Andrew Gross, MD is a Professor of Medicine at the University of California, San Francisco (UCSF) School of Medicine. He serves as Rheumatology Clinic Chief, overseeing clinical care, education, and research activities. He is co-director of the UCSF Scleroderma Center and collaborates with the Interstitial Lung Disease Program to provide multidisciplinary care for complex autoimmune conditions. His research focuses on translational studies investigating rheumatic disease mechanisms and improving clinical care strategies. Dr. Gross earned his MD from Tufts University School of Medicine (1996), a BS in Biology from Bates College (1991), and completed a Diversity, Equity, and Inclusion Champion Training at UCSF (2018). He holds an ORCID identifier (0000-0003-0439-1785). Education: M.D., Tufts University School of Medicine, 1996 B.S., Biology, Bates College, 1991 Diversity, Equity, and Inclusion Champion Training, UCSF, 2018 Research Interests: Autoimmune diseases, scleroderma, interstitial lung disease, translational medicine, and rheumatoid arthritis biomarkers. Awards/Grants: Principal Investigator for NIH K08AI052249 (2003-2008) studying EBV in systemic lupus erythematosus. Advisees/Grants: Collaborates with fellows and junior faculty in translational research programs. Labs/Teams: Leads rheumatology clinical and research programs at UCSF, including the Scleroderma Center and Interstitial Lung Disease Program.
Dr. Xinghua Mindy Shi is an Associate Professor in the Department of Computer & Information Sciences at Temple University's College of Science and Technology, where she has served since 2019. Previously, she held positions as an Assistant Professor at the University of North Carolina at Charlotte (2013-2019) and completed postdoctoral training at Harvard Medical School's Brigham and Women's Hospital (2009-2012) and the Broad Institute of MIT and Harvard (2009-2012). Her research focuses on developing statistical and machine learning methods for biomedical applications, spanning: Privacy-preserving machine learning for genomic data Deep learning architectures for genotype imputation Computational analysis of 3D genome organization Structural variation detection in diverse human populations Generative adversarial networks for biomedical data augmentation Her publication record demonstrates consistent contributions to genomics and machine learning, with recent works emphasizing: Advanced deep learning models (Transformers, GANs) for genomic tasks Privacy protection in biomedical data analysis Large-scale structural variation studies through international consortia Innovative methods for haplotype-resolved genome assembly Awards & Honors: NIH T32 Genetics Fellowship (2009-2012) She directs an active research group with current members including 4 PhD students and 1 master's candidate. Her lab has trained 4 postdoctoral researchers, 5 PhD graduates, and over 20 master's/undergraduate students who now hold positions in academia and industry. The group collaborates with Temple University's Institute for Genomics and Evolutionary Medicine (iGEM), Center for Data Analytics and Biomedical Informatics, and external institutions including Penn Medicine and Jackson Laboratory.
Christos Noutsos is an Assistant Professor in the Department of Biological Sciences at SUNY Old Westbury. He teaches courses such as Basic Biological Sciences I and Plant Biology, focusing on foundational and specialized plant biology topics. His research spans plant genomics, transcriptomics, and molecular biology, with contributions to understanding gene expression in organisms like Brachypodium distachyon and Zea mays. He also explores clinical and educational domains, including undergraduate student motivation in STEM and the psychological factors affecting preimplantation genetic testing outcomes. Noutsos has conducted studies on nutritional impacts on plant development and the effects of dietary fatty acids on neurobiological systems. His work integrates computational and experimental approaches, evidenced by contributions to bacteriophage genome sequencing and advancements in plant genome analysis. Noutsos' research also addresses agricultural challenges, such as optimizing phosphorus fertilization in lentils and understanding fruit ripening mechanisms in pear varieties. While no specific academic awards are listed, his publications reflect interdisciplinary engagement with both basic science and applied educational methodologies. Advising and grant details are not explicitly provided, though his involvement in course-based research experiences suggests active mentorship of undergraduate researchers. His contributions to the iPlant collaborative highlight infrastructure development for plant bioinformatics, emphasizing his role in advancing digital tools for genomic research.
Brian Trippe is an Assistant Professor of Statistics at Stanford University with a joint affiliation in Stanford Data Science. His research develops probabilistic machine learning methods to solve critical challenges in biotechnology and medicine, particularly focusing on reliable molecular design under physical constraints. Education: PhD in Computational and Systems Biology, MIT (2022) MPhil in Engineering, University of Cambridge (2017) BA in Biochemistry and Computer Science, Columbia University (2016) His work centers on probabilistic machine learning and Bayesian computation applied to computational biology , with breakthroughs in protein engineering yielding hundreds of experimentally validated molecular structures. By incorporating prior knowledge and providing theoretical guarantees, his methods address biotechnology's unique demands for data efficiency and physical constraint satisfaction. Analysis of his recent publications reveals dominant trends in diffusion models for protein design and Bayesian inference frameworks , demonstrating cross-cutting applications from ocean current modeling to genomic analysis. These works consistently bridge statistical theory with experimental validation through major collaborations like the University of Washington's Institute for Protein Design. Brian actively mentors students at Stanford and explicitly encourages applications from underrepresented groups. His collaborative network spans Columbia University, MIT, and the Baker lab, driving interdisciplinary advances in computational biotechnology while pursuing long-term goals in genetic engineering foundations.
Chloé-Agathe Azencott is a Professor in machine learning for genomics at the Centre for Computational Biology (CBIO) of Mines ParisTech, part of PSL Research University, and affiliated with Institut Curie and INSERM. She holds a Springboard Chair at PRAIRIE. Her research focuses on applying machine learning to therapeutic research, with a particular emphasis on genomic data analysis, network-guided genome-wide association studies (GWAS), and biomarker discovery. She has been a faculty member since 2013, transitioning from researcher to assistant professor before becoming a full professor. Education: PhD in Computer Science from UC Irvine (2010), Habilitation à Diriger des Recherches from Sorbonne Université (2020). She holds an MSc in Mathematics and Computer Science from ENST Bretagne (now IMT Atlantique). Professional experience includes postdoctoral research at the Max Planck Institutes (2011–2013) and collaborations with institutions like Janssen Research & Development and Sanofi. Research interests center on machine learning techniques for genomic analysis, including network integration, non-additive SNP interactions, and robust statistical methods for GWAS. Her work spans biomarker discovery, precision medicine, and computational systems biology. She has led grants such as SCAPHE (ANR JCJC) and STEVE (ANR PRC), and contributed to initiatives like the Druggable Genome Challenge. Teaching includes courses on bioinformatics, machine learning, and drug discovery at Mines ParisTech and OpenClassrooms. She co-founded the Paris chapter of Women in Machine Learning and Data Science, fostering diversity in STEM. Notable awards include the Young AI Woman Engineer Award (2021) and the Alexander von Humboldt Fellowship (2011–2013). Current advising includes PhD students working on topics like transcriptomic analysis for lung cancer detection and machine learning for breast cancer therapeutics. Her lab develops tools like the martini R package and gwas-tools for GWAS analysis. She actively participates in conferences, editorial roles (e.g., Computo journal), and outreach initiatives to demystify AI and promote scientific literacy.
Dr. Varun Warrier is an Assistant Professor in the Department of Psychology at the University of Cambridge, affiliated with the Department of Psychology. His research focuses on neurogenetic factors influencing autism, developmental disorders, and psychiatric conditions, with an emphasis on genetic and neuroimaging methodologies. He explores topics such as autism etiology, cognitive development, and the impact of environmental factors like child maltreatment or breastfeeding on neurodevelopmental outcomes. His work integrates large-scale genomic data, neuroimaging, and longitudinal studies to understand complex phenotypes. Dr. Warrier’s recent studies include investigations into polygenic risk scores for autism, genetic influences on brain structure, and the role of rare variants in sex differences in autism. He collaborates on projects analyzing developmental milestones, mental health comorbidities, and translational research in clinical populations. His research interests span autism genetics, neuroimaging phenotypes, and the interplay between genetic and environmental factors in psychopathology. He has contributed to studies on brain functional networks, cortical organization, and the biological basis of cognitive abilities like memory and systemizing. Dr. Warrier’s work often involves interdisciplinary approaches, combining computational methods with clinical data to enhance predictive models for neurodevelopmental outcomes.
C. Joel McManus is an Associate Professor in the Department of Biological Sciences at Carnegie Mellon University's Mellon College of Science. His research focuses on mechanisms regulating mRNA translation and their roles in phenotypic diversity and disease. Key areas include upstream open reading frames (uORFs) in yeast and translational control in fungal pathogens like Candida albicans. McManus received his Ph.D. from the University of Wisconsin-Madison and completed postdoctoral training at the University of Connecticut Health Center. His lab develops high-throughput assays and computational models to study RNA regulatory elements and their impact on protein production. Research interests span understanding how uORFs influence translation initiation, particularly through non-AUG start codons, and the role of translational control during fungal infections. Collaborations with the Mitchell and Filler labs investigate host-pathogen interactions in Candida albicans. McManus has published extensively on topics such as ribosome profiling, RNA structure-function relationships, and biofilm regulatory networks. His work bridges fundamental molecular biology with translational applications in pathogenesis and genetic regulation.
Dr. Yi Athena Ren is an Assistant Professor of Reproductive Biology in the Department of Animal Science at Cornell University's College of Agriculture and Life Sciences. Her research focuses on innovative applications of biotechnology and systems biology to address fundamental questions in reproductive biology, with particular emphasis on ovarian physiology and developmental programming of reproductive health. Dr. Ren earned her Doctorate in Reproductive Physiology from Cornell University in 2011 and completed her Bachelor's in Animal Science at China Agricultural University in 2006. Her academic journey has positioned her at the forefront of reproductive biology research, with a focus on translating basic science discoveries into potential clinical applications. Doctorate in Reproductive Physiology, Cornell University, 2011 Bachelor's in Animal Science, China Agricultural University, 2006 Dr. Ren's research spans multiple interconnected areas including ovarian physiology, where she investigates molecular mechanisms of ovarian function and uses the ovary as a model for tissue homeostasis; developmental programming of health and diseases related to ovarian function; vascular remodeling in ovulation; biomarkers for reproductive performance in dairy cattle; and the role of immune cells in the hypothalamic-pituitary-gonadal axis. Her work combines innovative biotechnologies with systems biology approaches to tackle open questions in reproductive biology. Analysis of Dr. Ren's recent publications reveals a strong focus on molecular mechanisms of ovulation, with particular attention to vascular remodeling processes, gene regulation, and the role of specific proteins like Semaphorin 3E in reproductive processes. Her research increasingly incorporates genomic and epigenetic approaches, as evidenced by her work on DNA methylation variants in cattle and spatiotemporal molecular atlases of the ovulating ovary. Dr. Ren has received significant recognition for her research contributions: Schwartz Research Award, Cornell University, 2022 (one of only two winners university-wide) PCCW Affinito-Stewart Award from President's Council of Cornell Women, 2021 Second Place, Cornelia Post Channing New Investigator Award, Society for the Study of Reproduction, 2014 Lalor Foundation Merit Award, Society for the Study of Reproduction, 2014 Dr. Ren actively mentors graduate and undergraduate students, with several advisees receiving prestigious research awards. Her laboratory has secured substantial funding from multiple sources including Cornell University start-up funds, USDA Federal Capacity Funds (HATCH grant and Multistate Research Project NE-2227), the Center for Vertebrate Genomics, President's Council of Cornell Women, and the Eunice Kennedy Shriver National Institute of Child Health and Human Development. She teaches courses including Model Organisms in Reproductive Sciences, Current Concepts in Reproductive Biology, Reproductive Biology Journal Club, and Fundamentals of Endocrinology. The Ren Laboratory, located in Morrison Hall at Cornell University, maintains active collaborations across multiple disciplines and has established itself as a center for innovative research in reproductive biology, with particular strengths in ovarian physiology, molecular mechanisms of ovulation, and applications to both human reproductive health and agricultural productivity.
Danny Nedialkova holds dual positions as Professor for Biochemistry of Gene Expression at Technische Universität München (TUM) and Max Planck Research Group Leader at the Max Planck Institute of Biochemistry. Her research focuses on understanding proteostasis mechanisms in metazoan cells, particularly how distinct cell proteomes are established and maintained. She employs genome-wide assays and stem cell models to investigate protein biogenesis, translation regulation, and systems biology. Key contributions include discoveries on tRNA modifications, ribosome elongation rates, and quality control systems. Education: PhD in Molecular Virology (Leiden University Medical Center, 2010), B.Sc. in Biotechnology (Università degli Studi di Perugia, 2004). Awards include the EMBO Young Investigator Award (2021) and ERC Starting Grant (2018). Funding includes grants from the European Research Council and Max Planck Society. Her lab explores cell-type specific vulnerabilities to proteome damage, leveraging CRISPRi screens and mim-tRNAseq profiling. Collaborative projects address translational control, mitochondrial DNA repair, and neuronal migration. Publicly accessible at https://www.biochem.mpg.de/nedialkova .
Dr. Judith Mank is a Professor and Canada 150 Research Chair in Evolutionary Genomics at the University of British Columbia (UBC), Department of Zoology. She leads the Mank Lab, focusing on evolutionary genomics, sexual dimorphism, and sex chromosome evolution. Her work integrates genomic, transcriptomic, and ecological approaches to study how selection shapes phenotypic diversity. Education: Ph.D. in Genetics, University of Georgia (2006) M.S. in Forest Resources, Pennsylvania State University (2001) B.A. in Anthropology, University of Florida (1997) Research Interests: Her lab investigates the genetic and genomic basis of sexual dimorphism, sex chromosome evolution, and dosage compensation. Key areas include: Genetic mechanisms underlying sexual conflict and adaptation Evolutionary dynamics of sex chromosomes (e.g., Y and W chromosomes) Role of transposable elements and epigenetics in genome evolution Behavioral genomics and social behavior in fish Awards & Honors: 2020 Honorary Doctorate, Uppsala University 2016 Royal Society Wolfson Fellowship 2013 Zoological Society of London Scientific Medal Labs & Collaborations: The Mank Lab is part of UBC’s Biodiversity Research Centre and collaborates with global institutions. They maintain state-of-the-art facilities for molecular genetics, including single-cell RNA-Seq and fish behavior experiments. Current projects involve guppies, willows, and other model organisms to study sex chromosome evolution and sexual selection.
Dr. Loren Rieseberg is a Professor in the Department of Botany at the University of British Columbia (UBC), affiliated with the Biodiversity Research Centre. His research focuses on evolutionary genomics, speciation, and plant adaptation, particularly in sunflowers and other Compositae species. He leads the Rieseberg Lab, which integrates genomic, computational, and ecological approaches to study plant evolution, hybridization, and crop improvement. Key research areas include: Evolutionary processes driving speciation and adaptation Role of hybridization in plant evolution and invasiveness Genomic basis of ecotype divergence and crop domestication Climate resilience and genetic resources for sunflower improvement His work highlights how structural variants like chromosomal inversions contribute to adaptation and reproductive isolation. Recent studies emphasize the genomic mechanisms underlying invasive species success and the application of evolutionary principles to crop breeding. Dr. Rieseberg collaborates globally, with projects spanning North America, South America, and Europe. Notable achievements include sequencing the sunflower genome and identifying genomic regions critical for stress tolerance and hybrid vigor. His lab’s pre-bred lines for agronomic traits have been widely adopted in sunflower breeding programs worldwide.
WEI Jiangbo is an Assistant Professor and holder of the NUS Presidential Young Professorship at the Department of Chemistry, National University of Singapore. His research focuses on RNA modifications, epigenetic mechanisms, and their applications in precision medicine and biotechnology. He holds a B.Sc. from Peking University (2015), a Ph.D. from The University of Chicago (2021), and completed a postdoctoral fellowship there (2021-2023). B.Sc., Peking University, 2015 Ph.D., The University of Chicago, 2021 Postdoctoral Researcher, The University of Chicago, 2021-2023 His research interests span three core areas: (1) Investigating RNA modifications' roles in genetic information flow and epigenetic inheritance, (2) Leveraging RNA modifications for precision medicine via synthetic lethality and therapeutic targeting, and (3) Developing next-generation RNA profiling and modulation technologies. Notable contributions include studies on FTO-mediated LINE1 demethylation and YTHDF1-driven neuronal translation regulation. His work has been recognized with awards such as the NUS Presidential Young Professorship (2023), Josef Fried Chemical Biology Award (2021), and Chinese Government Award for Outstanding Self-Financed Students (2020). Key findings include insights into m6A's role in adipocyte metabolism, cancer progression, and plant development. Labs/Teams : The Wei Lab at NUS focuses on RNA-centric regulatory mechanisms, with ongoing projects in cancer biology, epigenetic therapies, and RNA technology development.
Dr. John Pinney is a Senior Teaching Fellow and Early Career Researcher at Imperial College London's Central Faculty. As the Data Science Skills Leader within the Graduate School, he designs and delivers training programs in programming, statistics, and machine learning for graduate students. His research focuses on computational systems biology, integrating macromolecular sequences, protein structures, and biological networks to study biological systems' evolution and function. His research interests span biochemistry, evolutionary biology, microbiology, and computational tools development. He is affiliated with the Industrial Biotechnology Hub (BIO) and contributes to interdisciplinary projects. His publications emphasize viral evolution (e.g., herpesviruses), host-pathogen interactions, and metabolic network analysis. He has developed tools like PathwayBooster and metaSHARK for metabolic pathway curation and network reconstruction. No scientific awards are explicitly mentioned in the text. He advises no listed students but collaborates widely on grants and training initiatives. His work supports the Graduate School's mission to enhance data science skills for modern research. He is part of the Industrial Biotechnology Hub, contributing to applied systems biology and biotechnology research.
Joanna Moodie is a Research Associate at the Lothian Birth Cohort Studies Group within the School of Philosophy, Psychology and Language Sciences at the University of Edinburgh. She holds a PhD in Psychology (2021) from the University of St Andrews, funded by the Scottish Graduate School of Social Sciences, and an MSc in Human Cognitive Neuropsychology (Distinction) from the University of Edinburgh. Current Roles: Research Associate; Co-supervisor (with Prof. Simon Cox and Prof. Riccardo Marioni); Associate Fellow of the Higher Education Academy (AFHEA). Research Focus: Interdisciplinary studies linking brain structure, ageing, cognition, and vascular health; expertise in MRI analysis, epigenetics, and cognitive neuroscience. Her scientific contributions span neuroimaging, genetic analysis, and longitudinal cohort studies. She has peer-reviewed papers in her expertise areas and supervised multiple PhD rotation projects. Key Scientific Awards: Scottish Graduate School of Social Sciences (SGSSS) PhD Funding Highly Commended Dissertation Award (University of Edinburgh) Principal's Scholarship for Academic Excellence (University of St Andrews)
John T. Lis is the Barbara McClintock Professor of Molecular Biology and Genetics at Cornell University's College of Agriculture and Life Sciences (CALS). He obtained his Ph.D. in Biochemistry from Brandeis University (1975) and conducted postdoctoral research at Stanford University on Drosophila gene regulation. Since joining Cornell in 1978, his research has focused on transcriptional regulation, chromatin structure, and RNA polymerase dynamics, supported by grants from the NIH, March of Dimes, and Proctor & Gamble. His work has pioneered techniques like PRO-seq for mapping transcriptional activity. **Research Interests:** Lis’s lab investigates gene expression control mechanisms, including enhancer/promoter function, transcriptional pausing, and stress responses. Key areas include the role of transcriptional checkpoints (e.g., NELF-Cdk9), epigenetic regulation, and the interplay between chromatin architecture and transcription. Recent studies explore transcriptional memory, viral-host interactions (e.g., SARS-CoV-2), and cancer-related transcriptional dysregulation. **Awards & Grants:** He is a 2013 Fellow of the American Academy of Arts and Sciences and recipient of the NIH MERIT Award. His lab secured a $33M grant for Academic Integration efforts (2021), advancing collaborative research in computational biology and genomics. **Advancing Science:** Lis has developed groundbreaking methods like PRO-IP-seq and Femto-Seq to study RNA polymerase modifications and chromatin contacts. His work bridges basic science and translational research, addressing questions in cancer biology, viral pathogenesis, and developmental genetics.
