جست‌وجوی استاد و پژوهشگر

• Pediatrics
• Childhood Obesity Prevention
• Cardiovascular Risk Factors in Children
• +۵ مورد دیگر

Donna Moore is an Associate Professor in the Department of Pediatrics at the Medical College of Georgia, part of Augusta University. She is actively engaged in pediatric research, medical education, and clinical service, with a strong focus on childhood obesity prevention, cardiovascular risk factors, and health equity. Research Interests: Dr. Moore's research emphasizes environmental and community-based interventions to combat childhood obesity, particularly through school programs like the FitKid Project. Her work investigates physical activity, nutrition, body composition, and disparities related to ethnicity, gender, and socioeconomic status in pediatric populations. Publication Trends: Her recent scholarly output centers on preventive pediatrics and public health, with studies published between 2002 and 2005 analyzing obesity, adiposity, and cardiovascular risks in rural and at-risk youth. These works reflect a consistent theme of early-life intervention and population health strategies. Exemplary Teaching Award for Excellence in Teaching in Graduate Medical Education (2020) Exemplary Teaching Award for Undergraduate Medical Education (2020) Teacher of the Year, Department of Pediatrics (2015) Exemplary Teaching Award for Medical Student Education (2012) Exemplary Teaching Award for Medical Resident Education (2011) Advising and Service: While no formal students are listed, Dr. Moore plays a significant role in medical education through committee leadership, residency training, and curriculum development. She has chaired the Student Promotions Committee, served on the Liaison Committee on Medical Education site visit, and contributed to admissions. Her service extends to university-wide initiatives including depression screening, patient-centered care models, and data safety monitoring for asthma and tobacco control trials. Labs and Teams: Dr. Moore has been integral to the Medical College of Georgia FitKid Project, a multidisciplinary team focused on pediatric obesity intervention. She also contributes to the Pediatric Equity, Diversity and Inclusion Committee and the Pediatric Ambulatory Quality and Safety Council, reflecting her commitment to systemic improvements in child health care.

Lina von Sydowمشاهده پروفایل

استاد

• Computational Science
• Computational Finance
• Ice Sheet Modeling
• +۲ مورد دیگر

Lina von Sydow is a Professor in Computational Science at Uppsala University's Department of Information Technology. She serves as Section Dean for the Mathematical-Computer Science Section since July 2023. Her academic journey includes becoming an Associate Professor in 2000, Senior Lecturer since 1997, and leading the Department of Information Technology from 2018 to 2023. PhD in Domain Decomposition Methods (1995, Uppsala University) Postdoctoral Fellow at Oxford University (1996-1997) Her research spans computational science with dual focuses on Computational Finance and Ice Sheet Modeling . In finance, she develops numerical methods for option pricing using PDEs, radial basis functions, and stochastic volatility models. In climate science, she contributes to ice sheet dynamics through full Stokes models and adaptive time-stepping approaches, particularly in simulating grounding line migration. Recent publications (2025) address gender disparities in IT education, including comparative analysis of admission trends and intervention studies to boost female enrollment. Earlier works (2020-2015) focus on high-order finite difference methods for financial derivatives, BENCHOP benchmarking projects, and preconditioning techniques for PDEs. Scientific awards include Excellent Teacher (2013) She actively collaborates on educational reforms, co-authoring studies like Gender-aware course reform in Scientific Computing (2013). Her leadership roles include Head of Department (2018-2023) and Section Dean (2023-present), influencing academic governance and interdisciplinary research. Labs and teams: Works with Uppsala University's Computational Science group, Elmer/ICE project collaborators (e.g., Per Lötstedt, Gong Cheng), and international partners in numerical finance and climate modeling.

Eric F. Lockمشاهده پروفایل

دانشیار

• Statistical genomics
• High-dimensional data analysis
• Machine learning
• +۷ مورد دیگر

Eric F. Lock is an Associate Professor in the Division of Biostatistics & Health Data Science at the University of Minnesota's School of Public Health. He is also a Member of the Masonic Cancer Center (MCC) and has been at the University of Minnesota since 2014, after completing his PhD in Statistics from the University of North Carolina in 2012 and a postdoctoral fellowship in Statistical Genomics at Duke University in 2014. Lock's research focuses on developing methods for the analysis of multi-faceted high-dimensional data, particularly in "omics" fields such as genomics, metabolomics, and proteomics. His work emphasizes the integrated analysis of data from multiple sources (e.g., gene expression, metabolomics, imaging) or measured in multiple dimensions (e.g., multiple tissue types or body regions). He also specializes in exploratory factorization and clustering methods, and Bayesian nonparametric inference. His recent publications demonstrate significant contributions to tensor data imputation (BAMITA), matrix decomposition (EV-BIDIFAC), and methods for handling complex genomic data. His work bridges statistical theory with practical applications in molecular biology, addressing challenges in data integration across multiple biological measurement platforms. Delta Omega, Honorary Society in Public Health (2019) As an active researcher and educator, Lock serves on dissertation committees, including for Mykhaylo M. Malakhov who recently defended his PhD at the University of Minnesota School of Public Health. He is involved in organizing and participating in major conferences such as STATGEN 2025, demonstrating his leadership in the biostatistics community.

Summer Hanمشاهده پروفایل

دانشیار

• Statistical genetics
• Molecular epidemiology
• Cancer screening
• +۵ مورد دیگر

Dr. Summer Han serves as Associate Professor of Medicine, Neurosurgery, and Epidemiology at Stanford University School of Medicine. She leads research through the Quantitative Sciences Unit (QSU) in the Biomedical Informatics Research Division of the Department of Medicine and maintains joint appointments in the Department of Neurosurgery. Her work bridges statistical methodology development with clinical applications in cancer screening and neuroscience. Her research program focuses on statistical genetics, molecular epidemiology, and risk prediction modeling for complex diseases. Key areas include developing novel methods for analyzing high-dimensional genomic data, creating dynamic risk prediction models under competing risks, and establishing evidence-based cancer screening strategies. Her team integrates genetic, environmental, and clinical factors to improve early detection of lung cancer and second primary malignancies, with particular attention to reducing racial disparities in screening outcomes. Dr. Han's scientific contributions have been recognized through prestigious awards including the NCI R37 MERIT Award for Early-Stage Investigators and the Department of Medicine Teaching Award in Biomedical Informatics Research. Her team has developed impactful tools such as the SPLC-RAT for second primary lung cancer risk assessment and RAMBO for brain metastasis prediction in lung cancer patients. She actively mentors PhD students and postdoctoral fellows, with several former trainees securing faculty positions at institutions including Cornell University and IIT Roorkee. Current research initiatives include the Oncoshare-Lung database integrating EHRs from Stanford Health Care and 23+ Sutter Health sites across Northern California, and the Cancer Data Science Shared Resources Core which she co-directs at the Stanford Cancer Institute. NCI R37 MERIT Award (Early-Stage Investigator) 2022 Department of Medicine Teaching Award in Biomedical Informatics 2024 SCI Equity Impact Research Grant 2024 Neurosurgery Research Seed Grant Award Multiple NCI R01 grants (CA226081, CA282793) Her laboratory collaborates extensively across Stanford Medicine, working with thoracic oncologists, neurosurgeons, and epidemiologists to translate statistical innovations into clinical practice. Current projects address socioeconomic factors in cancer risk stratification, real-time physical activity monitoring in spine surgery recovery, and machine learning approaches for genomic data analysis.

• Crowdsourcing
• Human-Computer Interaction
• Digital Health
• +۷ مورد دیگر

Simo Hosio is an Academy Research Fellow (2022-2027) and Professor of Computer Science and Engineering at University of Oulu's Center for Ubiquitous Computing, where he leads the Crowd Computing Research Group. He also maintains a visiting position at University of Tokyo, Japan. Having graduated as the first Finnish scholar under Microsoft Research Cambridge's Ph.D. scholarship program, he has published over 150 peer-reviewed scientific articles spanning two decades of research. Hosio's research spans three primary domains: crowdsourcing methodologies, human-computer interaction, and digital health applications. His work pioneers novel approaches to online labor markets, investigates the suitability of crowdsourcing for diverse applications, and explores HCI aspects of digital health solutions for chronic conditions. His research group, founded in 2020, has secured nearly two million USD in funding, demonstrating significant research impact and recognition. Analysis of Hosio's recent publications reveals a strong trend toward interdisciplinary research at the intersection of crowdsourcing, healthcare technology, and emerging AI systems. His work increasingly focuses on practical applications of crowd computing in health contexts, with growing attention to mental health, women's health, and workplace well-being solutions. The integration of AI and machine learning techniques with traditional HCI approaches represents another significant trajectory in his recent scholarship. Distinguished Paper Award (2024) Best Paper Honourable Mention Award (2022) PMCJ Best Research Paper (awarded in 2024) Best Paper Award (2022) Best Full Paper Award (2015) Honorable Mention Award (2014) Best Paper Presentation award (2010) As an educator, Hosio has taught Human-Computer Interaction (2019-2025) to over 260 students in 2024, Social Computing (2018-2021) to approximately 60 students annually, and Applied Computing (2015-2018) to around 50 students each year. His research group's nearly two million USD in secured funding demonstrates significant grant acquisition success, supporting innovative work at the intersection of crowd computing, health technology, and human-centered AI systems. The Crowd Computing Research Group, founded by Hosio in 2020, represents a significant research infrastructure focused on advancing methodologies for crowd-powered systems. The group's work spans from fundamental research on crowd labor markets to applied projects in healthcare, workplace well-being, and social computing, demonstrating a strong commitment to both theoretical advancement and practical impact.

Michael Nothnagelمشاهده پروفایل

استاد

• Statistical Genetics
• Genetic Epidemiology
• Population Genetics
• +۵ مورد دیگر

Michael Nothnagel is a Professor at the University of Cologne, where he leads the Department of Statistical Genetics and Bioinformatics within the Cologne Center for Genomics (CCG). His work spans statistical genetics, genetic epidemiology, and forensic genetics, focusing on methodological development and large-scale genomic data analysis. His research interests encompass theoretical and applied statistical genetics, with emphasis on human genetic diversity, disease etiology, and forensic applications. Key areas include Y-chromosomal phylogeography, genome-wide association studies for complex diseases, development of statistical methods for variant interpretation, and forensic marker optimization. His group leverages next-generation sequencing data and specialized forensic markers to address questions in population history, disease mechanisms, and identification systems. Recent publications reveal a strong focus on computational approaches to genetic analysis, including spatial frequency interpolation for haplogroup mapping, polygenic risk score applications for behavioral traits, and advanced methods for variant classification. His work demonstrates consistent integration of statistical theory with practical applications in medical and forensic genetics, often through international collaborations like the VISAGE Consortium. Nothnagel maintains active involvement in the Cologne Center for Genomics, contributing to seminars and collaborative projects including the upcoming 34th International Genetic Epidemiology Society meeting. His research group operates at the intersection of computational biology and medicine, with particular strengths in handling complex genomic datasets and developing novel analytical frameworks for genetic epidemiology.

• Women's Health
• Public Health
• Domestic Violence
• +۶ مورد دیگر

Professor Deborah Loxton is a leading academic at the University of Newcastle , serving as Director of the Centre for Women's Health Research (CWHR) and the Australian Longitudinal Study on Women's Health (ALSWH) . Her work bridges quantitative and qualitative research in women's health, with a focus on reproductive health, domestic violence impacts, and social determinants of wellbeing. PhD in Health (University of New England, 2003) Bachelor of Psychology (Honours, University of New England) Loxton’s research examines lifelong health impacts of trauma, particularly domestic violence, and maternal/infant health disparities. She has pioneered the WWOMB program to reduce global maternal mortality and co-authored the #EndGenderBias survey report on healthcare discrimination. Her recent publications address topics like intimate partner violence in twin studies, contraceptive use among women with chronic diseases, and WASH services in Nepal. Awards include the CAPHIA Team Award (2015) and University of Newcastle Faculty Research Award (2008) . Secured over $50 million in grant funding Collaborated with WHO, USA Academy of Violence and Abuse, and Korean Women’s Development Institute She leads the HMRI Women’s Health Program , focusing on violence prevention, maternal health, and healthy aging. Her work has shaped Australia’s National Women’s Health Strategy and National Plan to End Violence policy.

Adriana Iamnitchiمشاهده پروفایل

استاد

• Computational Social Science
• Social Media Analysis
• Misinformation Detection
• +۳ مورد دیگر

Adriana Iamnitchi is a Full Professor and Key Domain Chair for Computational Science at Maastricht University's Faculty of Science and Engineering, affiliated with the Department of Advanced Computing Sciences. Her research focuses on computational social science, social media dynamics, and misinformation detection. Her primary research interests include: Analysis of coordinated information campaigns across social platforms Development of LLM-based synthetic data generation for social media research Polarization quantification in multi-community networks Policy compliance frameworks for digital regulation (e.g., EU's Digital Services Act) Ethical AI applications for content moderation and transparency Her recent publications (2023-2025) demonstrate strong focus on: Cross-platform disinformation detection using multimodal embeddings Generative AI for synthetic social media datasets Quantitative analysis of toxicity monetization in creator economies Regulatory compliance automation for content transparency

Özge Önerمشاهده پروفایل

دانشیار

• Migration
• Labour Mobility
• Micro-geography of Segregation
• +۶ مورد دیگر

Özge Öner serves as Associate Professor in Spatial Economics and Real Estate at the University of Cambridge's Department of Land Economy and holds a Fellowship at Sidney Sussex College, where she additionally serves as Vice Master and Director of Studies. Her institutional affiliations extend to research fellowships at Stockholm's Institute of Retail Economics and Jönköping's Centre for Entrepreneurship and Spatial Economics (CEnSE). Her academic foundation includes a 2014 PhD in Economics with specialization in Urban and Regional Economics from Jönköping International Business School, complemented by doctoral research at the University of Illinois' Regional Economics Applications Laboratory (REAL). Prior academic appointments include Assistant Professor at Jönköping International Business School and Researcher at Stockholm's Research Institute of Industrial Economics (IFN). Research Interests: Öner's scholarly work critically examines migration dynamics, labor mobility patterns, micro-geographic segregation mechanisms, ethnic enclave formation, retail/service geography, urban amenity distribution, entrepreneurial geography, and political spatial organization. Her methodological approach heavily leverages geocoded register data and spatial econometric techniques to investigate how geographic context shapes economic behavior, with particular emphasis on Swedish and European urban systems. This interdisciplinary framework bridges spatial economics, economic geography, and migration studies through rigorous quantitative analysis of neighborhood-level phenomena. Publication Trends: Her recent output (2023-2025) demonstrates evolving focus toward infrastructure-impact analysis (tramway effects on commercial vitality), refugee labor market integration pathways, and micro-scale retail/ethnic enclave dynamics. Methodologically, she increasingly employs synthetic control approaches and granular geospatial data to isolate causal mechanisms in urban economic processes, while maintaining strong connections to policy-relevant questions about segregation, integration, and commercial geography. Scientific Awards: Handelsbanken Wallander postdoctoral scholarship (2015) Young Investigator Award in Italy (2018) Young Researcher Award in Sweden (2019) from the Swedish Entrepreneurship Forum Advising and Public Engagement: As Director of Studies at Sidney Sussex College, Öner oversees academic progression for undergraduate students. She actively translates research into public discourse through monthly columns in Svenska Dagbladet (The Swedish Daily News), where she analyzes contemporary socioeconomic issues through her spatial economics lens. While specific doctoral advisees aren't documented in source materials, her leadership roles indicate significant mentoring responsibilities. Research Networks: Öner maintains active collaboration through dual research fellowships: at Stockholm's Handelns Forskninginstitut (Institute of Retail Economics) where she examines commercial geography, and at Jönköping's CEnSE focusing on spatial entrepreneurship patterns. These positions facilitate cross-institutional research on retail dynamics, migration geography, and urban economic structures using Scandinavian longitudinal datasets.

Ayla Humphreyمشاهده پروفایل

استادیار

• Child and Adolescent Mental Health
• Clinical Psychology
• Autism Spectrum Disorders
• +۵ مورد دیگر

Ayla Humphrey is an Assistant Professor and Consultant Clinical Psychologist at the University of Cambridge Department of Psychiatry . Her research focuses on early identification of mental health needs in children, cognitive therapy for trauma-exposed youth, and developmental disorders like autism and Tuberous Sclerosis . She serves as Course Director for the MPhil Foundations of Clinical Psychology and co-founded the NHS Cambridge Centre for Paediatric Neuropsychological Rehabilitation . Her research spans Child and Adolescent Mental Health Services (CAMHS) integration with social care, trauma-focused cognitive therapy , and developmental disorder screening . Key collaborations include the NIHR-funded COACHES study and the PYCES (Parents and Young Children under Extreme Stress) project. Scientific awards include the 2017 British Psychological Society Award for Outstanding Contribution to Applied Practice . She actively supervises PhD students and contributes to school-based mental health identification frameworks . Her work emphasizes evidence-based service transformation and cross-sector collaboration.

Neil Lawrenceمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Uncertainty Quantification
• +۳ مورد دیگر

Neil Lawrence is the inaugural DeepMind Professor of Machine Learning at the University of Cambridge's Department of Computer Science and Technology. He also holds positions as a Senior AI Fellow at The Alan Turing Institute and a Visiting Professor of Machine Learning at the University of Sheffield. After three years as Director of Machine Learning at Amazon, Lawrence recently returned to academia, bringing extensive industry experience to his academic work. Lawrence's research focuses on the intersection of machine learning with the physical world, particularly in uncertainty quantification and end-to-end solutions for real-world applications. His work was initially inspired by deploying machine learning systems in African contexts, where comprehensive solutions are often required. His technical expertise spans over two decades in machine learning methods, with a growing interest in public understanding of machine learning, policy decisions, and data governance implications. His recent publications reveal a diverse research portfolio spanning climate science, healthcare applications, systems engineering for AI deployment, data governance, and theoretical machine learning. Lawrence's work demonstrates a consistent theme of bridging theoretical machine learning with practical applications across multiple domains, with particular attention to uncertainty quantification and the societal implications of AI systems. Lawrence serves on the board of the AISTATS conference and the ELLIS Foundation, and acts as the founding and series editor for the Proceedings of Machine Learning Research. He is also the co-host of the Talking Machines podcast, demonstrating his commitment to public engagement with machine learning concepts. At Cambridge, Lawrence teaches Advanced Data Science (Part II) and Machine Learning and the Physical World (MPhil ACS, Part III), contributing to both undergraduate and postgraduate education in computer science. His work with the Accelerate Programme for Scientific Discovery and the Data Trusts Initiative positions him at the forefront of developing frameworks for responsible and effective AI deployment in scientific and societal contexts.

Benaissa Chidmiمشاهده پروفایل

دانشیار

• Industrial Organization
• Food Marketing
• Agribusiness
• +۲ مورد دیگر

Benaissa Chidmi , an Associate Professor in the Department of Agricultural and Applied Economics at Texas Tech University , specializes in industrial organization, food marketing, agribusiness, and consumer demand analysis. He teaches Applied Econometrics and Demand and Price Analysis . Education Ph.D. in Agricultural and Resource Economics, University of Connecticut (2006) M.S. in Applied Financial Mathematics, University of Connecticut (2006) M.S. in Agricultural and Resource Economics, University of Connecticut (2002) M.S. in Food Engineering, Institut Agronomique et Vétérinaire Hassan II, Morocco (1996) Research Trends Chidmi's research spans diverse applications of econometric modeling, including consumer food demand systems , energy economics , agricultural productivity , and industrial organization . His recent work (2025) examines Saudi Arabia's coffee import demand , machine learning in US residential energy usage , and animal protein consumption patterns . Earlier studies (2024-2019) focus on technical efficiency in cereal production, asymmetric price transmission in energy markets, and nutrient demand analysis in Sri Lanka. Key Methodologies Almost Ideal Demand System (AIDS) modeling Quantile regression analysis Random coefficients and logit demand models Machine learning applications in economics Censored regression techniques Technical efficiency measurement

Jonathan L. Auerbachمشاهده پروفایل

استادیار

• Data Science
• Causal Inference
• Survey Methods
• +۶ مورد دیگر

Jonathan L. Auerbach is an Assistant Professor in the Department of Statistics at George Mason University . His work bridges statistics and public policy , focusing on causal inference , longitudinal data analysis , and official statistics . He has contributed to understanding urban myths (e.g., New York City rat populations, building height trends), election fraud , and policy evaluation for initiatives like Vision Zero. Education : PhD in Statistics (Columbia University, 2020), BA in Economics (Cornell University, 2010) Research Interests include data science , causal inference , survey methodology , and urban analytics . His recent work addresses climate change impacts on cherry blossom seasons, federal data security , and street vendor demographics in New York City. Scientific Awards include the 2024-2025 President of Washington Statistical Society , 2020-2021 American Statistical Association Science Policy Fellow , and 2019 Howard Levene Outstanding Teaching Award . He has served as an instructor for courses like Capstone in Statistics and Causal Inference , emphasizing technical communication and data ethics .

Abderrahim Oulhajمشاهده پروفایل

استاد

• Biostatistics
• Epidemiology
• Public Health
• +۱۰ مورد دیگر

Abderrahim Oulhaj serves as a Professor of Biostatistics and Epidemiology in the Department of Public Health and Epidemiology at Khalifa University, bringing over 28 years of academic and research experience. His prior roles include eight years as Associate Professor at United Arab Emirates University (UAEU) where he directed the PhD program in Public Health, and nearly a decade as a senior statistician at University of Oxford leading projects like OPTIMA and EXSCEL. His educational background includes: PhD in Statistics (2003) from the Institute of Statistics, Biostatistics and Actuarial Sciences, UCL, Belgium Master degree in Statistics (1997) from the Institute of Statistics, Biostatistics and Actuarial Sciences, UCL, Belgium Prof. Oulhaj specializes in statistical modeling for infectious and chronic diseases—including diabetes, cardiovascular disorders, cancer, neurodegenerative conditions, COPD, and COVID-19—with methodological expertise in advanced survival analysis, risk prediction modeling, longitudinal data analysis, and joint modeling of repeated measures with time-to-event data. His work increasingly integrates artificial intelligence, machine learning, and deep learning into healthcare analytics. He has received multiple research excellence awards from UAE University and Khalifa University, alongside three international patents and copyrights focused on Alzheimer’s and cardiovascular diseases. Prof. Oulhaj directed UAEU's PhD program in Public Health and currently leads the KU-SEHA Clinical Research Certificate Program training 150+ medical professionals across Abu Dhabi. His grant leadership encompasses the EU-funded POCCardio project on cardiovascular diseases and the European Society of Cardiology's Cardiovascular Risk Collaboration Unit, with significant contributions to UAE national committees for therapeutic trials, epidemiology, diagnostics, and cardiovascular prevention guidelines. He operates within international research frameworks through POCCardio and the European Society of Cardiology, while maintaining strategic ties with the UAE Department of Health and SEHA for clinical research capacity building.

Kylie Tuckerمشاهده پروفایل

استاد

• Motor control
• Pain research
• Biomechanics
• +۷ مورد دیگر

Professor Kylie Tucker is a distinguished academic at the University of Queensland, serving as Professor and School Director of Teaching and Learning in the School of Biomedical Sciences within the Faculty of Health, Medicine and Behavioural Sciences. She is also an Affiliate of the Centre for Innovation in Pain and Health Research (CIPHeR) and currently serves as President of the International Society of Electrophysiology and Kinesiology (ISEK) for the term 2024-2026. Professor Tucker leads a dynamic research environment focused on advancing knowledge about muscles and movement control, with significant contributions to understanding how pain impacts movement, methods for estimating muscle forces, and assessment of childhood movement control and adolescent skeletal maturity. Professor Tucker earned her Bachelor of Arts, Bachelor of Science, and Doctor of Philosophy from the University of Adelaide. Her academic journey has positioned her as a leader in neuromuscular research, particularly in the areas of motor control and pain adaptation. Within the School of Biomedical Sciences, she has held significant leadership roles including Deputy Director of Teaching and Learning (2018-2020), inaugural chair of the REMEDE committee (2021-2023), and Director of Teaching and Learning (2024-2025). She also co-facilitates UQ's flagship Career Progression for Women program. Her research interests span motor control, pain research, biomechanics, electromyography, neuromuscular control, pediatric movement, scoliosis, and muscle physiology. Professor Tucker's work has transformed understanding of pain's impact on movement and advanced assessment methods for childhood movement control and skeletal maturity. She has recently proposed new insights into scoliosis progression, identifying unique muscle features that can be non-invasively detected early in curve progression. Approximately 3-7% of children worldwide develop adolescent idiopathic scoliosis, often requiring surgical intervention when conservative treatments fail. Analysis of Professor Tucker's recent publications reveals a strong focus on neuromuscular control mechanisms, particularly in relation to pain, scoliosis, and pediatric movement disorders. Her work integrates advanced methodologies including electromyography, shear wave elastography, and biomechanical modeling to investigate muscle function across diverse populations. A notable trend is her leadership in consensus projects (CEDE) establishing standardized methodologies for electromyography research, reflecting her commitment to methodological rigor in the field. Professor Tucker actively mentors the next generation of researchers, supervising numerous PhD students across projects related to scoliosis, knee osteoarthritis, pain research, and pediatric movement disorders. Her research is supported by significant funding including NHMRC MRFF EPCDR grants for chronic musculoskeletal conditions in children and the SRS Research Grant for novel insights into adolescent idiopathic scoliosis. She leads the Motor Control and Pain Research Lab, a collaborative environment bringing together basic science and clinical researchers. The lab focuses on two main research streams: Motor Control and Pain Research and Child and Adolescent Neuromotor Control Research. Professor Tucker teaches across 10 UQ programs with class sizes ranging from 70-1400 students, demonstrating her commitment to education alongside her research leadership.