جستجوی استاد راهنمای دانشگاهی

Pedro Fidelmanمشاهده پروفایل

دانشیار

• Environmental Policy
• Governance and Institutional Analysis
• Climate Change Adaptation
• +۴ مورد دیگر

Associate Professor Pedro Fidelman is an environmental policy scholar at The University of Queensland, affiliated with the Centre for Policy Futures and the Centre for Marine Science. He holds a PhD from the University of Wollongong and specializes in environmental governance, policy innovation, and institutional analysis. His work focuses on global environmental challenges, including climate change adaptation, marine conservation, and the governance of emerging technologies. Fidelman has contributed to major international initiatives such as the UN Global Environment Outlook and the Reef Restoration and Adaptation Program. Affiliations: Centre for Policy Futures (Principal Research Fellow), ARC Research Hub for Sustainable Crop Protection, Queensland Alliance for Agriculture and Food Innovation. Education: Doctor of Philosophy (University of Wollongong), MSc and BSc (Brazil). His research addresses governance of marine and coastal systems, policy implications of novel technologies, and institutional resilience to environmental change. He leads strategic projects in the Social and Environmental Sustainability theme at UQ, including contributions to the Blue Economy Cooperative Research Centre and the Reef Restoration Program. Fidelman has supervised over 10 PhD/Master’s students and teaches courses on public policy and sustainability. Recent articles highlight his work on blue economy policy networks, gene drive governance, and adaptive coastal management frameworks. He co-authored reports on regulatory challenges for coral reef interventions and policy solutions for migratory shorebird conservation. Fidelman’s work bridges academic research with practical policy outcomes, emphasizing stakeholder collaboration and systemic institutional innovation.

• Behavioral Neuroscience
• Cognitive Neuroscience
• Learning and Memory
• +۴ مورد دیگر

Dr Dominic Tran is an ARC DECRA Research Fellow at the School of Psychology, University of Sydney. His research focuses on behavioral and cognitive neuroscience, particularly in learning, memory, and cognition. He employs neurophysiological techniques such as transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to explore the neural bases of behavior. Current research interests include understanding how past experiences shape cognitive processes and motor control. Tran’s work has been supported by significant grants, including the Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) (2022) for investigating response inhibition mechanisms, a School of Psychology Booster Grant for studying predictive coding, and a Faculty of Science Seed Funding grant (2016) on diet and spatial ability. His research bridges experimental psychology, neuroscience, and translational health science. Key themes include the interplay between brain activity and behavior, with a focus on executive control, motor inhibition, and the impact of dietary factors on cognitive function. His publications span topics like sensory-motor prediction, neural inhibition mechanisms, and the neurophysiological underpinnings of decision-making. Grants: ARC DECRA: Stop it: Learning response inhibition (2022) School of Psychology Booster Grant: Testing predictive coding (2022) Faculty of Science Seed Funding: Diet impacts on spatial ability (2016) Awards: Australian Research Council DECRA Fellowship (2022) Tran’s lab focuses on translational neuroscience, integrating behavioral experiments with advanced neuroimaging to address fundamental questions in cognitive neuroscience and clinical applications.

• Sustainable Building Practices
• Facility Management Strategy
• Workplace Design and Ergonomics
• +۳ مورد دیگر

Eunhwa Yang is an Associate Professor and Curriculum Committee Chair at the School of Building Construction, Georgia Institute of Technology. She holds a Ph.D. in Human Behavior and Design from Cornell University and an MS in Building Construction from Georgia Tech. Her research focuses on the interplay between built environments and human outcomes, employing Bronfenbrenner’s ecological systems theory to study workplaces, campuses, and homes. Key areas include sustainable building practices, facility management optimization, and aging-in-place strategies for individuals with mild cognitive impairment. As an advocate for innovative teaching methods, Dr. Yang has developed facility management courses using active learning and service learning approaches. She has led workshops on pedagogical strategies at GT’s Center for Teaching and Learning and Cornell’s Center for Teaching Excellence. Professional affiliations include the International Facility Management Association (IFMA) and CoreNet Global, where she has received young researcher awards and fellowships. Her recent work emphasizes data-driven solutions for energy performance contracting, hybrid workspaces, and inclusive housing designs. The Workplace Ecology Lab under her direction explores environmental factors influencing sleep health, workplace safety, and aging-in-place technologies. Over 15 years of grant-funded research has produced impactful studies on green leasing, building lifecycle analysis, and multi-stakeholder decision-making in urban transformation projects. Awards: IFMA Fellowships, IAPS Workshop Grant Grants: CoreNet Global Academic Challenges, IAPS sponsored projects Labs: Workplace Ecology Lab at Georgia Tech School of Building Construction Dr. Yang’s advisory work supports facility managers, corporate real estate directors, and designers in optimizing space utilization through evidence-based strategies. Her research bridges environmental science, architectural design, and human behavior studies to create healthier, more equitable built environments.

• Circular Economy
• Sustainable Urban Development
• Climate Resilience
• +۷ مورد دیگر

Sara Torabi Moghadam is an Associate Professor in the Interuniversity Department of Regional and Urban Studies and Planning (DIST) at the Polytechnic University of Turin. She serves as a Junior project manager and member of the Interdepartmental Center R3C - Responsible Risk Resilience Centre. Her research focuses on circular economy in built environments , smart resilient urban development , and participatory approaches . She teaches courses in PhD programs on Urban and Regional Development and Master's programs in Urban Planning , emphasizing ESG frameworks and decision-making for sustainable goals. Research Projects: Lead investigator of the EU-funded GREEN-INC project (2024-2026) addressing inclusive climate actions for nature-based solutions. Responsible for a PhD student funding project (2023-2026) in Urban and Regional Development. Teaching and Academic Roles: Member of the College of Architecture and Design and College of Planning and Design at Politecnico di Torino. Core instructor for courses like Decision Making for Sustainable Development Goals and Post-Carbon Sustainable Communities . Research Themes: Her work integrates GIS-based spatial analysis , multi-criteria decision tools , and participatory methodologies to address urban sustainability challenges. Key areas include energy efficiency in cities, nature-based solutions (NBS), and resilience against climate change. She emphasizes ESG frameworks and justice-oriented planning to ensure equitable urban transitions. Supervised Students: Guiding five PhD students in topics like climate resilience, NBS effectiveness, and sustainable urban scenarios. Labs/Teams: Active in the R3C Center, focusing on risk management and resilience strategies for urban systems. Collaborates with interdisciplinary teams on projects like the SCORE H2020 initiative for energy communities.

• Industrial Infrastructure Vulnerability
• Multi-Hazard Risk Assessment
• Resilience Engineering
• +۳ مورد دیگر

David Javier Castro Rodriguez is a Research Fellow at the Department of Applied Science and Technology (DISAT) of the Polytechnic University of Turin. His research focuses on industrial infrastructure vulnerability assessment, multi-hazard risk analysis, and resilience engineering. He holds a doctoral degree from the same institution, specializing in multi-hazard frameworks for infrastructure resilience. His work integrates advanced methodologies for evaluating vulnerabilities in critical infrastructures such as wastewater treatment plants and industrial facilities. Key contributions include developing multi-risk indicators (e.g., NaTech vulnerability indicators) and multi-scale hazard mapping techniques. Recent publications emphasize territorial resilience through comprehensive risk modeling approaches. Dr. Castro Rodriguez frequently collaborates with researchers like Antonello Barresi and Micaela Demichela on projects addressing environmental safety and disaster risk management. His research bridges civil engineering, environmental science, and policy implementation to enhance societal preparedness against compound hazards.

Oleksiy Klymenkoمشاهده پروفایل

مدرس ارشد

• Model-Based Process Design
• Mathematical Modelling in Natural Sciences
• Uncertainty Quantification
• +۳ مورد دیگر

Dr. Oleksiy Klymenko is a Senior Lecturer in Chemical Process Engineering at the University of Surrey, affiliated with the School of Chemistry and Chemical Engineering and the Institute for Sustainability. He holds a DPhil and specializes in model-based process design, mathematical modeling, and uncertainty quantification. Research Interests: Model-based design and optimization of process systems Mathematical modeling in natural and life sciences Uncertainty quantification, particularly global sensitivity analysis Teaching: Module leader for three M-level modules: ENGM071 Process and Energy Integration (MSc) ENGM214 Process Modelling and Simulation (MSc/Year 4 MEng) ENGM256 Technology, Business and Research Seminars (MSc/Year 4 MEng) Contributes to a Year 2 BEng/MEng module. Research Trends: Publications focus on antimicrobial technologies, energy systems optimization, and electrochemical simulations. Recent work includes 3D modeling of microbial dynamics, sustainable energy design, and the development of tools like KISSA software for electrochemical analysis. Advising & Grants: No explicit student advisees or grant details provided in texts. Research collaborations likely underpin his work in interdisciplinary areas like food safety and energy systems. Labs/Teams: Part of the Institute for Sustainability at Surrey, collaborating on projects aligning with sustainable development goals, particularly in energy and food systems.

David Carslawمشاهده پروفایل

استاد

• Environmental Science
• Atmospheric Chemistry
• Air Pollution Monitoring
• +۴ مورد دیگر

Professor David Carslaw is a leading academic in the Department of Chemistry at the University of York, specializing in urban air pollution, vehicle emissions, and receptor modeling. His research focuses on developing open-source tools (e.g., openair) and applying statistical techniques to quantify emissions and evaluate air quality interventions. Collaborations with institutions like Ricardo Energy & the Environment have advanced understanding of real-world vehicle emissions, particularly regarding NOx, ammonia, and temperature dependencies. His work has exposed critical gaps in national emission inventories and contributed to global air quality policy frameworks. Education details are not explicitly stated in the text, but his professional background indicates advanced academic training in atmospheric chemistry or environmental science. The openair project, funded by NERC, underscores his commitment to democratizing air quality data analysis through software development. Research interests include: (1) Urban air pollution dynamics, (2) Remote sensing of vehicle emissions, (3) Meteorological normalization for time series analysis, and (4) Source apportionment using statistical methods like bivariate polar plots and clustering. His team’s innovations, such as ammonia emission quantification and temperature-dependent NOx emissions, challenge conventional emission assumptions. Recent articles highlight advances in machine learning applications for air quality policy, hydrogen combustion impacts, and indoor-outdoor pollutant linkages. While no scientific awards are listed, his contributions have been widely adopted by the international air quality community. Grant activities include NERC funding for openair. Supervision of PhD students is implied through research group activities, though specific advisee names are not provided. The openair project and vehicle emission studies form core lab activities, supported by partnerships with industry and academic collaborators.

• Medical Informatics
• Machine Learning in Healthcare
• Predictive Modeling in Medicine
• +۳ مورد دیگر

Thomas Lasko is an Associate Professor holding dual appointments in the Department of Biomedical Informatics and the Department of Computer Science at Vanderbilt University. His work focuses on advancing machine learning and computational methods to address critical challenges in healthcare, particularly leveraging electronic health records (EHR) for disease prediction, risk stratification, and clinical decision-making. Lasko’s research spans areas such as predictive modeling for chronic diseases (e.g., COPD, systemic lupus erythematosus), multimodal data integration (e.g., imaging and EHR), and improving the generalizability of clinical models across healthcare institutions. His academic contributions emphasize scalable solutions for large-scale EHR analysis, including lightweight natural language processing (NLP) models for document classification and contrastive learning approaches for patient-level representation. Lasko has also pioneered methods for uncovering latent disease signatures using probabilistic independence and has developed tools like pyPheWAS for phenome-disease association studies. His work frequently intersects with clinical practice, aiming to translate algorithmic advancements into actionable clinical decision support systems. Lasko’s recent research trends highlight a focus on longitudinal data analysis, model calibration drift mitigation, and explainable AI (XAI) for enhancing trust in medical AI systems. While his articles emphasize technical innovation, they consistently ground methodologies in real-world healthcare challenges, such as optimizing lung cancer screening protocols and identifying comorbidity patterns in autoimmune diseases. Despite his prolific output, no formal scientific awards or student advising records are explicitly mentioned in the provided texts. He collaborates across disciplines, integrating expertise from computer science, biomedical informatics, and clinical medicine to tackle problems such as automated patient acuity determination and novel disease subtyping. Ongoing work includes refining multimodal fusion techniques for pulmonary nodule classification and developing synthetic data frameworks to improve model robustness in resource-limited settings.

Greg Ridgewayمشاهده پروفایل

استاد

• Criminology
• Statistics
• Data Science
• +۳ مورد دیگر

Greg Ridgeway serves as the Rebecca W. Bushnell Professor of Criminology at the University of Pennsylvania's School of Arts and Sciences, with a dual appointment in the Department of Statistics and Data Science. He holds multiple leadership roles including Co-director of the Data Driven Discovery Initiative and Co-editor-in-chief of the Journal of Quantitative Criminology. His affiliations span the Quattrone Center for the Fair Administration of Justice, Penn Injury Science Center, Center for Causal Inference, and Population Studies Center. His educational background includes a Ph.D. in Statistics from the University of Washington (1999), where his dissertation focused on Bayesian inference for massive datasets under advisors David Madigan and Thomas Richardson. Additional degrees include an M.S. in Statistics (1997) and B.S. in Statistics (1995) from the University of Washington and California Polytechnic State University respectively. Ridgeway's research centers on statistical methods for crime analysis and justice system improvement, with major contributions in police use-of-force analysis, racial profiling detection, and justice system benchmarking. His work bridges criminology and data science through innovative applications of propensity scoring, causal inference, and predictive modeling to real-world criminal justice challenges. He has developed methods implemented by police departments in Cincinnati, Los Angeles, and New York City, as well as Federal Public Defender Organizations. His 15 most recent publications demonstrate consistent focus on police behavior analysis, sentencing disparities, and environmental crime prevention. Key trends include the development of conditional likelihood models for officer shooting analysis, benchmarking systems for judicial accountability, and rigorous evaluation of place-based interventions like vacant lot remediation. His methodological contributions span criminology, statistics, and public health with strong emphasis on practical policy applications. Fellow of the American Society of Criminology (2025) Fellow of the Academy of Experimental Criminology (2024) Fellow of the American Statistical Association (2013) ASA Outstanding Statistical Application Award (2007) RAND Gold Medal Award (2007) 8 granted US patents in medical treatment hypothesis testing and resource pre-fetching Ridgeway has secured over $20 million in research funding from entities including Arnold Ventures, National Institute of Justice, and Neubauer Family Foundation. His advisory work includes directing the Master of Science in Criminology program and mentoring students through Penn's Graduate Groups. As former Acting Director of the National Institute of Justice (2013-2014), he led an 80-person agency with a $250M budget, implementing reforms like a $75M school safety research program. Current service includes chairing the American Statistical Association's Committee on Law and Justice Statistics. His leadership extends to directing RAND's Safety and Justice Program and Center on Quality Policing, where he managed 50-person teams and $10M in annual research. Current institutional roles include Co-director of the Data Driven Discovery Initiative, which he launched to develop data science for social good programming, seed grants, and a data science minor.

Alex Chohlas-Woodمشاهده پروفایل

استادیار

• Computational Social Science
• Public Policy
• Algorithmic Fairness
• +۳ مورد دیگر

Alex Chohlas-Wood is an Assistant Professor of Computational Social Science at New York University’s Steinhardt School of Culture, Education, and Human Development. His work bridges computational methods with public policy, focusing on algorithmic fairness, criminal justice reform, and equitable decision-making frameworks. He holds a Ph.D. in Computational Social Science from Stanford University, an M.S. in Applied Urban Science from NYU CUSP, and a B.A. in Studio Art from Carleton College. His research emphasizes practical applications of AI to reduce bias in legal systems, including prototyping algorithms to mitigate racial disparities in charging decisions and testing behavioral nudges to reduce incarceration rates. Supported by organizations like the MacArthur Foundation and Arnold Ventures, his work has directly influenced state and local policymaking. As faculty co-director of the Computational Policy Lab since 2018 and former director of analytics for the New York City Police Department, he leads interdisciplinary teams collaborating with government agencies to design evidence-based solutions. His publications span topics from equitable algorithm design to policing practices analysis.

Bram Droppersمشاهده پروفایل

پژوهشگر

• Climate Change
• Water Resource Management
• Hydrological Modeling
• +۴ مورد دیگر

Bram Droppers is a Researcher and ICT developer at the Department of Physical Geography, Utrecht University. His work focuses on modeling hydrological systems to address water scarcity, climate adaptation, and sustainable agriculture. He holds a PhD in Earth and Environmental Sciences from Wageningen University (2022), with prior degrees from the same institution (BSc 2014, MSc 2017). His research emphasizes large-scale hydrological models like PCR-GLOBWB and VIC, integrating them with agricultural models and applying deep learning techniques to improve accuracy and computational efficiency. His expertise spans Human Impact on Global Water Systems, Integrated Water Management, and Climate Modeling. Key themes include the interplay between socio-economic factors, climate change, and water resources. He has developed frameworks to assess water constraints on crop production and pioneered high-resolution global hydrological modeling approaches. Recent work explores deep-learning surrogates for process-based models to enhance scalability. Publications highlight analyses of water scarcity hotspots in Pakistan, California, and global basins, alongside model improvements for irrigation management and lake system dynamics. His research supports Sustainable Development Goals, particularly in balancing agricultural productivity with ecosystem protection. Current projects aim to refine global hydrological models for hyper-resolution applications and multi-model ensemble approaches. Bram’s career includes roles as ICT Manager and developer, ensuring technical infrastructure supports his research. He has secured grants through Wageningen’s WIMEK institute and collaborates internationally on initiatives like the ISIMIP Lake Sector. His work bridges computational innovation with environmental sustainability, addressing critical water challenges at planetary scales.

Patrick Witteمشاهده پروفایل

دانشیار

• Spatial Planning
• Infrastructure Development
• Smart Cities
• +۴ مورد دیگر

Dr. Patrick Witte is an Associate Professor in Spatial Planning at Utrecht University's Faculty of Geosciences, specializing in integrated spatial planning, transport infrastructure systems, and digital urban planning. He leads research on corridor development, smart cities, and sustainable infrastructure, with over 60 peer-reviewed publications and international collaborations. His work bridges academia and practice, addressing challenges like port-city dynamics, flood resilience, and participatory governance. He advises governmental bodies and international projects, such as the Bali Mandara Highway and FLOODLABEL. Witte teaches advanced courses in urban governance and spatial planning, contributing to Utrecht's AESOP-accredited Master’s program. He actively engages in educational leadership and smart urban governance initiatives, advocating for technology integration while emphasizing equitable and participatory approaches.

Stephanie Greenمشاهده پروفایل

دانشیار

• Aquatic Global Change Ecology
• Marine Conservation Biology
• Invasive Species Management
• +۳ مورد دیگر

Stephanie Green is an Associate Professor and Canada Research Chair in Aquatic Global Change Ecology & Conservation at the University of Alberta's Faculty of Science. Her work focuses on understanding biodiversity change in marine ecosystems and developing science-based tools for conservation under global change. She leads the Green Lab, which combines ecological and social science approaches to address challenges in marine conservation, restoration, and human-natural system interactions. Her research integrates field experiments, modeling, and stakeholder collaboration to study topics like fisheries resilience to climate change, invasive species management, and coastal habitat restoration. Notable areas of focus include lionfish invasions, coral reef dynamics, and the socio-ecological impacts of energy development. Teaching responsibilities include courses on marine population ecology, ecological principles, and advanced ecology. She actively mentors students through independent research projects and encourages interdisciplinary collaboration. Her lab maintains active partnerships with practitioners and communities to ensure research addresses real-world needs.

Angela Rothمشاهده پروفایل

استاد

• Service Innovation
• Organizational Competencies in Service Innovation
• Service Systems in Digital Contexts
• +۳ مورد دیگر

Prof. Angela Roth is a Professor at the Friedrich-Alexander-University Erlangen-Nuremberg, leading the Chair of Information Systems I – Innovation and Value Creation. She co-chairs the department and directs the Open Service Lab (OSL). Her research focuses on service innovation, digital service systems, organizational competencies, and the future of work, with a strong emphasis on interactive value creation and living lab methodologies. She collaborates closely with industry partners and non-university research institutes, driving projects in servitization, service systems engineering, and workspace innovation. Prof. Roth previously led the Decision Support Systems department at Fraunhofer IIS-SCS and holds a habilitation and dissertation in logistics. Her teaching includes innovation strategies for digital transformation, service systems, and interactive service innovation. Her work explores stakeholder integration in service innovation, AI-driven service design, and workspace change dynamics. The Open Service Lab (OSL) serves as a platform for co-creation with customers and industry, exemplified by projects like JOSEPHS®. She also investigates the role of data in business model innovation and the societal implications of automation in service sectors.

• Biostatistics
• Spatial statistics and disease mapping
• Statistical methods for survival and longitudinal data
• +۳ مورد دیگر

Cindy Feng, PhD, is an Associate Professor in the Department of Community Health and Epidemiology at Dalhousie University's Faculty of Medicine. Her research focuses on developing biostatistical models for analyzing correlated public health data, including spatial statistics, longitudinal studies, and environmental health applications. She holds a PhD from Simon Fraser University and has received funding from NSERC, Canadian Statistical Sciences Institute, and MITACS. Dr. Feng collaborates with interdisciplinary teams across medicine, psychology, and environmental sciences. Education: PhD (Simon Fraser University), MSc (Simon Fraser University), BSc (Beijing University of Technology). Her work emphasizes bridging statistical theory and practice in public health, with notable contributions to disease mapping, survival analysis, and infectious disease surveillance. Key grants include NSERC Discovery Grants ($80,000, 2019-2023) and a MITACS Accelerate Grant ($45,000, 2016-2019). Research interests include zero-inflated models, spatial epidemiology, and methodological advancements for correlated data. Recent work addresses pandemic-related mental health trends, occupational injury risk factors, and global health challenges in malaria-schistosomiasis co-endemic regions. She has published over 30 peer-reviewed articles, with a focus on statistical diagnostics, public health policy, and environmental health impacts.