جست‌وجوی استاد و پژوهشگر

Daniel Hydeمشاهده پروفایل

دانشیار

• Cognitive Development
• Numerical Cognition
• Developmental Psychology
• +۷ مورد دیگر

Daniel Hyde is an Associate Professor in the Department of Psychology at the University of Illinois Urbana-Champaign, affiliated with the College of Liberal Arts & Sciences and the Neuroscience Program. His research explores the nature and development of abstract conceptual knowledge through behavioral and neural measures. PhD in Psychology from Harvard University Hyde investigates cognitive development from infancy to adulthood, focusing on quantitative reasoning , spatial reasoning , and psychological reasoning using techniques like event-related brain potentials (ERPs) , functional near-infrared spectroscopy (fNIRS) , and behavioral assessments. His recent work examines how symbolic number knowledge builds on non-symbolic foundations and how neural sensitivity to mental states in infancy predicts later theory of mind abilities. Hyde's publications demonstrate a consistent focus on numerical cognition, multisensory integration, and developmental neuroscience. He leads the Brain and Cognitive Development Lab , participates in global initiatives like ManyNumbers and ManyBabies , and collaborates across disciplines to apply developmental insights to education and public health contexts.

M. Laura Beninatiمشاهده پروفایل

دانشیار

• Environmental Fluid Mechanics
• Sediment Transport
• Multi-phase Fluid Dynamics
• +۳ مورد دیگر

M. Laura Beninati is an Associate Professor of Mechanical Engineering at Bucknell University. She holds dual B.S. degrees in Architectural and Civil Engineering from Drexel University (1994), M.S. in Civil and Mechanical Engineering from Drexel (1997), and a Ph.D. in Mechanical Engineering from the University of Iowa (2004). Her research focuses on environmental fluid mechanics, sediment transport, turbulence dynamics, and experimental fluid mechanics instrumentation. She teaches courses in fluid mechanics, thermodynamics, and engineering experimentation. Awards: Lindback Grant (2007), Swanson Research Fellow (2005-2007), Amelia Earhart Scholarship (2002-2003) Her experimental studies emphasize vortex dynamics and turbulence interactions in fluid flows, with applications to environmental and aerospace engineering. Research methodologies include advanced fluid dynamics instrumentation and computational modeling.

Martha Constantinouمشاهده پروفایل

دانشیار

• Quantum Chromodynamics (QCD)
• Theoretical/Computational Nuclear Physics
• Lattice Quantum Chromodynamics
• +۴ مورد دیگر

Martha Constantinou is an Associate Professor of Physics at Temple University, specializing in Theoretical/Computational Nuclear Physics with a focus on Lattice Quantum Chromodynamics (QCD). Her research addresses fundamental questions in hadron structure, including nucleon spin content and proton radius puzzles, leveraging supercomputing resources. She leads a group conducting advanced numerical simulations at major computational facilities. Constantinou holds a Ph.D. in Theoretical Computational Physics (University of Cyprus, 2008) and a BS in Physics (University of Cyprus, 2003). Her work aligns with the upcoming Electron-Ion Collider (EIC) at Brookhaven National Lab, aiming to explore nucleon structure and dark matter connections. Key research areas include generalized parton distributions (GPDs), axial form factors, and high-performance computing applications. Notable awards include the US Department of Energy Early Career Award (2019) and the Selma Lee Bloch Brown Professorship (2020). Her publications (15 most recent listed) emphasize Lattice QCD advancements, with contributions to GPDs, quark-gluon momentum partitioning, and EIC theory. She actively promotes STEM outreach and public engagement through collaborative initiatives.

Rebecca Coxمشاهده پروفایل

استادیار

• Sleep and Circadian Rhythms
• Anxiety-Related Disorders
• Psychopathology
• +۱۲ مورد دیگر

Rebecca Cox is an Assistant Professor in the Department of Psychological & Brain Sciences at Washington University in St. Louis, where she leads the Sleep, Circadian Rhythms, and Psychopathology (SCRAP) Laboratory. Her research investigates the role of sleep and circadian rhythm disruption in anxiety-related disorders, employing multimethod approaches such as actigraphy, melatonin assays, ecological momentary assessment, and clinical trials. Education: PhD, Vanderbilt University MA, Vanderbilt University BA, Hendrix College Her research focuses on how disruptions in sleep and circadian rhythms affect physiological, cognitive, and affective functioning, contributing to the development and persistence of anxiety disorders. She is particularly interested in leveraging sleep and circadian medicine—including light therapy and cognitive behavior therapy for insomnia—as novel treatment strategies. Her work spans populations such as young adults and perinatal individuals, aiming to identify modifiable behavioral targets to improve mental health outcomes. The recent publications highlight a strong trend in integrating objective and subjective sleep measures with clinical psychology, particularly in OCD, PTSD, and general anxiety. Her work increasingly employs real-time data collection and population-level analysis to understand temporal and biological influences on mental health. Scientific Awards: No awards listed in the provided text. Dr. Cox advises students through the SCRAP Lab and is involved in clinical and translational research, though specific grants are not detailed. Her lab uses innovative methodologies to bridge basic science with clinical applications in mental health treatment. Labs and Teams: She directs the SCRAP Lab (Sleep, Circadian Rhythms, and Psychopathology Laboratory), which conducts interdisciplinary research combining sleep science, circadian biology, and clinical psychology to address anxiety-related psychopathology.

Przemyslaw Grabowiczمشاهده پروفایل

استادیار

• fair and explainable machine learning
• data science
• computational social science
• +۱۲ مورد دیگر

Przemyslaw Grabowicz is an Assistant Professor of Computer Science at University College Dublin and an Adjunct Professor at the University of Massachusetts Amherst. He leads the SIMS (Socially Intelligent Media and Systems) Lab and the EQUATE initiative, and is actively involved in the Knowledge Discovery Lab (KDL). His work bridges computer science, social science, and public policy, focusing on responsible AI and digital society. Research Interests: Fair and Explainable Machine Learning Computational Social Science Social Media and Network Science Public Opinion Modeling Algorithmic Bias and Discrimination Prevention Open-World Learning His research develops statistical and machine learning methods to understand and augment public opinion in digital environments, ensuring fairness, transparency, and societal benefit. He emphasizes legal compliance and ethical design in AI systems. Recent Research Trends: His recent publications focus on social media polls, political bias, misinformation, and fairness in machine learning. He investigates how algorithmic systems shape public discourse, especially during elections and global crises, and develops methods to detect and mitigate bias in data and models. Scientific Awards and Recognition: Best Paper Honorable Mention, ICWSM’25 WICI Data Challenge Main Prize (2013) Arnold O. Beckman Research Award Multiple UMass Amherst Interdisciplinary Research Grants Volkswagen Foundation Grants (over €900k total) Advising and Grants: Dr. Grabowicz supervises several PhD students in the SIMS and KDL labs and collaborates with MS students. He has secured significant funding from the Volkswagen Foundation, UMass Amherst, and the University of Illinois, supporting research on political misinformation, media bias, and global agenda setting. He is currently recruiting a postdoc at UCD. Labs and Initiatives: He heads the SIMS Lab and the EQUATE initiative, and contributes to the KDL. His project socialpolls.org explores public opinion through social media, and he maintains an active presence through the Uncommon Good blog on responsible AI.

Britta Timm Knudsenمشاهده پروفایل

استاد

• Cultural Theory
• Film and Video
• Aesthetics and Philosophy of Art
• +۱۴ مورد دیگر

Britta Timm Knudsen is a Professor at Aarhus University, affiliated with the School of Communication and Culture, where she contributes to both the Experience Economy and Scandinavian Studies programs. Her research spans critical cultural theory, decolonial practices, digital media, and affective experimentation. University: Aarhus University School: School of Communication and Culture Position: Professor Email: norbtk@cc.au.dk Location: Jens Chr. Skous Vej 2, 8000 Aarhus C, Denmark Her research interests focus on cultural heritage, film and video, aesthetics, colonial legacies, and affective ambivalence. She explores how media and artistic practices engage with decolonial resistance, emotional geographies, and urban cultural memory. Her work often intersects with Indigenous perspectives, digital activism, and experimental methodologies. The recent articles reflect a strong engagement with decolonial visualities, translocal media events (such as the George Floyd video in Denmark), and playful resistance through internet memes. Her scholarship combines critical heritage studies with affect theory, digital culture, and postcolonial critique, forming a cohesive trajectory around memory, power, and representation. Britta Timm Knudsen has been involved in significant research projects such as Playing with Ghosts and ECHOES: European Colonial Heritage Modalities in Entangled Cities . She has supervised visiting PhD students, including Shama Patel, and secured external research funding. Her editorial roles in journals like International Journal of Heritage Studies and Nordicom Review demonstrate her academic leadership. Playing with Ghosts - Affective ambivalence in decolonial art practices (2023–2025) ECHOES: European Colonial Heritage Modalities in Entangled Cities (2018–2021) Emotionel geografi netværk (2008–ongoing) She is actively engaged in public discourse, having contributed to Danish media outlets such as DR P1 and various radio programs, discussing topics ranging from nostalgia in film to existential themes. Her work bridges academic research and public engagement, particularly in the context of colonial heritage and cultural memory.

Claudia Patricia Ayala Martinezمشاهده پروفایل

مدرس

• Empirical Software Engineering
• Off-The-Shelf Adoption
• Requirements Engineering
• +۴ مورد دیگر

Claudia Patricia Ayala Martinez serves as a Lecturer in the Department of Service and Information Systems Engineering at the Barcelona School of Informatics (FIB), Polytechnic University of Catalonia (UPC). She is actively involved in research through the GESSI - Group of Software and Service Engineering and the UPC inSSIDE - integrated Software, Services, Information and Data Engineering research groups. Her career spans over two decades of academic contributions in software engineering with consistent publication output. Dr. Ayala Martinez's research focuses on Empirical Software Engineering, Off-The-Shelf Adoption, Requirements Engineering, and Software and Architectural Quality. Her work demonstrates an evolution from traditional software engineering topics toward increasing integration with machine learning and AI systems. Recent publications show particular emphasis on software quality indicators, ML pipeline design principles, trustworthiness of ML models, and green computing in software systems. Analyzing her publication trends reveals a consistent research trajectory with growing focus on AI/ML integration in software engineering. Her work spans empirical studies, systematic literature reviews, and practical industrial applications. The research shows strong connections between software quality metrics, architectural decisions, and emerging technologies, with increasing attention to ethical considerations in ML systems and sustainability in software development. Most-Influential Paper Award at the 30th IEEE International Requirements Engineering Conference Dr. Ayala Martinez has participated in numerous competitive R&D projects including those funded by the Spanish National Research Plan, Horizon 2020, and the Catalan Innovation Strategy. Her collaborative network includes extensive work with Professor Javier Franch Gutierrez (69 joint publications), Silverio Juan Martinez Fernandez (26 joint publications), and Cristina Gomez Seoane (20 joint publications). Her research has been supported by various national and European funding programs focusing on software engineering, quality assessment, and open source adoption. She is actively involved with the GESSI and inSSIDE research groups at UPC, which focus on integrated software, services, information, and data engineering. These groups maintain strong industry connections and have produced significant research in empirical software engineering, reference architectures, and quality assessment methodologies. Her recent work shows increasing collaboration with researchers working at the intersection of software engineering and artificial intelligence.

Joel Greenhouseمشاهده پروفایل

استاد

• Statistical Methodology
• Biostatistics
• Meta-Analysis
• +۴ مورد دیگر

Joel Greenhouse is a Professor of Statistics at Carnegie Mellon University (CMU), affiliated with the Department of Statistics & Data Science. He has been on the faculty since 1983 and held leadership roles, including serving as Associate Dean of the College of Humanities and Social Sciences from 1997 to 2002. He also holds an adjunct appointment as Professor of Epidemiology and Psychiatry at the University of Pittsburgh. His expertise spans statistical methodology, clinical trial design, and meta-analysis, with a focus on integrating data from multiple sources to address complex healthcare and public health challenges. Greenhouse earned his Ph.D. in Biostatistics from the University of Michigan and completed a postdoctoral fellowship at CMU. His research emphasizes developing statistical tools for observational studies, clinical trials, and meta-analytic frameworks, particularly in neurology, mental health, and public policy contexts. Notable contributions include analyzing the impact of media on youth suicide rates, improving aphasia classification through automated speech analysis, and evaluating highway safety through driver health data. Education: Ph.D. in Biostatistics, University of Michigan Affiliations: Adjunct Professor at University of Pittsburgh, Member of National Academy of Sciences’ committees Professional Service: Data and safety monitoring boards for NIH/VA studies, co-chair of Federal Motor Carrier Safety Administration review panels His awards include CMU’s Doherty Award for Education, Ryan Teaching Award, and E. Dunlop Smith Award for teaching excellence. His work bridges theoretical statistics with real-world applications, particularly in interdisciplinary collaborations across medicine, psychology, and public policy. Greenhouse’s recent articles highlight trends in leveraging large datasets for clinical insights (e.g., aphasiaBank), re-evaluating environmental and behavioral health associations, and advancing causal inference methods. His interdisciplinary approach ensures statistical rigor addresses societal challenges, from suicide prevention to highway safety.

Fernando Zapateroمشاهده پروفایل

استاد

• Finance
• Asset Pricing
• Behavioral Economics
• +۳ مورد دیگر

Fernando Zapatero is the Richard D. Cohen Professor in Finance at the Questrom School of Business , Boston University. His office is located in the Rafik B. Hariri Building at 595 Commonwealth Avenue, Boston, MA 02215. Email: fzapa@bu.edu His research focuses on asset pricing , risk aversion , and investment behavior , with recent work exploring the economic foundations of demand for skewness , climate finance , and technological transitions . He has extensively studied the effects of heterogeneous investment horizons and convex incentives on financial markets. Selected Research Themes: Asset Pricing Implications of Behavioral Biases Climate Finance and Technological Innovation Dynamic Portfolio Allocation Options Market Anomalies Government Grants in Deep Tech Commercialization

Albert S. Berahasمشاهده پروفایل

استادیار

• Nonlinear Optimization
• Machine Learning Optimization
• Stochastic Optimization
• +۵ مورد دیگر

Albert S. Berahas is an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan's College of Engineering. He joined the university in 2020 after completing postdoctoral positions at Lehigh University (2018-2020) and Northwestern University (2018). He holds a PhD in Engineering Sciences and Applied Mathematics from Northwestern University (2018), an MS in Applied Mathematics from Northwestern (2012), and a BSE in Operations Research and Industrial Engineering from Cornell University (2009). His research focuses on designing, developing, analyzing, and implementing algorithms for solving large-scale nonlinear optimization problems. His work spans multiple sub-fields including constrained optimization, optimization for machine learning, stochastic optimization, derivative-free optimization, and decentralized optimization. He is affiliated with the Michigan Institute for Data Science (MIDAS), the Michigan Institute for Computational Discovery and Engineering (MICDE), and the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM). Berahas has received numerous honors including the Charles Broyden Prize (2025), the Air Force Office of Scientific Research Young Investigator Program award (2025), the IISE Operations Research Division Teaching Award (2024), and the North Campus Dean's MLK Spirit Award for Community Building & Impact (2024). His recent publications demonstrate strong activity in developing novel optimization frameworks with theoretical guarantees for challenging problem settings. His research has been supported by significant grants including from the Office of Naval Research (ONR) and the Air Force Office of Scientific Research. He actively mentors PhD students and has successfully advised Jiahao Shi, who defended his dissertation in March 2025 and joined Amazon. Berahas is also engaged in community outreach, particularly through initiatives like Engage Detroit that aim to empower Detroit's next generation of engineers.

• Causal Analysis
• Econometrics
• Machine Learning
• +۷ مورد دیگر

Martin Huber is Professor of Applied Econometrics and Policy Evaluation at the University of Fribourg, Switzerland, within the Faculty of Management, Economics and Social Sciences, Department of Economics. He leads the Chair of Applied Econometrics and maintains an active research profile with numerous publications in top economics and statistics journals. His work bridges theoretical econometrics with practical policy applications across multiple domains including labor, health, and education economics. Professor Huber earned his Ph.D. in Economics and Finance in 2010 and served as Assistant Professor at the University of St. Gallen until 2014. He has conducted research stays at Harvard University (2011/2012) and the University of Sydney (2014 and 2019), establishing an international research network. His academic affiliations include the Committee for Econometrics of the Verein für Socialpolitik, Global Labor Organization, Soda Labs (Monash Business School), and Centre for European Economic Research (ZEW) Mannheim. Huber's research focuses on data-based causal analysis , machine learning applications in economics , and policy evaluation methods . He specializes in developing and applying statistical and econometric methods for measuring causal effects, with particular emphasis on semi- and nonparametric microeconometrics. His work spans labor economics (gender occupational segregation, maternal labor supply), health economics, education policy, and competition policy (bid-rigging cartels detection). His recent publications (2023-2025) demonstrate a clear trajectory toward integrating machine learning techniques with traditional econometric methods for causal inference. This includes developing frameworks for causal discovery, improving difference-in-differences methods with machine learning, and creating novel approaches for detecting collusion in markets. His 2023 book "Causal Analysis: Impact Evaluation and Causal Machine Learning with Applications in R" (MIT Press) has become a key reference in the field. As an active researcher, Professor Huber directs several research projects including experimental evaluations of gender occupational segregation in the Swiss apprenticeship market. His work combines theoretical rigor with practical policy relevance, often employing experimental and quasi-experimental methods to address questions of causal mechanisms in social and economic phenomena. Through his Chair of Applied Econometrics, Huber supervises Ph.D. students and maintains an active research group focused on advancing causal inference methodologies. His work has significant implications for evidence-based policymaking across multiple sectors, particularly in evaluating the effectiveness of social programs and economic policies.

• Hydrogen fuel
• Combustion engineering
• Alternative energy systems
• +۷ مورد دیگر

Dr Stathis Tingas is a Lecturer at Edinburgh Napier University's School of Computing Engineering and the Built Environment. His research focuses on hydrogen fuel systems, combustion engineering, and sustainable transportation technologies. With numerous publications in high-impact journals and conference proceedings, Dr Tingas has established himself as a significant contributor to the field of alternative energy systems. Dr Tingas' research interests center on hydrogen and ammonia as alternative fuels for transportation, with particular emphasis on combustion characteristics, engine performance, and emissions control. His work spans theoretical modeling, computational analysis, and practical applications for decarbonizing various transportation sectors including aviation, heavy-duty vehicles, and maritime transport. Recent publications demonstrate his focus on hybrid propulsion systems combining fuel cells with traditional engine technologies. Dr Tingas' publication record shows consistent productivity with research outputs spanning from fundamental combustion science to applied engineering solutions. His work often employs computational singular perturbation techniques for analyzing complex combustion phenomena, with recent focus shifting toward practical applications of hydrogen and ammonia fuels in real-world engine systems. The trend in his publications indicates growing emphasis on zero-emission transportation solutions aligned with net-zero targets. Dr Tingas serves as a second supervisor for PhD students, including Richard Wallace who is working on subsurface hydrogen storage simulation. He has successfully secured multiple research grants from UK government bodies including the Department for Science, Innovation & Technology, Scottish Government, and the Royal Society of Edinburgh, with projects totaling over £500,000 in funding. His current research portfolio includes projects focused on accelerating clean energy technology development, creating sustainable cities, advancing electromobility, and developing zero-carbon hydrogen engines for heavy transport applications. These projects demonstrate his commitment to addressing practical challenges in the transition to sustainable energy systems.

Oskari Ville Pakariمشاهده پروفایل

مدرس

• Nuclear Engineering
• Reactor Physics
• Radiation Detection
• +۳ مورد دیگر

Oskari Ville Pakari is a Lecturer at the School of Basic Sciences, École polytechnique fédérale de Lausanne (EPFL), affiliated with both the Institute of Physics (IPHYS) and the Swiss Plasma Center (SPH-ENS). He contributes to teaching and research, particularly in reactor physics and radiation detection. His research focuses on nuclear reactor diagnostics , gamma noise analysis , and neutron spectroscopy . He actively develops mixed reality visualization tools for radiation detection data and participates in the European CORTEX project for reactor monitoring. Selected publications highlight his work in gamma-ray imaging , neutron noise simulations , and detector system validation using advanced statistical methods like bootstrapping and Welch's technique. Teaching activities include courses on Radiation biology, protection, and applications Radiation and reactor experiments He advises PhD student Saliba Michel and collaborates with international institutions such as CEA, KIT, and LRS (Laboratory of Reactor Physics and Systems Behaviour) at EPFL.

• Economic Development
• Regional Economics
• Applied Econometrics
• +۵ مورد دیگر

Marco Letta is a Tenure-Track Assistant Professor at the Department of Social and Economic Sciences , Sapienza University of Rome. His research focuses on economic development , regional economics , policy evaluation , and applied econometrics , with a strong emphasis on climate change impacts, food security, and machine learning applications in economic policy. University: Sapienza University of Rome Department: Department of Social and Economic Sciences Email: marco.letta@uniroma1.it His recent work explores the climate migration nexus , household resilience , and policy targeting , often leveraging machine learning and empirical econometric methods . Publications span topics such as local inequalities during the COVID-19 crisis , temperature shocks in rural Tanzania , and machine learning applications in state aid regulation . Notable trends in his research include: Integration of machine learning with traditional econometric techniques Focus on climate resilience and migration patterns Analysis of policy impacts in developing economies Investigation of local mortality estimates during global crises Development of cross-country empirical frameworks Current projects include assessing agrifood system vulnerabilities and refining counterfactual policy evaluation methodologies.

• Research Synthesis Methods
• Meta-Analysis
• Evidence Gap Maps
• +۱۲ مورد دیگر

Prof. Dr. Michael Bosnjak leads the Department for Psychological Research Methods at the University of Trier, Germany, focusing on research synthesis methods, theory-driven machine learning, survey methodology, and experimental designs applied to personality psychology (HEXACO model), consumer behavior, and public health. His team includes Dr. Henning Silber (GESIS), Dr. Bernd Weiß (GESIS), and international collaborators at Utrecht University. Affiliation: University of Trier (Department of Psychology) Editorial Roles: Zeitschrift für Psychologie (Editorial Board), Social Science Computer Review (Associate Editor), Frontiers in Psychology (Review Editorial Board) Grants: DFG SFB 884 (co-applicant), DFG Project PaCO (2019-2024, principle investigator), BMBF-funded GESIS Panel Campus His recent publications analyze panel conditioning effects in longitudinal studies, e-commerce privacy dynamics, personality-trait interactions, and psychosis proneness measurement. Scientific awards include the 2016 BMBF infrastructure grant, 2011 Isaac Manasseh Meyer Fellowship, and 2003 Karin Islinger Award. Current projects address data quality in probability-based and opt-in panels, with experimental designs across eight groups testing measurement error mechanisms. He serves as a co-editor for multiple special issues on survey methodology and tourism psychology.