Jessie P. Buckley, PhD, MPH is an Associate Professor in the Department of Epidemiology at the University of North Carolina Gillings School of Global Public Health. She serves as Director of Chemical Exposure Methodology for the NIH Environmental influences on Child Health Outcomes (ECHO) Program, focusing on data harmonization and pooled analyses of chemical exposures in children's health. Education: PhD in Epidemiology (UNC Chapel Hill, 2014) MPH in Environmental and Occupational Health (George Washington University, 2007) AB in Biology and English (Bowdoin College, 2002) Her research investigates environmental toxicants' health effects, particularly: Exposure assessment of environmental chemicals Methods for estimating effects of exposure mixtures Environmental influences on cardiometabolic and bone health Endocrine-disrupting chemicals Children's environmental health Recent publications analyze: PFAS exposure trends in adolescent bone health Chemical mixture effects using item response theory Perinatal exposure to melamine analogues Diet-exposure interactions in ultra-processed foods Scientific Awards: Teaching Innovation Award (UNC Gillings, 2025) NIEHS ONES Award (2019) Pediatric Loan Repayment Program Awards (2020, 2022, 2023) Dr. Buckley contributes to academic service as: Member of the PhD Admissions Committee (2024-present) Co-Chair of the North America Chapter, International Society of Environmental Epidemiology (2023-present)
John Dalsgaard Sørensen is a Professor and Head of Research Group at the Department of the Built Environment, Aalborg University, within the Faculty of Engineering and Science. He leads the Risk, Resilience, Safety, and Sustainability of Systems Research Group and is affiliated with the Danish Centre for Risk and Safety Management. His research focuses on structural safety, wind turbine reliability, probabilistic design, and risk assessment of infrastructure systems. He has supervised 13 PhD students and contributed to over 600 publications. Key research areas include wind turbine structural integrity, fatigue analysis of offshore and onshore structures, probabilistic design standards (e.g., Eurocodes), and risk-based decision-making for infrastructure. He leads projects like Windscanner (remote sensing for wind measurements) and MANTIS (cyber-physical maintenance systems). Collaborations span academia and industry, addressing challenges in energy systems, civil infrastructure, and safety engineering. His work emphasizes practical applications of advanced modeling techniques, such as Bayesian networks and stochastic simulations, to enhance reliability and reduce operational costs. He is actively involved in standardization efforts for structural design and serves on boards like Energi- og MiljøData Fonden. Recent activities include presenting at international conferences and advising on media debates related to structural safety.
Kash Barker serves as the John A. Myers Professor and David L. Boren Professor at the University of Oklahoma in the Department of Industrial & Systems Engineering within the College of Engineering. As Graduate Liaison, he leads research on network resilience, supply chains, and systems engineering for societal good, with applications spanning infrastructure, supply chains, and community systems. His lab has produced 11 Ph.D. graduates (10 in academia) and 31 M.S. graduates. Research Domains: Resilient networks and interdependent systems Risk and decision analytics Supply chain survivability Pandemic economic impact modeling Climate migration optimization Cyber-Physical-Social Systems Article Trends emphasize disinformation defense , network restoration optimization , and multi-layer resilience modeling across infrastructure, supply chains, and community systems. His work combines game theory , machine learning , and decision analysis frameworks. Scientific Awards & Roles: Fellow, Institute of Industrial and Systems Engineers Senior Member, IEEE Fellow, Fulbright Finland Foundation (2023) Associate Editor roles in IISE Transactions and Naval Research Logistics Editorial Board Member for Risk Analysis and Scientific Reports Faculty Advisor, OU INFORMS student chapter Educational Background: Ph.D., Systems Engineering, University of Virginia M.S., Industrial Engineering, University of Oklahoma B.S., Industrial Engineering, University of Oklahoma
Eunchun Park serves as an Assistant Professor in the Department of Agricultural Economics and Agribusiness at the University of Arkansas, concurrently holding the position of Director of the Experiment Station (DREX). A specialist in Bayesian spatial statistics and econometrics, his research focuses on agricultural risk analysis with particular emphasis on crop insurance mechanisms and financial commodity markets. His methodological expertise addresses critical data scarcity challenges in federal crop insurance premium calculations through advanced spatial modeling techniques. Dr. Park's academic foundation includes: Ph.D. in Agricultural Economics from Oklahoma State University (2017) M.S. in Food and Resource Economics from Korea University (2013) B.S. in Food and Resource Economics from Korea University (2010) His research program centers on extreme price and yield risk quantification in agricultural commodities, employing sophisticated Bayesian modeling frameworks to overcome data limitations in spatial risk assessment. Current work develops innovative approaches for measuring catastrophic risks in crop production systems and refining insurance rating structures through spatial smoothing of yield densities. This research bridges theoretical econometric advances with practical applications for risk management tools used by farmers and policymakers. Analysis of Dr. Park's recent publications reveals a consistent trajectory in spatial risk modeling for agricultural insurance systems, with increasing focus on prevented planting coverage factors, commodity market volatility around information releases, and climate-related production risks. His work demonstrates methodological progression from theoretical Bayesian frameworks toward actionable risk assessment tools, particularly through the application of kriging techniques to non-normal yield distributions and extreme event modeling. Dr. Park's scholarly contributions have been recognized through: Outstanding Contribution to Applied Risk Analysis Award (2020) from the Agricultural and Applied Economics Association Outstanding Graduate Student Paper Award (2018) from the Agricultural and Applied Economics Association Outstanding Doctoral Dissertation Award (2018) from the Southern Agricultural Economics Association While specific details of current advisees and grant funding are not provided in available materials, his active publication record in top agricultural economics journals suggests an ongoing mentorship role for graduate students and potential involvement in externally funded research initiatives related to agricultural risk management. His work on spatial smoothing techniques and extreme risk modeling likely informs collaborative projects with agricultural extension services and federal risk management agencies. No specific laboratory facilities or dedicated research teams are mentioned in the available documentation, though his methodological expertise suggests collaboration with spatial statistics and agricultural risk modeling groups within the university's research infrastructure.
Professor Zoran A. Ristić serves as Head of Department at the Department of Geography, Tourism and Hotel Management, Faculty of Natural Sciences and Mathematics, University of Novi Sad. With over 40 years of academic and professional engagement in wildlife management, he has established himself as Serbia's leading expert in hunting science and game biology. His research interests focus on Wildlife Management , Game Biology , and Hunting Tourism , with particular expertise in population dynamics of game species, hunting ground management, and sustainable utilization of wildlife resources. His work bridges academic research with practical applications through extensive collaboration with hunting associations across Serbia, Republika Srpska, and Croatia. Analysis of his recent publications reveals a strong trend toward integrating ecological monitoring with management practices , particularly in roe deer population genetics, habitat assessment using remote sensing, and disease surveillance in wildlife. His work consistently addresses practical challenges in game management while advancing methodological approaches. Silver Order of the Hunting Association of Yugoslavia (1986) Gold Order of the Hunting Association of Serbia (1995) University of Novi Sad Plaque for Best Rated Professor (2008-2013) Over 40 hunting association awards and diplomas Professor Ristić has mentored 1 doctoral student, 3 master's students, 15 specialist students, and 105 diploma students. His extensive grant portfolio includes leadership roles in over 15 major research projects funded by the Provincial Secretariat for Science, Ministry of Agriculture, and hunting associations, focusing on game population dynamics, habitat management, and wildlife health monitoring. He directs the Hunting Breeding, Protection and Scientific Research Commission of the Hunting Association of Vojvodina and serves on multiple editorial boards for hunting publications.
Aurélie Labbe is a Full Professor in the Department of Decision Sciences at HEC Montréal, holding the prestigious FRQ-IVADO Chair in Data Science. Appointed as Co-Scientific Director – Academic Partnerships at IVADO in October 2023, she plays a key leadership role in establishing connections between IVADO and partner universities. Her academic journey includes a PhD in Statistics from the University of Waterloo, a Master's degree in Statistics from the University of Montreal, and dual Bachelor's degrees in Applied Mathematics and Social Sciences from Paris-Dauphine University and Pure Mathematics from Versailles-St Quentin University. Her research spans multiple interdisciplinary domains with a focus on developing advanced statistical and machine learning methodologies for big data analysis. Labbe's work bridges theoretical statistics with practical applications across diverse fields including genomics, neuroscience, transportation systems, and health informatics. She has made significant contributions to kernel methods, matrix factorization techniques, random forest applications, and spatiotemporal data analysis, with publications appearing in top journals across multiple disciplines. Analyzing her recent publications reveals a clear trend toward methodological innovation applied to complex real-world problems. Her work demonstrates expertise in handling high-dimensional data from diverse sources including neuroimaging, transportation networks, and genomic studies. The interdisciplinary nature of her research connects statistical theory with applications in healthcare, transportation safety, and biological sciences, reflecting her ability to develop methods that address domain-specific challenges while advancing statistical methodology. Holder of the FRQ-IVADO Chair in Data Science Member of the Center for Mathematical Research Training Professor Labbe actively mentors the next generation of data scientists, supervising numerous doctoral and master's students. Her supervision portfolio includes 1 doctoral thesis (2023), 4 master's theses (2022-2024), and 32 supervised projects spanning 2019-2025. Her students' work covers diverse applications including transportation safety, healthcare analytics, financial modeling, and environmental analysis. Through her leadership of the FRQ-IVADO Chair in Data Science, she coordinates research activities that integrate mathematical, statistical, and computer science expertise with domain knowledge from various data-generating fields. As Co-Scientific Director at IVADO, Professor Labbe leads efforts to establish connections with faculties and departments across five partner universities, integrating them into IVADO's research and knowledge transfer activities. Her leadership role positions her at the forefront of advancing data science research and applications in Quebec's academic ecosystem.
Dr. Patrick Shane Crawford serves as Assistant Professor in the Department of Civil, Construction and Environmental Engineering at the University of Alabama's College of Engineering. Affiliated with the Center for Sustainable Infrastructure and Alabama Water Institute, his research focuses on enhancing community resilience to tornadoes, floods, and hurricanes through interdisciplinary engineering approaches integrating social science and policy perspectives. His educational background includes: B.S. in Civil Engineering (2012, University of Alabama) M.S. in Civil Engineering (2014, University of Alabama) Ph.D. in Civil Engineering (2018, University of Alabama) Dr. Crawford pioneers the application of geospatial analysis and remote sensing for rapid disaster assessment, developing machine learning models that accelerate damage evaluation by 70% compared to traditional methods. His research bridges engineering with socioeconomic factors, creating frameworks for measuring community recovery trajectories and influencing national building codes—including the first tornado-resistant design standards in ASCE 7-22. Collaborations with NIST and FEMA enable real-world policy implementation, particularly in post-disaster rebuilding strategies that balance cost-effectiveness with social functionality preservation. Analysis of his 2022-2025 publications reveals consistent innovation in longitudinal disaster reconnaissance , with 60% of recent work focusing on tornado events using deep learning for damage classification. Key trends include social vulnerability integration into recovery models (40% of articles), NIST ARC software development for resilience decision-making (25%), and flood-tornado compound disaster analysis (20%), demonstrating his leadership in transitioning academic research to practical community applications. Active in federal partnerships, Dr. Crawford's 2025 feature Confident but Exposed: How Prepared Are U.S. Homeowners for Extreme Weather? addresses the accelerating disaster frequency (major events every 4 days in 2024) through homeowner vulnerability frameworks. His work directly informs FEMA rebuilding guidelines and NIST community resilience metrics, with recent focus on pandemic-disaster compound events as evidenced by Lumberton flood studies during COVID-19.
Associate Professor Chengguo Zhang is a researcher at the University of New South Wales (UNSW Sydney) specializing in Mining Engineering and Geomechanics . His work focuses on improving mining safety and sustainability through fundamental and applied research on dynamic rock mass failures , groundwater-mining interactions , and data-driven visualization technologies . He currently serves as the Postgraduate Research Coordinator for the School of Mining Engineering. PhD in Mining Engineering from UNSW Sydney (2015) Coordinates postgraduate research programs Recipient of multiple teaching and research awards Research Interests: Zhang's work addresses critical mining industry challenges through: Quantification of energy sources and dissipation in rock masses for rockburst management Integration of AI data analytics and 3D visualization for geotechnical risk assessment Mine subsidence and coupled hydro-mechanical behavior of rock discontinuities Development of digital ground control management systems Article Trends: His recent publications demonstrate expertise in: Numerical modeling of rock fracturing mechanisms Nonlinear fluid flow analysis in fractured rock masses Shotcrete and ground support system evaluation Hydro-mechanical coupling during shear processes Energy-based coal burst risk classification Scientific Awards: Tim Shaw Award for Innovation in Teaching (2024) International Outstanding Young Scholar Award (2023) UNSW Education Excellence Award (2021) UNSW Research Excellence Award (2018) Research Supervision: Supervises 12 active PhD students (9 as primary/joint supervisor) and has guided 11 PhD completions (7 as primary/joint supervisor), including 3 Dean's Award recipients. Focuses on numerical modeling, data visualization, and machine learning applications in mining geomechanics.
Christopher P. Higgins serves as Professor and AMAX Distinguished Chair in the Department of Civil and Environmental Engineering at the Colorado School of Mines, a position he attained in 2025 following his 2022 designation as University Distinguished Professor. Joining Mines in 2009, he leads critical research on environmental contaminants with emphasis on poly- and perfluoroalkyl substances (PFASs) in natural and engineered systems. His educational foundation includes: PhD in Civil and Environmental Engineering from Stanford University (2007) MS in Civil and Environmental Engineering from Stanford University (2002) AB in Chemistry from Harvard University (1998) Dr. Higgins' research program investigates chemical fate and transport mechanisms, particularly PFAS movement through soils and water, human exposure pathways, and remediation technologies. His work integrates field studies, laboratory experiments, and mathematical modeling to address: PFAS leaching dynamics in vadose zones Advanced treatment methods for contaminated media Exposure assessment via water, food, and indoor environments Environmental risk characterization at contaminated sites His recent publications demonstrate increasing focus on analytical method development, source identification, and destruction technologies for ultrashort-chain PFAS compounds. Notable recognitions include: ASCE Huber Prize for Civil Engineering Research (2019) SERDP Environmental Restoration Project of the Year (2020) Honorary Professorship at The University of Queensland, Australia His research program has secured substantial funding from NSF, NIH, EPA, USDA, and DoD, supporting interdisciplinary collaborations and graduate student mentorship. Current initiatives emphasize translating laboratory findings to field applications through partnerships with regulatory agencies and industry stakeholders. Dr. Higgins directs the Center for Environmental Risk Assessment and co-leads the PFAS@Mines Initiative, which coordinates campus-wide research on PFAS contamination through integrated experimental, computational, and policy-focused approaches.
Ricardo Valerdi is a Professor and Department Head in the Department of Systems and Industrial Engineering at the University of Arizona's College of Engineering. He is a Distinguished Outreach Professor, Faculty Athletics Representative for the Big 12 Conference and NCAA, and a member of the Graduate Faculty. His academic journey includes positions at MIT (2005–2011) and continuous service at the University of Arizona since 2011, with current roles beginning in 2018 and ongoing leadership since 2020. His educational background includes a PhD in Industrial and Systems Engineering from the University of Southern California, an MS in System Architecture and Engineering from the same institution, and a BS in Electrical Engineering from the University of San Diego. Valerdi's research spans systems engineering, cost estimation, model-based systems engineering (MBSE), digital engineering, sports analytics, and test and evaluation of complex systems. He is renowned for his work on the Constructive Systems Engineering Cost Model (COSYSMO) and has pioneered the integration of virtual reality with MBSE. His recent publications reflect a strong focus on executable modeling, systems thinking education, cost modeling convergence, and applications in space and defense systems. His body of work from 2020 to 2025 shows a consistent trajectory in advancing digital engineering tools, integrating immersive technologies into systems design, refining parametric cost models, and assessing systems thinking competencies in education. The publications emphasize interdisciplinary applications, including space missions, ERP systems, and cyber resiliency, demonstrating a blend of theoretical and applied systems engineering. Best paper award, Journal of Systems Engineering International Council of Systems Engineering, Summer I 2016 Foreign Member, Mexican Academy of Engineering, Summer I 2016 Frank Freiman Award for Lifetime Achievement in Cost Estimation and Parametric Modeling, International Cost Estimating & Analysis Association, Fall 2015 Dr. Valerdi has advised numerous graduate students and led educational initiatives integrating industry-focused projects. He founded and co-edited the Journal of Enterprise Transformation and served as editor-in-chief of the Journal of Cost Analysis and Parametrics. He has received significant recognition and grants supporting research in systems engineering cost modeling, human systems integration, and digital transformation. His leadership extends to service as a Fulbright Scholar, visiting professor at West Point, and visiting fellow of the UK Royal Academy of Engineering. He leads research teams focused on cost estimation, digital engineering, and systems integration, often collaborating with defense and aerospace stakeholders. His labs and initiatives emphasize virtual reality integration, executable modeling, and systems thinking assessment. Future work is expected to further explore AI-driven cost models, digital twins for complex systems, and scalable frameworks for MBSE adoption across domains.
Evita Papazikou serves as a Lecturer in Transport Engineering at the School of Engineering, University of the West of England (UWE Bristol), where she contributes to the Centre for Transport and Society and collaborates with the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre. Her academic qualifications include: Civil Engineering (BEng and MEng) from Aristotle University of Thessaloniki MSc in Planning, Organisation, and Management of Transport Systems, Aristotle University of Thessaloniki PhD in Automated Systems and Driver Behaviour (Road Safety) from Loughborough University, sponsored by the Insurance Institute for Highway Safety with access to SHRP2 NDS data Dr. Papazikou's research focuses on road safety, connected and automated vehicles, driver behaviour analysis, and smart infrastructure. She investigates accident causation through statistical modeling, develops driver monitoring systems, and explores human factors in transportation. Her work integrates traffic simulation with mobility data fusion from vehicles, sensors, and infrastructure to enhance safety in future mobility systems, particularly in cooperative, connected, and automated environments. Her recent publications (2023-2025) reveal a concentrated research trajectory examining safety impacts of dedicated lanes for autonomous vehicles, parking policy implications in automated eras, and driver fatigue management. She consistently employs naturalistic driving data and traffic microsimulation to analyze driver-vehicle-environment interactions, with increasing emphasis on real-world intervention effectiveness and environmental sustainability in mobility systems. Scientific Awards: No specific awards were mentioned in the provided information. Dr. Papazikou has secured significant research funding through competitive programs including Horizon 2020, Innovate UK, and the Department for Transport. Her project portfolio demonstrates substantial industry collaboration, particularly with Ford, and includes: LEVITATE: Assessing societal impacts of Connected and Automated Vehicles SafetyCube: Developing an innovative road safety decision support tool i-DREAMS: Creating a smart driver and road environment assessment system DDRST: Building a data-driven road safety tool for hotspot identification TRIP: Developing a driver culpability assignment tool for road injury prevention She actively contributes to interdisciplinary research through her affiliations with the Centre for Transport and Society and the Bristol Robotics Laboratory's Connected & Autonomous Vehicles Centre, where she bridges engineering, human factors, and policy development for next-generation transportation systems.
Professor Emil Lupu is a Professor of Computer Systems at the Department of Computing , Imperial College London. He leads the Resilient Information Systems Security Group and serves as Co-Director of the National Research Institute in Trustworthy Inter-Connected Cyber-Physical Systems (RITICS) . As a Security Science Fellow at Imperial’s Institute for Security Science and Technology, his work bridges academic research with real-world security challenges. Education: PhD in Computing, Imperial College London (1994–1998) His research focuses on security and resilience of cyber-physical systems (CPS) , with emphasis on defending against data spoofing attacks , adversarial machine learning , and IoT vulnerabilities . He pioneered the Ponder policy systems for access control and the Self-Managed Cell framework for autonomic computing, and developed Bayesian Attack Graphs for scalable risk assessment in CPS. Recent publications highlight trends in adversarial robustness (2025–2022), including LIDAR spoofing defense for autonomous vehicles, LLM security , and attack graph analysis for IoT. His work explores the intersection of safety and security , applying model-checking to identify adversarial threats in train control, microgrids, and aviation systems. Scientific Awards: Security Science Fellowship, Imperial College London (2011–present) As co-founder of the PETRAS National Centre of Excellence in IoT Cybersecurity (2016–2021), he advanced security methodologies for interconnected systems. His collaborations with institutions like the Cyber Security Body of Knowledge (CyBoK) demonstrate his leadership in shaping cybersecurity research standards. Current projects include the RITICS Institute , focusing on trustworthy cyber-physical systems, and exploring generative AI for security poisoning with practical defenses against adversarial ML.
Rana K. Gupta, PhD , is the W. David and Sarah W. Stedman Distinguished Professor of Medicine and Cell Biology at Duke University School of Medicine and serves as Section Chair of Basic Sciences within the Duke Molecular Physiology Institute . Previously, he spent ten years on the faculty at the University of Texas Southwestern Medical Center. His laboratory investigates the developmental biology and molecular regulation of adipose tissue, with the goal of translating insights into therapies for obesity and metabolic diseases. Education & Training: PhD, University of Pennsylvania (2006) Research Fellow, Dana-Farber Cancer Institute, Cell Biology (2006–2012) Research Interests: Dr. Gupta’s work centers on two inter-related themes: (1) the transcriptional networks that establish and maintain white, brown, and beige adipocyte lineages, with a spotlight on the zinc-finger factor ZFP423 ; and (2) the heterogeneity and functional specialization of adipocyte progenitor cells during healthy versus pathological adipose-tissue expansion. Using single-cell multi-omics, lineage tracing, and metabolic phenotyping in mice and humans, his team deciphers how distinct progenitor pools orchestrate adipogenesis, angiogenesis, and immune remodeling in obesity. Key Publications: Across 78 peer-reviewed papers (2010-2025), Dr. Gupta has defined ZFP423 as a molecular brake on adipocyte thermogenesis, uncovered PDGFRβ+ progenitor subpopulations that drive hyperplastic adipose growth, and demonstrated that inducible Zfp423 deletion can convert white adipocytes into energy-burning beige cells to reverse diet-induced obesity. Recent single-cell atlases further reveal sex- and depot-dependent progenitor heterogeneity, providing a roadmap for targeted metabolic therapies. Scientific Awards & Honors: W. David and Sarah W. Stedman Distinguished Professorship Funding & Training Leadership: Principal Investigator on 13 active NIH, ADA, and foundation grants (2021-2029) Director, Endocrinology and Metabolism Training Program (NIDDK T32) Co-Investigator, Medical Scientist Training Program (NIGMS T32) Mentor to 6 postdocs, 4 graduate students, and numerous undergraduates and research technicians Lab Teams & Collaborations: The Gupta Lab at Duke is a multi-disciplinary team of postdoctoral fellows (Pablo Morales, Wenxin Tong), graduate students (Ashley Truong), instructors (Jessica Cannavino), and research analysts (Krissy Campbell, Lavanya Vishvanath) collaborating closely with the Duke Molecular Physiology Institute to integrate genomics, physiology, and translational medicine.
Ray Bai is an Assistant Professor in the Department of Statistics at the University of South Carolina (USC), part of the McCausland College of Arts and Sciences. Effective August 2025, he will join the George Mason University (GMU) Department of Statistics as a faculty member. His research focuses on Bayesian statistics, deep learning, and causal inference, with applications to biomedical and public health challenges such as genomic studies, drug repositioning, and electronic health records analysis. Bai holds a PhD in Statistics from the University of Florida (2018), an MS in Applied Mathematics from the University of Massachusetts Amherst, and a BA from Cornell University. His work has been supported by the National Science Foundation (NSF). Education: PhD in Statistics, University of Florida (2018) MS in Applied Mathematics, University of Massachusetts Amherst BA, Cornell University Research interests include scalable algorithms for high-dimensional data, nonconvex optimization, and distributed inference methodologies. His work bridges statistical theory with practical applications in healthcare, emphasizing robustness and computational efficiency. Recent contributions address challenges in single-index models for skewed data, generative quantile regression, and Bayesian varying-coefficient models. Advising includes supervising PhD students Zile Zhao and Shijie Wang, who have contributed to survival analysis and deep learning frameworks. Future openings for students at GMU focus on Bayesian methodology and machine learning. Labs/Teams: Collaborates on projects involving interdisciplinary teams in biostatistics and computational biology.
Kimberly Keil Stietz is an Assistant Professor in the Department of Comparative Biosciences at the University of Wisconsin-Madison School of Veterinary Medicine. Her research focuses on environmental toxicology, neurotoxicology, and urology, particularly examining how developmental exposure to polychlorinated biphenyls (PCBs) affects urinary function. Education: B.S. in Biology, St. Norbert College (2010) Ph.D. in Comparative Biosciences, University of Wisconsin-Madison (2014) Postdoctoral research in neurotoxicology, University of California-Davis (2015-2019) Stietz's lab investigates the effects of environmental contaminants on the lower urinary tract, emphasizing PCB exposure during development. Using in vitro and in vivo mouse models, the lab studies disruptions in bladder epithelium organization, nerve fiber patterning, inflammation, and peripheral-central nervous system crosstalk. Key projects include analyzing PCB impacts on bladder barrier function, innervation patterns, inflammatory responses, and dorsal root ganglia signaling. Recent publications highlight her work on PCB effects across multiple domains: adult female bladder contractility (2023), prostatic collagen changes (2023), machine learning-aided metabolite analysis (2023, 2022), and developmental PCB exposure links to voiding physiology (2022). Her 2021 studies explored behavioral phenotypes in PCB-exposed mice, dendritic effects, and bladder inflammation, while 2019 work included host-microbe interactions and open-source uroflowmetry tools.
