Taro Mieno is an Associate Professor in the Department of Agricultural Economics at the University of Nebraska-Lincoln, specializing in precision agriculture and water resource economics. His work bridges agricultural policy, spatial econometrics, and environmental sustainability. University: University of Nebraska-Lincoln Department: Agricultural Economics Academic Rank: Associate Professor Research Interests: Precision agriculture and variable rate technologies Groundwater economics and drought resilience On-farm experimentation and data-driven decision making Agricultural policy and environmental externalities Machine learning applications in agronomic optimization Soil-water interactions and resource management Email: tmieno2@unl.edu
Dr. Sahani Pathiraja is a Lecturer (tenure track assistant professor) at UNSW Sydney , specializing in Data Science . Her research bridges mathematical and statistical foundations with practical applications in environmental and biomedical sciences. Research Focus : Sequential Bayesian inference, Monte Carlo methods, stochastic analysis of non-linear filtering, uncertainty quantification, and real-time parameter estimation. Current Projects : Co-investigator in the ARC Industrial Transformation Training Centre: Data Analytics for Resources and Environment (DARE) and the Next Generation Graduate Program (NGGP) in Sports Data Science and AI . Research Supervision : Dr. Pathiraja supervises PhD students in areas including: Bayesian inference Stochastic differential equations Data assimilation Non-linear filtering Scientific Collaborations : Her work intersects with environmental science, biomedical applications, and machine learning. Projects include stochastic hydrology, SDEs, and operator learning for environmental systems. Contact Information : Email: s.pathiraja@unsw.edu.au Phone: +61 2 8065 0836 Office: Room 2070, Level 2, The Red Centre, UNSW Sydney
Professor Stefan Siebert is Head of the Department of Crop Sciences at the Agricultural Faculty of the University of Göttingen, a position he has held since October 2017. His academic career spans multiple prestigious institutions including the University of Bonn, University of Frankfurt, and University of Kassel, where he completed his doctoral studies. University of Göttingen (2017-present): Professor and Head of Crop Science/Agronomy University of Bonn (2016-2017): Temporary Head of Chair Crop Science University of Bonn (2009-2015): Habilitation in Crop Science and Resource Conservation University of Frankfurt (2004-2009): Postdoctoral Scientist University of Kassel (2002-2005): Ph.D. Student and Scientist Professor Siebert's research focuses on sustainable resource use in crop production, climate change impacts on plant growth, plant growth modeling, and drought risk assessment. His work integrates large-scale data analysis with modeling approaches to understand the complex interactions between resource use, crop management, and productivity. He has developed comprehensive datasets on water, soil, and nutrient use in agriculture and pioneered methods for analyzing irrigation systems globally. His recent publication trends reveal a strong emphasis on irrigation systems, climate change impacts on agriculture, and advanced crop modeling techniques. The analysis of his 15 most recent articles shows consistent focus on water resource management, spatial analysis of agricultural systems, and the effects of climate variability on crop production. His work frequently combines remote sensing data with ground-based measurements to create high-resolution datasets for agricultural decision-making. Professor Siebert leads several significant research projects including ZERN (Future of Nutrition in Lower Saxony, 2024-2029), Collaborative Research Center 1502 on Regional Climate Change (2022-2025), and OUTLAST (Development of a global drought hazard forecasting system, 2022-2025). He has been continuously developing and maintaining a global dataset on irrigated areas since 1997, establishing himself as a leading authority in agricultural water management. His teaching portfolio is extensive, covering scientific writing, field production exercises, general crop production, methodical work, plant biology, crop production and breeding, sustainability of production systems, and applications of data analysis to agronomy. Professor Siebert's work bridges theoretical research with practical applications in sustainable agriculture, making significant contributions to our understanding of how to maintain food security in the face of climate change.
Harpa Birgisdottir is a Professor and Head of the Building Sustainability Section at Aalborg University's Department of Construction, Urban and Environmental Engineering. Her work focuses on Life Cycle Assessment (LCA), net-zero carbon buildings, and circular economy strategies in construction. Key Research Areas: Greenhouse Gas Emissions, Environmental Product Declarations (EPD), Urban Development, and Climate Mitigation Academic Recognition: 2022 Best Paper at Sustainable Built Environment, 2020 Applied Energy Highly Cited Award Research Trends Recent publications emphasize data-driven sustainability assessments, embodied carbon in buildings, and fire safety LCA tools. She leads EU-wide projects on greenhouse gas emissions and co-develops frameworks for net-zero carbon buildings through IEA EBC Annex 89. Scientific Awards Best Paper (Sustainable Built Environment Berlin 2022) Highly Cited Research Paper (Applied Energy 2020) Det Bæredygtige Element - Produktprisen (2019) ROCKWOOL Prisen (2017) Best Paper (2013) As a principal investigator and supervisor, she guides PhD projects on biobased fire safety and urban circularity. Her team collaborates with international researchers on climate impact metrics and sustainable construction standards.
Zeenat Kotval-Karamchandani, Ph.D., AICP is an Associate Professor of Urban & Regional Planning and Director of the M.U.R.P. Program at Michigan State University's School of Planning, Design and Construction. She joined the Urban & Regional Planning Program at SPDC in 2013 as an instructor and has established herself as a leading researcher in food systems, transportation planning, and aging population mobility. Education: PhD in Geography from Michigan State University Master in Urban & Regional Planning from Michigan State University Master in Hospitality Administration from University of Massachusetts, Amherst Bachelor of Commerce from Mithibai College of Arts, Science and Commerce Research Interests: Dr. Kotval-Karamchandani's research focuses on critical urban planning issues including food access systems in developing countries like Mumbai, India; mobility challenges for aging populations in Michigan; and travel behavior impacts in urban and suburban areas of Michigan, particularly Detroit. Her work integrates spatial analysis, survey research, and statistical tools to examine the intersection of transportation infrastructure, environmental burdens, and public health outcomes. She applies her expertise in GIS and SPSS to address complex planning challenges related to food deserts, aging in place, and sustainable mobility. Recent Publications: Dr. Kotval-Karamchandani's recent work demonstrates a strong focus on food systems during the pandemic, emotional aspects of urban design through the eMOTIONAL Cities project, and sociomobility research. Her publications reflect an interdisciplinary approach combining urban planning, public health, and transportation studies, with particular attention to vulnerable populations including older adults and residents of food deserts. Awards: MSU Outstanding Faculty Award (2016) Grants and Research Leadership: Dr. Kotval-Karamchandani has secured significant research funding including a $106K grant from the Urban Institute and Robert Wood Johnson Foundation to address factors influencing health of older adults in Michigan, and multiple MDOT grants totaling over $650K to study Michigan's public transit systems. She leads the Autonomous Futures and MSU Mobility initiatives, focusing on emerging transportation technologies and their impacts on community planning.
Professor Stephen Jenkins is a leading expert in Economic and Social Policy at the London School of Economics and Political Science (LSE) since 2011, with a focus on inequality , poverty dynamics , and applied econometrics . He has held leadership roles including Head of the Department of Social Policy (2016-2019, 2023-2024) and coordinates the Global Inequalities Observatory at LSE’s International Inequalities Institute. Education: BSc in Economics, University of Otago (1974-1977) PhD in Economics, University of York (1983) His research interests span: Analysis of income distribution, redistribution via taxation and social security Income mobility and poverty dynamics Measurement errors in survey and administrative data Survival analysis and limited dependent variable models Recent research trends emphasize: Top-income inequality using tax and survey data Labour market volatility and income risk Policy impacts on inequality and poverty Statistical methods for income distribution analysis Scientific awards and honors : Presidency of three major global associations: IARIW (2006-08), ECINEQ (2021-23), ESPE (1998) Distinguished Fellow of the New Zealand Association of Economists (2019) Research Fellow at IZA, Bonn (since 2000) Editorial leadership roles: Journal of Economic Inequality (2014-17), The Stata Journal (current) Advising and grants : Supervises doctoral research in inequality, poverty, and econometrics Contributed to high-impact policy reports for UK DWP, OECD, and New Zealand Treasury REF2021 Impact Case Study: Better measurement of income inequality Member of scientific advisory boards for IAB, WIFO, and Motu Labs and teams : Coordinator of the Global Inequalities Observatory at LSE Key member of LSE’s Department of Social Policy and International Inequalities Institute Collaborates with institutions including IZA, Motu, and IAB
Nikitas Karanikolas serves as Professor in the Department of Informatics and Computer Engineering at the University of West Attica since March 2018, following a distinguished career progression from Assistant Professor (2004) to Associate Professor (2010) and Professor (2014) at the Technological Educational Institute of Athens. His professional trajectory includes significant roles as Systems Head of TEI Athens Library (1996-1997) and Chief of Informatics at Aretaieio University Hospital (1997-2004), alongside leadership positions in the Greek Computer Society as Board Member (2004-2006) and Secretary General (2006-2008). His academic foundation includes: Bachelor's in Statistics and Informatics from Athens University of Economics and Business (1988) PhD in Applied Informatics from Athens University of Economics and Business (1994) with thesis "Technological and Linguistic approaches in Natural Language Understanding" Dr. Karanikolas maintains an exceptionally broad research portfolio spanning Natural Language Processing , Computational Linguistics , Medical Informatics , and Green Energy systems. His work consistently bridges theoretical computational frameworks with practical healthcare applications, particularly evident in recent dementia care technologies and Greek language processing systems. The interdisciplinary nature of his research connects computational phonology with medical diagnostics and e-government applications. Analysis of his 15 most recent publications reveals a pronounced shift toward AI-driven healthcare solutions (particularly dementia patient monitoring), multilingual NLP systems (Greek and Polish), and urban safety applications . His work demonstrates consistent methodology development in ontological representations and multimodal fusion techniques, with increasing emphasis on real-world clinical and governmental implementations since 2023. No scientific awards were documented in the source materials. With 16 journal papers, 68 conference publications, and six authoritative Greek university textbooks, Dr. Karanikolas maintains an active research trajectory. His advising capacity is evidenced through extensive publication mentorship, particularly in medical informatics and NLP projects. While specific grant details are unavailable, his hospital information system implementations and textbook authorship suggest successful research funding acquisition. Current research activities focus on multimodal aggression prediction systems for dementia care, Greek language ontological frameworks, and urban navigation safety applications, primarily conducted through the University of West Attica's informatics infrastructure.
Dr. Jing Zhang is an Assistant Professor in the Department of Computer Science at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences. She holds a Ph.D. in Electrical Engineering and Molecular/Computational Biology from the University of Southern California (2012) and completed postdoctoral training in Computational Biology at Yale University. Her research focuses on developing computational methods to unravel gene regulation mechanisms and link genetic variations to diseases, particularly in noncoding regions of the genome. She has contributed extensively to the ENCODE project, co-authoring pivotal studies in Nature and producing over 5,900 experimental datasets. Dr. Zhang’s work bridges engineering, mathematics, and biology, with applications in precision medicine for cancers and psychiatric disorders. She emphasizes the importance of noncoding DNA in disease causation and has pioneered tools like EN-TEx and scENCORE to analyze epigenomes and regulatory elements. Her lab actively seeks to recruit Ph.D. students, postdocs, and interns to advance genomic technologies. Key research areas include single-cell and spatial transcriptomics, gene regulatory networks, and computational methods for multi-omics data integration. Despite pandemic-related challenges, she maintains strong collaborations and teaches courses in bioinformatics. Her future goals include expanding lab interactions and applying computational models to predict disease susceptibility and treatment responses.
Prof. Sara Merino Aceituno is a Professor at the Faculty of Mathematics, University of Vienna, leading research in kinetic theory and its applications to biology, medicine, and social sciences. She holds roles as Vice-Dean of the Faculty and Head of the Institute of Mathematics. Her work bridges mathematical models with experimental data, focusing on emergent phenomena in collective dynamics, opinion formation, and cell behavior. She teaches advanced courses on kinetic theory, biomathematics, and mathematical strategies for learning. Her contributions include modeling cell delamination, nematic alignment, and swarm dynamics through PDEs and probabilistic methods. Collaborations with experimentalists drive her interdisciplinary research. She actively engages in education, advising, and public outreach, including a video series explaining mathematical patterns in nature. Her research emphasizes understanding macroscopic patterns arising from microscopic interactions in complex systems. Education: Holds a PhD in Mathematics, with expertise in kinetic theory and applied partial differential equations. Teaching and leadership roles reflect her commitment to academic excellence and student support. Her work integrates experimental and computational models to study clonal dynamics in tissues and mechanical constraints in epithelial layers. She has authored over 20 papers on topics ranging from active matter to opinion formation networks, contributing to both theoretical advancements and practical applications in biology and social sciences. Research focuses on deriving hydrodynamic and continuum models from particle systems, analyzing stability and bifurcations in collective behavior. Grants and collaborations include the Vienna Biocenter PhD Program and experimental groups in cell biology. Her lab explores how environmental factors influence particle swarms and how mechanical forces shape cell cycles in pseudostratified epithelia.
Ted Mouw is a Professor of Sociology at the University of North Carolina at Chapel Hill. He holds a B.A. in English Literature from Oberlin College, an M.A. in Economics, and a Ph.D. in Sociology from the University of Michigan. His research focuses on demography, social stratification, and economic sociology, with emphasis on labor markets, globalization’s impact, and immigration. Current projects include studies on social mobility in the U.S., economic effects of globalization in Indonesia and Mexico, and labor market dynamics for Hispanic immigrants in North Carolina. He has taught courses such as Social Stratification, Economy and Society, and Applied Regression Analysis, reflecting his expertise in quantitative methods and social theory. His work frequently intersects with the Carolina Population Center and addresses topics like occupational segregation, wage inequality, and transnational social networks. Mouw’s research also explores the interplay between spatial diffusion, migration patterns, and racial/ethnic integration in urban areas.
Prof. Floris de Lange is a Professor at the Donders Institute for Brain, Cognition and Behaviour, Radboud University, and holds a part-time W3-Professorship in Cognitive Computational Neuroscience at the University of Bonn. His research focuses on understanding how top-down factors like goals, attention, expectations, and prior knowledge shape perception, cognition, and decision-making. He uses behavioral and neuroimaging techniques (MEG, fMRI, TMS) to study these processes in healthy and pathological brains. Key research themes include predictive perception, attention, and the neural mechanisms underlying decision-making. His work has been supported by prestigious grants such as the Vici and ERC Consolidator Grants. He teaches courses on Attention and Prediction, Cognitive Control, and Neurophysiology of Cognition and Behaviour. Education: Not explicitly stated in the provided text. Awards: Vici Grant (NWO), ERC Consolidator Grant, Ammodo Science Award, and others. Labs/Teams: Leads the Predictive Perception and Cognition group within the Donders Institute. His research highlights the brain’s predictive nature, demonstrating how expectations modulate sensory processing in early visual cortex and influence decision-making. He collaborates internationally, including an adversarial testing project on theories of consciousness.
Liang Choon Wang is an Associate Professor and Economics PhD Program Director at the Department of Economics, Monash University. He holds a PhD from the University of California San Diego (2010), where he was a Spencer Foundation Dissertation Fellow. Prior to joining Monash in 2011, he worked at the World Bank’s Development Research Group in Washington DC. His research focuses on behavioral economics, education economics, labor economics, development economics, public economics, and health economics, employing field/natural experiments and observational data to analyze outcomes in both developed and developing nations such as Australia, Bangladesh, India, and Vietnam. He has led and contributed to research projects including the 'Reliable Affordable Clean Energy for 2030 CRC' and studies on affirmative action, energy conservation, and educational interventions. His work contributes to UN Sustainable Development Goals, particularly in reducing inequalities and promoting sustainable development. Key publications include studies on electoral competence, remote learning efficacy in Bangladesh, and the impact of housing costs on transportation. Education: PhD in Economics, University of California San Diego (2010) Grants/Projects: Multiple grants from RACE for 2030 CRC, World Bank collaborations, and randomized controlled trials in education and health. Teaching: ECC4860 (2012–2015) and ECC2400 (2016–present). Wang’s research emphasizes policy relevance, with contributions to government technical assistance and global equity initiatives. His recent articles analyze low-tech education solutions, energy conservation, and labor market dynamics, reflecting his interdisciplinary approach to socio-economic challenges.
Yudong Chen is an Assistant Professor in the Department of Statistics at the University of Warwick, starting September 2024. Previously, he was an LSE Fellow (2023–2024) and a postdoctoral researcher at the London School of Economics. He holds a PhD in Statistics from the University of Cambridge (2023), with a thesis on High-dimensional Online Changepoint Detection, supervised by Richard J. Samworth and Tengyao Wang. His research focuses on changepoint detection, high-dimensional statistics, robust methods, and machine learning. Education: PhD in Statistics, University of Cambridge (2023) MA & MMath in Mathematics, University of Cambridge (2018) BA in Mathematics, University of Cambridge (2018) Teaching: University of Warwick: Module leader for ST420 Statistical Learning and Big Data (2024/25) LSE: Taught ST202/6 Probability, ST447 Data Analysis, and ST449 Artificial Intelligence His research interests span statistical methodologies including online algorithms, robust statistics, and spatial models. He has published in top journals like the Journal of the American Statistical Association and presented at venues such as the IMS Annual Meeting. Awards include the LSE Class Teacher Award (2023) and the Smith–Knight Prize (2020). Grants: Worked on EPSRC-funded research on 'Change-point analysis in high dimensions' at LSE. Labs/Teams: Engaged in collaborative projects on online changepoint detection and statistical methodologies.
Zheng Li is an Assistant Professor in the Department of Agricultural and Resource Economics at North Carolina State University. His research focuses on econometric methodologies with applications in agricultural economics, resource management, and policy analysis. He holds expertise in nonparametric estimation, quantile regression, and structural econometric modeling. Key research interests include analyzing agricultural production risks, evaluating policy impacts on housing markets, and developing advanced statistical techniques for mixed data types. His work bridges econometric theory with practical applications in environmental, urban, and transportation sectors. Recent publications explore topics such as lung cancer detection via biomedical sensing technologies, ridesharing platform incentives, and pandemic effects on real estate markets. Methodologically, his contributions span kernel-based specification tests, bootstrap methods for heavy-tailed data, and monotonicity-constrained estimation techniques. No scientific awards or formal advisees are listed. His research often intersects with interdisciplinary challenges, reflecting a commitment to innovative solutions in applied economics and data science.
Glenn Boreman is a Professor and Chair of the Department of Physics and Optical Science at the University of North Carolina at Charlotte (UNC Charlotte). He also serves as Director of the Center for Optoelectronics & Optical Communications. His academic journey includes a BS in Optics from the University of Rochester and a PhD in Optics from the University of Arizona. Previously, he spent over 27 years at the University of Central Florida, supervising 25 PhD students to completion. His research focuses on infrared antennas, metamaterials, frequency-selective surfaces, and nano-scale optical phenomena. Notable contributions include pioneering work on antenna-coupled infrared sensors and the design of advanced optical systems. He has authored/co-authored over 190 journal articles and four textbooks, including Infrared Detectors and Systems and Modulation Transfer Function in Optical & Electro-Optical Systems . Prof. Boreman holds prestigious fellowships from SPIE, IEEE, the Optical Society of America, and the Military Sensing Symposium. His awards include the 'Best Paper' honor at the 2001 AIAA/BMDO meeting. His lab, the Infrared Systems Lab, actively explores nanofabrication, high-resolution lithography, and advanced sensor technologies. Current doctoral students include Matthew Potter and Frances Bodrucki, both researching infrared devices and metamaterials. He directs interdisciplinary projects involving collaborators from materials science, electrical engineering, and astrophysics.
