-specific teaching contexts.