Kim May Lee is a Research Fellow at King’s College London (since 2021), specializing in clinical trial methodology. She previously held roles as Lecturer in Medical Statistics at Queen Mary University of London (2020–2021) and Research Associate at the MRC Biostatistics Unit, University of Cambridge (pre-2020). She earned her PhD in Statistics from the University of Southampton, following an undergraduate degree in Mathematics with Actuarial Science from the same institution. Her research focuses on advancing clinical trial methodologies, particularly adaptive designs, platform trials, and subgroup analysis. Key interests include improving trial efficiency through personalized approaches, handling missing data, and optimizing experimental designs. She also provides statistical consultation for clinical trials and has lectured in medical statistics across multiple institutions. Recent publications emphasize innovative trial designs, sample size calculations, and methodological challenges in adaptive approaches. Notable work includes evaluating the Personalised Randomized Controlled Trial (PRACT) framework and exploring the impact of heterogeneity in platform trials. Her expertise bridges statistical rigor with practical clinical applications, addressing gaps in trial conduct and data quality. Current research trends highlight collaboration with multi-disciplinary teams to enhance methodological solutions for modern clinical challenges.
Dr. Jeremiah K. N. Mbindyo is a Full Professor in the Department of Chemistry at Millersville University, within the College of Science and Technology. He has been a core faculty member since 2002, contributing significantly to undergraduate education and research in analytical, environmental, and nanoscale chemistry. His research focuses on the development and application of nanomaterials for environmental and biomedical purposes. Key areas include the use of microemulsions as green solvents for pollutant extraction, biodegradable and magnetic nanoparticles for drug delivery and diagnostics, catalytic nanowires for fuel cells and sensors, and innovative undergraduate laboratory experiments in nanotechnology. He also leads collaborative watershed studies through the Millersville University Center for Environmental Sciences (MUCES). The trend in his scholarly output from 1997 to 2008 reflects a strong interdisciplinary focus at the intersection of materials science, environmental analysis, and electrochemistry. His work bridges fundamental nanofabrication techniques with practical applications in sustainability and education, particularly in developing accessible nanotechnology experiments for undergraduates. Scientific Awards: Sustainability Award, American Chemical Society Committee on Environmental Improvement (ACS-CEI), 2016 IEEC Student Achievement Award, Electrochemical Society Teaching Assistant Award, University of Connecticut Harvey S. Sadow Fellowship, University of Connecticut Dr. Mbindyo advises undergraduate researchers and has developed curriculum and lab modules that integrate research into teaching. He serves as coordinator for the B.S. Chemistry Environmental Option, the Nanotechnology Option, and departmental internships, demonstrating strong commitment to student development and experiential learning. While no external grants are explicitly listed, his postdoctoral training and publication record suggest prior research funding. He is actively involved in professional societies, including the American Chemical Society (ACS) and the American Association for the Advancement of Science (AAAS), and contributes to advancing science education and sustainable chemistry practices.
Gary F. Templeton is a Professor of Management Information Systems (MIS) at West Virginia University's John Chambers College of Business and Economics. He holds a PhD in MIS from Auburn University and has previously held faculty positions at the University of Alabama in Huntsville and Mississippi State University. Education: PhD in MIS, Master of MIS, MBA, and Bachelor of Finance from Auburn University Teaching Experience: 10,000+ students at undergraduate, master's, and doctoral levels in business analytics, decision support systems, programming, and healthcare-related topics His research spans three decades, focusing on organizational learning, methodological challenges in MIS research, and the economics of information technology firms. Current work emphasizes messy data problems like non-normality and missing data, with applications in healthcare analytics, cybersecurity, and financial technology. Recent publications (2021-2025) examine topics including regression imputation methods, cluster analysis applications, AI frameworks for financial portfolio optimization, and vulnerability diffusion models in software ecosystems. His research demonstrates interdisciplinary applications of MIS principles across business, healthcare, and public policy domains. Key Contributions: Developed the Two-Step Normality Transformation method Created frameworks for organizational learning constructs Advanced methodologies for handling messy data in MIS research Explored digital resource clusters in software ecosystems Investigated economic structures of emerging technology providers Professor Templeton has taught across multiple MIS domains including systems analysis and design, information resource management, and advanced research topics. His recent work increasingly integrates artificial intelligence and machine learning techniques to address complex business and technical challenges.
Guvenc Arslan serves as a Professor in the Department of Statistics within the Faculty of Engineering and Natural Sciences, focusing on advanced statistical methodologies and machine learning applications. His work bridges theoretical statistics with real-world problem solving across diverse domains. His core research interests include: Machine Learning and Classification Algorithms Statistical Clustering Methods Applied Statistics in Healthcare and Earth Sciences Data Mining and Pattern Recognition Fuzzy Logic and Bayesian Methods Parameter Estimation and Distribution Theory Analysis of his 15 most recent publications (2024-2015) reveals consistent innovation in classification techniques, particularly for medical diagnostics (e.g., COVID-19, cryotherapy) and environmental monitoring (e.g., earthquake engineering, satellite data analysis). His methodology frequently integrates support vector machines, k-means clustering, and fuzzy Bayesian approaches to address complex data challenges. Dr. Arslan's scholarly contributions extend to software development, including a JAVA implementation for multivariate statistical testing, demonstrating his commitment to practical tool creation alongside theoretical advancement. His research maintains strong connections to both medical applications and geospatial engineering problems.
Michelle Cluver is an Associate Professor at the School of Science, Computing and Emerging Technologies at Swinburne University of Technology. As a researcher in the Centre for Astrophysics and Supercomputing , her work focuses on galaxy evolution in group environments, star formation physics, and the interplay between gas, dust, and galactic dynamics. She pioneered the use of mid-infrared WISE data for stellar mass and star formation rate calibration. PhD in Astronomy (University of Cape Town, 2009) ARC Future Fellow (2018–2022) Her research spans galaxy groups, HI gas distribution, and radio continuum studies, with recent work on the 4MOST Hemisphere Survey (co-PI). Key methodologies include MeerKAT, WALLABY, and JWST observations. Awards include the Anne Green Prize (2023) and UCT's Best PhD Thesis (2009). Grants highlight her leadership in projects like 'From Feast to Famine: Tracing Transformation in Galaxy Groups' (ARC, 2018–2022). She supervises PhD students in topics ranging from cosmic web assembly to transient universe studies.
Luis Leon Novelo is an Associate Professor in the Department of Biostatistics and Data Science at the University of Texas Health Science Center at Houston (UTHealth) School of Public Health . Since 2015, he has focused on Traumatic Brain Injury (TBI) research with TIRR Herman Memorial collaborators, alongside methodological work in Bayesian non-parametric statistics , model selection , and genetic data analysis . His expertise extends to clinical trials , longitudinal data analysis , and electronic health records (EHR) applications. Research Focus Neurobehavioral and psychological outcomes in TBI patients Bayesian statistical methods for biomedical data Genetic regulation and allelic imbalance Health literacy and outcomes in post-injury populations Statistical modeling of longitudinal and censored clinical data Recent Publications His recent articles (2023–2025) span traumatic brain injury symptom profiles , Bayesian modeling techniques , and health equity in chronic disease populations . Key collaborations include TBI-QOL quality-of-life assessments and allelic imbalance studies in Drosophila hybrid models.
Patricia Soranno is a Professor in the Department of Fisheries and Wildlife at Michigan State University's College of Agriculture & Natural Resources, where she co-directs the Data-intensive Landscape Limnology Lab. She maintains dual affiliations with Integrative Biology and the Ecology, Evolution, and Behavior program, reflecting her cross-disciplinary approach to freshwater science. Her research focuses on landscape limnology and macrosystems ecology, investigating multi-scaled spatial and temporal drivers of aquatic chemistry and biology. She pioneers data-intensive approaches to study land-water interactions, water quality dynamics, and freshwater responses to climate change across continental scales. Her work integrates large-scale datasets like the LAGOS-US platform to address complex ecological questions through collaborative frameworks. Analysis of her recent publications (2023-2025) reveals a dominant focus on continental-scale freshwater ecology, with emphasis on climate-lake interactions, nutrient limitation patterns, drought responses, and environmental justice in monitoring systems. Her research consistently leverages big data methodologies and multi-institutional collaborations to advance predictive understanding of lake ecosystems. Dr. Soranno's scientific contributions have been recognized through prestigious fellowships: American Association for the Advancement of Science (AAAS) Fellow (2019) Association for the Sciences of Limnology and Oceanography (ASLO) Fellow (2019) She has secured significant National Science Foundation funding, including a major collaborative macrosystems ecology project (2016-2025) and intergovernmental mobility awards (2019-2023). Her research program emphasizes collaborative data generation and sharing, exemplified by the LAGOS-US database containing information on over 50,000 US lakes. As co-director of the Data-intensive Landscape Limnology Lab, Dr. Soranno leads a research team developing innovative approaches for continental-scale freshwater ecology. The lab specializes in creating integrated datasets, advancing spatial modeling techniques, and training next-generation scientists in data-intensive research methods through active participation in large collaborative networks.
Nicola Aceto is a Professor at ETH Zurich leading the Aceto Research Group within the Institute of Molecular Health Sciences. His laboratory focuses on understanding the fundamental molecular mechanisms that drive cancer metastasis, with particular expertise in circulating tumor cells (CTCs) and their clusters. The research addresses a critical oncology challenge: more than 90% of cancer-related deaths result from metastatic disease, accounting for over 7 million deaths worldwide annually. Dr. Aceto's research primarily focuses on: Circulating tumor cells and their clusters in metastasis The role of circadian rhythm in cancer cell intravasation Genetic and epigenetic drivers of metastasis Development of metastasis-tailored therapies Application of microfluidic and robotic technologies for CTC analysis CRISPR screening to identify metastasis-relevant genes Analysis of Dr. Aceto's publication record reveals a strong trajectory from initial discoveries about CTC clusters in breast cancer (2014) to recent work exploring circadian regulation of metastasis (2022) and therapeutic targeting of CTC clusters (2025). His research consistently applies innovative technologies including microfluidics, next-generation sequencing, and CRISPR screening to address fundamental questions in cancer metastasis. Dr. Aceto actively mentors researchers at multiple levels including PhD students, postdoctoral fellows, clinical fellows, and undergraduates. His laboratory maintains extensive collaborations with academic research groups, hospitals, and healthcare companies worldwide to identify novel therapeutic opportunities against cancer metastasis. The Aceto lab operates within the Institute of Molecular Health Sciences at ETH Zurich, utilizing advanced molecular biology techniques, next-generation sequencing, computational biology approaches, and specialized microfluidic technologies to isolate and analyze circulating tumor cells from patient samples. The laboratory maintains active clinical partnerships to ensure research remains closely connected to patient needs and therapeutic development.
Professor Mark Blaxter serves as Programme Lead for the Tree of Life Programme at the Wellcome Sanger Institute and Professor of Evolutionary Genomics at the University of Edinburgh. He heads the Blaxter Group, which focuses on evolutionary genomics with an emphasis on biodiversity conservation through high-quality genome sequencing. As a key figure in the Darwin Tree of Life Project, he leads efforts to sequence all 60,000 named eukaryotic species in the British Isles over the next decade, working within the global framework of the Earth BioGenome Project. Blaxter completed his BSc (Honours Zoology) at the University of Edinburgh followed by a PhD from the London School of Hygiene and Tropical Medicine. His academic career progressed from Lecturer to Reader to Professor at Edinburgh, with previous research fellowships at Imperial College London supported by the Wellcome Trust and Medical Research Council. Professor Blaxter's research spans evolutionary genomics, biodiversity science, and conservation. His work focuses on using high-quality genome sequences to explore evolutionary relationships, build the tree of life, and provide resources for conservation and biotechnology. He has pioneered approaches to generate reference-quality genomes for thousands of species beyond traditional model organisms. His research investigates genome evolution through time, cryptic species diversity, symbiosis (particularly parasitism), and chromosomal structure evolution. With over 30% of all eukaryotes classified as parasites, understanding these relationships is central to his work on genomic diversity and biodiversity conservation. Analysis of Blaxter's recent publications reveals a strong focus on biodiversity genomics, with particular emphasis on creating reference genomes for diverse species across the tree of life. His work spans nematodes, insects, marine organisms, and other eukaryotes, contributing to large-scale initiatives like the Earth BioGenome Project. The research demonstrates increasing sophistication in genomic technologies, moving from single-species studies to large-scale comparative analyses that address fundamental evolutionary questions while providing practical conservation tools. Throughout his career, Professor Blaxter has championed open access to genomic data, releasing datasets well in advance of publication to encourage reuse. His group develops essential tools for genome analysis including BlobToolKit for quality assessment, KinFin for taxon-aware protein analysis, and MitoHiFi for mitochondrial genome assembly. The Blaxter Group collaborates extensively with institutions across the British Isles including the Natural History Museum, Royal Botanic Gardens Kew, Royal Botanic Gardens Edinburgh, Marine Biological Association, and universities including Oxford and Cambridge. Blaxter leads the Tree of Life Programme at the Sanger Institute, a major initiative generating high-quality genome sequences to explore evolutionary relationships across the tree of life. The program works closely with the Darwin Tree of Life Project and other international genome sequencing efforts to create a comprehensive genomic resource for biological science. His laboratory combines wet-lab genomic approaches with advanced bioinformatics to tackle questions at the intersection of evolution, biodiversity, and conservation, addressing the critical challenge of the sixth great extinction through genomic insights.
Georgios Magdis is an Associate Professor in the Department of Space Research and Technology at the Technical University of Denmark (DTU), specializing in Astrophysics and Atmospheric Physics. He also holds an external position as Affiliated Associate Professor at the University of Copenhagen since 2021. His research focuses on galaxy formation and evolution across cosmic time, with particular expertise in high-redshift galaxies, star formation processes, and the interstellar medium. Magdis's research interests center on galaxies and their evolution, with specific focus areas including star formation (93% of his work), stellar mass (79%), star formation rates (65%), spectral energy distribution (45%), molecular gas (39%), interstellar matter (38%), and active galactic nuclei (36%). His work heavily utilizes cutting-edge observational facilities including JWST, ALMA, and NOEMA, with research spanning from the local universe to the cosmic dawn. He has published 116 research outputs, with a significant portion focusing on early universe galaxy formation and evolution. His recent publications reveal a strong emphasis on high-redshift galaxy studies using JWST data, with particular interest in galaxy structure, star formation processes, and dust properties in the early universe. His work often involves large international collaborations, particularly with the COSMOS-Web survey, which represents one of the most ambitious JWST projects to date. His research frequently combines multi-wavelength observations to build comprehensive models of galaxy evolution across cosmic time. Magdis actively supervises multiple PhD students and leads significant research projects including 'The Hidden Cosmos' and 'Unveiling the physics of galaxies and structure assembly in the early Universe.' His work has generated several important datasets, including the NOEMA formIng Cluster survEy (NICE), which has been widely referenced in the astronomical community.
Magda Sofia Roberto is an Assistant Professor at the Faculty of Psychology, Universidade de Lisboa, actively contributing to the Pedagogical Council. Her academic role centers on teaching core quantitative courses including Introduction to Probability , Statistics Applied to Psychology , and Data Analysis and Processing , reflecting her expertise in methodological training. Her research program addresses three critical domains: Digital Exclusion and eHealth : Investigating health disparities among digitally marginalized populations using participatory methods like digital storytelling Migrant Health : Examining social determinants of health in immigrant communities, particularly Portuguese and South American populations Compliance Behaviors : Analyzing social/moral norms influencing health behaviors such as hand hygiene in medical settings She actively develops student-centered approaches to reduce statistics anxiety, bridging educational psychology with quantitative methods training. Her publication record demonstrates consistent output in high-impact journals including PLoS ONE and Health Promotion International , with recent work focusing on systematic reviews of web-based interventions for parental feeding practices and social-emotional learning impacts on teacher burnout. Current projects include developing the SmartFeeding4Kids online parenting intervention and studying sexual distress through transdiagnostic frameworks. Scientific recognition includes: Principal investigator for FCT-funded project PTDC/PSI-GER/30432/2017 on web-based parenting interventions Postdoctoral research with CLAHRC at Birmingham Children's Hospital FCT fellowship SFRH/BPD/78903/2011 on digital literacy As a statistical consultant for DECRA DE150100731 at Murdoch University, she supports international research on self-regulated learning development. Her methodological expertise spans mixed-methods designs, systematic reviews, and meta-analyses, with particular emphasis on participatory approaches that amplify marginalized voices in health research.
Dr Pedro Beltran-Alvarez is a Senior Lecturer in Health and Climate Change at Hull York Medical School (HYMS), University of Hull, where he serves as co-Director of the MSc Health and Climate Change program. His work explores the critical links between human health and climate change, identified by the WHO as the biggest health threat facing humanity. Dr Beltran-Alvarez completed his PhD at the University of Bristol (2004-2007) with funding from a Marie Curie grant, followed by postdoctoral research at the European Molecular Biology Laboratory (EMBL, Heidelberg, 2007-2009). He then worked at the Cardiovascular Research Centre at the University of Girona (2009-2014), where he held a Sara Borrell Postdoctoral Fellowship. He joined the University of Hull in 2015 as a Lecturer and was promoted to Senior Lecturer in 2022. His research focuses on protein post-translational modifications, particularly arginine methylation, and their role in biological responses to environmental changes with implications for human health. His work spans cardiovascular disease, brain tumors (particularly glioblastoma), and climate change impacts on biological systems, employing innovative approaches including tissue-on-chip technology. Analysis of his recent publications reveals a consistent focus on environmental factors and human health across diverse model systems from zebrafish and lizards to human clinical samples. Dr Beltran-Alvarez actively supervises PhD students working on cardiovascular disease, stress signaling in fish, and brain tumor research. His research has been supported by grants totaling over £147,000 from The Hull and East Riding Cardiac Trust and Yorkshire Brain Tumour Charity, in addition to internal university funding for his 'Happy Chemical Cluster' project. He contributes to the academic community as Editor of Amino Acids (Springer) in the Environmental Science section, serves on the Yorkshire and Humber Climate Commission, and acts as an external PhD thesis examiner, demonstrating his commitment to translating research into policy and practice.
Academic Affiliation An Goris is a full professor at the Faculty of Medicine , KU Leuven, affiliated with the Department of Neuroscience and Laboratory for Neuroimmunology . She serves on the Faculty Council of Medicine and Departmental Council of Neurosciences as a ZAP member. Research Focus Her work bridges neuroimmunology and genetic epidemiology , with specific emphasis on: Mechanistic understanding of multiple sclerosis (MS) through single-cell transcriptomics Epstein-Barr virus as a causal trigger in MS Machine learning for MS prognosis prediction Immune cell dynamics under immunomodulatory treatments CNS resilience and neuroprotection in disease progression Genetic clustering of severity markers Publications Recent work demonstrates multidisciplinary approaches combining immunology, genetics, and computational methods. Key trends include: Single-cell resolution of immune subsets in neuroinflammatory diseases Integration of AI for longitudinal disease modeling Identification of genetic loci influencing MS severity Characterization of NK cell diversity in MS Exploration of viral reactivity in MS cohorts Development of genomic biobanking infrastructure Mentorship She actively supervises research projects, including co-supervision of Swinnen S. (2024) and Masrori P. (2023). Her leadership spans multiple collaborative consortiums like MultipleMS and Belgian Genomic Biobank initiatives.
Soundar Rajan Tirupatikumara is the Allen E. Pearce and Allen M. Pearce Professor in the Marcus Department of Industrial and Manufacturing Engineering at Pennsylvania State University, affiliated with the Institute for Computational and Data Sciences (ICDS) and the Center for Interdisciplinary Mathematics . With over 4,000 citations and an h-index of 41, his work spans industrial engineering, systems engineering, and artificial intelligence. Key Research Areas: Supply Chain Management, Digital Twins, Machine Learning, and Sustainable Energy Systems. Notable Projects: NSF-funded initiatives on AI-based sensing, digital twin integration for SMEs, and energy analytics. Collaborations: Contributions to UN Sustainable Development Goals (SDGs), particularly in sustainable manufacturing and interdisciplinary research.
Dr James W E Drewitt is an Honorary Industrial Fellow in the School of Physics at the University of Bristol. He holds a BSc, PhD and is a Fellow of the Higher Education Academy (FHEA). His research integrates synchrotron and neutron experiments, containerless processing, and high-performance molecular dynamics to investigate liquids and glasses under conditions ranging from quantum-optical device fabrication to the deep interiors of planets. Education: BSc – physics-related discipline PhD – physics-related discipline Fellow of the Higher Education Academy (FHEA) Research Interests: Dr Drewitt’s work spans three interconnected themes: Physics of Liquids and Glasses. Using in situ synchrotron x-ray and neutron scattering, he probes atomic-scale structure and rheology that control glass formation, combining these data with classical and density-functional molecular dynamics on the University of Bristol Advanced Computing Research Centre and the UK national supercomputer ARCHER. Containerless Processing. Aerodynamic and ultrasonic acoustic levitation with laser heating allows ultrafast quench rates, enabling deep supercooling studies and the creation of novel optical glasses—particularly for whispering-gallery-mode microresonators—while avoiding heterogeneous nucleation. Melt and Mineral Physics of Planetary Interiors. Diamond-anvil-cell experiments coupled with laser or resistive heating reproduce deep-Earth and planetary interior conditions, elucidating the structure and properties of silicate melts and liquid metals under extreme pressures and temperatures. Scientific Awards & Honours: Fellow of the Higher Education Academy (FHEA) Research Outputs & Impact: Dr Drewitt has authored 41 peer-reviewed articles (including 2 review articles) and produced 7 open datasets. His 2021 review on high-pressure liquid structure alone has attracted 17 citations within two years, while his 2020 Physical Review Letters study on liquid gallium garnered 22 citations. His datasets, downloaded hundreds of times, underpin collaborative projects with Diamond Light Source, ESRF, ILL and other central facilities. Collaboration, Grants & Facilities: Principal user of Diamond Light Source (UK), European Synchrotron Radiation Facility and Institut Laue–Langevin (France). Extensive computational resources via the University of Bristol Advanced Computing Research Centre and the ARCHER UK supercomputer. Co-investigator on the NERC-funded “Deep Water: Hydrous Silicate Melts and the Transition Zone Water Filter” project (2016–2020). Invited speaker at international conferences and users’ meetings, including NSLS-II/CFN/LBMS (2023) and Frontiers in Glass II (2021). Labs & Teams: Dr Drewitt is affiliated with the Physics Education Group at Bristol, while operating experimental stations at central facilities, maintaining high-pressure laser-heated diamond anvil cell laboratories, and coordinating simulation campaigns on national HPC platforms.
