جست‌وجوی استاد و پژوهشگر

• Macroeconomics
• Macroeconomic Forecasting
• Macroeconomic Policy
• +۷ مورد دیگر

Chetan Dave is a Professor of Economics at the University of Alberta's Department of Economics within the Faculty of Arts. He holds a PhD from the University of Pittsburgh, an MA from the University of British Columbia, and a BA (Hons.) from McGill University. His expertise spans macroeconomics, behavioral economics, and experimental economics, with a focus on macroeconomic forecasting, policy analysis, and structural econometrics. He served as an associate editor of the Journal of Economic Behavior and Organization (2011–2016) and has presented globally. Key awards include the 2018 EBES Best Paper Award for work on public goods and inequality aversion. His teaching includes undergraduate courses on money and graduate courses in macroeconomic theory and structural econometrics. Education: Bachelor’s in Economics (Hons.), McGill University Master’s in Economics, University of British Columbia PhD in Economics, University of Pittsburgh Research Interests: Macroeconomic modeling with fat tails Behavioral and experimental economics Public goods and policy design DSGE models and structural econometrics Advising & Grants: Supervised PhD students across institutions and secured grants including a $30K City of Edmonton grant (2021) and NSF awards. His work bridges theoretical macroeconomics with empirical and experimental applications.

Janice Chenمشاهده پروفایل

استادیار

• Cognitive Neuroscience
• Memory Science
• Temporal Dynamics
• +۴ مورد دیگر

Janice Chen is an Assistant Professor in the Department of Psychological & Brain Sciences at Johns Hopkins University, affiliated with the Krieger School of Arts & Sciences. Her research focuses on understanding how real-world memories are constructed and retrieved, using advanced neuroimaging and behavioral methods. Her work emphasizes the interplay between sensory input and mnemonic systems across multiple timescales, particularly during naturalistic experiences like movie viewing and narrative recall. Chen's education includes a PhD in Psychological & Brain Sciences. She leads a lab investigating topics such as neural coding of social interactions, temporal dynamics of memory, and cross-modal processing in blind individuals. Her lab employs fMRI, EEG, and behavioral experiments to map brain activity patterns during perception and recall. Current projects explore how causal structures in narratives shape memory organization, and the role of gaze behavior in linking visual perception to memory retrieval. Key contributions include developing datasets like 'Sherlock' and 'Film Festival,' widely used in cognitive neuroscience research. Her team collaborates on analyzing shared neural responses across individuals during narrative comprehension and transmission. She advises a diverse group of postdoctoral researchers and graduate students in cognitive and computational neuroscience. Chen's lab is not currently recruiting but maintains active research collaborations. Findings emphasize the brain's shared representational structures during memory recall, suggesting systematic neural reorganization from perception to memory storage.

Lindsey McGowenمشاهده پروفایل

پژوهشگر ارشد

• Program Evaluation
• Cooperative Research Centers
• Science and Technology Policy
• +۳ مورد دیگر

Dr. Lindsey McGowen is a Senior Research Fellow and Director of the Innovation Studies Lab in the Department of Psychology at North Carolina State University. She specializes in evaluating cooperative science and technology programs, particularly focusing on the outcomes and impacts of academic-industry collaborations like the NSF IUCRC program. Her research addresses program sustainability, innovation ecosystems, and policy evaluation for cooperative research centers. Education: PhD (2012) and MS (2010) in Psychology in the Public Interest from NC State, BA (2003) in Psychology and Communication from Lewis & Clark College. Research Interests: Program evaluation methodologies, cooperative research center dynamics, science & technology policy, innovation studies, and collaborative partnerships between academia, industry, and government. Her work emphasizes understanding how interdisciplinary teams address grand challenges and translate research into societal impact. Funded Projects: Evaluated major NSF, USDA, and NSA initiatives including the NSF IUCRC Evaluation Project (2016-2021), USDA AFRI SAS bioeconomy grants (2020-2025), and the NSA Science of Security Lablet (2014-2017). Her projects span food safety, nanotechnology, and cybersecurity sectors. Labs/Teams: Leads the Innovation Studies Lab, which investigates innovation processes in large multi-institutional research centers. The lab focuses on team science dynamics and program evaluation for projects tackling global challenges.

Roman Shorمشاهده پروفایل

دانشیار

• Geothermal Energy Systems
• Drilling Systems Modeling
• Data Analytics
• +۳ مورد دیگر

Dr. Roman Shor is an Associate Professor in the Harold Vance Department of Petroleum Engineering at Texas A&M University's College of Engineering. He holds the Douglas Von Gonten Faculty Fellowship. His research focuses on geothermal energy systems, drilling systems optimization, and machine learning applications in subsurface engineering. Shor leads the Wells for the Future Consortium , aiming to develop open-source tools for safe, efficient well construction. Educational Background: Ph.D. and M.S. in Petroleum Engineering, UT Austin (2016, 2014) M.S.E. in Computer and Information Science, University of Pennsylvania (2010) B.S.E. in Computer Science & Engineering and B.A. in Mathematics, University of Pennsylvania (2009) His research integrates advanced data analytics with drilling physics, addressing challenges in geothermal energy, multilateral well construction, and real-time subsurface imaging. Shor's work emphasizes industry collaboration, evidenced by his leadership in consortium initiatives and open-source projects like the Open Source Drilling Community (OSDC). His recent publications highlight innovations in geothermal well repurposing, seismic-while-drilling applications, and hybrid data-physics architectures for production forecasting. Dr. Shor's technical contributions include developing reduced-order drilling models, robust estimation techniques for subsurface parameters, and control methodologies to mitigate drilling vibrations. He actively engages with industry partners through events like the 2025 Biannual Research Update and the 2023 consortium symposium. His lab focuses on translating theoretical advancements into practical solutions, such as optimizing geothermal heat pumps for cold climates and enhancing drilling efficiency in hard-rock formations.

Gerald Adamsمشاهده پروفایل

استاد مدعو

• Interventional Cardiology
• Cardiovascular Medicine
• Clinical Cardiology
• +۳ مورد دیگر

Gerald Adams, MD, is an Adjunct Professor in the Department of Medicine at Queen’s University. He joined the faculty in 1990 as an interventional cardiologist and pioneered the Percutaneous Coronary Intervention (PCI) program at KHSC. In 2000, his team became the first in Ontario to offer 24/7 Primary PCI for STEMI. Dr. Adams has held leadership roles including Division Chair, Cardiology Service Chief, and postgraduate training Program Director. He remains clinically active in the PCI lab, inpatient services, and outpatient stress testing. His research interests span interventional cardiology, cardiovascular medicine, and healthcare administration. Recent scholarly work focuses on software engineering advancements, including cybersecurity protocols, AI-driven bug fixing, and blockchain smart contract analysis. Dr. Adams has contributed to over 15 peer-reviewed articles since 2020, addressing topics like MCP server security, semantic versioning of language models, and swarm robotics optimization. His interdisciplinary research bridges clinical practice and computational innovations.

Chadni Islamمشاهده پروفایل

مدرس

• Cyber Security
• Software Engineering
• Machine Learning
• +۵ مورد دیگر

Dr Chadni Islam is a Lecturer in the School of Computer Science at Queensland University of Technology (QUT), specializing in Cyber Security and Software Development. She holds a PhD from the University of Adelaide. Her research focuses on cybersecurity, software supply chain attacks, machine learning applications in security, and NLP techniques in software debugging. Dr. Islam has contributed to frameworks for post-quantum cryptography migration, dynamic threat hunting, and security tool orchestration. Her work includes developing datasets like QUT-DV25 for analyzing next-gen software supply chain attacks, and tools such as DySec for detecting malicious packages in the PyPI ecosystem. She has published extensively on topics like API misuse detection, system-level bug reproduction, and risk assessment frameworks. Dr. Islam’s research bridges theoretical advancements with practical cybersecurity challenges, emphasizing automation, tool integration, and threat intelligence. Her articles reflect a strong focus on real-world applications, including improving software supply chain resilience and enhancing security through machine learning.

Paula Onuchicمشاهده پروفایل

استادیار

• Microeconomic Theory
• Information Economics
• Organizational Economics
• +۵ مورد دیگر

Paula Onuchic is an Assistant Professor of Economics at the London School of Economics (LSE), affiliated with the Department of Economics and STICERD. Previously, she was a Postdoctoral Prize Research Fellow at Nuffield College, Oxford (2021–2024) and earned her PhD in Economics from New York University (2015–2021). Her education includes a BS and MA in Economics from Escola de Economia de São Paulo (EESP-FGV), Brazil (2009–2014). Her research focuses on microeconomic theory, information economics, and organizational economics. Key themes include team production dynamics, disclosure mechanisms, credit attribution, statistical discrimination, and signaling in collaborative environments. She explores how groups communicate outcomes to external observers and how these processes shape incentives and perceptions of responsibility. Her work has been presented at over 50 institutions worldwide, including Harvard, Princeton, Yale, and leading European universities. She serves as a referee for top journals (AER, Econometrica, QJE) and is a CEPR Research Affiliate. Teaching includes advanced microeconomics at Oxford and LSE. Technical skills include MATLAB and Python programming. Professional contributions include organizing economic theory conferences and seminars, co-editing work for the American Economic Review, and serving on scientific committees for Brazilian and international econometric societies.

• Agricultural Economics
• Food Economics
• Resource Economics
• +۵ مورد دیگر

Bob Myers is a University Distinguished Professor and serves as Associate Chairperson and Director of Graduate Programs in the Department of Agricultural, Food, and Resource Economics (AFRE) at Michigan State University (MSU). He was honored as a 2017 Agricultural and Applied Economics Association (AAEA) Fellow, recognizing his 30-year contributions to research, teaching, and service in agricultural economics. His leadership focuses on advancing AFRE’s graduate programs through administrative reforms, policy updates, and fostering interdisciplinary collaboration. Research interests include applied economic methodologies such as choice-modeling and experimental approaches, alongside leveraging microdata for policy analysis. Myers emphasizes modernizing the graduate curriculum to align with emerging trends while maintaining MSU’s reputation for rigorous research and industry connections. As Director of Graduate Programs, Myers aims to enhance student support systems, streamline electronic record-keeping, and champion initiatives led by AFRE’s dynamic junior faculty, who specialize in cutting-edge fields like behavioral economics and data-driven research. His vision prioritizes student career success and global academic impact.

Urs Hugentoblerمشاهده پروفایل

استاد

• Satellite Geodesy
• Global Navigation Satellite Systems (GNSS)
• Precise Orbit Determination
• +۴ مورد دیگر

Prof. Urs Hugentobler is a full professor at the Institute for Astronomical and Physical Geodesy at Technische Universität München (TUM), leading the Satellite Geodesy Department and the Forschungseinrichtung Satellitengeodäsie (FESG). His work focuses on precise geodetic applications of GNSS systems, satellite orbit determination, and Earth rotation studies. He holds a doctorate in astronomy from the University of Bern (1997) and has extensive experience with the ESA and international geodetic networks. Education: Master’s in theoretical physics (University of Bern, 1989), PhD in astronomy (University of Bern, 1997). Professional roles include leadership at the Bernese GPS Software group and the Wettzell Geodetic Observatory collaboration. His research emphasizes satellite gravimetry, solar radiation pressure modeling, and multi-technique geodetic observations. Research interests span satellite geodesy, GNSS applications, time/frequency transfer, and Earth system monitoring. Key contributions include advancements in Galileo and BeiDou satellite modeling, and the development of the Bernese GNSS Software. His work bridges geodesy with space science, addressing challenges in precision positioning and global reference frames. Publications highlight innovations in multi-GNSS analysis, satellite orbit determination, and Earth rotation parameters. His lab, FESG, supports TUM’s geodetic research and operational activities at Wettzell. Ongoing projects include the ESA Baltic+ and NEROGRAV initiatives, focusing on gravimetry and Earth dynamics.

• Self-Control
• Sense of Agency
• Human-Computer Interactions
• +۳ مورد دیگر

Dr. Jakob Kaiser is a Post-Doctoral Research Fellow at the Department of Psychology: General and Experimental Psychology, Ludwig-Maximilians-Universität München (LMU Munich). He holds a PhD in Cognitive Science from the University of Sussex, focusing on emotions in decision-making. Currently, he leads a DFG-funded project investigating self-control mechanisms and sense of agency. His research explores how humans regulate impulses, perceive control in social interactions, and interact with technology/AI systems. Education: Bachelor's in Computer Science, University of Greifswald Master's in Cognitive Science, University of Osnabrueck PhD in Cognitive Science, University of Sussex (2015) Research Interests: Self-Control: Neurobehavioral mechanisms underlying impulse regulation Sense of Agency: Subjective control's impact on behavior and social dynamics Human-Computer Interaction: Ethical implications of AI on human autonomy His recent work bridges neuroscience and psychology, examining neural correlates of decision-making (e.g., midfrontal theta oscillations) and societal impacts of technology. Current projects emphasize agency dynamics in learning processes and AI-driven feedback systems. Advising & Grants: Principal Investigator of a DFG-funded project. No listed advisees. Labs: Member of LMU's Psychology research group focused on action control and social cognition.

Kevin Roeمشاهده پروفایل

دانشیار

• Conservation Biology
• Freshwater Ecology
• Phylogenetics
• +۴ مورد دیگر

Kevin Roe is an Associate Professor at Iowa State University's Department of Natural Resource Ecology and Management (NREM). His research focuses on freshwater mollusks, fishes, and shrimps, employing phylogenetic and population genetic tools to study species evolution and conservation. His lab actively works with endangered species like the scaleshell mussel and Topeka shiner. Education: B.S., University of Georgia, 1988 M.S., University of Georgia, 1994 Ph.D., University of Alabama, 2000 Research Interests: Dr. Roe combines molecular techniques with ecological studies to address conservation challenges. His work spans phylogenetic analysis of freshwater taxa, genetic structure of endangered populations, and impacts of human activities on aquatic biodiversity. Recent studies emphasize habitat restoration for species like the Sheepnose mussel and Topeka shiner, leveraging genomic data to refine conservation strategies. Publications: Recent articles highlight his focus on endangered species genetics (e.g., scaleshell mussels), phylogeographic patterns in North American and Chinese Unionidae, and habitat restoration assessments. His work bridges basic science and applied conservation, often involving international collaborations and field-based studies. Awards & Grants: No explicit awards listed, but his research aligns with grants focusing on endangered species recovery and aquatic biodiversity conservation. Advising & Labs: As head of The Roe Lab , he mentors students in conservation genetics and phylogenetics. His projects often involve fieldwork in streams and rivers, integrating molecular biology and ecological sampling. Labs/Teams: Primary affiliation with Iowa State University's NREM department and collaborations with U.S. Fish and Wildlife Service and international institutions.

Valérie Doyèreمشاهده پروفایل

پژوهشگر

• Neuroscience
• Cognitive Neuroscience
• Behavioral Neuroscience
• +۳ مورد دیگر

Valérie Doyère is a Research Director and Group Leader of the 'Memory, Emotion & Time' team at the University Paris-Saclay. Her research focuses on understanding neural mechanisms underlying associative memory formation, temporal processing, and their modulation by emotion. She leads a multidisciplinary team employing pharmacological, molecular, electrophysiological, and behavioral techniques in rats. Research Focus: Her work centers on interconnected brain networks involving the amygdala, hippocampus, prefrontal cortex, and striatum. Key strategies include studying neuronal correlates of interval timing and the impact of developmental disruptions on emotional memory and timing. The team is affiliated with the doctoral school ED419 Bio-sigNE. Publications: Recent work includes studies on rodents' error monitoring during timing tasks (PNAS, 2022), amygdala dysfunction in fear responses (Cerebral Cortex, 2022), and neural encoding of time (Neuroscience & Biobehavioral Reviews, 2020). Themes emphasize temporal expectancy, fear conditioning, and neurodevelopmental disorders like Huntington's disease. Labs/Teams: Her group operates within the University Paris-Saclay's neuroscience facilities, focusing on translational research between cellular mechanisms and behavioral outcomes. Collaborations include institutions like CNRS and international journals.

Anna Petrasovaمشاهده پروفایل

پژوهشگر

• Geospatial Analytics
• Environmental Modeling
• Open Source Software Development
• +۳ مورد دیگر

Anna Petrasova is a Geospatial Software Engineer at North Carolina State University (NCSU), specializing in dynamic spatio-temporal modeling of urbanization, pest/pathogen spread, and geospatial simulation interfaces. She holds a Ph.D. in Geospatial Analytics and is a core contributor to the open-source GRASS GIS project. Her work focuses on participatory modeling, cloud-based geospatial platforms, and intuitive GUI design for collaborative decision-making in environmental and urban planning contexts. As a member of the OSGeo Foundation and GRASS GIS Steering Committee, she advocates for open-source software in research and education. Research interests span geospatial analytics, environmental modeling, and participatory approaches to addressing climate change and invasive species threats. She has developed tools like Rapid-DEM for topographic updates and GRASS_FUTURES for urban growth simulation. Her 15 most recent articles (2021–2024) emphasize open-source platforms, stakeholder engagement in modeling, and applications of GIS in flood risk reduction, invasive species forecasting, and landscape dynamics. Contributions include integrating FUTURES and PoPS models into GRASS, as well as Jupyter Notebook workflows for geospatial education. Anna collaborates with institutions like the Tangible Landscape Lab and has led over 900 code contributions across repositories, including core GRASS GIS development and educational tutorials.

Daniel V. McGeheeمشاهده پروفایل

استاد

• Driver attention and response
• Automotive Safety
• Crash avoidance
• +۴ مورد دیگر

Professor Daniel V. McGehee is a leading academic at the University of Iowa's College of Engineering, holding appointments in Industrial and Systems Engineering, Emergency Medicine, and Public Health. He directs the Driving Safety Research Institute (DSRI) and National Advanced Driving Simulator (NADS), focusing on driver behavior, automation safety, and human factors in transportation. His research spans ADAS systems, cannabis impairment effects, and tractor driving risks, with over $42M in grant funding. Key projects include 'ADS for Rural America' and the MyCarDoesWhat campaign. McGehee earned a PhD in Human Factors from the University of Leeds and has authored 150+ publications. His work integrates engineering, medicine, and policy to reduce traffic injuries. Education: PhD (Human Factors, University of Leeds), MS (Human Factors/Engineering Psychology, University of Idaho), BA (Psychology, Central Washington University). Research Priorities: Driver attention automation, crash avoidance, and trauma outcomes Labs: Applied Cognitive Engineering (ACE) Lab, DSRI Society Memberships: SAE International, Human Factors and Ergonomics Society Grants include studies on pedal misapplication, regenerative braking, and distracted driving trends. His work bridges academic research with real-world applications like NADS-Net AI for seat belt monitoring. McGehee collaborates globally, serving on the U.S.-EU-Japan trilateral automated vehicle working group.

Abbas Kaziempourمشاهده پروفایل

مدرس

• Deep Learning
• Machine Learning
• Neuroscience
• +۶ مورد دیگر

Abbas Kaziempour is a Lecturer at the School of Data Science, University of Virginia. He holds a Ph.D. in Electrical Engineering from the University of Maryland and a B.S. in Electrical Engineering from the University of Tehran. His research bridges deep learning, signal processing, and neuroscience, focusing on optimization, nonlinear dimensionality reduction, and biomedical imaging technologies. Ph.D., Electrical Engineering, University of Maryland B.S., Electrical Engineering, University of Tehran Kaziempour's work spans three key areas: (1) advancing deep learning theory through analysis of loss landscapes and optimization algorithms, (2) developing compressed sensing and polynomial PCA techniques for neuroscience and biomedical signal processing, and (3) engineering high-speed imaging systems like kilohertz frame-rate two-photon tomography. His recent publications highlight methodological innovations in machine learning and their applications to neural data analysis. As an applied scientist at Amazon's search relevance team, he translates theoretical insights into practical feature design and modeling solutions for industrial-scale problems. His academic contributions include (1) theoretical guarantees for sparse model recovery, (2) stability analysis of autoregressive estimation, and (3) novel approaches to signal deconvolution using state-space models.