Zorana Jovanovic Andersen is an Associate Professor at the University of Copenhagen, Department of Public Health, Section of Environmental Health, specializing in Environmental and Occupational Epidemiology. Her research focuses on health impacts of air pollution , noise exposure , and lifestyle factors across large cohorts including the Danish Nurse Cohort and Diet, Health, and Cancer cohort. Primary research areas: Environmental Epidemiology, Breast Cancer Risk, Air Pollution, Noise Studies, Physical Activity Interactions Key projects: Hyperion (road traffic noise), ELAPSE (low-level air pollution), TAPAS (climate-transportation health risks) Research Themes She investigates long-term exposure to air pollution and noise in relation to breast cancer , diabetes , cardiovascular disease , and brain cancer , while exploring how factors like physical activity modify these risks. Recent work includes dementia and COVID-19 mortality analyses. Scientific Contributions Her 15 most recent publications address: 1) Air pollution disparities in Europe 2) Dementia-air pollution links 3) Stroke-noise interactions 4) Airport ultrafine particle exposure 5) Asthma-COPD overlap 6) Breast cancer-mammographic density relationships. Major Grants Danish Working Environment Research Fund (1.79M DKK, 2017) Danish Heart Association (433K DKK, 2016) Danish Council for Independent Research (1.93M DKK, 2015) Teaching & Leadership Course Leader for Data Processing in Health Care and Public Health Informatics at UCPH since 2011. Organized Danish Health Registries seminars and served on scientific committees for environmental conferences.
Ethan Williams is an Assistant Professor at the University of California, Santa Cruz, Department of Earth & Planetary Sciences. His research focuses on distributed acoustic sensing (DAS) applications in seismology, oceanography, and environmental monitoring, particularly studying wave dynamics, subduction geohazards, and ocean-solid Earth interactions. Ph.D. in Geophysics, California Institute of Technology (2023) M.S. in Geophysics, California Institute of Technology (2019) B.S. in Geophysics and B.A. in Music, Stanford University (2017) Research Interests: Williams specializes in DAS technology, subduction zone geohazards, surface wave dynamics, and ocean-solid Earth coupling. His work bridges seismic monitoring, marine geophysics, and environmental sensing. Publication Trends: His recent articles emphasize DAS innovation for offshore seismic monitoring, wave propagation analysis, and integrating fiber-optic data with conventional measurements. Themes include earthquake detection, climate change impacts, and multi-scale ocean dynamics. Scientific Awards: 2022 SSA Student Presentation Award for 'Continuous seismic monitoring of a building over 20 years' Advising & Collaboration: Williams collaborates with institutions like the University of Washington and Caltech, working on NSF-funded projects such as the Ocean Observatories Initiative. He invites prospective students/postdocs to contact him via email.
Jie Chen is an Assistant Professor in the Department of Mechanical Engineering at Virginia Tech's College of Engineering. Their research bridges machine learning with engineering analysis and design under uncertainty, focusing on process-structure-property-performance relationships. PhD, Mechanical Engineering (2022) – Arizona State University MS, Civil Engineering (2018) – Beihang University BS, Civil Engineering (2015) – Beihang University Research interests include: physics-informed machine learning, uncertainty quantification, predictive maintenance, materials design, and advanced manufacturing. The SEAD Lab develops methods to integrate engineering analysis into stochastic machine learning algorithms and uses AI for knowledge discovery in uncertain environments. Recent publications emphasize: Digital twin frameworks combining machine learning and Bayesian optimization Graph neural networks for high-entropy alloy and molecular mixture property prediction Physics-guided neural networks for fatigue life analysis of additively manufactured alloys Uncertainty quantification in imbalanced regression tasks and multi-fidelity data fusion Real-time imaging of polymer deformation mechanisms The lab actively mentors students, including PhD candidate Yisheng Lu, and manages projects in predictive maintenance, fatigue modeling, and materials design.
Soraya de Chadarevian serves as Professor in the Department of History and the Institute for Society and Genetics at the University of California, Los Angeles, where she bridges historical scholarship with contemporary bioscience through rigorous analysis of material practices and cultural contexts in the life sciences. Her academic trajectory spans over three decades with significant contributions to understanding molecular biology's development and human heredity's evolution from the nineteenth century to present. Her educational foundation includes a PhD in Philosophy from the University of Konstanz, Germany, and an Advanced degree (Diplom) in Biology from the University of Freiburg, Germany, providing unique interdisciplinary perspective. These qualifications enabled her dual expertise in scientific practice and philosophical inquiry that defines her scholarly approach. De Chadarevian's research centers on the intricate relationship between scientific practice and cultural context in the life sciences, with particular emphasis on visual and material dimensions of molecular biology and chromosome research. She examines how laboratory techniques, archival practices, and data systems shape biological knowledge, exploring themes like the microscope's role in heredity studies, genetic evidence in historical narratives, and pandemic responses. Her work reveals how scientific concepts like the double helix or human genome emerge through complex negotiations between technical possibilities, institutional frameworks, and societal concerns. Analysis of her recent publications shows a decisive shift toward contemporary scientific challenges including pandemic responses, data-intensive biology, and ethical dimensions of genetic research. While maintaining deep historical perspective, her scholarship increasingly engages with urgent present-day issues such as biobanking, forensic genetics, and the societal implications of genomic databases, demonstrating how historical understanding informs current scientific controversies. Her scientific recognition includes: National Science Foundation Scholar Award (2015-2021) Walther Rathenau Program Fellowship Max Planck Institute for History of Science Fellowship Fellowship at La Villette Fellowship at École des Hautes Études en Sciences Sociales Hamburg Institute for Social Research Fellowship Churchill College Cambridge Fellowship Institute for Advanced Studies in the Humanities Fellowship Research funding has been consistently secured through competitive grants, most notably the six-year NSF award supporting her chromosome history project. She actively mentors students through UCLA's graduate programs in History and the Institute for Society and Genetics, teaching specialized courses on genetics and society while supervising research on science-society intersections. Her collaborative approach extends to co-editing special journal issues and organizing international research networks. Through sustained engagement with institutions like the Max Planck Society and Cambridge University, de Chadarevian maintains active participation in global scholarly communities. Her current work involves interdisciplinary teams examining data practices in contemporary biology and historical dimensions of pandemic responses, positioning her at the forefront of science studies' engagement with pressing societal challenges.
Professor Massimiliano Tani Bertuol is a distinguished academic specializing in economics at UNSW Canberra's School of Business, where he has served as Professor since 2015. His professional affiliations extend beyond UNSW as he is an Associate Investigator/Member at CEPAR; Ageing Futures; uDASH; AI Institute; and Cyber security (IFCYBER). Additionally, he maintains international connections as a Research Fellow at the Institute for the Future of Labor (IZA) in Germany since 2005, an Associate Member at Macquarie University's Centre for Workforce Futures since 2018, and a Research Fellow at the Global Labor Organization (GLO) in Maastricht since 2016. His educational background reflects a strong foundation in economics and business, having earned a PhD in Economics from the Australian National University (2003), a Master of Science in Economics from the London School of Economics (1992), and a Bachelor's degree in Business/Economics from Bocconi University in Milan, Italy (1989). His academic journey has positioned him as a leading researcher in human capital economics with international recognition. Professor Tani Bertuol's research centers on human capital development and its economic implications. His work examines how human capital can be fostered, efficiently transferred internationally through migration, and how it affects productivity, innovation, and economic growth at both firm and national levels. His research spans multiple regions including Australia, Europe, the US, Africa, and China, with particular focus on migration economics, labor market outcomes, and the economic impacts of education and skills. His current research agenda includes non-pecuniary incentives, behavioral/financial decisions in China, occupational licensing, language skills and economic assimilation, AI-human interactions in health contexts, and labor mobility and productivity. Analysis of his recent publications reveals significant interdisciplinary trends bridging economics with public health, environmental science, and technology. His work connects migration dynamics with economic outcomes, examines household financial behaviors through gender lenses, and investigates the complex relationships between environmental factors like air pollution and economic activities including education investment and entrepreneurship. More recent work explores AI applications in health and the economic implications of pandemic responses, demonstrating his ability to address contemporary challenges through rigorous economic analysis. 2023: UNSW ARC Postgraduate Council (Arc PGC) award for excellence in research supervision 2011: Vice-Chancellor Award for Teaching Excellence 2011: Faculty Award for Teaching Excellence for teaching economics Professor Tani Bertuol has successfully supervised 4 PhD students to completion, with 1 submitted dissertation and 5 currently under supervision. His active research program is supported by significant grant funding including an ARC Linkage Project (2023-27) on regional Australia's skills shortages and high-skill refugees' employment ($354,811), an ARC Discovery Project (2019-23) on migrant aging and wellbeing ($478,000), and a NUW Alliance grant (2021-23) on hearing screening and academic outcomes ($73,367). He serves as Associate Editor for Social Indicators Research and Higher Education Research & Development, contributing to scholarly discourse in his fields of expertise. His teaching portfolio includes courses in data analytics, finance, and professional executive education focused on cost-benefit analysis and data communication. He teaches ZBUS2333 Data Analytics and Visualisation, ZBUS8105 Finance and Investment Appraisal, and ZBUS8149 Introduction to Finance, demonstrating his commitment to developing the next generation of economics professionals with both theoretical knowledge and practical skills.
Tom Wenseleers is a Professor at KU Leuven's Department of Biology within the Faculty of Science, where he leads the Laboratory of Socioecology and Social Evolution. His research spans theoretical and experimental approaches to evolutionary biology, with particular focus on social insect systems. Research spans social insects (ants, bees, wasps), microbes, viruses, and human systems Primary model organisms: social insects studying major evolutionary transitions Current projects examine caste determination, chemical communication, and evolutionary conflicts His research integrates theoretical modeling with experimental, behavioral, and comparative studies. Recent work combines genomic techniques and high-throughput GC/MS analysis to decipher chemical communication systems. Current trends show increasing interdisciplinary work spanning virology (SARS-CoV-2 variants), microbial ecology (antibiotic resistance), and robotics (pollinator behavior monitoring). The research demonstrates consistent application of evolutionary theory to diverse biological systems while maintaining social insects as the core model. Wenseleers actively mentors PhD students and postdocs, with recent graduates including Kamiel Debeuckelaere and Viviana Di Pietro. His lab receives substantial funding through multiple concurrent research projects, including Promotor roles on grants examining caste development in bee societies and microbial metabolite screening. The laboratory maintains strong international collaborations across Europe and South America. The lab operates within the Ecology, Evolution and Biodiversity Conservation unit at KU Leuven, with physical location at Naamsestraat 59, box 2466, 3000 Leuven. The research group maintains active outreach programs including science workshops for schools and public engagement events focused on insect conservation.
Yingdan Lu is an Assistant Professor in the Department of Communication Studies at Northwestern University's School of Communication. She serves as Director of the Computational Media and Politics Lab, co-director of the Computational Multimodal Communication Lab, and is core faculty in Northwestern's Media, Technology, and Society (MTS) and Technology and Social Behavior (TSB) PhD programs. She is also affiliated with the Center for Communication & Public Policy and the Center for Human-Computer Interaction + Design. Her educational background includes a Ph.D. in Communication from Stanford University (2023), where she also earned a Ph.D. minor in Political Science and an M.A. in East Asian Studies. She received her B.A. in Journalism and Communication from Tsinghua University. Dr. Lu's research centers on digital technology, political communication, and authoritarian politics, with two primary focus areas: the role of digital technologies in authoritarian politics, and multimodal communication across different contexts. Her work employs computational and qualitative methods to examine how authoritarian governments use digital media and AI to maintain rule, and how individuals experience technology in different media environments. As a computational social scientist, she advances methods for analyzing multimodal data (images, videos), cross-lingual digital communication, and mixed-method research. Her publications reveal a consistent focus on digital authoritarianism, particularly Chinese state propaganda on social media platforms, multimodal communication analysis, and information manipulation. Her work spans interdisciplinary outlets including Political Communication, New Media & Society, International Journal of Press/Politics, and Proceedings of the National Academy of Sciences. Dr. Lu's research has received funding from the National Science Foundation, Brown Institute for Media Innovation, and the Stanford Institute for Human-Centered Artificial Intelligence. She is the founder of COMputation Island ("计传岛"), a WeChat-based platform serving over 10,000 Mandarin-speaking scholars in computational communication research. She leads the Computational Media and Politics Lab and co-directs the Computational Multimodal Communication Lab, where she develops innovative frameworks for analyzing multimodal data and promotes mixed-method approaches to computational social science research.
Ridhi Kashyap is a Professor of Demography and Computational Social Science at the University of Oxford, where she contributes significantly to demographic research through innovative computational approaches. She is affiliated with the Leverhulme Centre for Demographic Science, where she co-leads the Digital and Computational Science strand. Her work bridges traditional demographic methods with cutting-edge computational techniques to address pressing social issues related to population dynamics and inequalities. Dr. Kashyap's research spans multiple areas of demography, with particular focus on: Mortality and population health, including pandemic impacts on life expectancy Gender inequality, especially son preference and digital gender gaps Marriage and family dynamics in relation to educational expansion and gender norms Migration and ethnicity patterns using digital data sources Sustainable development goals related to digital access and gender equality Her methodological expertise lies at the intersection of demography and computational social science. She leverages agent-based models, microsimulation, and machine learning techniques applied to novel data streams such as digital trace data from social media platforms. A notable example of her work is the digitalgendergaps.org platform, which nowcasts global digital gender inequalities in internet and mobile access - a key sustainable development goal indicator where official data is lacking. Her research demonstrates how computational approaches can fill critical data gaps and provide timely insights for policy decision-making. Analysis of Dr. Kashyap's recent publications reveals a strong focus on digital demography and computational approaches to understanding population dynamics. Her work frequently examines gender inequalities through digital lenses, including analyses of LinkedIn data to understand professional gender gaps and social media data to track digital access disparities. She has made significant contributions to understanding pandemic mortality patterns, particularly in India and the US, and has pioneered methods for using social media data to nowcast demographic phenomena. Her research consistently bridges theoretical demographic concepts with practical computational methodologies. Dr. Kashyap has been actively involved in several significant research initiatives, including leading the development of the Digital Gender Gaps dashboard and contributing to the creation of the World Cybercrime Index. Her work with the Leverhulme Centre for Demographic Science has positioned her at the forefront of computational demographic research. Within her academic role, Dr. Kashyap supervises graduate students and collaborates with interdisciplinary teams across demography, computer science, and public health. She has secured funding for projects that leverage digital data to address demographic research questions, particularly those related to gender inequality and sustainable development goals. Her work with social media data platforms demonstrates innovative approaches to overcoming traditional data limitations in demographic research. Dr. Kashyap co-leads the Digital and Computational Science strand at the Leverhulme Centre for Demographic Science, where she oversees a team of researchers working at the intersection of demography and computational methods. Her team develops innovative approaches to using digital trace data for demographic research, with particular focus on gender inequality metrics and pandemic impact assessment. The Digital Gender Gaps project represents one of her team's flagship initiatives, providing near-real-time monitoring of a key sustainable development indicator.
Dr. Sasan Mahmoodi is an Associate Professor at the School of Electronic and Computer Science , University of Southampton. His research focuses on Medical Image Analysis , Biometrics , and Computer Vision , with applications in healthcare and security systems. Research Groups: Vision, Learning and Control; Institute for Life Sciences; Centre for Machine Intelligence His work spans deep learning , rule-based AI , and pattern recognition in medical imaging, including applications for neonatal brain injury prognosis and radiographic knee osteoarthritis classification. He also contributes to biometric technologies like facial profile recognition and gait analysis. Recent publications highlight his expertise in: Domain adaptation for biometric systems Infrared gait recognition databases Motion artefact correction in HRpQCT imaging Histopathology image segmentation using U-Net variants Dr. Mahmoodi supervises PhD students in computer science and human health development and collaborates on interdisciplinary projects involving machine learning and medical imaging.
Paul Hufe is a Senior Lecturer (Assistant Professor) at the University of Bristol, with affiliations at IZA, CESifo, IFS, and HCEO. His research bridges public, labor, and normative economics, focusing on equality of opportunity, intergenerational mobility, and fairness. Education: PhD from LMU Munich; visiting appointments at Cornell, Princeton, and FAIR at NHH Bergen. Research interests include measuring unfair inequality, skill formation, and the role of genetic and circumstantial factors in life chances. Methodologically, he integrates regression trees and experimental evidence to advance inequality analysis. His recent work spans multidimensional fairness in Europe, genetic lotteries in education, and parental wage impacts on child development. Articles often involve collaborations with leading economists. Awards: UKRI Future Leaders Fellowship (GBP 1.6m, 2024-2028). Grants: Co-Investigator for European Social Science Genetics Network (Horizon Europe).
Ji Ma is an Assistant Professor at the Lyndon B. Johnson School of Public Affairs at the University of Texas at Austin, with affiliate appointments at the Center for East Asian Studies, School of Information, and Asia Policy Program. He also serves as a Visiting Researcher at the Gradel Institute of Charity, University of Oxford. Dr. Ma received his PhD from Indiana University, establishing a foundation for his interdisciplinary work at the intersection of computational methods and social science. Dr. Ma's research centers on three interconnected streams: computational approaches to social science, knowledge production for evidence-based policymaking, and state-society relations in China. His work bridges advanced technologies with public affairs, developing innovative methods to analyze nonprofit sectors and civil society dynamics. He has pioneered the application of computational social science in nonprofit studies, creating valuable research infrastructure for the field. His recent publications show a clear trend toward integrating AI and computational methods with traditional social science questions. He has made significant contributions to understanding citation patterns in policy communities, consensus formation in academic fields, and the dynamics of state-society relations in China. His work often combines large-scale data analysis with theoretical insights from multiple disciplines. Dr. Ma actively contributes to teaching through courses like "Computational Social Science Methods" and "Data Management and the Research Life Cycle," helping students develop skills in data analysis and research methodology. His teaching emphasizes practical applications of computational methods in public affairs research. Among his notable projects are pracademia.one (an information aggregation platform), npoclass (a nonprofit classifier), and the Research Infrastructure of Chinese Foundations (RICF). These projects reflect his commitment to developing methodological tools that advance research in public administration and nonprofit studies, creating valuable resources for scholars worldwide.
Catherine Neish is an Associate Professor in the Department of Earth Sciences at The University of Western Ontario. She serves as the Associate Director of Research for Western Space and is a Co-Investigator on NASA's Dragonfly mission to Titan. Her research focuses on planetary radar observations, impact cratering processes, and the geological evolution of planetary surfaces, particularly on the Moon, Titan, and other Solar System bodies. Ph.D. in Planetary Sciences, University of Arizona (2008) B.Sc. in Combined Honours Physics and Astronomy, University of British Columbia (2004) Her recent publications highlight studies on lunar impact crater thermophysics, Titan's impact melt dynamics, and radar-based analyses of planetary surfaces. She has contributed to missions including Lunar Reconnaissance Orbiter (Mini-RF), Cassini RADAR, and Dragonfly. Scientific Awards: College of New Scholars, Royal Society of Canada (2021) Early Researcher Award, Ontario (2017) Minor Planet 16972 Neish (2017) AGU Ron Greeley Award (2014) NASA Postdoctoral Fellowship (2012) NASA Group Achievement Award (2010) NSERC Postgraduate Scholarship (2005-2008) Julie Payette-NSERC Research Scholarship (2004-2005) Dr. Neish supervises a dynamic lab with current and former students investigating planetary geology, impact cratering, and remote sensing. Her work bridges field studies (e.g., Earth analogs), laboratory experiments, and spacecraft data analysis.
Cameron Churchill is an Assistant Professor at McMaster University 's Faculty of Engineering , Department of Civil Engineering. His work focuses on Life Cycle Assessment (LCA) of concrete materials and infrastructure, Sustainable Civil Infrastructure , and GIS-based Decision Support Systems for urban planning. Research Interests : LCA methodologies, sustainable concrete mixes, environmental impact analysis, photocatalytic materials, corrosion modeling, and transportation infrastructure design. Teaching : Courses include Engineering: Communications and Social Impact (2025), Integrated Cornerstone Design Projects (2017–2025), and Design and Synthesis Project in Civil Engineering (2012–2025). Recent publications analyze LCA trends in concrete with fly ash allocation, transportation distance impacts, and photocatalytic barrier cost analysis. His work also explores GIS applications for urban greening and traffic calming .
Veronica Frans is a Stanford Science Fellow at Stanford University and a sixth-year PhD Candidate in Fisheries & Wildlife and Ecology, Evolutionary Biology & Behavior at Michigan State University (MSU). She is affiliated with MSU’s Center for Systems Integration and Sustainability (CSIS), the Klausmeier-Litchman lab at Kellogg Biological Station, and holds certifications in Community Engaged Scholarship and Spatial Ecology. Her research focuses on human influence on species distributions, integrating ecological modeling, GIS, and community outreach. BS/BA in Environmental Sciences and French from Messiah College MSc in International Nature Conservation from Goettingen University Her research spans ecology, conservation biology, and sustainability, emphasizing human-nature interactions through metacoupling, telecoupling, and stakeholder collaboration. She has conducted fieldwork in Alaska, Hong Kong, and the Falkland Islands, leveraging local knowledge to address global conservation challenges. Recent publications highlight her expertise in species distribution modeling, sustainability tool development (e.g., seesus, SDGdetector), and conservation policy analysis. Articles frequently explore metacoupling, anthropogenic impacts, and marine ecosystem dynamics, with applications in deforestation, biodiversity, and SDG implementation. NSF GRFP Fellow University Enrichment Fellow Outstanding Paper in Landscape Ecology Award Veronica collaborates with the Klausmeier-Litchman lab at MSU’s Kellogg Biological Station and works under Dr. Jianguo (Jack) Liu at CSIS. Her work bridges marine environments, stakeholder engagement, and global sustainability through interdisciplinary research and community-based conservation.
Christian Hirsch is an Associate Professor for Data Science and Statistics at Aarhus University, where he studies random networks motivated from biology and health sciences through techniques from topological data analysis and stochastic geometry. He is a member of the Stochastics group at the Department of Mathematics and holds additional affiliations as an Associate Fellow of the Aarhus Institute for Advanced Studies, and with the AU DIGIT Centre and the AU Quantum Campus. Current Position: Associate Professor for Data Science and Statistics, Aarhus University Previous Positions: Assistant Professor at University of Groningen and University of Mannheim Postdoctoral Experience: Aalborg University, LMU Munich, WIAS Berlin Education: PhD from Ulm University Christian Hirsch's research focuses on the statistical foundations of topological data analysis, large deviations theory in stochastic geometry, and percolation theory of spatial random networks. His work bridges theoretical mathematics with practical applications in data science, particularly in analyzing complex structures through topological methods. He investigates how topological features form and disappear in growing data structures, developing statistical tests to determine whether observed patterns are significant or merely random occurrences. His recent publications reveal a strong trend toward applying topological data analysis to increasingly complex structures, with significant focus on statistical validation of topological features. Hirsch has made substantial contributions to understanding the probabilistic behavior of persistent homology, developing functional central limit theorems and large deviation principles for topological functionals. His work spans theoretical foundations in stochastic geometry while finding applications in materials science, neural networks, and wireless communication systems. As an educator, Hirsch teaches graduate courses including Topological Data Analysis, Stochastic Geometry, Monte Carlo Simulation, Markov Decision Processes, Probability Theory, and Stochastic Processes. He has supervised numerous PhD, MSc, and BSc students, with several of his former students securing academic positions at institutions like University of Leiden, Tokyo Institute of Technology, and Budapest University of Technology. Hirsch leads a research group within the Stochastics group at Aarhus University, collaborating extensively with researchers across Europe and North America. His work demonstrates how topological methods can provide rigorous statistical insights into complex data structures, making significant contributions to both theoretical mathematics and practical data analysis techniques.
