Find Academic Supervisors

• Digital Health
• Health Informatics
• Healthcare Transformation
• +4 more

Kerryn Butler-Henderson is an Adjunct Professor in the Department of Health and Biomedical Sciences at RMIT University. Her research focuses on digital health transformation, healthcare informatics, and workforce education. She actively contributes to understanding the integration of artificial intelligence, predictive analytics, and electronic health records (EHR) into healthcare systems. Her work emphasizes improving clinical outcomes through data-driven approaches and addressing challenges in workforce digital literacy. She holds an ORCID identifier (0000-0002-6082-2108) and is open to supervising PhD and Masters students. Research interests include: Learning health systems and AI applications Prediction modeling for musculoskeletal disorders Digital health workforce development Value-based healthcare frameworks Educational innovations in nursing and healthcare Key publications from 2024-2025 explore topics like EHR generalizability, digital health literacy measures, and global digital health workforce roles. Her interdisciplinary collaborations span occupational health, gerontology, and healthcare accounting. Dr. Butler-Henderson is engaged in curriculum development for digital health competencies and has contributed to national surveys on nursing education trends. She maintains strong industry connections through RMIT's Health and Biomedical Sciences research networks.

• Economics of Innovation
• Industrial Dynamics
• Productivity Analysis
• +3 more

Mark J. Roberts is a Professor of Economics at Pennsylvania State University and a Research Associate at the National Bureau of Economic Research. His work focuses on productivity analysis, industrial organization, and international trade, particularly examining how export market exposure influences firm R&D investment and structural modeling of firm dynamics in oligopolistic markets. Key affiliations: Penn State University, NBER, Penn State Census Bureau Research Data Center His research investigates the causal relationships between exporting activities and R&D investment, showing that exporters experience higher returns on innovation and productivity growth. He has developed structural models to quantify how trade barriers like tariffs reduce long-term R&D payoff for firms in high-tech German manufacturing sectors. Recent methodological contributions include counterfactual simulations using dynamic panel data to analyze institutional determinants of R&D investment in emerging economies. The work highlights corruption, regulatory quality, and political stability as critical factors affecting innovation incentives.

Nina SchwarzView profile

Assistant Professor

• Urban land-use change
• Urban ecosystem services
• Agent-based modelling
• +7 more

Nina Schwarz is Assistant Professor of human-environment interactions in cities at the Department of Urban and Regional Planning and Geo-Information Management, ITC—University of Twente. Holding a Diploma in Environmental Sciences (University of Lüneburg, 2003) and a PhD in Social and Economic Sciences (University of Kassel, 2007), she spent a decade as senior scientist at the Helmholtz Centre for Environmental Research – UFZ before joining ITC. Her interdisciplinary research integrates urban land-use science, ecosystem-service evaluation and advanced modelling techniques—especially agent-based models—to explore sustainable urban development under global change. Research interests revolve around three interconnected themes: (i) urban land-use change —understanding how residential, commercial and green-space dynamics co-evolve; (ii) urban ecosystem services —quantifying both supply and demand of services such as local climate regulation, recreation and biodiversity; and (iii) behavioural modelling —formalising human decision-making to simulate policy scenarios ranging from slum-upgrading to vineyard management. She actively links these themes to UN Sustainable Development Goals, notably SDG 11 (Sustainable Cities) and SDG 15 (Life on Land). Recent publications (2022-2025) reveal a methodological breadth spanning citizen-science impact assessment in Suriname, cooling effects of urban water bodies in Chinese mega-cities, European wine-growers’ adaptive behaviour, and methodological advances in upscaling and validating agent-based land-use models. Across these studies, Schwarz consistently combines empirical field data, geospatial analytics and participatory approaches to produce policy-relevant insights for cities in both the Global North and South. She has (co-)authored >80 peer-reviewed works, accumulating c. 5 900 citations and an h-index of 28 (Scopus). While specific honours are not itemised in the supplied text, her sustained citation impact and invited contributions to major conferences (e.g., iEMSs 2020, IAHR 2025) underscore scientific recognition. Schwarz frequently engages with societal stakeholders: her projects have generated open datasets on urban green-space monitoring in Paramaribo, e-learning modules for Latin-American universities, and interactive dashboards for sustainable water management. Within ITC she contributes to capacity-building programmes for emerging economies, supervises graduate researchers and maintains active collaborations across Europe, Latin America, Africa and Asia. No explicit lists of PhD students or personal grants are provided in the current corpus, but her leadership of externally funded projects (e.g., citizen-science evaluation, vineyard decision-making database) indicates ongoing acquisition of research funding.

Om P. DamaniView profile

Professor

• Technology for Development
• System Dynamics
• Modeling and Simulation
• +7 more

Om P. Damani is a Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Bombay. He serves as Faculty In-Charge of the Sustainable Development unit of the Center for Policy Studies and is also associated with the Centre for Technology Alternatives for Rural Areas (CTARA). His work bridges computer science with social development challenges, focusing on practical applications for rural communities. Dr. Damani's research interests span Technology for Development of the bottom 80%, System Dynamics: Modeling and Simulation for Social Development, System Architecture, and Data Science. His work demonstrates how computational approaches can address complex development challenges through projects like GramDrishti (for detecting rural infrastructure in satellite images), JalTantra (for optimizing water distribution networks), and FAI (Farm Assessment Index for holistic farming practice evaluation). His publications reveal a consistent focus on applying computer science to solve real-world problems in water management, agricultural systems, and rural infrastructure. His research has been recognized with significant awards including the IIT Bombay Industrial Impact Award 2010, IIT Bombay Impactful Research Award 2019, and Best Poster Award at Agriculture Science Congress 2017. Dr. Damani has successfully translated theoretical research into practical tools that address development challenges, particularly in water resource management and agricultural systems. As an educator, he has mentored numerous PhD students including Chintan Tundia, Shreenivas Kunte, Nikhil Hooda, Sivamuthu Prakash Murugan, Dipak L. Chaudhari, Prateek Kapadia, and Manoj K. Chinnakotla. His teaching portfolio includes courses on System Dynamics: Modeling and Simulation for Development (CS 752), Program Derivation (CS 420), and ICT for Development. Dr. Damani's educational background includes a Ph.D. in Computer Sciences from the University of Texas at Austin (1994-1999), B.Tech. in Computer Science and Engineering from IIT Kanpur (1990-1994), and prior professional experience at IBM T J Watson Research Lab and Akamai Technologies.

Marc D. AbramsView profile

Professor

• Forest Ecology
• Fire Ecology
• Climate Change Impacts
• +3 more

Marc D. Abrams is the Nancy and John Steimer Professor of Ecosystem Science and Management at Pennsylvania State University's College of Agricultural Sciences. His research focuses on forest dynamics, particularly the impact of fire exclusion, climate change, and human activity on forest composition and biodiversity. He has conducted extensive studies on oak and pine ecosystems, historical fire regimes, and the role of indigenous burning practices in shaping eastern US forests. Key research interests include dendroecology, paleoecological reconstruction, and vegetation classification. His work frequently integrates historical data, such as witness tree records and colonial land-use patterns, to understand long-term ecological changes. Recent studies have explored deer population impacts, wind damage probability modeling, and the effects of precipitation trends on forest health. His publications highlight interdisciplinary approaches to assess climate change impacts and advocate for adaptive forest management strategies. Abrams retired after 35 years at Penn State in 2022 but continues contributing to scholarly discussions on forest conservation and ecological resilience.

Kenan LiView profile

Associate Professor

• Spatial Computation
• Environmental Health
• Community Resilience
• +12 more

Kenan Li, Ph.D., is an Associate Professor in the Department of Epidemiology and Biostatistics at Saint Louis University’s College for Public Health and Social Justice. He joined SLU in August 2022 and teaches courses such as Statistical Learning, R for Spatial Analysis, and Environmental Determinants of Health. His research bridges data science, GIS, and public health, focusing on spatial computation, environmental exposures, and community resilience. Ph.D. in Environmental Sciences, Louisiana State University M.S. in Environmental Sciences, Louisiana State University B.S. in Environmental Sciences and Applied Mathematics, Nankai University, China Dr. Li’s research interests lie at the intersection of spatial computation, environmental health, and community resilience . He develops geo-AI frameworks , integrated geo-cyber-infrastructures , and biostatistics algorithms using big data, deep learning, and sensor data. His work emphasizes understanding human-environment interactions, urban sustainability, and health disparities. His recent publications from 2023 to 2015 reveal a strong trend in spatial modeling of population dynamics , machine learning for environmental exposure analysis , and resilience assessment in vulnerable coastal regions. He has pioneered methods like Dynamic Time Warping Self-Organizing Maps and Wavelet-based Shapelet Discovery to extract meaningful patterns from high-frequency sensor data. His scientific awards include the Taylor Geospatial Institute Seed Grant (2023) , the Saint Louis University 2023 Health Research Grant , and selection for the Scholarly Undergraduate Research Grants and Experiences . He has secured funding from NSF, NIH, USC Keck School of Medicine, and the US Army Corps of Engineers. Dr. Li has advised and collaborated on numerous research projects, particularly in interdisciplinary teams studying the Mississippi River Delta and urban health interventions. He has been involved in NIH/NIBIB-funded projects and led research on emergency management of trail systems in Los Angeles County. He is actively involved in building research labs and teams focused on spatial data science and public health analytics , having previously worked at USC’s Spatial Sciences Institute and Population and Public Health Sciences Department.

Humphrey SouthallView profile

Professor

• Historical Geography
• Geographical Information Systems (GIS)
• Historical GIS
• +12 more

Humphrey Southall is Professor of Historical Geography at the University of Portsmouth, affiliated with the Faculty of Science & Health and the School of the Environment and Life Sciences. He has been a key figure in advancing digital historical geography through large-scale projects such as A Vision of Britain through Time and the Great Britain Historical GIS . University: University of Portsmouth Faculty: Faculty of Science & Health Department: School of the Environment and Life Sciences Academic Rank: Professor Education: Bachelor's Degree, University of Cambridge (1976) Special Student, Harvard University (1976–1977) PhD, University of Cambridge (awarded 1984) Humphrey Southall's research centers on historical geography, with a focus on geospatial data modeling, gazetteers, and historical GIS. His work explores the long-term impacts of locality on health inequalities, the North-South divide in Britain, and the political roles of travellers. He has pioneered methods for disambiguating historical place names and constructing digital gazetteers from old maps and census data. His interdisciplinary approach bridges geography, history, and data science, contributing to digital humanities and sustainable development goals related to health and inequality. His recent publications reveal a strong trend toward integrating historical data with modern GIS and ontologies. Themes include electoral analysis (e.g., Reform UK), climate-land use interactions, and the digitization of historical statistics. His work emphasizes data accessibility, public engagement, and the application of historical insights to contemporary policy challenges. Scientific Awards and Recognition: No specific awards listed in the provided text. Humphrey Southall has secured major research grants from the ESRC, AHRC, JISC, and the European Commission. He leads the DDME: Data Discovery Made Easy project, applying machine learning to social science databases. He has supervised PhD students and actively collaborates with researchers across disciplines. His public engagement includes media commentary on homelessness, air pollution, and elections via The Conversation and national press. Labs and Research Teams: Lead Principal Investigator, A Vision of Britain through Time (VoB) Lead, Great Britain Historical GIS (GBHGIS) Team Member, PastPlace and AOU Resources as a Pelagios GIF Resource Collaborator with Patrick Aucott, Chris Thomas, and others on biodiversity and health projects

Rebecca NugentView profile

Professor

• Clustering Methodology
• Record Linkage
• Educational Data Mining
• +5 more

Rebecca Nugent is the Stephen E. and Joyce Fienberg Professor of Statistics & Data Science and Department Head at Carnegie Mellon University. She holds a PhD in Statistics from the University of Washington (2006), an MS in Statistics from Stanford (2006), and a BA in Mathematics, Statistics, and Spanish from Rice University (2002). Her research spans clustering methodology , record linkage , educational data mining , public health , and semantic organization , with a focus on high-dimensional data and adaptive learning environments. She leads the Integrated Statistics Learning Environment (ISLE) and Corporate Capstone programs, emphasizing low-barrier data platforms for education and industry collaboration. Academic Roles : Department Head, Carnegie Mellon; Affiliated Faculty, Block Center for Technology and Society Research Grants : NSF (2017-2019), NIH (2018), Carnegie Mellon ProSEED/Simon Initiative (2020, 2018), Berkman Fund (2014) Her 15 most recent publications focus on data science pedagogy, clustering algorithms, record linkage applications in historical and medical data, educational data mining, and semantic organization studies. Awards include the ASA Waller Education Award (2015) and the William H. and Frances S. Ryan Award (2015) . She mentors a diverse group of PhD, Master's, and undergraduate students, with alumni pursuing careers in academia, industry, and sports analytics.

Wayne A FullerView profile

Research Professor

• Survey Methodology
• Sampling Statistics
• Measurement Error Models
• +4 more

Wayne A Fuller is a Research Professor at Iowa State University , specializing in survey methodology and sampling statistics. His work focuses on advanced techniques for handling missing data, small area estimation, and measurement error models, with applications to agricultural surveys and public health research. Education: PhD in Statistics from Iowa State University Research Interests: Fuller's work bridges theoretical and applied statistics through: Development of fractional hot deck imputation methods Bootstrap techniques for variance estimation Small area prediction under constrained models Measurement error correction in health and agricultural data Time series analysis with autoregressive components Integration of administrative data with survey samples Publication Trends: His recent work emphasizes computational approaches to small area estimation (2016-2025), including bootstrap prediction intervals and benchmarking techniques, alongside methodological advancements in imputation and measurement error correction (2004-2015). Contact: Email: waf@iastate.edu Phone: 515-294-5830 Location: Ames, Iowa

Michael J. CafarellaView profile

Associate Professor

• Databases
• Information Extraction
• Data Integration
• +6 more

Michael J. Cafarella is an Associate Professor in the Computer Science and Engineering department at the University of Michigan . His research focuses on databases, information extraction, data integration, and data mining, with applications in economics, social media analysis, and combating human trafficking. He leads the Software Systems Lab and Michigan Database Group . Scientific Awards NSF CAREER award Sloan Research Fellowship (2016) 2018 VLDB Ten-Year Best Paper award Research Impact : Cafarella co-founded the Hadoop open-source project and Lattice Data (acquired by Apple). His work on DeepDive and DARPA MEMEX was featured on 60 Minutes and in Scientific American . Funding from The Census Bureau, DARPA, Google, NSF, Yahoo!, General Electric, and Dow.

Andrew HoView profile

Professor

• Educational Assessment
• Diversity and Inclusion in Education
• Educational Inequality
• +3 more

Andrew Ho is the Charles William Eliot Professor of Education at Harvard University's Graduate School of Education (HGSE). He holds a Ph.D. in Educational Psychology and an M.S. in Statistics from Stanford University. His research focuses on improving educational assessment design, particularly in measuring educational progress and inequality. He developed the Stanford Education Data Archive (SEDA), a national repository of student achievement data, and advocates for low-stakes assessment use in policy. Ho has held leadership roles including Immediate Past President of the National Council on Measurement in Education and trustee of the Carnegie Foundation. He advises seven U.S. states' testing programs and teaches graduate courses in statistics and psychometrics at HGSE. His work emphasizes the importance of accurate assessment during crises like the pandemic, advocating for standardized testing as part of a multi-measure 'census' approach to identify learning disparities and allocate resources effectively. Education: Ph.D. in Educational Psychology (Stanford, 2005), M.S. in Statistics (Stanford) Affiliations: Harvard Graduate School of Education, Technical Advisory Committees for 7 states Key Projects: SEDA, Assessment Literacy initiatives, pandemic-era testing advocacy His research bridges psychometrics with policy, emphasizing equitable assessment practices. Notable contributions include frameworks for interpreting test scores in multi-measure systems and critiques of 'learning loss' terminology favoring actionable 'learning lag' perspectives. Ho's recent work addresses pandemic-era education challenges through rigorous data analysis and policy recommendations.

Jon WakefieldView profile

Professor

• Spatial epidemiology
• Spatial demography
• Small area estimation
• +7 more

Jon Wakefield is a Professor in the Department of Biostatistics at the University of Washington's School of Public Health, with additional appointments in the Department of Statistics. He maintains affiliations with the Fred Hutchinson Cancer Research Center, the Center for Statistics and the Social Sciences, and serves on technical advisory groups for the World Health Organization and United Nations on mortality assessment, child mortality estimation, stillbirths, and pre-term births. Wakefield's research focuses on spatial epidemiology, spatial demography, and small area estimation, with particular emphasis on estimating under-5 mortality in low and medium income countries. His work integrates hierarchical models for survey data, space-time models for infectious disease data, and ecological inference methods for both infectious and non-infectious disease contexts. He has made significant contributions to understanding the links between Bayesian and frequentist statistical procedures, developing innovative methods for spatial modeling and disease burden estimation. His publication record shows a strong focus on methodological development with practical applications in global health, particularly in mortality estimation, infectious disease modeling, and demographic analysis. Recent work has addressed critical issues in pandemic response, including excess mortality estimation during the COVID-19 pandemic and seroprevalence studies. His research increasingly incorporates advanced computational methods, including Template Model Builder and integrated nested Laplace approximations for spatial modeling. Fellow, American Statistical Association (2007) Guy Medal in Bronze, Royal Statistical Society (2000) Member of the National Academies of Sciences, Engineering and Medicine Wakefield leads significant research initiatives funded by NIH/NCI and NIH/NIAID, including projects on spatio-temporal epidemiology and statistical issues in AIDS research. He has developed influential software tools including SUMMER, surveyPrev, and SAE4Health, which enable sophisticated small area estimation and spatial analysis for public health applications. His work with WHO and UN technical advisory groups demonstrates the real-world impact of his methodological contributions to global health measurement.

Konrad BurchardiView profile

Professor

• Development Economics
• Labor Economics
• Agricultural Economics
• +3 more

Konrad Burchardi is Professor of Economics at the Institute for International Economic Studies (IIES) at Stockholm University. His academic work focuses on understanding economic development processes and the social foundations of economic behavior, with significant contributions to development economics and migration studies. Professor Burchardi obtained his PhD in Economics from the London School of Economics (LSE), with prior studies conducted in Munich, Aix-en-Provence, and at LSE. His educational background reflects a strong international foundation in economic theory and development perspectives. His research primarily centers on productivity growth at early stages of economic development and the social underpinnings of economic interactions. Key contributions include field experiments on sharecropping contracts in developing countries, demonstrating how output-sharing rules affect agricultural productivity, and research showing how migration ancestry influences foreign direct investment patterns. His work spans agricultural economics, migration studies, experimental economics, and economic networks, often employing rigorous field and natural experimental designs to establish causal relationships. Analysis of Professor Burchardi's publication record reveals consistent contributions to top economics journals with a focus on development and labor economics. His work shows an evolution from examining micro-level economic behaviors in developing countries to broader questions about migration networks and their economic impacts. His recent publications indicate increasing attention to historical economic data and financial inclusion, with work scheduled through 2025.

Gary GrewalView profile

Associate Professor

• Computer-Aided Design (CAD) Tools
• Field Programmable Gate Arrays (FPGAs)
• Machine Learning
• +5 more

Gary Grewal is an Associate Professor at the School of Computer Science , University of Guelph. His research focuses on developing intelligent Computer-Aided Design (CAD) tools for Field Programmable Gate Arrays (FPGAs) , integrating classical optimization techniques with machine learning and deep learning to address challenges in placement and routing for heterogeneous devices. He has received the Michal Servit Award (2017, 2018) for outstanding FPGA research and the University of Guelph Faculty Association Distinguished Professor Award for Excellence in Teaching (2017) . Grewal has held NSERC Discovery Grants annually from 1999 to 2023. Co-founder of the Guelph FPGA CAD Group Key collaborator with institutions like Ryerson University , University of Toronto , and University of British Columbia His work extends to health technology through the IronTracker mobile app , developed with Andrew Hamilton-Wright and students (A. D'Angelo, J. Carter, F. Liu, R. Pattison) to manage Hereditary Hemochromatosis (HHC) . The app, available in four languages and adopted in 100+ countries, was recognized at Parliament Hill and the Ontario Legislature. Scientific Awards : Michal Servit Award (2018) Michal Servit Award (2017) Distinguished Professor Award for Teaching (2017) NSERC Discovery Grants (1999-2023) His recent publications highlight trends in machine learning for FPGA CAD , including reinforcement learning for partitioning, deep learning for congestion estimation, and adaptive algorithms for placement. Grewal remains active in teaching courses like Discrete Optimization (CIS*6070) and Digital Systems I (CIS*3120).

Einar LieView profile

Professor

• Economic History
• Norwegian Economic Policy
• State-Business Relations
• +5 more

Einar Lie is a Professor of Economic History at the Department of Archaeology, Conservation and History, University of Oslo. He holds a cand.polit. in Economics (1991) and a dr.philos. in History (1996) from the University of Oslo. Lie has undertaken research stays at INSEE (Paris), Lancaster University, University of Oxford, and UC Berkeley. He served as Vice Dean for Research at the Faculty of Humanities, University of Oslo (2010-2014), and as Board Chairman of the Norwegian University Center in St. Petersburg (2011-2014) and Kultrans. Lie is a member of the Norwegian Academy of Science and Letters and has contributed to boards of institutions like the Nansen Fund and Rosendal Barony. Education: cand.polit. (Economics), University of Oslo (1991) dr.philos. (History), University of Oslo (1996) Einar Lie's research focuses on Norwegian economic and political history, particularly state-business relations in banking, manufacturing, and the oil sector. His work explores themes like economic policy, central banking, state ownership, and statistical methodologies. Lie's publications include analyses of Norway's postwar economic strategies, the origins of the Norwegian Oil Fund, and the interplay between technocrats and policymakers in historical contexts. His work often bridges economic theory and historical practice, emphasizing institutional and methodological developments. Lie's scholarly contributions span economic policy debates, banking crises (e.g., 1987-1992), and state interventions in industry. His recent articles address historical lessons for contemporary fiscal and energy policies, with a focus on Norway's unique economic model. Lie's interdisciplinary approach incorporates economic theory, statistical science, and political economy. Scientific Awards: Member of the Norwegian Academy of Science and Letters As a regular op-ed columnist for Aftenposten , Lie engages public discourse on topics like climate policy, economic inequality, and historical parallels in modern governance. He contributes to research groups on contemporary history and climate-environment-energy studies (KLIMER) at the University of Oslo.