Yuriy Ushenko is Professor and Head of the Department of Computer Science at Chernivtsi National University named after Yuriy Fedkovych. An Academician of the Academy of Engineering Sciences of Ukraine (2021), he holds a Doctor of Physical and Mathematical Sciences degree with specialization in optics and laser physics. His interdisciplinary work bridges computer science, biomedical engineering, and optical diagnostics. His educational background includes: Master of Telecommunications from Chernivtsi National University (2003, Diploma with honors) Doctor of Physical and Mathematical Sciences (2015) in specialty 01.04.05 – Optics, Laser Physics Professor title in Computer Science (2017) Professor Ushenko's research focuses on information systems design , data mining , pattern recognition , and digital image processing with specialization in laser polarimetry and interferometry . His work pioneers Mueller-matrix tomography and polarization-correlation microscopy for biomedical applications, developing computational methods to analyze biological tissues and fluids for diagnostic purposes. Key innovations include 3D digital polarization-holographic histology for myocardial damage assessment and intelligent systems for disease identification from medical images. His publication trends reveal a strong emphasis on applying machine learning to biomedical imaging and geospatial analysis, with recent work spanning transformer-based lyrics generation, polarization-singular tissue processing, and migration forecasting systems. The research demonstrates consistent translation of theoretical optics into practical diagnostic tools. Scientific recognition includes: Academician of the Academy of Engineering Sciences of Ukraine (2021) As Director of the Bukovinian Innovation Technologies Cluster (since 2019), he leads regional IT initiatives while serving as Associate Editor for the SCOPUS Q3 journal International Journal of Image, Graphics and Signal Processing . His mentorship has guided students to international awards including ICYS silver medals and EUCYS special prizes. Current projects involve developing automated intelligent systems for LLC 'KM Trade' and advancing Mueller-matrix diagnostic techniques through international collaborations with Springer and SPIE conferences. His laboratory work centers on creating computational frameworks for polarization-correlation microscopy, with active teams developing laser autofluorescence polarimetry techniques and digital image processing pipelines for biomedical diagnostics. The research group maintains strong ties with international partners in optical engineering and medical diagnostics.
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Jerry SH LeeView profile
Associate Clinical Professor
Jerry SH Lee is an Associate Professor of Clinical Medicine, Chemical Engineering and Material Sciences, and Quantitative and Computational Biology at the University of Southern California, affiliated with the Keck School of Medicine, Viterbi School of Engineering, and Dornsife College. He serves as the Chief Science and Innovation Officer at the Lawrence J. Ellison Institute for Transformative Medicine, leading cancer research initiatives. Prior to USC, he was a Health Sciences Director at the National Cancer Institute and Deputy Director for Cancer Research and Technology in the White House Cancer Moonshot Task Force. Education: B.S. in Biomedical Engineering, Johns Hopkins University (2001) Ph.D. in Chemical and Biomolecular Engineering, Johns Hopkins University (2006) Dr. Lee’s research focuses on the interplay between biophysical and biochemical drivers of age-related diseases, particularly in oncology. His work spans cell biophysics , computational biology , liquid biopsy technology , and data-driven molecular medicine . He has pioneered methods in single-cell analysis and proteogenomic data harmonization to transform cancer care. His 15 most recent publications highlight trends in liquid biopsy standardization , immune checkpoint inhibitor outcomes , and single-cell proteogenomics . Collaborations with institutions like the BloodPAC Consortium and the VA National Research Advisory Council underscore his transdisciplinary approach. Scientific Awards: National Cancer Institute Director’s Merit Awards NASA Graduate Student Research Fellowship Tau Beta Pi Honorary Society Dr. Lee has co-authored over 50 papers, advised multidisciplinary teams, and contributed to national frameworks for real-world data in cancer care . His current work involves the APOLLO Network and Blood Profiling Atlas in Cancer initiatives.
Shishir ShakyaView profile
Assistant Professor
Shishir Shakya is an Assistant Professor of Economics in the Department of Economics at Walker College of Business, Appalachian State University. He also holds a position as a Research Fellow at the Knee Center for the Study of Occupational Regulation at West Virginia University. Previously, he served as an Assistant Professor at Shippensburg University of Pennsylvania and as an Instructor of Record at West Virginia University, where he taught courses in business statistics and macroeconomics. Dr. Shakya is an applied economist specializing in healthcare provider labor, licensing, and regulation markets, with a particular focus on improving healthcare access and quality at reduced costs. His research methodology combines traditional applied econometrics with spatial analysis, policy evaluation techniques, and technology-driven approaches including data scraping, big data analytics, predictive modeling, and causal machine learning. His work frequently examines the impact of scope of practice regulations, particularly regarding nurse practitioners and pharmacists, on healthcare access and outcomes. Analysis of his recent publications reveals a strong emphasis on healthcare economics, particularly the opioid crisis, provider scope of practice, and healthcare regulation. His work demonstrates significant interdisciplinary reach, connecting labor economics, spatial analysis, energy economics, and public policy. His research often employs sophisticated spatial econometric techniques to examine spillover effects across regions, while his more recent work increasingly incorporates machine learning approaches for causal inference. Dr. Shakya has taught a diverse range of economics courses including Business and Economic Statistics II, Time Series Forecasting, Regional Economics, Economic Analysis of Big Data, Principles of Economics, Macroeconomics, Managerial Economics, and Business Data Visualization. His teaching evaluations consistently highlight his enthusiasm for the subject, use of real-world examples, student engagement, and willingness to provide assistance. Specializes in healthcare provider labor markets and regulation Expertise in spatial econometrics and policy evaluation Active researcher on opioid crisis and healthcare access Skilled in integrating technology-driven methods with traditional economics Recognized for engaging teaching style and student support Dr. Shakya maintains an active research agenda with numerous working papers examining topics including Advanced Practice Registered Nurse Full Practice Authority, pharmacist prescriptive authority, public libraries' impact on crime, gender gaps in test scores, and prescription opioid spillovers. His work appears in reputable journals including World Development, Annals of Regional Science, Energy Economics, Contemporary Economic Policy, Drug and Alcohol Dependence, Spatial Economic Analysis, and Applied Economics Letters.
Daniel John LawsonView profile
Professor
Daniel John Lawson is a Professor of Data Science at the School of Mathematics, University of Bristol , affiliated with the Bristol Population Health Science Institute and the MRC Integrative Epidemiology Unit . His research bridges mathematical techniques with applications in genetics, epidemiology, and network analysis. Education: MSc (Bristol), PhD (London) Research Interests include Bayesian modelling, statistical genetics, big data analysis, and dynamical systems. He focuses on population structure inference, local ancestry, and their implications in health and history. Recent Publications highlight geographic polarization in digital landscapes, ancient DNA analysis for population history, and statistical frameworks for network embeddings. These works reflect his interdisciplinary approach. Projects like OCSEAN (2020–2023) explore oceanic migration patterns. His datasets on ancestry anomalies and genetic variants are widely accessible.
Lucas JoppaView profile
Adjunct Professor
Lucas Joppa is an Adjunct Professor at the Yale School of Public Health and serves as Microsoft’s first Chief Environmental Officer . With a Ph.D. in Ecology from Duke University, he bridges technology and conservation through initiatives like the AI for Earth program, a $50 million effort to develop environmental solutions using artificial intelligence. His research integrates ecology, biodiversity, and AI to address planetary-scale challenges. Adjunct Professor, Yale School of Public Health Chief Environmental Officer, Microsoft Associate Editor in Chief, EcoSphere journal Fortune 40 Under 40 honoree Joppa’s research focuses on leveraging artificial intelligence to combat climate change, protect biodiversity, and scale environmental data systems. He advocates for technology-driven conservation and has pioneered tools for poacher detection, carbon accounting, and global biodiversity monitoring. His work emphasizes interdisciplinary collaboration between tech and environmental science. Scientific awards include being named to Fortune’s 40 Under 40, serving as Associate Editor in Chief for EcoSphere, and recognition as a highly cited researcher. He also contributes to international environmental policy, including IPBES assessments and the Global Deal for Nature.
Arsalan NajafiView profile
Research Fellow
Arsalan Najafi is a Postdoc Research Fellow at Chalmers University of Technology, affiliated with the School of Architecture and Civil Engineering and the Urban Mobility Group . His work bridges transportation and energy systems through advanced optimization techniques. University: Chalmers University of Technology School: School of Architecture and Civil Engineering Department: Urban Mobility Group Academic Rank: Research Fellow Research Interests: Arsalan specializes in transportation electrification , multi-energy systems , and optimization methodologies . His current work focuses on integrating renewable energy with electric transport infrastructure, optimizing charging networks, and modeling urban mobility's environmental impact. Publication Trends: Recent outputs emphasize data-driven urban mobility solutions , electric bus energy modeling , and multi-sector energy optimization . Key journals include Transportation Research Part D , Applied Energy , and IEEE Access .
Andrea Ingeborg RieblerView profile
Professor
Andrea Ingeborg Riebler is a Professor in the Department of Mathematical Sciences at the Norwegian University of Science and Technology (NTNU). Her research focuses on Bayesian statistics, spatial modeling, disease mapping, and statistical software development. She is a leading contributor to the R-INLA framework for Bayesian hierarchical modeling and has developed packages like SUMMER and makemyprior for spatial-temporal analysis and prior elicitation. Her work bridges methodological advancements with applications in public health, demography, and epidemiology. Key research interests include spatial epidemiology, meta-analysis, and robust statistical modeling. She collaborates widely, particularly with researchers in geostatistics, computational statistics, and health sciences. Notable contributions include methods for small-area estimation in low/middle-income countries, cancer burden projections, and addressing positional uncertainty in geostatistical surveys. Her recent publications (2023–2025) emphasize scalable disease forecasting, mortality-based cancer incidence prediction, and improving DHS data analysis through positional adjustment. Teaching includes advanced computational statistics, survival analysis, and statistical modeling for biologists. Education: Doctoral dissertation work at NTNU (2021) focused on robust hierarchical models. Grants/Projects: Active in international health surveys (e.g., European Social Survey Health Inequalities Module). Labs/Teams: Collaborates with the NTNU Statistics Group and global health data initiatives.
Jia YuView profile
Researcher
Jia Yu is a researcher affiliated with Arizona State University , Tempe, AZ, USA. Their work focuses on geospatial data management, database systems, and cluster computing frameworks like Apache Spark. They have collaborated extensively with Mohamed Sarwat and other researchers on projects such as GeoSpark , GeoSparkViz , and GeoSparkSim , contributing to scalable spatial data processing and visualization systems. Key research areas include Learned indexing mechanisms (e.g., GLIN) Microscopic traffic simulation Parallel and distributed data processing Interactive geospatial dashboards Column correlation exploitation for database efficiency Integration of visualization with backend data systems Recent publications (2014-2024) demonstrate expertise in geospatial analytics, database indexing, software testing, and Apache Spark-based systems. Notable projects include Turbocharging Visualization Dashboards , HERMIT Indexing , and Spindra Knowledge Graph Management . Work emphasizes both theoretical innovation and practical implementation for handling massive-scale spatial data.
Guiming ZhangView profile
Associate Professor
Guiming Zhang is an Associate Professor in the Department of Geography & the Environment at the University of Denver's College of Natural Sciences and Mathematics. He specializes in Geographic Information Science (GIS) with research focusing on Volunteered Geographic Information (VGI), spatial big data analytics, and high-performance geo-computing. His work bridges computational methods with geographical analysis to address challenges in data quality, scalability, and real-world applications from disaster response to ecological conservation. Education Ph.D. in Geography, University of Wisconsin-Madison (2018) M.S. in Computer Sciences, University of Wisconsin-Madison (2016) M.S. in Geographic Information Science, Beijing Normal University (2013) B.S. in Geographic Information Systems, Beijing Normal University (2010) Research Focus Dr. Zhang's research explores the theoretical and practical dimensions of crowdsourced geographical data. Key areas include: Developing GPU-accelerated computational frameworks for large-scale spatial analysis Analyzing social dynamics and bias mitigation in VGI communities Creating predictive models for environmental applications like wildlife habitat mapping and digital soil characterization Investigating spatiotemporal patterns in citizen science data platforms Publication Trends His recent publications (2020-2025) demonstrate a strong focus on enhancing the reliability and scalability of spatial data analysis. Predominant themes include computational optimization of geospatial algorithms, social behavior analysis within VGI ecosystems, and applications in environmental monitoring. Methodological innovations feature GPU parallelization and multi-source data integration, while applied research spans disaster impact studies, biodiversity conservation, and urban digital twins. Professional Affiliations American Association of Geographers International Association of Chinese Professionals in Geographic Information Sciences
Belgacem RaggadView profile
Professor
Belgacem Raggad is a Professor at the Seidenberg School of Computer Science and Information Systems at Pace University . His academic work spans Management Information Systems, Software Engineering, and Artificial Intelligence, with a focus on Decision Support Systems and Approximate Reasoning. He has taught courses in Information Systems, Artificial Intelligence, and Cybersecurity. Education: PhD in Information Management (Pennsylvania State University, 1989) MS in Computer Information Systems (University of Tunis, 1979) Associate Degree in Mathematics and Physics (University of Tunis, 1975) Research Interests include Big Data Analytics, IoT collaboration models, Cybersecurity frameworks, and Telemedicine systems. His work emphasizes the integration of Evidential Reasoning and Approximate Reasoning into real-time monitoring and security applications. Awards and Honors highlight his contributions: Gold Medal for Great Contributions in IS Security (Tunisia, 2001) CSIS Excellence in Research Award (Pace University, 1998) Fulbright Scholarship (1982) Professional Contributions involve memberships in organizations such as the Association of Information Systems, Decision Science Institute, and International Association of Computer Information Systems, along with editorial and reviewing roles in multiple journals and conferences.
Andrew RundleView profile
Professor
Andrew Rundle is a Professor of Epidemiology at Columbia University's Mailman School of Public Health, where he directs the Built Environment and Health Research Group. He holds affiliations with the Health Analytics and Smart Cities centers, bridging public health, urban planning, and data science to address community health challenges through trans-disciplinary research. Dr. Rundle's research centers on neighborhood built, economic, and social environments as determinants of health behaviors and outcomes, with primary focus on obesity, sedentary lifestyles, and energy balance. His work extends to childhood neurodevelopment, asthma, pedestrian injuries, cancer survivorship, and elderly mental health. He has directly influenced urban policy through contributions to New York City's Active Design Guidelines, the FRESH food retail initiative, and the WELL Building certification program, demonstrating real-world application of epidemiological findings. His recent publications (2024-2025) reveal strong methodological innovation in spatial epidemiology and big data analytics, with recurring themes in neighborhood walkability-physical activity relationships, environmental health disparities, and cancer outcome inequities. Key approaches include geospatial modeling, electronic health record analysis, and Google Street View-based environmental assessments, reflecting his expertise in translating complex data into actionable public health insights. Scientific Awards: None explicitly mentioned in the provided information. Dr. Rundle maintains extensive industry partnerships with organizations including Schlumberger, BMW, Delos Living, and Fidelity Investments, focusing on employee health optimization, medical cost reduction, and data analytics capacity building. These collaborations involve product development, research strategy, and business analytics, demonstrating his ability to bridge academic research with corporate health initiatives through sophisticated analysis of medical claims and administrative datasets. He leads the Built Environment and Health Research Group, which employs innovative trans-disciplinary methods including GIS mapping, street view assessments, and spatial statistics to investigate how neighborhood characteristics shape health outcomes. The group's work directly informs urban policy frameworks and has established foundational evidence for built environment interventions targeting obesity and chronic disease prevention in diverse populations.
Chris SherlockView profile
Professor
Professor Chris Sherlock is a Professor of Statistics at Lancaster University , affiliated with the School of Mathematical Sciences and the Department of Mathematics and Statistics . His research spans MCMC theory , methodology , and applications in epidemiology, ecology, and environmental science, with a focus on stochastic processes (SDEs, hidden Markov models) and spatial statistics . Key research areas : Non-reversible MCMC algorithms (e.g., Bouncy Particle Sampler), pseudo-marginal methods, and inference for reaction networks. Recent publications address flood risk estimation, scalable Bayesian learning, and clinical trial recruitment prediction using novel MCMC frameworks. He leads the Computational Statistics group (2019-present) and the MARS UG program (2024-present). Supervised PhD students have explored topics like extreme value theory, particle filters, and disease modeling. Collaborations include researchers such as Paul Fearnhead , Chris Nemeth , and Andrew Golightly , with EPSRC funding (EP/P033075/1) supporting non-reversible MCMC innovations.
Paulo R. DellaniView profile
Research Fellow
Dr. Paulo R. Dellani serves as a Postdoctoral Researcher at the Research Center Jülich, affiliated with the Institute of Neuroscience and Medicine (INM-1), where he investigates structural and functional brain organization. His work integrates advanced neuroimaging techniques, artificial intelligence, and clinical neuroscience to explore brain architecture, connectivity, and pathology. His research interests encompass: Novel brain mapping methodologies Clinical neuroanatomy and genomic imaging Big data analytics for neural systems Diffusion tensor imaging and fiber tract analysis Neurodegenerative disorder biomarkers Recent publications demonstrate a strong focus on translational neuroscience, including MRI-based diagnostics for vestibular disorders, Alzheimer's disease biomarkers, and computational approaches to white matter tractography. Common themes include validation of imaging protocols, neuropathology characterization, and clinical application of quantitative neuroimaging techniques. Dr. Dellani contributes to the Bernstein Coordination Site and participates in teaching activities at universities. His laboratory develops tools and services supporting brain research, including the Julich-Brain atlas project.
Rob KitchinView profile
Professor
Rob Kitchin is Professor in the Maynooth University Social Sciences Institute (MUSSI) and the Department of Geography at Maynooth University (National University of Ireland, Maynooth). Since 1998 he has directed or co-directed several flagship interdisciplinary centres, including the National Institute for Regional and Spatial Analysis (2002–2013), the Digital Repository of Ireland (2009–2017) and the All-Island Research Observatory (2005–2017), and currently leads the ERC-funded Data Stories project (2022–2027). Education PhD Geography, University of Wales Swansea (1992–1995) MSc Geographical Information Systems, University of Leicester (1991–1992) BSc (Hons) Geography, University of Lancaster (1988–1991) Research Interests Rob’s work sits at the intersection of human geography , digital geographies and urban studies . He interrogates how software, big data, algorithms and spatial media reshape cities, governance and everyday life, with particular attention to questions of social justice, ethics and power. His research clusters include smart cities and urban science, software studies and code/space, cartographic theory and dashboards, data infrastructures and practices, and social geography of Ireland. Scientific Awards Maynooth University Research Achievement Award 2018 (inaugural, university-wide) Royal Irish Academy Gold Medal for the Social Sciences 2013 ERC Advanced Investigator Award 2013 ( The Programmable City ) Meridian Book Award 2011 (Association of American Geographers) Cantemir Prize 2012 (Berendel Foundation) Elected Member of the Royal Irish Academy 2015 Media Achievement Award 2015 (AAG) Numerous national e-government and geography prizes Research Funding & Leadership Principal or co-investigator on 50 funded projects worth c. €39 million from ERC, SFI, HEA, ESRC, NSF, RIA and others. Recent roles include PI of Data Stories (ERC, €2.5 m, 2022–2027), Building City Dashboards (SFI, €2.35 m, 2016–2021) and The Programmable City (ERC, €2.31 m, 2013–2018). He previously directed the National Institute for Regional and Spatial Analysis (2002–2013) and the Digital Repository of Ireland (2009–2017). Labs, Teams & Editorial Roles Rob leads the Programmable City and Data Stories research teams at Maynooth, supervising post-docs and graduate researchers across geography, computer science and urban planning. He is Editor-in-Chief of Dialogues on Digital Society (2024–), former Managing Editor of Dialogues in Human Geography (2011–2020) and Social & Cultural Geography (2000–2009), and Editor-in-Chief of the 12-volume International Encyclopedia of Human Geography .
Francesco RavazzoloView profile
Professor
Francesco Ravazzolo is Full Professor of Econometrics at the Free University of Bozen-Bolzano (Faculty of Economics and Management) and Head of the Department of Data Science & Analytics at BI Norwegian Business School. He also acts as visiting professor at BI’s Center for Applied Macro and Commodity Prices and is president of the Society of Nonlinear Dynamics and Econometrics. Education: Ph.D. in Econometrics, Tinbergen Institute & Erasmus University Rotterdam, 2007 Research domains: Ravazzolo’s work sits at the intersection of Bayesian econometrics, energy economics, financial econometrics and macroeconometrics. He develops forecasting methods for electricity prices, commodity markets, cryptocurrencies and macro aggregates, with particular emphasis on regime-switching, mixed-frequency and high-dimensional techniques. His recent projects exploit textual data and semantic networks to predict consumer confidence and financial volatility. Publication trends: Since 2022 he has published extensively on (i) hourly/daily electricity-price forecasting with renewables and macro drivers, (ii) robust or Markov-switching time-series methodologies, (iii) big-data sentiment indicators for bond and stock markets, and (iv) energy-commodity and crypto-asset econometrics. Applications span European gas-price caps, Italian zonal imbalances, Nordic and German power markets, and global CDS indices. Editorial & professional service: Editorial boards: Annals of Applied Statistics, International Journal of Forecasting, Journal of Applied Econometrics, Spatial Economic Analysis, Studies in Nonlinear Dynamics & Econometrics President, Society of Nonlinear Dynamics & Econometrics Grants & enterprise: He is co-founder of three academic spin-offs: AIAQUA (AI for water and energy management), COMMODIA (commodity-data analytics) and STAIRS (forecasting platforms), securing continuous grant and industry funding for applied research. Labs & teams: At BI he leads the Department of Data Science & Analytics (ca. 40 faculty) and coordinates the Commodity Prices Research Hub; at unibz he supervises the Econometrics & Forecasting group involved in regional energy-market projects.