جست‌وجوی استاد و پژوهشگر

• Experimental Economics
• Healthcare Economics
• Game Theory
• +۳ مورد دیگر

Katri Sieberg is a Professor at Tampere University's Faculty of Social Sciences, Department of History, Philosophy and Literary Studies, specializing in North American Studies and leading the Public Policy Analysis Master's Program. She holds a Ph.D. from New York University (1998), with prior studies at Northwestern University (BA, 1990), California Institute of Technology (MS, 1992), and visiting scholarships at the University of Chicago and University of North Carolina. Her research focuses on experimental economics, healthcare economics, game theory, and social choice theory. Key areas include exploring theoretical models through experiments, analyzing healthcare system efficiencies, voting mechanisms' impacts on outcomes, and criminal policy frameworks. Recent work includes studies on basic income experiments, conflict bargaining models, and healthcare payment systems. Major grants include the Yrjö Jahnsson Foundation (2022, €8,000) and Tampere University's Sustainable Welfare Systems Seed Funding (2022, €20,000). She has also led the American Studies Workshop through grants totaling over €600,000 from Jane and Aatos Erkko Foundation. A U.S. National Science Foundation grant (2020s) supported collaborative research on conflict bargaining models. Her work spans academic leadership, including organizing the Institutions in Context workshop series and contributing to interdisciplinary policy analysis. Research outputs emphasize experimental methodologies and their applications in understanding complex social, economic, and political systems.

• Data Mining
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Jyrki Nummenmaa is a Professor at the Faculty of Information Technology and Communication Sciences, Department of Computing Sciences at Tampere University. He holds an ORCID ID (0000-0002-7476-7840) and can be contacted via jyrki.nummenmaa@tuni.fi. His research focuses on data mining, machine learning, natural language processing, and database systems. Key research interests include computational methods for analyzing political language, RDF graph processing, ethical AI security systems, and sequential pattern mining. He has collaborated extensively with researchers such as Peltonen J., Zimina E., and Duan L. Recent publications (2022–2024) emphasize interdisciplinary applications like parliamentary discourse analysis and transparent question-answering systems. He has edited conference proceedings and contributed to over 100 peer-reviewed works since 1992. His work spans theoretical advancements (e.g., fair neighbor embeddings, nonparametric graph embeddings) and applied solutions (e.g., bus delay analysis, health-e-living simulations). Notable projects include TraQuLA for RDF querying and PiHVI for forum posting analysis.

Yingni Guoمشاهده پروفایل

دانشیار مهمان

• Economics
• Game Theory
• Information Economics
• +۵ مورد دیگر

Yingni Guo is a Visiting Associate Professor of Economics at Duke University, affiliated with the Trinity College of Arts & Sciences. She holds a Ph.D. from Yale University (2014). Her research focuses on game theory, mechanism design, and information economics with applications to regulatory policy, optimal disclosure strategies, and strategic interactions in economic systems. Recent work includes studies on robust monopoly regulation, regret-minimizing project selection, and optimal information transmission in voting contexts. Selected publications highlight contributions to Journal of Economic Theory , American Economic Review , and Econometrica . Notable topics include Bayesian persuasion, principal-agent problems, and cooperative game theory. Guo teaches graduate-level courses like ECON 885 (Special Topics in Economic Theory) and ECON 905 (Microeconomic Theory Workshop), emphasizing advanced theoretical frameworks. Her work often addresses real-world challenges such as designing robust regulatory policies and mitigating strategic misbehavior in economic systems.

• Machine Learning
• Neural Networks
• Stochastic Processes
• +۳ مورد دیگر

Ella Tamir is a Visiting Professor at the Department of Computer Science , School of Science , University of Helsinki. She concurrently holds a Doctoral Student position. Her research focuses on stochastic processes, neural networks, and sequential learning. Education: Master's degree in Natural Sciences, University of Helsinki (2017) Bachelor's degree in Natural Sciences, University of Helsinki (2016) Research Interests: She explores stochastic differential equations, function-space representations, and diffusion processes. Her work emphasizes applications in neural networks, data generation, and sequential learning. Recent studies involve diffusion generative models for particle smoothing and sparse parameterization techniques. Research Output: Her recent publications address topics like function-space neural networks, diffusion bridges for time series, and scalable inference methods. These contributions highlight advancements in both theoretical and applied machine learning domains. Grants & Advising: No specific grants or advisees are listed in the provided materials. Labs/Teams: No lab affiliations or team collaborations are explicitly mentioned.

Rajesh Manchandaمشاهده پروفایل

استاد

• Consumer Behavior
• Sustainability Marketing
• Social Marketing
• +۳ مورد دیگر

Rajesh Manchanda is a Professor of Marketing at the Asper School of Business, University of Manitoba, and holds the title of The Associates Fellow in Sustainability. He has been affiliated with the university since 1997. His research focuses on two primary areas: the role of negative affect (e.g., guilt, embarrassment) in consumer behavior and sustainability/social marketing, including alternative frameworks to capitalism and environmental/social issues from consumer and organizational perspectives. He teaches sustainability, social marketing, and integrated marketing communications at both undergraduate and graduate levels (MBA and Ph.D.). Dr. Manchanda’s educational background includes a Ph.D. and M.S. from the University of Illinois at Urbana-Champaign, and an MBA and B.Com from the University of Bombay. His industry experience includes roles at Kellogg Company, Procter & Gamble, and J. Walter Thompson Advertising Agency. His research has been published in leading journals such as the Journal of Consumer Research and Journal of Consumer Psychology. His research trends emphasize interdisciplinary approaches, blending consumer psychology with sustainability, and exploring how emotions and ethical frameworks shape market behaviors. Articles often address contemporary challenges like data privacy, climate communication, and culturally rooted marketing strategies.

Ehsan Forootanمشاهده پروفایل

استاد

• Geodesy
• Satellite Gravity
• Hydrology
• +۷ مورد دیگر

Ehsan Forootan is a Professor of Geodesy and Earth Observation at Aalborg University, Denmark. He holds a PhD in Geodesy from the University of Bonn and has held academic positions at Cardiff University, University of Hohenheim, and Robert Bosch GmbH. His research focuses on applying satellite geodetic techniques (GNSS, satellite gravity, altimetry) to monitor Earth System processes, including mass redistribution, hydrological cycles, and climate change impacts. He leads projects on flood awareness systems, digital twin Earth hydrology, and data assimilation frameworks. Forootan serves as vice-chair of the IAG's Sub-Commission 4.3 (Atmosphere Remote Sensing) and editor for Remote Sensing journals. Education: B.Sc. Civil-Surveying Engineering (Khaje Nasir Technical University, 2006), M.Sc. Geodesy-Hydrography (University of Tehran, 2008), PhD in Geodesy (University of Bonn, 2014). Postdoctoral fellowships include Curtin University and German Aerospace Center (DLR). Research interests include geodetic data assimilation, satellite remote sensing applications, and Bayesian methods for hydrological modeling. His work addresses UN SDGs related to climate action, water sustainability, and environmental monitoring. Key contributions include frameworks for GRACE/GRACE-FO data integration into hydrological models and thermospheric neutral density forecasting. Awards: ABC/J Young Academic Award (2015). Active in research networks (ESA, NASA) and editorial roles (Geodinamica Acta, Nature Geoscience). Projects include Space-based Flood Awareness System for Africa (SFAS) and Digital Twin Earth Hydrology initiatives.

Stuart Medleyمشاهده پروفایل

دانشیار

• Graphic Design
• Service Design
• Visual Communication
• +۴ مورد دیگر

Associate Professor Stuart Medley is an Honorary Lecturer in the School of Arts and Humanities at Edith Cowan University (ECU). He holds a Bachelor of Arts from Western Australian Institute of Technology and a PhD from ECU (2009). His primary research focuses on deliberate communication through visual mediums, including comics, graphic design, and service design. Medley is a co-founder and Chair of the Perth Comic Arts Festival and a founding partner of Hidden Shoal Recordings, a critically acclaimed record label. His professional affiliations include membership in the Australian Graphic Design Association (since 2022) and the Design Institute of Australia. He has received national and international recognition, including the DesignBoom Korea award (2010). Medley’s work spans academic research, creative projects, and industry collaborations, emphasizing the intersection of design, communication, and societal impact. Research interests include visual rhetoric in AI design, service design methodologies, and the application of comics in research and law. He has led or contributed to major grants, such as the 'Diagnosing Innovation' project (2021–2024) and the WA Healthy Children Program (2013–2022). Medley actively supervises doctoral and master’s students, focusing on topics like computational thinking visualization, graphic design significance, and disaster management interfaces. Key creative outputs include the book The Picture in Design (2012) and exhibitions like Vox Caldus (2014) and Becoming Catalogue (2013). His research bridges academic rigor with practical design solutions, addressing challenges in healthcare, disaster communication, and cultural representation.

Peter Lynnمشاهده پروفایل

استاد

• Survey Methodology
• Longitudinal Surveys
• Sampling Techniques
• +۴ مورد دیگر

Prof. Peter Lynn is a Professor at the University of Essex, serving as Director of Survey Futures and Chair of the European Social Survey Sampling and Weighting Panel. He is also the Associate Director for Methodology at Understanding Society. His research focuses on survey methodology, particularly longitudinal surveys, emphasizing sampling, weighting, non-response strategies, adaptive design, and mixed-mode methodologies. He has led numerous studies on improving survey response rates, addressing attrition, and enhancing data quality through innovative approaches like targeted incentives and sequential mixed-mode designs. Key roles include leading Survey Futures, a research group advancing survey methodologies, and contributing to high-profile initiatives such as the European Social Survey and Understanding Society. His work addresses challenges in maintaining sample representativeness, tackling non-response bias, and leveraging technology for efficient data collection. Recent projects include evaluating early bird incentives, optimizing incentive strategies, and exploring the impact of text messaging on web survey participation. Publications span methodological innovations, including frameworks for exclusion risk mitigation, pandemic-related attrition analysis, and technical reports on weighting strategies. His research often bridges theory and practice, informing policy and survey design globally.

Adrianus van Duinمشاهده پروفایل

استاد

• Reactive Force Fields (ReaxFF)
• Catalysis
• Combustion Chemistry
• +۵ مورد دیگر

Adrianus van Duin is a Distinguished University Professor at Pennsylvania State University, holding joint appointments in Mechanical Engineering, Chemical Engineering, Engineering Science and Mechanics, Chemistry, and Materials Science and Engineering. He leads the Materials Computation Center and specializes in developing and applying the ReaxFF reactive force field for simulating chemical and physical interactions in materials and molecules. His work spans catalysis, combustion, nanomaterials, and environmental chemistry. Van Duin has held prestigious fellowships, including the Marie Curie and Royal Society awards, and has contributed over 70 publications. His research integrates computational methods with experimental validation, focusing on applications like fuel cells, corrosion, and energy storage. Education: Ph.D. in Chemistry, Delft University of Technology, Netherlands (1996) M.Sc./B.Sc. in Chemistry, University of Amsterdam, Netherlands (1986-1991) Research Interests: ReaxFF development and integration into computational tools like ADF/BAND Water/metal oxide interactions and surface catalysis Combustion chemistry and reaction mechanism derivation Material degradation and corrosion mechanisms Environmental applications, including carbon mineralization Recent Trends in Articles: Recent work emphasizes ReaxFF applications in 2D materials (e.g., graphene, MoS₂), energy systems (hydrogen storage, batteries), and environmental remediation (PFAS removal). Simulations frequently address interfacial chemistry and phase transitions under extreme conditions. Awards: Marie Curie Research Fellowship (1997-1999) Royal Society Fellowship (1999-2002) Named Distinguished University Professor at Penn State Grants & Labs: Leads the van Duin Group, collaborating with over 80 academic institutions globally. Active in NSF-funded initiatives and industry partnerships (e.g., SCM, NASA/AMES). Current projects include ReaxFF workshops, code distribution, and experimental-computational synergy in material design. Labs/Teams: Directs the Materials Computation Center and oversees interdisciplinary collaborations across departments at Penn State.

• Artificial Intelligence
• Machine Learning
• Multi-agent Systems
• +۶ مورد دیگر

Leandro Soriano Marcolino is a Lecturer (Assistant Professor) in Data Engineering at Lancaster University's Computing and Communications Department. He holds a PhD from the University of Southern California (USC), advised by Milind Tambe, and completed his master's in Japan under a Monbukagakusho Scholarship and his undergraduate studies at Universidade Federal de Minas Gerais in Brazil, where he graduated with top honors. His research focuses on multi-agent systems, machine learning, and robotics, emphasizing teamwork, online learning, and real-world applications in domains like swarm robotics, computer games, and architectural design. Education: PhD in Computer Science, University of Southern California (USC), 2016 Master's Degree in Japan (Monbukagakusho Scholarship) Undergraduate Degree in Computer Science, Universidade Federal de Minas Gerais (Brazil), 2009 Research Interests: Multi-agent teamwork and coordination Online learning and planning Robotics (swarm robotics, real-time strategy games) Applications in computer vision, social networks, and bioinformatics Highlights: Recipient of the Best Dissertation and Best Research Assistant Awards at USC (2016, 2015) Best Paper Nomination at AAMAS 2011 and Best Undergraduate Paper in Brazil (2009) Active in PhD supervision, mentoring students in AI, multi-agent systems, and robotics Co-founder of the COLAB research group at Lancaster University Labs/Teams: Lancaster Intelligent, Robotic and Autonomous Systems Centre (LIRAS), LIRA - Fundamentals, SCC (Data Science).

Geir Olve Storvikمشاهده پروفایل

استاد

• Data Science
• Computational Statistics
• Bayesian Hierarchical Modelling
• +۵ مورد دیگر

Geir Olve Storvik is a Professor in Statistics and Data Science at the University of Oslo. His research focuses on computational statistics, Bayesian hierarchical modeling, Monte Carlo methods, spatio-temporal modeling, and dynamical processes. He has made significant contributions to Bayesian machine learning and its applications in biological and environmental domains. University: University of Oslo Department: Statistics and Data Science Academic Rank: Professor Storvik's research spans interdisciplinary applications of Bayesian methods in fields such as neural networks, DNA methylation, and infectious disease modeling. His recent work includes sparse Bayesian neural networks and sequential Monte Carlo approaches for epidemiology. Key projects include Bayesian methods in machine learning and BigInsight Statistical and machine learning methods for sensor data . He serves as an advisor to PhD students like Aliaksandr Hubin and Ivar Grytten, with completed theses in graph-based genomics and Bayesian variable selection. His work appears in journals like Transactions on Machine Learning Research , The Journal of Artificial Intelligence Research , and Journal of the Royal Statistical Society , covering topics from model sparsity to ecological forecasting.

Daniel Büscherمشاهده پروفایل

پژوهشگر

• Autonomous Robot Navigation
• Deep Learning
• Computer Vision
• +۱ مورد دیگر

Daniel Büscher is a post-doctoral researcher at the Robot Learning Lab of the University of Freiburg. His work focuses on autonomous robot navigation , deep learning , and probabilistic state estimation . He has contributed to robotics research through projects involving mobile manipulation and audio-visual navigation . Research Interests : Autonomous navigation, deep learning, computer vision, probabilistic estimation Teaching : Lecturer and tutor for Introduction to Mobile Robotics and Robot Mapping (2017–2023) Publication Trends : Recent work emphasizes robot design optimization , language-grounded scene graphs , and uncertainty-aware perception . His research connects reinforcement learning with mobile manipulation and cross-domain navigation challenges.

John Perezمشاهده پروفایل

استادیار

• Animation
• Screenwriting
• Comic Book Narrative
• +۲ مورد دیگر

John Perez is an Assistant Professor at the Dodge College of Film and Media Arts at Chapman University, specializing in Animation & Visual Effects. He holds a BFA in Animation from Laguna College of Art + Design and an MFA from the John Wells Division of Writing for Screen & Television at USC School of Cinematic Arts. Educated at Laguna College of Art + Design (BFA) and University of Southern California (MFA) Former storyboard artist/animator at Obsidian Entertainment, contributing to projects like South Park: The Stick of Truth Published comic book author and Writers Guild of America West associate-caucus member His research and creative work focuses on narrative design in animation, Latinx cultural representation in visual media, and the intersection of comics with speculative fiction. He has contributed to publications such as MAÑANA: Latinx Comics From The 25th Century and created a comic series at Action Lab Comics. Key themes in his work include visual storytelling techniques, gaming cinematics, and future-oriented narrative frameworks. Awards include the Fogelman-Rodriguez Fellowship during his MFA studies.

• Theoretical Computer Science
• Machine Learning
• Algorithms
• +۴ مورد دیگر

Nicholas J. A. Harvey is a Professor of Computer Science at the University of British Columbia. His research spans multiple areas of theoretical computer science with significant contributions to algorithms, machine learning theory, and network coding. Harvey's research focuses on the theoretical foundations of computer science with particular emphasis on: Theory and analysis of randomized algorithms Machine learning theory, including online learning and neural networks Network coding and information theory Combinatorial optimization and graph algorithms High-dimensional probability and statistics His work combines deep mathematical insights with practical applications in computer systems and networking. Analysis of Harvey's recent publications (2022-2025) reveals a strong focus on theoretical aspects of machine learning and optimization. His work spans continuous prediction with experts' advice, tight analyses of optimization algorithms like subgradient descent, and fundamental questions in randomized algorithms. A significant portion of his recent research addresses challenges in high-dimensional statistics, privacy-preserving estimation, and graph neural networks. His publications demonstrate a consistent pattern of addressing foundational theoretical questions with implications for practical machine learning systems. Harvey has maintained a strong publication record with an h-index of 35 and over 6,000 citations according to Google Scholar metrics. His influential papers include 'SkipNet: A Scalable Overlay Network with Practical Locality Properties' (2003), 'On the capacity of information networks' (2006), and 'Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks' (2019). Harvey has supervised numerous graduate students and postdoctoral researchers, contributing to the development of the next generation of theoretical computer scientists. His research has been supported by various grants from funding agencies including the Natural Sciences and Engineering Research Council of Canada (NSERC) and collaborations with industry partners. While specific details about laboratory facilities are not available in the provided information, Professor Harvey appears to be part of the theoretical computer science research group at the University of British Columbia, collaborating with researchers across multiple institutions on fundamental problems in algorithms and machine learning theory.

Suzanne H. Mitchellمشاهده پروفایل

استاد

• Risky and impulsive decision-making
• Alcohol use disorder
• Neurobiology of choice
• +۲ مورد دیگر

Suzanne H. Mitchell is a tenured Professor at Oregon Health & Science University (OHSU) in the Department of Behavioral Neuroscience, with secondary appointments in Psychiatry and the Oregon Institute for Occupational Health Sciences. She holds a B.Sc. and M.Sc. from the University of Hull, England, and a Ph.D. from SUNY-Stony Brook, USA, where her dissertation examined behavioral economics in rodent foraging decisions. Education: B.Sc./M.Sc. (Hull), Ph.D. (SUNY-Stony Brook) Secondary Appointments: Psychiatry, Oregon Institute for Occupational Health Sciences Her research spans behavioral economics, impulsivity neuroscience, and addiction models , focusing on: Decision-making in substance users Delay discounting mechanisms Energetic cost-benefit analysis Translational rodent-human studies Behavioral genetics of impulsivity Recent publications show expertise in fMRI, behavioral paradigms (e.g., patch depletion tasks) , and genetic models applied to: Alcohol use disorder neurobiology Chronic pain decision-making Neuroplasticity in enriched environments STEM education behavioral influences Scientific contributions include: NIH-funded grants (NHLBI, NIAAA, NIDA, NIMH) Awards for education and mentoring Leadership in behavioral economics societies She collaborates with researchers like Abraham A. Palmer and Jerry B. Richards, applying human/animal models to clinical populations while maintaining active NIH study section participation.