Prof. Dr. Deniz Tasdemir is a Full Professor (W3) of Marine Natural Products Chemistry at GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel and serves as Director of the GEOMAR-Biotech center and Head of the Marine Natural Product Chemistry Research Unit. Her career spans institutions including the National University of Ireland Galway and UCL School of Pharmacy. PhD in Pharmacy, ETH Zurich (1997) Post-doctoral work, University of Utah (2001) Dr. Helmut Legerlotz Fellowship, University of Zurich (2002-2025) Her research focuses on marine chemical ecology , metabolomics , and bioprospecting for bioactive compounds from sponges, algae, and marine microbiomes. Recent work explores seagrass pathogen reduction, microbiome interactions, and aquafeed applications. Scientific awards include: Waters Award for Natural Products Innovation (2016) Egon Stahl Silver Medal (2005) Pierre Fabre Prize (2004) ETH Zurich Medal (1997) She leads collaborative projects on ocean sustainability and marine drug discovery, with editorial roles in Marine Drugs , Planta Medica , and Phytochemistry Letters .
Leonie Bentsink is a Professor at the Laboratory of Plant Physiology , part of Wageningen University . Her research focuses on molecular mechanisms underlying seed dormancy, germination, and longevity in plants like Arabidopsis thaliana . She leads projects investigating translational regulation, seed microbiomes, and abiotic stress tolerance, supported by an NWO Vici grant (2018). Dr. Bentsink supervises multiple PhD candidates and has authored over 69 publications. Key contributions include discovering roles for genes like DOG1 and ANAC060 in dormancy regulation, and developing tools like the SeedTransNet translational network. Key Projects: Seed microbiome impacts on drought tolerance Seed germination cell communication mechanisms Spatial transcriptomics for abiotic stress resilience Datasets: 11 publicly available datasets on seed transcriptomes/metabolomes, including seed dormancy cycling and parental effect studies. Citations: Over 70 publications since 2000, with notable work on seed longevity and translational regulation.
Professor Luke Prendergast is the Deputy Dean of the School of Computing, Engineering & Mathematical Sciences (SCEMS) at La Trobe University (LTU) and holds a Professorship in the Department of Mathematics and Statistics. He previously served as Head of Department (2014–2020) and led LTU's Statistics Consulting Platform. His research focuses on robust statistics, meta-analysis, dimension reduction, and applied statistics, leading the DRAMA research group. Collaborations span fields like endocrinology, disability studies, and respiratory health. He actively contributes to research grants, including projects on Prader-Willi syndrome and exercise for disability populations. Professor Prendergast's recent work emphasizes statistical software development (e.g., the rquest package) and applications in biostatistics, such as metabolomics analysis and health intervention fidelity. His articles address topics like quantile-based hypothesis testing, geospatial accessibility for disability care, and motivational interviewing efficacy. Professional roles include NHMRC grant review panels, editorial boards for Nutrients and Respirology , and leadership in the Statistical Society of Australia (SSA Vic). His teaching includes courses in meta-analysis, linear models, and data-based critical thinking. Grants funded projects on exercise programs for cerebral palsy populations and community-university partnerships for disability inclusion. Luke's work bridges statistical theory with real-world health challenges, emphasizing robust methodologies and interdisciplinary collaboration.
Joshua D. Rabinowitz is a Professor of Chemistry and the Lewis-Sigler Institute for Integrative Genomics at Princeton University, where he also serves as Director of the Ludwig Princeton Branch. His research focuses on achieving a quantitative, comprehensive understanding of cellular metabolism, with applications in both basic science and medical research. Dr. Rabinowitz's research interests span multiple areas of metabolism and systems biology: Quantitative analysis of metabolic networks and regulation Metabolomics and measurement of metabolite concentrations and fluxes Cancer cell metabolism and therapeutic targeting Metabolic regulation in microbes (E. coli, Saccharomyces cerevisiae) Biofuel production (focusing on Clostridium acetobutylicum) Metabolic impact of pathogen infection (viral infection of human cells) His laboratory has developed innovative methods for measuring cellular metabolites using state-of-the-art mass spectrometry technology and approaches for quantitating metabolic fluxes through isotope-labeling data interpretation. Analysis of recent publications reveals a strong focus on NAD+ metabolism, cancer metabolism, metabolic adaptations in disease states, and the intersection of metabolism with immunology and neuroscience, particularly in areas like T cell metabolism, Alzheimer's disease, and cardiac function. Dr. Rabinowitz has received recognition as a Highly Cited Researcher by Web of Science, indicating significant impact in his field. He advises several graduate students and has mentored numerous alumni, including Michel I. Nofal, Edmundo Leiva III, and Sean Hackett. His research is supported by multiple programs including NIH NHGRI Training Program and QCB Graduate Program. The Rabinowitz Lab operates at the intersection of chemistry, biology, and computational science, with all projects involving a mix of biological experiments, metabolomics, and computation to achieve their goal of a holistic understanding of cellular metabolism.
Guizhen Zhao is an Assistant Professor at the University of Houston College of Pharmacy , Department of Pharmacological and Pharmaceutical Sciences. Her research focuses on epigenetic and molecular mechanisms in cardiovascular diseases (CVD), particularly aortic aneurysm, dissection, and atherosclerosis, with a goal to drive drug discovery innovations. Major research areas: Metaboloepigenetic properties of vascular cells, chromatin remodeling, vascular cell crosstalk Methodologies: bulk RNA-seq, single-cell RNA-seq, ChIP-seq, ATAC-seq, spatial transcriptomics, metabolomics Ongoing projects include studying BAF60c-dependent epigenetic modifications in smooth muscle cell biology, BAF60c-mediated iPSC differentiation, BAF60a in endothelial dysfunction, and vascular cell interactions in CVD development. Scientific contributions include 15+ publications on abdominal aortic aneurysm, atherosclerosis, and chromatin remodeling mechanisms, with recent work on adenosine kinase inhibition and KLF11 as therapeutic targets. 2023-25: Career Development Award, American Heart Association 2021-22: Postdoctoral Fellowship, American Heart Association 2019: Young Investigator Award, American Heart Association
Dr. Imad El Haddad serves as Group Head of the Molecular Cluster and Particle Processes group at the Laboratory of Atmospheric Chemistry (LAC), part of the Center for Energy and Environmental Sciences at Paul Scherrer Institute (PSI), Switzerland, since 2018. Previously, he held positions as Tenured Scientist and Deputy Head (2018-2019), Senior Scientist in the Smog Chamber group (2015-2018), and Postdoctoral Fellow (2011-2015) at PSI. His research aims to quantify how anthropogenic emissions alter atmospheric pollutant composition and impact Earth's climate and public health through molecular-level analysis using advanced mass spectrometry techniques. His academic background includes: Ph.D. in Atmospheric Chemistry, University of Provence, Marseille (2007-2011) Master's in Environmental Sciences (with distinction, rank 1/9), University of Provence (2006-2007) Master's in General Chemistry (with distinction, rank 1/10), Saint-Joseph University of Beirut (2005-2006) Bachelor of Science in Chemistry (with distinction, rank 1/14), Saint-Joseph University of Beirut (2002-2005) El Haddad's work centers on molecular fingerprinting of atmospheric aerosols , utilizing mass spectrometry (GC/MS, HPLC/APCI-MS2, HPLC/ESI-MS2) to identify primary and secondary molecular markers. He conducts smog chamber experiments to characterize emissions from wood burning, traffic, and cooking processes, determining secondary organic aerosol potential and oxidation state evolution. His group also studies in-cloud aqueous-phase aging and collaborates with global modelers to link aerosol composition to climate forcing and health outcomes like oxidative stress. Recent publications (2025-2024) reveal three dominant trends: (1) rigorous molecular-scale analysis of secondary aerosol formation under varying humidity/temperature, (2) source apportionment breakthroughs in diverse regions (India, Europe, Arctic) using 14C and AMS data, and (3) quantification of health-relevant aerosol properties such as oxidative potential through DTT assays. High-resolution mass spectrometry is a consistent methodological thread across these studies. His scientific awards include: MENRT research fellowship from French ministry of research (2007-2010) Excellence Scholarship (top 1% student, University of Saint Joseph, 2005) Distinction Prize (best student, University of Saint Joseph, 2005) As Group Head, El Haddad oversees the Molecular Cluster and Particle Processes group's research direction and mentorship of junior scientists. While specific grant details are absent from the text, his leadership in multi-institutional publications (e.g., CERN CLOUD, iCUPE) implies active grant management and international collaboration. The group's work bridges laboratory simulations, field deployments, and health/climate modeling to address air pollution complexities. The Molecular Cluster and Particle Processes group develops cutting-edge online/offline mass spectrometers for 1 Hz-resolution atmospheric analysis. They deploy instruments in laboratory smog chamber experiments and global field studies, focusing on molecular marker identification, emission source characterization, and aging process quantification. Collaborations with biochemists and climate modelers extend their impact beyond pure aerosol physics into health risk assessment and policy-relevant climate science.
Facundo M. Fernandez is a Regents' Professor and Vasser-Woolley Chair in Bioanalytical Chemistry at the Georgia Institute of Technology, where he leads the Fernandez Research Group within the School of Chemistry and Biochemistry in the College of Sciences. His research spans multiple cutting-edge areas of analytical chemistry with significant applications in medicine, forensics, and basic science. Dr. Fernandez earned his M.Sc. in Chemistry (1996) and Ph.D. in Analytical Spectrometry/Metallomics (1999) from the Facultad de Ciencias Exactas y Naturales at Buenos Aires University, Argentina. His research program focuses on Bioanalytical Mass Spectrometry with particular emphasis on Ambient Sampling/Ionization & Molecular Imaging, Ion Mobility Spectrometry, Metabolomics, and Pharmaceutical Forensics. His work has pioneered new approaches in ambient ionization techniques that enable direct analysis of complex samples without extensive preparation. His recent publications reveal a strong trend toward spatial metabolomics, particularly in traumatic brain injury and ovarian cancer research, with increasing integration of machine learning approaches for data analysis. His work also extends to pharmaceutical quality control, exercise physiology through the MoTrPAC consortium, and prebiotic chemistry investigations. The interdisciplinary nature of his research is evident in collaborations across Georgia Tech's campus and with external institutions. NSF CAREER Award (2007) 3M Non-tenured Faculty Award (2008) CETL/BP Junior Faculty Teaching Excellence Award (2009) Ron A. Hites Award for Outstanding Research Publication (2010) Sigma Xi (GT Chapter) Best Faculty Paper Award (2010) Vasser-Wooley Faculty Fellow (2012) Dr. Fernandez has secured significant funding for his research, including NSF CAREER support, and leads projects related to metabolomics for ovarian cancer detection, pharmaceutical forensics through the CODFIN network, and participation in the large-scale Molecular Transducers of Physical Activity Consortium (MoTrPAC). His laboratory develops advanced instrumentation for mass spectrometry applications and maintains strong collaborations with the Integrated Cancer Research Center, the College of Computing, and the Center for Chemical Evolution at Georgia Tech.
Aaron Puri is an Assistant Professor of Chemistry at the University of Utah, specializing in chemical ecology and natural product discovery. His research focuses on bacterial interactions in methane-oxidizing communities and the biosynthesis of secondary metabolites. Education: B.S. from University of Chicago, Ph.D. from Stanford University School of Medicine Dr. Puri's work bridges microbiology and chemistry, with projects targeting: Chemical Ecology: Decoding interspecies signaling in methane-oxidizing bacteria Natural Products: Discovering therapeutics from underexplored bacterial genomes Biosynthesis: Activating cryptic gene clusters for novel compound production Recent publications highlight advancements in quorum sensing mechanisms (2025), inverse stable isotopic labeling techniques (2024), and methanotroph community dynamics. His research also explores spatially resolved model ecosystems for studying microbial phenotypes (2023-2024). Key methods include GNPS Dashboard for mass spectrometry analysis (2021-2022). Dr. Puri leads the CAREER-funded project on quorum sensing in methanotrophs (2024) and has developed genetic tools for industrial methanotrophs (2015). His lab maintains a strong focus on environmental microbiology and biotechnological applications.
Ali Shojaie is a Professor of Biostatistics and Statistics at the University of Washington, serving as Associate Chair for Strategic Research Affairs in the Department of Biostatistics. He leads the Summer Institute for Statistics in Big Data (SISBID) and the Data Management and Statistics (DMS) Core for the UW Alzheimer's Disease Research Center. His research focuses on developing statistical and machine learning methods for high-dimensional data, with applications in genomics, neuroscience, and public health. Shojaie's work includes advancements in graphical models, Granger causality, and spatial statistics. He has contributed to methodologies for analyzing networks from time series and spatial data, with applications in understanding gene regulatory networks and brain connectivity. His recent projects involve NIH-funded grants exploring gene-phenotype associations using omic data and explainable machine learning for brain stimulation research. Scientific awards include the 2022 Leo Breiman Award from ASA's Statistical Learning and Data Science section, and election as a Fellow of the Institute of Mathematical Statistics (IMS) and American Statistical Association (ASA). He serves on editorial boards for journals like the Journal of the American Statistical Association and Biometrika. Shojaie advises numerous PhD students and postdocs, many of whom have secured academic and industry positions. His lab develops open-source software tools, including the netgsa and ngc packages for network analysis and Granger causality estimation.
Bärbel Finkenstädt Rand is a Senior Tutor at the Warwick Medical School , University of Warwick, with extensive research contributions at the intersection of statistics, machine learning, and biomedical sciences. Her work focuses on developing advanced methodologies for analyzing temporal and spatio-temporal data, particularly in circadian rhythms and disease dynamics. Research Themes : Bayesian inference, Hidden Markov Models, circadian rhythm stability, transcriptional bursting, and wearable sensor data analysis. Collaborations : Chronotherapy Group at Warwick, Université Paris-Saclay, and interdisciplinary teams across medicine, genetics, and computational biology. Publications reveal a strong emphasis on circadian health monitoring, gene expression dynamics, and epidemic modeling using stochastic frameworks. Her recent work prioritizes personalized medicine applications through telemonitored biomarkers and IoT platforms . Methodological Innovations include spline-based HMMs, distributed delay systems, and harmonic modeling for nonstationary time series. Applications span oncology, sleep medicine, and population ecology.
Bo Lu is a Professor of Biostatistics and Statistics at The Ohio State University. His research focuses on advancing early detection technologies for forest pathogens and pests using spectroscopy, machine learning, and metabolomics. He specializes in understanding plant defense mechanisms against invasive species and climate-driven disease dynamics. Key research areas include: Non-invasive disease diagnostics via FT-IR/Raman spectroscopy Machine learning applications in plant health monitoring Molecular basis of plant-pathogen interactions Environmental risk modeling for emerging forest diseases Notable projects include developing early detection systems for ash dieback, beech leaf disease, and soybean cyst nematode infestations. His work integrates statistical modeling with biochemical analysis to improve forest biosecurity strategies globally. He advocates for international collaboration in addressing the global forest health crisis through improved diagnostic frameworks and resistance breeding programs.
Megan Romano, PhD is an Associate Professor of Epidemiology at the Geisel School of Medicine at Dartmouth College . Her research focuses on environmental epidemiology, particularly examining how exposure to endocrine disrupting chemicals during pregnancy affects maternal and child health outcomes. Education: PhD, Epidemiology - University of Washington (2013) MPH - Boston University (2007) BS - Allegheny College (2004) Research Focus: Dr. Romano's research explores the influence of environmental endocrine disrupting chemicals (EDCs) during critical windows of pregnancy and gestation on pregnancy complications, maternal and infant hormones, breastfeeding behaviors, and early life growth. Her work specifically examines EDCs commonly found in US consumer products including bisphenol A, phthalates, perfluoroalkyl substances (PFAS), parabens, and flame retardants. She actively collaborates with local and regional stakeholders to address community concerns regarding PFAS contamination in New England. Her recent publications demonstrate a comprehensive approach to understanding environmental health impacts, with particular emphasis on PFAS exposure through multiple pathways including diet, consumer products, and environmental contamination. Her research employs sophisticated epidemiological methods including metabolomics, miRNA analysis, and longitudinal cohort studies to understand biological mechanisms underlying environmental health effects. Professional Affiliations: Director, Romano Lab - focusing on environmental exposures during pregnancy and childhood Member, Environmental influences on Child Health Outcomes (ECHO) Program Collaborator, New Hampshire Birth Cohort Study Contact Information: Email: Megan.E.Romano@Dartmouth.edu Phone: (603) 646-5495
Ben Raphael is a Professor in the Department of Computer Science at Princeton University, with affiliations at the Lewis-Sigler Institute for Integrative Genomics, Omenn-Darling Bioengineering Institute, and Center for Statistics and Machine Learning. He is also an Affiliate Faculty member at the Rutgers Cancer Institute of New Jersey, Irving Institute for Cancer Dynamics at Columbia University, and New York Genome Center. His research focuses on computational methods for analyzing large-scale biological data, emphasizing cancer evolution, network/pathway analysis, and structural variation in genomes. Research Trends: His recent work spans cancer lineage trees, spatial transcriptomics, optimal transport for developmental models, and network analysis of mutations. Articles highlight applications in prostate cancer, pancreatic cancer, and single-cell genomics. Scientific Awards: 2024 ACM Fellow 2023 RECOMB Test of Time Award 2022 RECOMB Test of Time Runner-Up 2021 ISCB Innovator Award 2021 RECOMB Best Paper Runner-Up 2020 ISCB Fellow 2020 AACR Team Science Award 2011 NSF CAREER Award 2013 RECOMB Best Paper 2010-2012 Sloan Research Fellowship Advising: He has mentored numerous Ph.D. students and postdoctoral fellows, many of whom have transitioned to academic and industry roles. Current advisees include Uthsav Chitra, Gillian Chu, and Alexander Strzalkowski. Labs & Teams: Raphael leads the Raphael Lab at Princeton, developing tools like HotNet2, CHISEL, and HATCHet for cancer genomics and network analysis.
Prof. Dr. Jörg Hackermüller is a computational biologist with expertise in Omics data integration Toxicology Environmental risk assessment Non-coding RNA biology . He serves as Head of the Department of Computational Biology and Chemistry at the Helmholtz Centre for Environmental Research (UFZ) since 2024 and holds a Professorship at the Faculty of Mathematics and Computer Science at Leipzig University since 2021. His research focuses on Developing AI methods for chemical toxicity prediction Multi-omics integration for mechanistic toxicology Data standardization in environmental monitoring Non-coding RNAs as biomarkers in disease and toxicity and has produced 15+ recent publications spanning tools like multiGSEA and deepFPlearn+ . He collaborates with teams across UFZ Leipzig University Novartis Fraunhofer Institute and leads projects like InCeTo and SafePol , integrating exposome research with systems biology.
Zhandong Liu is an Associate Professor at Baylor College of Medicine with joint appointments in the Department of Pediatrics and Department of Neurology . He serves as Chief of Computational Sciences at Texas Children's Hospital and co-directs the Quantitative & Computational Biosciences Graduate Program at Baylor. Education: B.S. in Computer Science, Nankai University (2001) M.S. in Computer Science, Wayne State University (2003) Ph.D. in Genomics and Computational Biology, University of Pennsylvania (2010) Dr. Liu's research integrates genomics , machine learning , and bioinformatics to advance understanding of neurological diseases. His work focuses on: Multi-omics data integration for disease mechanism discovery Development of cloud-based CRISPR analysis tools like CRISPRcloud Augmented reality platforms for biomedical data visualization Identification of disease genes through computational models Alternative splicing analysis in cancer and neurodegeneration Single-cell and spatial transcriptomics algorithms His recent publications emphasize Alzheimer's disease , MECP2 syndromes , and computational therapy prediction across multiple domains. Scientific awards include the 2018 Outstanding Service Award from the International Association for Intelligent Biology and Medicine. He has secured major grants from NIH, CPRIT, and NSF for projects including: NSF grant #199977 (2018-2020): Augmented reality therapy platforms CPRIT grant #RP170387 (2016-2019): Network-guided cancer analysis NIH #1R01AG057339 (2017-2022): Alzheimer's disease networks As head of the Liu Lab , he leads teams developing tools like: MARRVEL : Human-model organism gene variant integration CRISPRcloud : Secure CRISPR screen analysis platform CrypSplice : Cryptic splicing detection algorithm
