Sean O'Donoghue is a Conjoint Professor at the School of Biotechnology and Biomolecular Science, University of New South Wales (UNSW). He concurrently serves as a Laboratory Head and Senior Faculty Member at the Garvan Institute of Medical Research and a Visiting Scientist at CSIRO Data61. He holds a B.Sc. (Hons) and Ph.D. in Biophysics from the University of Sydney. His research integrates bioinformatics, structural biology, and data visualization to decode complex biological systems. Key interests include: Development of computational tools for protein structure/function analysis Visual analytics for genomics and multiomics data Mechanisms of viral protein assembly (e.g., SARS-CoV-2) Epigenetic dynamics and cancer transcriptomics Recent publications (2018–2022) demonstrate a strong focus on: Protein annotation frameworks and dark proteome characterization SARS-CoV-2 structural mechanisms Single-cell transcriptomics in breast cancer Innovations in biological data visualization tools He leads the VIZBI initiative (advancing bioinformatics visualization) and VizbiPlus (public science outreach). No awards or student advisories are detailed in the source material.
Brooke N. Wolford is a Marie Skłodowska-Curie Postdoctoral Fellow at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Public Health and Nursing within the Faculty of Medicine and Health Sciences. She leads the ProtectHearts and HUNT AI for Heart Health projects at the HUNT Center for Molecular and Clinical Epidemiology, while also contributing to the EU-funded INTERVENE project through the Finnish Institute for Molecular Medicine. Her work bridges statistical genetics, computational biology, and clinical applications to advance precision public health initiatives. Dr. Wolford earned her PhD in Bioinformatics and Master's in Statistics from the University of Michigan, where she completed her dissertation on 'Genetic Discovery and Precision Medicine in Cardiovascular Diseases Using Electronic Health Record-linked Biobanks' under Dr. Cristen Willer and Dr. Michael Boehnke. Her undergraduate training includes a Bachelor of Science in Quantitative Biology with highest honors from the University of North Carolina at Chapel Hill, where she was a Phi Beta Kappa honors graduate. Her research program focuses on artificial intelligence-driven precision public health, particularly in cardiovascular disease prediction and prevention. By integrating genomics, proteomics, and clinical data from large biobanks like HUNT, UK Biobank, and FinnGen, she develops novel risk prediction models that address critical gaps in women's heart health and young adult disease prevention. Her work on polygenic risk scores and proteomic biomarkers aims to transform population-scale screening programs through explainable AI methodologies. Dr. Wolford's recent publications demonstrate significant contributions to genetic epidemiology, with high-impact work in Nature Genetics, Nature Communications, and Circulation: Genomic and Precision Medicine. Her research outputs reveal consistent themes in cross-population polygenic score development, sex-specific disease mechanisms, and innovative biobank data integration approaches that enhance cardiovascular risk prediction across diverse populations. 2022/2023 Best Dissemination Award (K.G. Jebsen Centers) 2022 ASHG Trainee Research Excellence Award Finalist 2021 ASHG Trainee Research Excellence Award Semi-Finalist National Science Foundation Graduate Research Fellowship Genome Sciences Predoctoral Traineeship University of Michigan Program in Biomedical Sciences 20th Anniversary Award As a dedicated mentor, Dr. Wolford supervises multiple graduate students across Master's and PhD programs at NTNU, focusing on proteomic risk prediction for diabetes, cardiovascular-Alzheimer's disease connections, and polygenic scoring for women's heart health. She actively promotes open science through R-ladies Trondheim leadership and develops educational resources like the Health AI in R workshop. Her ongoing projects with INTERVENE and ProtectHearts secure substantial European research funding for translational genomics initiatives. Dr. Wolford co-leads the HUNT AI for Heart Health initiative and ProtectHearts project within the HUNT Center for Molecular and Clinical Epidemiology. These teams integrate computational biologists, clinicians, and epidemiologists to develop explainable AI models that translate genomic discoveries into clinical prevention strategies, with particular emphasis on addressing health disparities in cardiovascular outcomes for women and younger populations.
Camila Consiglio is a Senior Lecturer and Principal Investigator at the Division of Molecular Hematology (DMH) , Department of Laboratory Medicine , Lund University. She leads research initiatives at LUCC: Lund University Cancer Centre and StemTherapy: National Initiative on Stem Cells for Regenerative Therapy , while also managing the Systems Immunology research team and coordinating projects at Infect@LU . Her research focuses on elucidating how biological sex and sex hormones modulate human immunity through systems immunology and multiomics technologies. Key areas include: Sex differences in immune responses Testosterone signaling in immunity Immunomonitoring of human cohorts Computational modeling of immune-gonadal interactions Her recent publications include studies on gender-affirming testosterone treatment effects on immunity (Nature, 2024) and sex/gender impacts on infection outcomes (Royal Society Open Science, 2023). These works integrate immunology, endocrinology, and computational biology. Awards: DDLS Fellow (Knut and Alice Wallenberg Foundation, 2023) She supervises MSc students and collaborates with cross-disciplinary teams at Lund University and SciLifeLab. Her work bridges data-driven life science with public health implications for sex-biased immune disorders.
Levi Adams is an Assistant in Instruction/Lecturer in the Biology Department at Bates College. He holds a Ph.D. in Biomedical Sciences from the University of Central Florida. His research focuses on how aging affects the brain and contributes to neurological diseases like Parkinson’s and Alzheimer’s. Using techniques such as single-nuclei multiomic analysis and epigenomic editing, he investigates gene regulation changes during aging and identifies novel cellular markers linked to disease risk. Adams previously worked in culinary arts before transitioning to biology, bringing a unique interdisciplinary perspective to his research. Education: Ph.D. in Biomedical Sciences, University of Central Florida Research Interests: Adams explores age-related neurodegenerative mechanisms, protective gene silencing in aging, and innovative tools for studying α-synuclein and histone modifications. His work integrates molecular biology, transcriptomics, and computational methods to uncover disease pathways. Publications Overview: His recent work includes groundbreaking studies on glial changes in Parkinson’s disease, epigenetic editing tools, and drug efficacy in neurodegenerative models. These studies highlight advancements in understanding disease progression and potential therapeutic strategies. Advising & Grants: While no formal advisees are listed, his collaborative research often involves undergraduate students (denoted with * in publications). Funding sources and specific grants are not detailed in available texts. Affiliations: Located in Dana Hall, Room 322 at Bates College, Adams contributes to teaching and research activities within the Biology Department.
Preetam Ghosh, Ph.D. , is a Research Professor in the Department of Computer Science at Virginia Commonwealth University (VCU) , with cross-disciplinary focus in computational biology, machine learning, and network science. His work bridges engineering and biomedical research , particularly in pandemic modeling, multiomics data integration, and bioinformatics tool development. Academic Role: Research Professor, VCU School of Engineering Key Research Areas: Computational Biology, Network Analysis, Pandemic Modeling, Multiomics Data, Bioinformatics Algorithms Recent Research Trends include: Application of machine learning to biomedical data (e.g., drug-target affinity prediction, breast cancer subgroup classification) Development of physics-informed models for pandemic propagation and chemical reaction networks Innovations in network science , such as link prediction and vulnerability analysis for biological and IoT systems Advancing single-cell genomics through consensus algorithms (COFFEE, CHAI, CORTADO) Design of adaptive routing protocols for disaster-resilient IoT networks (ADRIN, ADRIN2.0)
Hayan Lee is an Assistant Professor at the Fox Chase Cancer Center and a member of the Cancer Epigenetics Institute with a focus on the Nuclear Dynamics and Cancer (NDC) program. Her lab investigates computational epigenetics in cancer and aging, emphasizing machine learning for biomarker development and therapeutic optimization. Ph.D. in Computer Science, Stony Brook University (2015) M.S. in Information Security Technology and Management, Carnegie Mellon University (2008) B.S. in Computer Science and Engineering, Seoul National University (2002, Cum Laude) Research interests span computational epigenetics, multi-omics data analysis, and cutting-edge technologies like single-cell sequencing and spatial transcriptomics. Her work identifies predictive epigenetic signatures and models cancer microenvironment dynamics. Recent publications highlight trends in applying machine learning to cancer diagnostics, epigenetic dysregulation, and single-cell technologies. Notable awards include the Best Paper Award at ISMCO’21 and the Simons Postdoctoral Fellowship . Scientific Awards Best Paper Award, ISMCO’21 Simons Postdoctoral Fellowship, 2015-2016 Ph.D. Fellowship, Stony Brook, 2009-2010 M.S. Scholarship, Carnegie Mellon, 2006 Cum Laude, Seoul National University, 2002 Hayan Lee leads the Nuclear Dynamics and Cancer Lab, collaborating with institutions like Stanford University and Temple University. Her research integrates high-performance computing and machine learning frameworks to advance cancer and aging diagnostics.
Jie Hao is a researcher at the Information Security Center of Beijing University of Posts and Telecommunications , with a focus on interdisciplinary applications spanning Bioinformatics , Artificial Intelligence , and Medical Informatics . His work bridges computational methods with real-world challenges in healthcare, ecology, and network optimization. Recent publications highlight his contributions to Single-cell RNA sequencing deconvolution (2025) AI-driven intergenerational communication in VR (2025) Digital health applications for COPD management (2025) Deep reinforcement learning for vehicle routing (2025) His methodological innovations include adaptive attention mechanisms for object detection (2025), memory-efficient DNN accelerators (2025), and bilevel optimization algorithms with unbounded smoothness (2024). Collaborations span institutions like University of Melbourne and Chinese Academy of Sciences , reflecting his cross-disciplinary impact.
Dr. Heather Waddell is a Researcher in Infectious Disease Epidemiology at the University of Glasgow's Department of Public Health. She holds a PhD from the University of Edinburgh, where her research focused on circadian rhythm dysregulation in critical illnesses like acute pancreatitis. Her work integrates multi-omics data analysis, Bayesian networks, and large-scale health surveys to address public health challenges. Education: - PhD (Medical Research Doctoral Training Programme), University of Edinburgh (focus: circadian rhythms in critical illness) - Background in multi-omics and clinical data analysis. Research Interests: Infectious disease modelling, tuberculosis research, epidemiology, critical care, and applications of systems biology. She has extensively worked with datasets like the Chilean National Health Survey and NHS multi-omics records. Recent Work Trends: Recent publications emphasize acute pancreatitis pathophysiology, circadian rhythm disruptions in critical illness, and socio-demographic health correlations in Chile and the UK. Her 2023 Heliyon paper explored circadian rhythms' role in acute pancreatitis, while 2024 conference work highlighted multiomic analyses of clinical outcomes in this condition. Grants & Collaborations: Collaborative projects include work with NHS datasets and international teams on metabolic pathways in acute pancreatitis. No explicit grants mentioned, but her work reflects multi-institutional partnerships. Labs/Teams: Affiliated with Glasgow's Department of Public Health, though specific lab affiliations are not detailed.
Dr. Mengyuan Ren is a Researcher in the Gangarosa Department of Environmental Health at Emory University. Their work focuses on understanding how environmental factors impact maternal and child health using multi-omics approaches, including exposome analysis, microbiome studies, and machine learning. Dr. Ren holds a Ph.D. from Peking University's Institute of Reproductive and Child Health (School of Public Health), with additional training in epidemiology, biostatistics, and bioinformatics. Dr. Ren leads key initiatives such as the 'Exposomex' platform (http://www.exposomex.cn/#/home), an integrative exposomic tool accelerating discovery of environmental-biology-disease linkages, and contributed to establishing a national infertility registry study in China (CCC2021112202). Their research emphasizes identifying biomarkers for environmental exposures and developing interpretable predictive models. Recent studies explore effects of air pollution on in vitro fertilization success, metalloid exposure in reproductive health, and machine learning applications in health risk assessment. Dr. Ren's work bridges environmental science and clinical practice, addressing critical public health challenges in maternal-child health through innovative analytical frameworks.
Dr. Micha Wijesingha Ahchige is a Senior Research Officer at the School of Life Sciences, University of Essex. He holds a B.Sc. from the University of Cologne (2014), an M.Sc. from the University of Giessen (2017), and a Dr. rer. nat. (Ph.D.) from the University of Potsdam (2022). His research focuses on plant biochemistry, metabolomics, and genetics, with particular emphasis on understanding metabolic pathways and genetic regulation in plants under stress conditions. He uses multi-omics approaches to study lipid metabolism, secondary metabolites, and stress responses in model organisms like tomato and Arabidopsis. Key research areas include the analysis of mutant phenotypes (e.g., canalized-1 tomato mutants), genome-wide association studies (GWAS), and the integration of biochemical and genetic data to uncover mechanisms of metabolic adaptation. His work often involves collaboration with international teams, leveraging advanced analytical techniques such as metabolite profiling and proteomics. Dr. Ahchige’s publications highlight contributions to understanding photosystem assembly defects, lipid metabolism networks, and the role of specific genes in stress acclimation. He maintains active engagement through social media (Mastodon: @plantscimike) and academic platforms like ResearchGate, ensuring broader dissemination of his findings.
Alexandre G. Maia, Ph.D., is an Associate Professor in the Department of Laboratory Medicine and Pathology and Assistant Professor of Pharmacology at Mayo Clinic in Rochester, Minnesota. He serves as Senior Associate Consultant II-Research in the Division of Experimental Pathology and Laboratory Medicine and is the Associate Director of the Epigenomics Program at the Center for Individualized Medicine. Dr. Maia leads the Functional Epigenomics Laboratory, focusing on cutting-edge research in cancer and stem cell biology. Education: Postdoctoral Fellowship in Chromatin Biology, Icahn School of Medicine at Mount Sinai Ph.D. in Molecular Biology, University of Coimbra Predoctoral Research Fellow, University of California at San Francisco (UCSF) B.S. in Aquatic Sciences, ICBAS, University of Porto Undergraduate Studies, University of Rome (La Sapienza) Dr. Maia's research is centered on understanding the epigenomic regulation of cancer stem cells, particularly in ovarian cancer. His work integrates single-cell sequencing technologies such as ATAC-seq and RNA-seq to profile enhancer elements and transcriptional dependencies. He employs advanced model systems including 3D organoids, patient-derived xenografts, and liquid biopsies to study tumor heterogeneity. His lab utilizes CRISPR/Cas9 for functional validation and microfluidic devices for drug combination testing. Bioinformatic analysis of multi-omics data is a key component of his research. The recent publications reflect a strong trend in functional genomics, epigenetics, and personalized cancer therapy. His work spans multiple myeloma, clonal hematopoiesis, post-translational modifications, CAR T cell exhaustion, and personalized drug testing in pancreatic cancer. The recurring themes include single-cell multiomics, enhancer biology, and translational applications in oncology. Scientific Awards and Honors: Career Enhancement Program Award, Breast SPORE, Mayo Clinic (2022–2024) Early-Career Investigator, Ovarian Cancer Academy, U.S. Department of Defense (2021–2025) Regenerative Sciences Curriculum Development Award, Mayo Clinic (2020) Career Enhancement Program Award, Ovarian SPORE, Mayo Clinic (2019–2020) Career Development Award, Department of Laboratory Medicine and Pathology (2018) NYSCF-Druckenmiller Fellowship (2014–2017) Postdoctoral Recognition Award, Icahn School of Medicine (2014) Ph.D. Fellowship, Science and Technology Foundation, Portugal (2003–2007) Dr. Maia has received substantial grant support from prestigious programs including the Department of Defense Breast and Ovarian Cancer SPOREs, and has been recognized with multiple early-career awards. He mentors research trainees and contributes to curriculum development in regenerative sciences. His laboratory actively collaborates across disciplines to advance epigenomic technologies and their clinical applications. Dr. Maia leads the Functional Epigenomics Laboratory and plays a key role in the Epigenomics Program at the Center for Individualized Medicine. His team integrates wet-lab experimentation with computational biology to develop novel approaches for cancer diagnosis and therapy.
Hanna Björck is a Senior Research Specialist (Docent) at the Karolinska Institutet , leading a translational research group focused on molecular and epidemiological studies of ascending aortic aneurysms (AscAA). Her work integrates clinical cohort analysis, multiomic profiling, and in vitro functional studies of vascular cells. Education: PhD in Physiology (2012), Linköping University Postdoctoral Fellowship, Karolinska Institutet (2012-2016) Research: Mechanisms of AscAA in bicuspid aortic valve (BAV) and degenerative disease Biobank of >2400 patients with vascular tissue and biomarker collections Genetic risk factors, DNA methylation, and flow-dependent endothelial dysfunction Grants: Prince Daniel’s Research Grant for Promising Young Researchers (2025-2027) Swedish Heart-Lung Foundation Fellowship (2025-2030) Swedish Research Council (2021-2023; 2017-2020) Swedish Heart-Lung Foundation (2019-2021) Collaborations: STAR (Stockholm Aneurysm Research Group) Prof. Anders Franco-Cereceda & Docent Christian Olsson (Karolinska University Hospital) Docent Joy Roy & Prof. Rebecka Hultgren (Vascular Surgery, Karolinska) Dr. Maria Sabater Lleal (Genetic Analyses, Barcelona) Dr. Pelin Sahlén (Promoter-Enhancer Mapping, SciLifeLab)
Professor Bart De Moor is a full professor at the KU Leuven Faculty of Engineering Sciences, affiliated with the Department of Electrical Engineering (ESAT) and the STADIUS Center for Dynamic Systems, Signal Processing, and Data Analysis. His research spans mathematical engineering, system theory, and biomedical data science, with significant contributions to Machine Learning Medical AI Time Series Analysis High-Dimensional Data Optimization underpinned by an ERC Advanced Grant and the Order of the Crown (2025). His recent work includes AI-driven clinical decision support systems ( BJOG , 2025), spatial omics pipelines for pancreatic cancer ( Cancer Research , 2025), and energy demand forecasting ( Applied Energy , 2025). He has supervised over 93 PhD students and founded 9 spin-offs, including Health House and Athumi .
Sergio Mosquim Junior is a Researcher and Doctoral student in the Department of Immunotechnology at Lund University's LTH (Faculty of Engineering), with additional affiliations at the Lund University Cancer Center (LUCC) and the Technology for Health profile area. His research focuses on advancing precision medicine through innovative proteomics approaches. His primary research interests include Proteomics , Biomarker Discovery , and Mass Spectrometry , with specific expertise in developing automated workflows for proteomics and phosphoproteomics analysis of clinical samples. He bridges advanced wet lab protocols with bioinformatics workflows, applying multiomic data integration and machine learning to drive discovery efforts in precision medicine and cancer research. His recent publications demonstrate a clear trajectory toward integrating high-throughput proteomics with other omics data to enhance biomarker discovery, particularly in oncology applications. The research shows increasing sophistication in methodology, from basic plasma proteome profiling to advanced multiomic integration approaches. As Principal Investigator, he leads the active research project "Hög genomströmningsproteomik för analys av stora kliniska kohorter" (High-throughput proteomics for analysis of large clinical cohorts), funded by Kungliga Fysiografiska Sällskapet i Lund from November 2023 to November 2025. He has presented his work at the Lund University Cancer Centre (LUCC) meeting in May 2023 as a speaker. His technical expertise spans both wet lab protocols and bioinformatics, with particular strength in automation of proteomics workflows for clinical samples. He actively contributes to the Lund University Cancer Center's research ecosystem through his specialized proteomics expertise.
Hagen Tilgner is an Associate Professor of Neuroscience at Weill Cornell Medical College . His research focuses on integrating long-read sequencing with single-cell and spatial transcriptomics to study RNA splicing, isoform expression, and their roles in neurodevelopmental disorders and cancers like gliomas. Education M.Sc., Joseph Fourier University (Grenoble I) Faculty of Medicine (France), 2005 Ph.D., Pompeu Fabra University (Spain), 2011 M.Sc., University of Karlsruhe (Germany), 2005 Hagen's research has led to groundbreaking work on spatial isoform sequencing, uncovering cell-type-specific splicing patterns in cortical layers and diseases like Alzheimer's. His recent publications highlight advancements in precision medicine and isoform detection using RNA-Seq. Key trends in his publications include: Long-read sequencing for isoform mapping Single-cell and spatial transcriptomics Splicing regulation in neurodevelopment and disease Algorithm development for RNA data analysis Targeting RNA variants in cancer Epigenetic and chromatin interactions
