جست‌وجوی استاد و پژوهشگر

Heather Desaireمشاهده پروفایل

استاد

• Mass Spectrometry
• Bioanalytical Chemistry
• Physical Organic Chemistry
• +۳ مورد دیگر

Heather Desaire is a University Distinguished Professor and holds the Keith D. Wilner Chair in Chemistry at the University of Kansas, Department of Chemistry. Her research focuses on mass spectrometry applications in bioanalytical and physical organic chemistry, including structural analysis of glycoproteins and organic reaction mechanisms. She pioneered methods to characterize glycopeptides using tandem mass spectrometry and developed rules for dissociation reactions in mass spectrometry. Her recent work integrates machine learning for biomarker discovery, Alzheimer’s disease studies, and detecting AI-generated academic texts. Key tools developed by her group include GlycoPep DB and GlycoPep ID for glycopeptide analysis. Education: B.A. in Chemistry from Grinnell College (1997), Ph.D. in Chemistry from University of California, Berkeley (2001). Postdoctoral work at Quintiles Inc. (2002). Research Interests: Mass spectrometry of glycoproteins and small organic molecules. Machine learning applications in proteomics and biomarker validation. Forensic analysis of latent fingerprints and sebum via mass spectrometry. Structural studies of HIV envelope glycoproteins and vaccine development. Publications highlight advancements in AI detection (over 99% accuracy distinguishing ChatGPT text), Alzheimer’s biomarkers, and lipidomic studies using non-invasive sampling. Her work has been supported by grants including the NSF Career Award and the ASMS Research Award. Awards: William T. Kemper Award for Excellence in Teaching (2009), NSF Career Award (2007-2012), and ASMS Research Award (2006). Lab: Desaire Research Group develops cutting-edge tools for glycoproteomics and mass spectrometry data analysis. Collaborations focus on translational research in virology, neurodegenerative diseases, and forensic science.

John V. Tuckerمشاهده پروفایل

استاد

• Theory of synchronous algorithms with digital and analogue components
• History of science
• Physical foundations of computation
• +۵ مورد دیگر

John V. Tucker is a Professor of Computer Science at Swansea University since 1989. He served as Head of the Department of Computer Science (1994-2007) and Head of the School of Physical Sciences (2007-2011). His research spans theoretical computer science, history of computing, and computational foundations of physics. Education: MSc in Mathematical Logic and Foundations of Mathematics and Computer Science (1974) and PhD in Mathematical Logic (1977) from the University of Bristol. His research interests include the theory of synchronous algorithms, physical foundations of computation, algebraic specification, and algorithmic models of nonlinear systems. He pioneered equational specification methods for microprocessors, 3D graphics, and whole-heart modeling. Scientific awards include: Founding Fellow of the Learned Society of Wales (2010) Elected Fellow of British Computer Society (1998) He has supervised 16 PhD students directly and contributed to supervision in Uppsala, served on EU project evaluation panels, chaired appointments, and led editorial roles in journals and book series.

Ahmet Alkan ÇELİKمشاهده پروفایل

استاد

• Macroeconomics
• Economic Growth
• Inflation
• +۳ مورد دیگر

Prof. Ahmet Alkan ÇELİK is the current Rector of Doğuş Üniversitesi, serving since September 2024. He holds a Professorship in the Department of Economics at the Faculty of Economics and Administrative Sciences. His academic journey includes roles as Beykent Üniversitesi’s Vice Rector (2024), Dean (2018–2024), and Chair of the Board of Trustees (2013–2024). He earned his PhD from Marmara Üniversitesi’s Middle East Studies Institute in 2019, focusing on macroeconomic analysis of Gulf economies. Education: Bachelor’s in Economics, İstanbul Üniversitesi (2000) Master’s in Social Sciences, Beykent Üniversitesi (2004) PhD in Middle Eastern Economic Analysis, Marmara Üniversitesi (2006) Research focuses on Macroeconomics, Economic Growth, Inflation, and Development Economics , with emphasis on policy impacts in emerging markets. His work bridges theoretical frameworks with regional case studies, particularly in the Middle East and Balkans. Recent studies analyze pandemic-era monetary policies and university-industry collaboration models. Administrative leadership spans over 15 years, including roles as University Secretary (2009), Institute Director (2013), and International Relations Officer (2018). He has advised numerous academic programs and led institutional reforms.

Cristian Marius Litanمشاهده پروفایل

دانشیار

• Econometrics
• Statistics
• Public Economics
• +۳ مورد دیگر

Cristian Marius Litan is an Associate Professor in the Department of Statistics, Forecasting, and Mathematics at the Faculty of Economics and Business Administration, Babeș-Bolyai University, Cluj-Napoca, Romania. He has served in significant administrative roles, including Vice-Rector of the university since 2016 (with a brief interruption in 2021), and as State Secretary at the Ministry of Research, Innovation and Digitalization in Bucharest. His academic background includes a PhD in Economics from Universidad Carlos III de Madrid (2009), an MA from Central European University, Budapest (2002), and a BA from Babeș-Bolyai University (2000). He has taught courses such as Descriptive and Inferential Statistics, Public Economics, Basic and Advanced Econometrics, and Panel Data Econometrics at both undergraduate and graduate levels. His research interests center on econometrics, statistical modeling, economic forecasting, and public economics, reflecting his teaching and professional work in economic policy and modeling. His expertise is supported by proficiency in statistical software including Stata, EViews, SPSS, and programming languages like MATLAB, Gauss, and C++. Cristian Marius Litan has held long-standing academic and leadership roles at Babeș-Bolyai University, contributing to both education and institutional governance. He has not been mentioned as receiving specific scientific awards or leading research grants in the provided text. He is fluent in English and Spanish, with advanced writing skills in Spanish, and maintains an active academic presence through teaching and university administration. No information on PhD or master's students under his supervision is provided in the available data.

• Atmospheric Physics
• High Energy Atmospheric Physics
• Lightning Physics
• +۷ مورد دیگر

Joseph Dwyer is a Professor in the Department of Physics and Astronomy at the University of New Hampshire (UNH), where he conducts groundbreaking research in high-energy atmospheric physics. His work focuses on lightning physics, terrestrial gamma-ray flashes (TGFs), x-rays from lightning, and thunderstorm radiation environments. Research Interests: His primary research areas include Atmospheric Physics, High-Energy Atmospheric Physics, Lightning Physics, Terrestrial Gamma-Ray Flashes, X-rays from Lightning, and Relativistic Runaway Electron Avalanches. He investigates how thunderstorms can produce intense bursts of gamma rays and energetic particles, challenging traditional models of atmospheric discharges. Recent Research Trends: Over the past decade, Dwyer’s publications have centered on the mechanisms of TGF generation, relativistic feedback discharges, radio emissions from lightning, and high-speed observations of streamer and leader processes. His work combines theoretical modeling, numerical simulations, and data from ground-based, airborne, and satellite instruments such as Fermi GBM and LOFAR. Scientific Awards: Dwyer has not been explicitly mentioned as receiving specific prizes or fellowships in the provided text, but his extensive funding and leadership roles indicate high recognition in the field. Advising and Grants: He has served as Principal Investigator on numerous federally funded research projects from NASA, NSF, and DOD. His grants support investigations into lightning initiation, TGF modeling, radio emissions, and high-speed imaging. He has also been repeatedly appointed to advisory panels, including multiple Lightning Advisory Panels for NASA and a Blue Ribbon Panel for the Department of Energy, underscoring his national influence. Labs and Teams: While specific lab names are not provided, Dwyer leads a research group focused on high-energy atmospheric phenomena, collaborating with institutions such as Duke University, Florida Institute of Technology, and the Air Force. His team utilizes advanced computational models and participates in airborne and ground-based observational campaigns.

• Communication Sciences
• Digital Media
• Journalism
• +۸ مورد دیگر

Alexandra Figueira is a researcher at CICANT and holds academic roles at Universidade Lusófona, serving as Director of the Master's program in Communication, Marketing and Digital Media and Deputy Director of the Bachelor's in Communication Sciences. She has taught Journalism, Strategic Communication, and Research Methodologies since 2021 and has over 25 years of experience in media industries. PhD in Communication Sciences (University of Minho) Postgraduate studies in Brand Creation and Management (IPAM), Economics for Journalists (University of Porto), and Company Analysis Certifications in Investigative Reporting, Social Entrepreneurship, and AI for Education Her research focuses on Communication Sciences , Digital Media , and Journalism Ethics , with a particular interest in algorithmic influence , media transparency , and digital activism for education . Recent publications explore topics like AI integration in higher education, social capital in digital networks, and ethical challenges in contemporary journalism. She has received three notable awards: two recognitions from the ANMP Journalism and Local Power Award (1st place for a collective piece and an honorable mention for an individual report) and the António Sérgio Cooperation and Solidarity Award for doctoral research. Figueira actively participates in international conferences and serves on academic examination panels.

• Risk Assessment
• Ecosystem Services
• Environmental Exposure
• +۷ مورد دیگر

Katherine Ellen von Stackelberg is a Senior Research Scientist in the Department of Environmental Health at Harvard T.H. Chan School of Public Health. She holds leadership roles as Team Leader for the Biogeochemistry of Global Contaminants Group (Sunderland Lab) and Director of Research Translation for the Harvard Superfund Research Program (MEMCARE). Her interdisciplinary work bridges environmental science, risk assessment, and policy development. Education: AB, cum laude in General Studies from Harvard College (1988) ScM in Environmental Health and Health Policy from Harvard School of Public Health (1998) ScD in Environmental Science and Risk Management from Harvard School of Public Health (2006) Her research focuses on the intersection of environmental exposures, ecosystem services, and human health. Key areas include: Risk assessment frameworks for environmental contaminants (PFAS, metals, PCBs) Valuation of natural capital and biodiversity through ecosystem integrity indices Development of probabilistic bioaccumulation models for aquatic systems Socio-ecological approaches to planetary health and regenerative futures She teaches courses on socio-ecological systems that analyze economic drivers of environmental degradation. Her scholarly publications demonstrate consistent focus on environmental risk assessment methodologies, with recent expansion into global contaminant distribution, ecosystem service valuation, and health impacts in vulnerable populations. Research frequently incorporates machine learning, spatial modeling, and decision-analytic frameworks. Dr. von Stackelberg has served on the US EPA's Board of Scientific Counselors and National Academies panels, and regularly reviews for the European Commission Horizon program. She leads multiple projects on risk assessment frameworks and contaminant bioaccumulation modeling.

Emilio Zagheniمشاهده پروفایل

استاد پژوهشی

• Migration
• Mobility
• Population Dynamics
• +۴ مورد دیگر

Emilio Zagheni is a Director at the Max Planck Institute for Demographic Research (MPIDR) and affiliate faculty in the Department of Sociology at the University of Washington, Seattle, where he served as Training Director of the Center for Studies in Demography and Ecology. He earned a Ph.D. in Demography (2010) and an M.A. in Statistics (2008) from UC Berkeley. His research focuses on migration , mobility , and population dynamics , integrating computational methods with traditional demographic approaches. Key themes include gender disparities in migration , climate change impacts on well-being , and digital data bias correction . Recent publications analyze global academic migration patterns , temperature-related mortality , and social media's role in migration studies . His work leverages digital trace data from platforms like Facebook and LinkedIn to innovate migration measurement. President, European Association for Population Studies (EAPS) Chair, Digital Demography Panel (IUSSP, 2015-2022) Zagheni leads the MPIDR's Department of Digital and Computational Demography , which includes the Labs of Migration and Mobility and Population Dynamics and Sustainable Well-Being . His initiatives, such as the Population and Social Data Science Summer Incubator Program , foster interdisciplinary collaboration.

• Macroeconomics
• Financial Development-Economic Growth Relationship
• Energy Economics
• +۷ مورد دیگر

Prof. Dr. Ahmet Gökçe Akpolat is an Associate Professor at Kütahya Dumlupınar University's Department of Finance and Banking. He holds a PhD in Economics from Sakarya University (2019), an MSc in Economics (2012), and a BSc in Economics (2008) from Marmara University. His academic career includes roles as a Researcher at Sakarya University (2010–2019) and Bartın University (2009–2010), and current tenure as a full-time faculty member. His research focuses on Macroeconomics , Financial Development and Growth Relationships , Energy Economics , and Dynamic Stochastic General Equilibrium (DSGE) Models . Prof. Akpolat has received multiple TÜBİTAK Publication Incentive Awards (2024, 2020, 2018) for his impactful research. His teaching portfolio includes courses on Banking and Finance Applications , Monetary Theory , and International Economics at both undergraduate and graduate levels. His recent work examines commodity price impacts on growth, nonlinear energy policies, and financial development's role in inequality reduction. Key publications include analyses of oil market dynamics, housing price asymmetries, and FDI's macroeconomic effects. His research integrates advanced econometric techniques like nonlinear ARDL, DSGE modeling, and structural break analysis to address global and regional economic challenges.

Wajih Ul Hassanمشاهده پروفایل

استادیار

• System Security
• Network Security
• Machine Learning
• +۵ مورد دیگر

Wajih Ul Hassan is an Assistant Professor of Computer Science at the University of Virginia (UVA), leading the DART Lab. His research focuses on system security, emphasizing practical solutions for safeguarding networked systems using data-driven approaches and scalable design. He was awarded the NSF CAREER Award in 2024. His service roles include program committee (PC) membership at IEEE S&P, NDSS, ACM CCS, and NSF panel participation since 2018. Research Interests : Hassan’s work centers on intrusion detection, provenance analytics, threat detection, and forensic analysis. He explores how provenance graphs and machine learning can enhance cybersecurity resilience against advanced persistent threats (APTs), AR/VR attacks, and configuration-based exploits. Teaching : He teaches CS 6501: Machine Learning in Systems Security , CS 4630: Defense Against the Dark Arts , and DS 6559: Machine Learning in Systems and Network Security . Courses emphasize threat detection, vulnerability management, and forensic investigation. Awards : NSF CAREER Award (2024) Labs & Teams : Directs the DART Lab, focused on applied security research and scalable defense mechanisms.

Karen Robsonمشاهده پروفایل

استاد

• Sociology of Education
• Race and Education
• Postsecondary Transitions
• +۴ مورد دیگر

Karen Robson is a Professor in the Department of Sociology within McMaster University's Faculty of Social Sciences, where she conducts influential research on educational inequality, race, and postsecondary transitions. Her work focuses particularly on Toronto student populations and employs rigorous quantitative methodologies to examine systemic barriers in education. Education Background: Bachelor of Arts (Honours) in Sociology from University of Alberta, Edmonton Master of Arts in Sociology from University of Calgary, Calgary PhD in Applied Social and Economic Research from University of Essex, Colchester Professor Robson's research primarily investigates the intersection of race, immigration status, and educational outcomes, with particular emphasis on postsecondary transitions in Canadian urban contexts. She has developed expertise in multilevel modeling and longitudinal research methods, frequently analyzing Toronto District School Board data to uncover patterns of educational inequality. Her work consistently addresses how systemic factors like food insecurity, school climate, and policy frameworks impact marginalized student populations. Through her publications and public engagement, she has become a leading voice on the need for race-conscious data collection in Canadian education policy. Her scholarly output demonstrates consistent productivity with 46 publications in the last decade, including influential books such as Basics of Social Research, Fourth Canadian Edition (2017) and Multilevel Modeling in Plain Language (2015). Her recent work increasingly focuses on intersectional analyses of educational barriers, with publications examining everything from the gendered and racialized pathways to full professorship to the impact of food insecurity on academic performance. Professor Robson actively teaches sociology courses at both undergraduate and graduate levels, including Sociology of Education (SOCIOL 2GG3 and SOCIOL 716) and Supervised Research Course (SOCIOL 730). Her teaching reflects her research expertise in quantitative methods and educational sociology. She has been instrumental in bringing sociological perspectives to public policy debates, particularly regarding charter schools in Ontario and the collection of race-based education data. Her research has gained significant attention, being referenced in Wikipedia pages, cited by policy sources, and picked up by multiple news outlets. With over 196 readers on Mendeley for her work on university-to-college transfer, her scholarship demonstrates substantial reach within academic and policy communities.

David Cairnsمشاهده پروفایل

استاد

• Clinical Trials
• Biostatistics
• Haematological Oncology
• +۱۲ مورد دیگر

Professor David Cairns is a leading academic in clinical trials research at the University of Leeds, Faculty of Medicine and Health, School of Medicine. He serves as Professor of Clinical Trials Research, Deputy Director of the Leeds Cancer Research UK Clinical Trials Unit (CTRU), and Director of Late Phase Trials in the Cancer Division. His work bridges biostatistics and oncology, with a focus on designing and analyzing large-scale confirmatory trials. His educational background includes a PhD and MSc in Statistics from the University of Sheffield and a BSc in Mathematics from the University of Leeds. David Cairns specializes in the design and analysis of cancer clinical trials, particularly in haematological malignancies such as multiple myeloma and chronic lymphocytic leukaemia, as well as solid tumours including colon, gastro-oesophageal, and urological cancers. He is passionate about developing efficient trial designs that incorporate biomarkers to define treatment pathways and enhance personalization. He actively promotes the integration of translational research within clinical trials to improve scientific value and inform future study designs. The 15 most recent articles reflect a strong focus on methodological innovation in clinical trials, including platform trials, non-concurrent controls, biomarker-driven designs, and the integration of real-world data. His work combines statistical rigor with clinical relevance, particularly in oncology settings. His scientific recognition includes the MRC Career Development Award in Biostatistics. He is also actively involved in national research governance through membership in key panels: Fellow of the Royal Statistical Society NCRI Multiple Myeloma Subgroup (Member) NIHR Clinical Trial Fellowship Panel (Member) NIHR Development and Skills Enhancement Fellowship Panel (Member) NIHR Doctoral Research Fellowship Panel (Deputy Chair) Cancer Research UK Expert Review Panel (Member) David Cairns is deeply committed to student education and the training of future clinical researchers. He welcomes PhD applicants interested in clinical trials, biostatistics, and cancer research. He supervises postgraduate research and contributes to the academic development of junior researchers through mentorship and collaborative projects. His leadership roles indicate substantial grant oversight and management of large-scale research initiatives. He is embedded in the Leeds Institute of Clinical Trials Research, a multidisciplinary team dedicated to improving patient outcomes through high-quality trial design and execution. He is affiliated with several research groups and institutes, primarily the Leeds Institute of Clinical Trials Research (Populations) and contributes to national and international efforts in advancing cancer clinical research methodology.

Suyong Songمشاهده پروفایل

دانشیار

• Econometrics
• Corporate Finance
• Empirical Industrial Organization
• +۵ مورد دیگر

Suyong Song is an Associate Professor in both the Department of Economics and the Department of Finance at the Tippie College of Business, University of Iowa. He is also a Henry B. Tippie Research Fellow, recognizing his contributions to research in economics and finance. His academic appointments reflect a strong interdisciplinary profile bridging econometric theory and financial applications. Education: Ph.D. in Economics, University of California-San Diego (2010) M.A. in Economics, Korea University (2004) B.A. in Economics, Korea University (2002) Suyong Song's research lies at the intersection of econometrics, corporate finance, and machine learning. His work focuses on developing and applying advanced statistical methods to economic and financial problems, particularly in the areas of quantile regression, measurement error models, network analysis, and non-Euclidean data. He investigates how social and interfirm networks influence corporate decisions, and applies machine learning techniques to diverse domains such as body shape-income relationships and social media sentiment analysis. His methodological rigor is evident in his publications in top-tier econometrics and finance journals. The recent publications highlight a consistent trend toward integrating modern data science tools—especially machine learning and network analytics—into traditional economic frameworks. His work spans corporate governance, supply chain resilience, monetary policy evaluation, and labor economics, demonstrating broad applicability of his methodological innovations. The articles reflect a strong emphasis on causal inference, robust estimation, and the use of novel data sources such as social media and biometric data. Scientific Awards and Recognitions: Henry B. Tippie Research Fellow Suyong Song actively engages in research advising and has collaborated with numerous scholars across institutions. While specific grant details are not listed, his publication record in high-impact journals suggests successful funding and research leadership. His interdisciplinary collaborations indicate involvement in team-based research projects, particularly in econometrics and applied finance. There is no mention of formal student advising in the provided text, but his role as a research fellow and associate professor implies mentorship responsibilities. He is involved in the broader research ecosystem at the Tippie College of Business, contributing to seminars and research initiatives in business analytics and econometrics. His work with the Tippie Analytics Cooperative and participation in research seminars suggest engagement with data-driven research platforms and academic discourse. His research program appears poised to continue advancing econometric methods and their application to pressing economic and business challenges.

• Energy Management
• Renewable Energy Systems
• Life Cycle Assessment
• +۷ مورد دیگر

Scott Frazier is an Associate Professor in the Department of Biosystems and Agricultural Engineering at Oklahoma State University (OSU), where he also serves as an Extension Specialist for Energy Management with OSU Extension. His work integrates teaching, applied research, and extension outreach focused on energy and resource management in agricultural and industrial sectors. PhD, Oklahoma State University MS, Oklahoma State University BS, Oklahoma State University Dr. Frazier's research spans energy management, renewable energy systems, life cycle assessment (LCA), irrigation efficiency, and decision science. His applied work emphasizes sustainability in agricultural processes, including biofuel technologies, water use efficiency, and energy conservation in farming operations. He has led numerous projects evaluating the performance of irrigation systems, particularly center pivots in western Oklahoma, and assessing the environmental and economic impacts of energy technologies. His recent scholarly output shows a strong focus on sustainability analysis, including LCA studies comparing landfilling and gasification for municipal solid waste, and evaluating biochar versus metal catalysts in syngas cleaning. He also explores synthetic data generation for agricultural loads using TimeGANs and conducts economic analyses of household solar and wind energy systems. These works reflect a consistent theme of using engineering and systems analysis to promote sustainable resource use. Professional Engineer (PE), National Society of Professional Engineers Certified Energy Manager (CEM), Association of Energy Engineers Dr. Frazier is actively involved in teaching courses such as Energy and Power in Biosystems Engineering, Experimental Methods, and doctoral research. He advises graduate students and teaches specialized topics including life cycle assessment and off-grid energy systems. His funded research includes projects on the Oklahoma Master Irrigator Program, hazardous materials transportation risk modeling (OK-EFRA), and irrigation pump diagnostics, supported by agencies such as the Oklahoma Department of Emergency Management, USDA, and USGS. He also leads extension efforts in residential and commercial energy use, biofuels, and sustainability.

• Computer Vision
• Image Processing
• Photometric Stereo
• +۱۲ مورد دیگر

Vasileios Argyriou is an academic researcher affiliated with Kingston University, with extensive contributions in computer vision, image processing, and AI applications in IoT, healthcare, and smart agriculture. His work spans photometric stereo, motion estimation, federated learning, and UAV-based remote sensing. Research Interests: His research focuses on developing advanced computer vision techniques including photometric stereo for 3D reconstruction, deep learning for anomaly detection, federated learning for privacy-preserving AI, and AI-driven solutions for smart farming and healthcare. He explores motion estimation, facial recognition, and synthetic data generation for training robust models. The recent publications (2024–2025) highlight a strong trend toward applying machine learning in real-world systems—particularly federated learning for intrusion detection, UAV-based agricultural monitoring, 5G security, and medical imaging. His work integrates computer vision with IoT, wireless communications, and edge computing, demonstrating interdisciplinary innovation. Scientific Contributions: Author of a book on image and video registration with quality metrics. Extensive publication record in top journals including IEEE Transactions, Sensors, and Pattern Recognition. Pioneering work in photometric stereo, motion estimation using phase correlation, and GAN-based face reenactment. He has advised or collaborated with numerous researchers across fields, though specific student names are not listed. His work often involves large-scale data analysis, simulation frameworks, and real-time systems. He is involved in projects related to smart cities, precision agriculture, and autonomous systems. Laboratories and Teams: His collaborations suggest involvement with research groups focused on intelligent systems, computer vision, and IoT at Kingston University and beyond, particularly with Panagiotis Sarigiannidis, Thomas Lagkas, and others in networking and AI.