Markus Reichstein is a Professor for Global Geoecology at Friedrich Schiller University (FSU) Jena and Director of the Biogeochemical Integration Department at the Max Planck Institute for Biogeochemistry. His research focuses on ecosystem responses to climate variability, climate extremes, and the application of AI in Earth system science. He holds a PhD in Plant Ecology from the University of Bayreuth and has pioneered interdisciplinary approaches combining machine learning with environmental modeling. Key roles include leadership in the Michael-Stifel-Center Jena for Data-driven and Simulation Science and founding director of the ELLIS Unit Jena. He contributed to the IPCC Special Report on Climate Extremes and has received prestigious awards such as the Leibniz Prize. His work bridges ecology, hydrology, and atmospheric science, addressing critical global challenges like carbon cycle feedbacks and ecosystem resilience. Recent research emphasizes AI-driven early warning systems for climate risks, integrating observational data with mechanistic models. His team explores land-atmosphere interactions, soil-vegetation dynamics, and the impacts of climate extremes on societal systems. Notable projects include GartenDiv, a citizen science initiative for garden biodiversity, and advancements in global water cycle modeling using hybrid AI-physics frameworks. Awards include the Piers J. Sellers Award (2018), ERC Synergy Grant (2019), and Leibniz Prize (2020). He collaborates with international networks like ELLIS and Future Earth, advancing data-driven solutions for sustainability science.
Professor Lindsay Turnbull is a Professor of Plant Ecology at the University of Oxford's Department of Biology. Her research focuses on understanding the evolutionary and ecological basis of plant trait diversity and its consequences for ecosystems. Key interests include seed size variation, plant-soil interactions, and the impact of organic farming on biodiversity. She leads a research group exploring topics such as mutualism stability, species coexistence, and island conservation genetics. Turnbull's work integrates experimental, observational, and computational approaches to address fundamental questions in ecology. Her lab, based at the Department of Biology (Mansfield Road and South Parks Road campuses), has contributed to global understanding of biodiversity-ecosystem functioning relationships and plant-microbe symbioses. Notable projects include studies on Aldabra giant tortoises and coral reef connectivity in the Seychelles, highlighting her commitment to applied conservation science. Her research spans multiple scales—from molecular interactions in legume-rhizobia systems to large-scale biodiversity patterns in grasslands and tropical ecosystems. Recent work emphasizes the role of trait-based approaches in predicting ecological responses to environmental changes such as eutrophication and climate variability. Her publications frequently bridge theoretical and applied ecology, offering insights into both natural and human-managed ecosystems.
Shili Lin is a Professor of Statistics at The Ohio State University's Department of Statistics, within the College of Arts and Sciences. She joined the faculty in 1995 after serving as the Neyman Visiting Assistant Professor at the University of California, Berkeley. Her expertise spans statistical genomics, bioinformatics, high-dimensional data analysis, Bayesian statistics, and Monte Carlo methods. Lin collaborates extensively with medical researchers to address challenges in genomic data such as ultra-high dimensionality, complex dependencies, and sparsity, focusing on diseases like cancer, multiple sclerosis, tuberculosis, and diabetes. She has contributed to developing computational tools for analyzing chromatin interactions, methylation patterns, and metagenomic samples. Lin holds a PhD from the University of Washington (1993). Her professional roles include serving as an Associate Editor for Biometrics , Statistical Applications in Genetics and Molecular Biology , and Statistics in Biosciences , as well as an Editorial Board member for Genetic Epidemiology . She is a standing member of NIH's Biostatistical Methods and Research Design Study Section and has served on multiple NSF and NIH grant review panels. Additionally, she is President Elect of the Caucus for Women in Statistics and has been a member of the ASA Committee on AAAS representation for six years. Her research interests emphasize statistical methodologies tailored to genomic data, including model selection, epigenetic analysis, and integrative approaches for multi-omics data. Lin's work often combines theoretical advancements with practical applications, such as predicting relapse in immune-mediated disorders and improving imputation techniques for single-cell Hi-C analysis. She has pioneered software tools like TopKLists and GrammR to facilitate ranked list aggregation and metagenomic data analysis. Lin's scientific accolades include ASA Fellowship (2004), AAAS Fellowship (2009), and membership in the International Statistical Institute (2014). Her contributions to statistical genetics and epigenomics have been recognized through grants and editorial leadership roles. While her research group focuses on cutting-edge methods, no formal advisees or students are explicitly listed in the provided materials.
Zhaoli Song is an Associate Professor at the Department of Management and Organisation within NUS Business School, Singapore. His research bridges behavioral genetics with organizational behavior, focusing on leadership, AI in the workplace, cross-cultural management, and work-family dynamics. PhD in Human Resources and Industrial Relations (2004), University of Minnesota Master in Statistics (2004), University of Minnesota Master in Applied Psychology (1999), Chinese Academy of Sciences Bachelor in Optics (1995), Sichuan University Dr. Song pioneered molecular genetics applications in management research, achieving media recognition in Economist and Washington Post . His work spans AI strategy formulation, pandemic scenario modeling, and team innovation across Asia. He has taught organizational behavior, HRM, and research methods at undergraduate, Master's, EMBA, and executive levels. Recent publications analyze AI adoption frameworks, emotional dynamics in leader-member exchanges, and genetic determinants of creativity. He served as Academic Director for NUS Asian Pacific EMBA (Chinese) program (2013-2017), demonstrating educational leadership alongside scholarly contributions.
Giulia Giordano is a Full Professor in the Department of Industrial Engineering at the University of Trento, Italy, where she leads the Dynamical Networks and Systems Biology research group. She also holds a dual appointment as Visiting Professor and Delft Technology Fellow at the Delft Center for Systems and Control, Delft University of Technology, The Netherlands. Her career includes previous positions as Assistant Professor at Delft University of Technology (2017-2019), Postdoctoral Research Fellow at Lund University, Sweden (2016-2017), and Research Fellow at the University of Udine, Italy (2016). Giulia earned her Ph.D. in Industrial and Information Engineering: Automation (Excellent) from the University of Udine with a thesis titled "Structural Analysis and Control of Dynamical Networks." She completed her M.Sc. and B.Sc. in Electrical Engineering (both Summa cum laude) at the same institution. She also undertook research visits at Caltech (2012) as a SURF Fellow and at the University of Stuttgart (2015) as a DAAD Research Scholar. Her primary research focuses on the analysis and control of dynamical networks with applications in systems biology, mathematical ecology, and mathematical epidemiology. She develops mathematical frameworks that bridge control theory, network theory, and dynamical systems to address complex problems in biological systems. Her recent work spans epidemic modeling, opinion dynamics, biochemical networks, and neurological disorders, with a particular emphasis on structural analysis of networked systems. She employs both theoretical and computational approaches to understand system behavior under uncertainty. Giulia's publications reveal a strong interdisciplinary focus, spanning from theoretical control systems to practical applications in epidemiology and biology. Her recent work shows increasing emphasis on epidemic modeling (particularly related to mpox and SARS-CoV-2), network synchronization, and the application of control theory to biological phenomena like fibromyalgia pathogenesis and opinion formation. Many of her papers appear in top-tier control journals including Automatica and IEEE Transactions on Automatic Control. 2024: Outstanding Service as Associate Editor of IEEE Control Systems Letters 2021: SIAM Activity Group on Control and Systems Theory Prize 2020: Outstanding Reviewer, Annals of Internal Medicine 2017: NAHS Best Paper Prize and EECI PhD Award 2016: Outstanding TAC Reviewer, IEEE Transactions on Automatic Control Giulia actively mentors students and postdoctoral researchers, currently supervising five postdoctoral researchers and two Ph.D. students at the University of Trento. She has advised numerous M.Sc. and B.Sc. students on topics ranging from bio-inspired modeling to optimal control of epidemic systems. Her research is supported by competitive grants including the ERC Starting Grant INSPIRE (Integrated Structural and Probabilistic Approaches for Biological and Epidemiological Systems). She serves as Associate Editor for IEEE Control Systems Letters and Automatica, and is a Senior Member of IEEE and the Control Systems Society. Giulia leads the Dynamical Networks and Systems Biology research group at the University of Trento, which maintains strong international collaborations across Europe and North America. The group's work combines theoretical advances in control theory with practical applications to pressing problems in public health and biological systems, demonstrating the power of mathematical approaches to understanding complex phenomena in the life sciences.
Christopher Lawson is an Assistant Professor in the Department of Chemical Engineering and Applied Chemistry at the University of Toronto, affiliated with the Faculty of Applied Science and Engineering. He serves as Principal Investigator of the Microbiome Engineering Lab and is part of BioZone – the Centre for Applied Bioscience and Bioengineering. His research focuses on engineering anaerobic microbiomes for resource recovery from waste streams using systems biology, synthetic biology, and machine learning approaches. B.A.Sc., M.A.Sc. (University of British Columbia) Ph.D. (University of Wisconsin-Madison) Postdoctoral Training (Berkeley Lab) Lawson's work addresses the challenge of controlling complex microbial interactions in engineered systems to enable scalable biotechnologies for renewable energy, chemicals, and materials. His lab develops high-throughput methods integrating automation and computational tools to optimize microbiome assembly and metabolic fluxes. Recent publications highlight advancements in metabolic modeling , isotope tracing , and systems-level analysis of anaerobic microbiomes, with applications in wastewater treatment , anammox granules , and bioenergy production . His research bridges fundamental microbiology with industrial-scale bioprocess engineering. Scientific Awards ISME/IWA BioCluster Rising Star Award (2022) Jacobs Engineering Group/AEESP Outstanding Doctoral Dissertation Award (2020) Wesley Eckenfelder Graduate Research Award (2019) WEF Canham Graduate Studies Scholarship (2018) NSERC Post-Graduate Scholarship – Doctoral (2014) Lawson actively mentors students and postdocs, emphasizing technical rigor, communication skills, and independence. His lab collaborates within BioZone and with industry partners to advance "team science" principles. Current projects focus on creating engineered microbiomes for commercial-scale waste valorization.
Elizabeth Phelps is the Pershing Square Professor of Human Neuroscience in the Department of Psychology at Harvard University's Faculty of Arts and Sciences. She directs the Phelps Lab, which investigates how emotions influence learning, memory, and decision-making using multidisciplinary approaches including behavioral studies, neuroimaging (fMRI), physiological measurements, and computational modeling. The lab collaborates widely across psychology, neuroscience, economics, and clinical disciplines. Her research examines: Human neuroscience of affect and cognition interactions Emotional modulation of learning and memory systems Neural mechanisms of decision-making under uncertainty Impact of emotion on social cognition and behavior Translational applications for psychological disorders Contact information: Email: phelps@fas.harvard.edu Lab email: phelpslab@fas.harvard.edu Address: Northwest Lab Building, 52 Oxford Street, Cambridge, MA 02138 The lab welcomes study participants and research assistant applicants, emphasizing diversity and inclusion in research.
Ross Meentemeyer is a Professor and Director of the Center for Geospatial Analytics at North Carolina State University, affiliated with the Department of Forestry and Environmental Resources in the College of Natural Resources. He holds a Ph.D. in Geography from the University of North Carolina, Chapel Hill (2000) and a B.S. in Geography from the University of Georgia (1993). His research focuses on geospatial analytics, ecological forecasting, biological invasions, and forest health, with a strong emphasis on integrating geospatial data and modeling to address environmental challenges. Dr. Meentemeyer's work includes developing decision-support tools for pest management, climate adaptation, and land-use planning. Notable projects involve forecasting invasive species spread via international trade, creating open-source geospatial platforms, and modeling floodplain development risks. He collaborates extensively with federal agencies like USDA, DOI, and NPS to translate research into practical solutions. His grants include multi-million dollar NSF and USDA-funded initiatives addressing plant disease pandemics, agricultural pest threats, and geospatial infrastructure development. Key outcomes include the PAdb system for pandemic prediction and the FUTURES model for urbanization forecasting. He also leads efforts to enhance stakeholder engagement through participatory modeling tools like Tangible Landscape. Research contributions span 20+ years, with over 100 peer-reviewed articles on topics like viewscape modeling, river water dynamics, and wildfire-epidemic interactions. His work bridges ecological and social sciences, emphasizing actionable solutions for sustainable land management and climate resilience.
Dr. Jason Gibbs is an Associate Professor in the Department of Entomology at the University of Manitoba, Faculty of Agricultural and Food Sciences. He also serves as the Curator of the J. B. Wallis / R. E. Roughley Museum of Entomology (WRME), a significant center for the study of bee biodiversity. His work is central to advancing knowledge in wild bee systematics, phylogenetics, and conservation. PhD in Biology, York University, Canada MSc in Botany, University of Toronto, Canada BSc in Biological Sciences, University of Toronto Scarborough, Canada His research focuses on the diversity, taxonomy, and conservation of wild bees , particularly halictid and panurgine bees. He employs integrative taxonomic approaches , combining morphological, molecular, and ecological data to resolve species boundaries and evolutionary relationships. His work extends to pollinator ecology , examining how habitat management, agricultural practices, and landscape changes affect bee communities and pollination services. He is deeply involved in bee conservation , including the rediscovery of rare species and the development of habitat strategies to support pollinators in human-modified landscapes. The trends in his recent publications reveal a strong emphasis on systematics and alpha-taxonomy , with numerous revisions of bee genera and checklists of regional faunas. He frequently uses DNA barcoding and phylogenomics to address taxonomic challenges. Additionally, his work explores pollination dynamics in agricultural systems , particularly in blueberry and other crops, assessing the roles of wild versus managed bees. There is a consistent theme of habitat enhancement and conservation across his research, with studies on floral strips, prairie restoration, and the impacts of land-use change. Dr. Gibbs is actively involved in mentoring and training the next generation of entomologists. His lab includes several graduate students and highly qualified personnel who contribute to his diverse research projects, as indicated by the asterisked names in his publications. He leads the Gibbs Wild Bee Lab, which is dedicated to understanding bee diversity and evolution. The lab combines field research with molecular and morphological analyses, and maintains close ties with the WRME museum, which serves as a vital resource for specimen-based research and education.
Stacy Farina is an Associate Professor in the Department of Biology at Howard University, affiliated with the College of Arts & Sciences. Her research focuses on functional morphology, biomechanics, and evolutionary biology, particularly in fish systems. She holds a B.S. in Marine and Freshwater Biology from the University of New Hampshire (2010) and a Ph.D. in Evolutionary Biology from Cornell University (2015). Her work examines skeletal morphology, respiratory systems, and functional adaptations in diverse fish species, including flatfishes, snailfishes, and elasmobranchs. Recent studies investigate remote research methodologies during the pandemic, deep-sea adaptation, and biomechanical integration in feeding systems. She directs a research lab in Just Hall, Room 410, and maintains a Google Scholar profile. Publications span topics like ventilation mechanics, acoustic signaling evolution, and skeletal density patterns in deep-sea environments. Her research emphasizes interdisciplinary approaches, combining anatomical analysis, computational modeling, and experimental biomechanics. No scientific awards or grants are explicitly listed in the provided texts. She advises no listed students, though her research involves undergraduate participation. Her lab focuses on fish morphology, ecology, and evolutionary processes.
Dr. Nancy L. Sin is an Associate Professor in the Department of Psychology within the Faculty of Arts at the University of British Columbia. She teaches undergraduate and graduate courses in health psychology and supervises students at multiple levels. She is Co-Chair of the Antiracism Task Force for the Society for Biopsychosocial Science and Medicine and a member of the Steering Committee at the UBC Edwin S.H. Leong Centre for Healthy Aging. Previously, she served on the Executive Committee for the American Psychological Association's Division on Adult Development and Aging and established the Diversity Mentorship Program. PhD, University of California, Riverside, 2012 Dr. Sin's research focuses on biological and behavioural pathways linking daily well-being and stress to health. Her work demonstrates that emotional responses to daily stressors are associated with inflammatory, neuroendocrine, and autonomic mechanisms implicated in aging-related conditions like cardiovascular disease. She investigates daily positive events as protective factors for stress processes and health, with particular interest in emotional well-being and aging, stress-sleep cycles, and health equity. Her research spans multiple disciplines including health psychology, gerontology, and social psychology. Analysis of Dr. Sin's recent publications reveals consistent focus on daily stress processes, positive emotions, and health outcomes across the lifespan. Her work increasingly examines pandemic-related stressors, social determinants of health, and health disparities, with strong emphasis on methodological rigor through daily diary and longitudinal approaches. The publications demonstrate interdisciplinary collaboration across psychology, public health, and medicine, with growing attention to diversity, equity, and inclusion in health research. Distinguished Alumni Award, Department of Psychology, University of California, Riverside (2025) Fellow, Gerontological Society of America (2025) Innovative Research on Aging Award (Bronze Award) from the Mather Institute (2021) Michael Smith Foundation for Health Research Scholar (2020) Springer Early Career Achievement Award in Research on Adult Development and Aging (2019) Gerontological Society of America's Behavioral and Social Sciences Student Research Award Editor's Choice article at Annals of Behavioral Medicine Dr. Sin actively supervises undergraduate, MA, and PhD students, with a current focus on Health Psychology graduate students specializing in adult development and aging, stress, and health equity/disparities. Her research has been supported by significant grants as PI or Co-I from the U.S. National Institute on Aging, Social Sciences and Humanities Research Council of Canada, Canadian Institutes of Health Research, Canada Foundation for Innovation, and the Michael Smith Foundation for Health Research. She has established a strong research program examining daily experiences and their health implications across adulthood. Dr. Sin directs the UPLIFT Health Lab (Understanding Pathways Linking Inter- and Intraindividual Factors To Health), which explores psychosocial well-being and biobehavioural mechanisms underlying healthy aging. The lab investigates how daily positive events promote health through lower inflammation, adaptive cortisol profiles, and better health behaviors, with particular attention to how positive emotions buffer stress processes. The lab actively recruits community participants for studies on daily experiences and health, contributing to intervention development for promoting psychological and physical well-being across adulthood.
Gary M. Shaw is the Rosemarie Hess Professor and Professor (Research) at Stanford University , with courtesy appointments in the Department of Epidemiology and Population Health and Department of Obstetrics & Gynecology - Maternal Fetal Medicine . He serves as Co-PI of the March of Dimes Prematurity Research Center at Stanford and PI of the California Center for Finding Causes and Preventives of Birth Defects . His research focuses on the Epidemiology of birth defects Gene-environment interactions in perinatal outcomes Nutritional factors in reproductive health . He has developed machine learning approaches for precision parenteral nutrition and predictive models for preterm birth, while investigating persistent metabolomic signatures following hypertensive pregnancy disorders. Shaw's recent work explores Climate change impacts on reproductive health Maternal-fetal immune interactions Epigenetic mechanisms in perinatal disease with applications of multiomics to neonatal intensive care units. As a member of Bio-X and the Maternal & Child Health Research Institute , he contributes to translational research networks while serving as Associate Editor for Birth Defects Research and American Journal of Medical Genetics . He supervises Med Scholar Project student Richard Liang Doctoral co-advisor for Saskia Comess and Richard Liang Master's advisor for Lenae Joe while leading the Division of Neonatology as Associate Chair for Clinical Research (2012-2025). His laboratory work integrates Metabolomic profiling Proteomic analysis Computational modeling Machine learning for biomedical data to advance neonatal care through precision medicine approaches.
Deqiong Ma is an Assistant Professor in the Department of Genetics at Yale University School of Medicine and Associate Director of the DNA Diagnostic Laboratory. She holds an MD from Tongji Medical University (1991), a PhD from the University of Tasmania (2003), and completed a postdoctoral fellowship at Duke University and a clinical fellowship at Albert Einstein College of Medicine. Her research focuses on genetic and genomic mechanisms underlying autism spectrum disorders, particularly copy number variants (CNVs), structural variation analysis, and clinical diagnostic methodologies. Key research interests include identifying novel genetic risk factors for autism using advanced genomic techniques, such as homozygosity mapping and fine-scale structural variation analysis. Her work bridges clinical genetics and molecular biology, with applications in diagnostic testing and understanding neurodevelopmental disorders. She collaborates extensively on studies involving autism candidate genes (e.g., MBD5, TBL1X) and genomic pathway analysis. Publications emphasize translational research, including diagnostic improvements for pediatric patients and elucidating genetic architecture in autism. She leads efforts in the DNA Diagnostic Lab to integrate genomic data into clinical practice, focusing on regions of homozygosity and uniparental disomy.
Qiaoning Carol Zhang serves as Assistant Professor of Human Systems Engineering within The Polytechnic School at Arizona State University's Ira A. Fulton Schools of Engineering. Her research investigates the critical intersection of human perception, social contexts, and emerging technologies including artificial intelligence, robotics, and automated vehicles, with emphasis on creating intuitive, user-friendly, and inclusive systems. Her academic foundation includes: Ph.D. in Information, University of Michigan (2023) M.S. in Industrial and Operations Engineering, University of Michigan (2018) B.S. in Industrial Engineering, Hunan University (2016) Dr. Zhang's research program centers on understanding how individual differences and social dynamics shape technology interactions. Key focus areas include Human-AI Collaboration , Human-Robot Interaction , Human Factors in Automated Vehicles , and User Experience Design . Her work employs interdisciplinary methodologies to ensure technology adapts to diverse user needs across complex socio-technical environments, particularly in transportation and healthcare robotics. Analysis of her 15 most recent publications (2021-2025) reveals dominant themes in trust dynamics within automated vehicles, with significant attention to explainable AI interfaces. Research consistently examines how voice characteristics (gender, similarity), explanation modalities, and individual differences (age, personality) impact cognitive and affective trust. Recent work extends to healthcare robotics for elderly populations using Kano model analysis to identify critical user requirements. No scientific awards are documented in the provided materials. Dr. Zhang actively recruits Ph.D. candidates and undergraduate/master's researchers with backgrounds in human-computer interaction, data science, and interdisciplinary fields (design, computer science, cognitive science). She emphasizes opportunities in transportation technology, healthcare robotics, AI, and UX research/design, requiring applicants to submit CVs, research statements, and representative work samples. While specific grants aren't detailed, her research scope indicates substantial funding in human factors and emerging technology domains. Her research team focuses on developing empathetic technology through projects examining trust calibration in automated vehicles and healthcare robot design for older adults. Current initiatives include voice interface optimization for diverse user groups and Kano model applications in home healthcare robotics, aiming to bridge technical capabilities with human-centered design principles.
Prof. Dr. Florian Jeltsch leads the Plant Ecology and Nature Conservation research group at the Institute of Biology and Biochemistry, University of Potsdam. His work spans multiple ecological domains with a focus on understanding biodiversity patterns and processes in changing environments. His research group investigates community ecology across various landscapes including grasslands, agricultural systems, and drylands. Dr. Jeltsch's research interests encompass Community Ecology of Grasslands and Agricultural Landscapes, Community Ecology of Drylands, Biodiversity in Heterogeneous Environments, Movement Ecology and Biodiversity Dynamics, and Applied Regional Conservation. His work integrates theoretical and empirical approaches to address pressing ecological questions related to global change. He has been instrumental in developing and applying individual-based models to understand complex ecological systems. Analysis of Dr. Jeltsch's recent publications reveals a strong focus on individual-based ecological modeling, movement ecology, and the impacts of landscape heterogeneity on biodiversity. His work spans from theoretical foundations to practical conservation applications, with particular emphasis on savanna ecosystems, habitat fragmentation effects, and climate change impacts. The research demonstrates integration of multiple scales from individual energetics to community dynamics. Dr. Jeltsch has mentored numerous doctoral students and postdoctoral researchers who have gone on to establish their own research careers. His group has been involved in multiple collaborative projects including BioHet, GrassYear, BioMove, and ORYCS, addressing biodiversity conservation in heterogeneous environments. The Plant Ecology and Nature Conservation group maintains active research stations including the Gülpe Research Station, providing field-based research opportunities. The group's work bridges theoretical ecology with practical conservation applications, particularly in the context of global environmental change.
