Find Academic Supervisors

• Skeletal Muscle Physiology
• Ribosome Biogenesis
• Transcriptional Regulation
• +4 more

Gustavo Alberto Nader is a Professor of Kinesiology at The Pennsylvania State University , holding the Dorothy Foher and J. Lloyd Huck Chair in Molecular, Cellular and Integrative Physiology. His research focuses on skeletal muscle growth control , ribosome biogenesis , and transcriptional/epigenetic regulation in health and disease contexts. Affiliated with the Huck Institutes of the Life Sciences and College of Health and Human Development Principal Investigator on NIH-funded projects examining ribosomal control of muscle mass Research Interests span molecular mechanisms of muscle adaptation to exercise, cancer cachexia, chronic disease impacts on muscle, and cross-species Wnt signaling regulation by CO₂ levels. Key methodologies include human/animal/cell models, ribosomal analysis, and epigenetic profiling. Publication Trends show sustained focus on: Ribosome biogenesis in muscle hypertrophy (2012–2025) Cancer-induced muscle wasting mechanisms (2015–2024) CO₂/Wnt pathway interactions (2015–2019) Exercise-induced transcriptional responses (2001–2016) Scientific Awards include the Huck Chair, while his Grants & Collaborations involve NIH-funded studies on transcriptional/epigenetic mechanisms (2019–2026) with cross-disciplinary teams in physiology, oncology, and respiratory medicine.

Hao ChenView profile

Associate Professor

• Anomaly/signal detection for streaming data
• Graph-based methods
• Two-sample test for high-dimensional and non-Euclidean data
• +7 more

Hao Chen, Ph.D. is an Associate Professor in the Department of Statistics at the University of California, Davis. His research focuses on statistical methodology for high-dimensional and non-Euclidean data, including anomaly detection, graph-based methods, and change-point analysis. He also explores AI security, multimodal models, and geospatial applications. His work bridges statistical theory and practical machine learning challenges. Education: Ph.D., Graduate Group in Biostatistics, Stanford University Research Interests: Dr. Chen’s expertise spans statistical methods for streaming data, categorical data analysis, and allele-specific copy number variation. He has pioneered work in detecting signals in complex datasets and developing robust AI systems. His recent focus includes mitigating modality interference in LLMs, enhancing model safety via guardrails, and advancing geospatial AI through projects like GeoLM. Publications: His recent work addresses cutting-edge topics such as multimodal model vulnerabilities, unlearning algorithms, and clinical radiology applications. Key themes include improving model robustness, ethical AI design, and interdisciplinary data integration. Labs/Teams: Engages in collaborative projects at UC Davis, though specific lab names are not listed in the provided information.

Michael NothnagelView profile

Professor

• Statistical Genetics
• Genetic Epidemiology
• Population Genetics
• +5 more

Michael Nothnagel is a Professor at the University of Cologne, where he leads the Department of Statistical Genetics and Bioinformatics within the Cologne Center for Genomics (CCG). His work spans statistical genetics, genetic epidemiology, and forensic genetics, focusing on methodological development and large-scale genomic data analysis. His research interests encompass theoretical and applied statistical genetics, with emphasis on human genetic diversity, disease etiology, and forensic applications. Key areas include Y-chromosomal phylogeography, genome-wide association studies for complex diseases, development of statistical methods for variant interpretation, and forensic marker optimization. His group leverages next-generation sequencing data and specialized forensic markers to address questions in population history, disease mechanisms, and identification systems. Recent publications reveal a strong focus on computational approaches to genetic analysis, including spatial frequency interpolation for haplogroup mapping, polygenic risk score applications for behavioral traits, and advanced methods for variant classification. His work demonstrates consistent integration of statistical theory with practical applications in medical and forensic genetics, often through international collaborations like the VISAGE Consortium. Nothnagel maintains active involvement in the Cologne Center for Genomics, contributing to seminars and collaborative projects including the upcoming 34th International Genetic Epidemiology Society meeting. His research group operates at the intersection of computational biology and medicine, with particular strengths in handling complex genomic datasets and developing novel analytical frameworks for genetic epidemiology.

Kaitlyn CrawfordView profile

Associate Professor

• Soft Materials
• Flexible Electronics
• Sustainable Polymers
• +1 more

Kaitlyn Crawford is an Associate Professor of Materials Science and Engineering at the University of Central Florida, with a secondary appointment in Chemistry. She directs the Functional Materials and Sensors Lab, focusing on sustainable soft materials for flexible electronics and biomedical applications. Her research integrates polymer science and engineering to develop wearable sensors for health monitoring, biodegradable materials to reduce e-waste, and natural polymer composites. Current projects include a $1.5M DHS-funded wearable for firefighter heat-stress monitoring and NASA-funded space applications. Her recent publications emphasize sustainable polymers, bionic devices, and AI-driven diagnostics. Awards include the 2024 ACS PMSE Early Investigator Award and a Jewish National Fund fellowship. She leads multiple graduate students in biomedical and materials research. Awards: 2024 ACS PMSE Early Investigator Award Faculty Fellowship Program in Israel, Jewish National Fund Faculty Excellence Honoree, Women’s History Month (UCF)

Chiara SabattiView profile

Professor

• Statistical Genetics
• Computational Biology
• Bayesian Statistics
• +2 more

Chiara Sabatti is a Professor of Biomedical Data Science and Statistics at Stanford University, with affiliations to the Stanford Center for Computational, Evolutionary and Human Genomics (CEHG), Bio-X, and the Stanford Cancer Institute. She serves as Associate Director for Stanford Data Science and has led the development of the Data Science Major curriculum since 2012. Research Focus: Statistical models for high-throughput genomics data, causal inference in genetic studies, false discovery rate control, and knockoff methods for variable selection. Key Leadership: Associate Chair for Education and Training (2020-present), Vice Chair of Biomedical Data Science (2018-2019). Her work bridges statistical genetics with data science education, emphasizing robustness and interpretability in scientific findings. Recent publications highlight innovations in genome-wide association studies (GWAS), causal variant localization, and cost-effective sequencing techniques for underrepresented populations. Current projects include developing knockoff-based methods to address population structure and multi-resolution hypothesis testing. Scientific Awards: Institute of Mathematical Statistics (IMS) Fellow (2022) NSF CAREER Award (2003-2008) She mentors doctoral and graduate students in Biomedical Data Science, collaborates with the Data Studio on interdisciplinary projects, and actively recruits curious researchers to her lab. Her outreach efforts focus on expanding data science education and increasing research participation from underrepresented groups.

Rudy GuerraView profile

Professor

• Biostatistics
• Bioinformatics
• Statistical Genetics
• +4 more

Rudy Guerra is a Professor and Chair of the Department of Statistics at Rice University, where he has been since 2000. His research spans biomedical applications of statistics, including bioinformatics, statistical genetics, and medical imaging, alongside sociological research in education and Mexican migration. He holds academic leadership roles, including Director of the Data Science Minor and member of the BRIDGE and Doerr Institute steering committees. Guerra earned his Ph.D. in Statistics from UC Berkeley, M.A. in Mathematics from UC Berkeley, and B.S. in Applied Mathematics from UT San Antonio. Education: Ph.D., Statistics, UC Berkeley (1992) M.A., Mathematics, UC Berkeley (1987) B.S., Applied Mathematics, UT San Antonio (1984) Key Roles: Department Chair, Statistics (2019–present) Associate Chair, Statistics (2016–2019) Former Jones College Magister (Residential College Leader, 2005–2011) Research Interests: Dr. Guerra’s work integrates statistical methods with biomedical and social science challenges. His biomedical focus includes cancer genomics (e.g., osteosarcoma metastasis, biomarker discovery), medical imaging (e.g., CT ventilation analysis), and bioinformatics. In social sciences, he examines educational inequities and Mexican migration impacts on health. His recent projects include collaborations with Texas Medical Center institutions and sociologists at Rice. Articles Trends: His publications emphasize interdisciplinary applications, combining statistical rigor with domain-specific insights. Recent work spans oncology, public health, and computational biology, reflecting a commitment to bridging theory and practical medical/sociological challenges. Awards & Roles: Panel Member, Ford Foundation Fellowship (2016–present) Associate Editor, BMC Genetics (2014–present) Former Residential College Master of Jones College (2005–2011) Advising & Grants: Guerra advises students on statistical research and curricula. He has led initiatives like the Keck Center for Quantitative Biomedical Sciences Training and co-founded the Empowering Leadership Alliance (ELA) to support underrepresented minorities in STEM. His grants include funding for bioinformatics consortia and educational outreach programs. Labs & Teams: Active in the Gulf Coast Consortia for Bioinformatics and collaborates with multidisciplinary teams at MD Anderson, Baylor College of Medicine, and UT Health Science Center.

Emilia LimView profile

Assistant Professor

• Bioinformatics
• Cancer
• Aging
• +5 more

Dr. Emilia Lim is an Assistant Professor in the Department of Biochemistry and Molecular Biology at the University of British Columbia's Faculty of Medicine , with an investigator role at the Edwin S.H. Leong Centre for Healthy Aging . She specializes in computational analysis of environmental exposures, particularly pollution, in age-related diseases like cancer. Education: BSc from University of Alberta (2009) PhD from University of British Columbia (2016) Postdoctoral training at Francis Crick Research Institute, University College London (2023) Her research integrates multi-omic approaches (genomics, transcriptomics, epigenomics) to investigate how environmental pollutants drive disease states in samples like cancer patients. Recent work focuses on lung cancer evolution , immune evasion , and epigenetic aging under pollution exposure, with applications in precision oncology and healthy aging initiatives across Canada. Publications highlight her expertise in cancer genomics , environmental toxicology , and computational biology , with key contributions to understanding air pollution-induced carcinogenesis (2023) and subclonal tumor dynamics (2020, 2023). Her lab develops tools like SPRINTER for single-cell cancer evolution analysis and explores haplotype-specific copy number in tumor heterogeneity ( Refphase , 2023).

• Genomics
• Yeast Genetics
• Chromosome Biology
• +7 more

Conrad Nieduszynski is a Senior Group Leader in the School of Biological Sciences at the University of East Anglia (UEA), where he leads a research group focused on yeast genomics and chromosome biology. His work bridges molecular biology, synthetic biology, and computational genomics, with a strong emphasis on fission yeast and pathogenic Candida species. His research interests include genome assembly , chromosome engineering , copy number variation , and telomere biology . He employs cutting-edge genomic technologies to understand genome structure, evolution, and function in model and pathogenic yeasts. His lab investigates both fundamental mechanisms and applied aspects, such as drug resistance in fungal pathogens. The recent articles highlight a strong trend in synthetic genomics (e.g., tRNA neochromosome construction) and high-resolution genome analysis (e.g., telomere-to-telomere assemblies). His work spans evolutionary biology, medical microbiology, and biotechnological innovation, reflecting a multidisciplinary approach to understanding genome dynamics. Scientific Impact: Publishes in high-impact journals including Cell and mBio Research referenced in patents and Wikipedia Widely shared in social media and covered by numerous news outlets Active collaborations across international research networks Dr. Nieduszynski advises a research team and collaborates extensively with leading scientists in genomics and synthetic biology. While specific grants are not listed, his publication record and high-profile work suggest active funding support. His research output is both prolific and influential, with applications in biotechnology and medicine. Laboratory and Collaborations: Leads an active research group at UEA Collaborates with experts in yeast genetics, synthetic biology, and infectious disease Engaged in large-scale genome projects and chromosome engineering initiatives

Oh Jeong-miView profile

Professor

• Clinical Pharmacy
• Pharmacogenomics
• Translational Research
• +3 more

Oh Jeong-mi is a Professor in the Department of Pharmacy, College of Pharmacy, Seoul National University, and concurrently holds a Professorship at Seoul National University Hospital since 2005. Her 20-year academic career at SNU progressed from Assistant Professor (2004-2007) to Associate Professor (2007-2012) and full Professor (2012-present), with additional leadership roles including Chairman of the Practical Training Committee for the Korean Council for Pharmaceutical Education (2010-2012). Education: B.S. from University of Texas at Austin Pharm.D. from University of Maryland at Baltimore Professor Oh's research centers on clinical and translational pharmacy with three interconnected pillars: (1) pharmacogenomics of drug transporters and metabolic enzymes in organ transplantation, (2) age- and disease-specific drug safety and appropriateness, and (3) chemotherapy optimization through pharmacokinetic modeling. Her work bridges genomic science with clinical practice to enable personalized immunosuppressant therapy, particularly for kidney and liver transplant recipients. Analysis of her 15 most recent publications reveals dominant research trajectories in CYP3A5/ABCB1 polymorphism impacts on tacrolimus/cyclosporine pharmacokinetics, with strong emphasis on Korean population-specific responses. Key subfields include pharmacometric modeling, transplant immunology, and genetic biomarker validation, consistently targeting clinical implementation of precision dosing protocols. Scientific Awards: Howol Songam Next-Generation Academic Award (2022) She has mentored 11 graduate students in pharmacogenomic applications for transplantation and oncology, with thesis topics spanning population pharmacokinetics, genetic association studies, and multidisciplinary team care models. Her research is conducted through the Clinical Pharmacy Laboratory, which employs collaborative frameworks involving clinicians, geneticists, and pharmacometricians to address complex drug therapy challenges in high-risk patient populations. The laboratory maintains active partnerships with Seoul National University Hospital's transplant and oncology units, focusing on real-world implementation of pharmacogenomic-guided dosing protocols while investigating novel drug-drug interaction mechanisms in polypharmacy scenarios common among elderly and multi-morbid patients.

• Mathematical oncology
• Cancer evolution
• Multiscale modeling
• +4 more

Dr. Kathleen Curtius is an Assistant Professor in the Department of Medicine at the University of California San Diego (UCSD), affiliated with the Division of Biomedical Informatics and the UCSD Moores Cancer Center. She leads the Quantitative Cancer Control laboratory, focusing on early cancer detection and prevention through mathematical modeling and multi-scale data analysis. Previously, she held a Medical Research Council Rutherford Fellowship at Barts Cancer Institute (London) and completed postdoctoral training in Prof. Trevor Graham's lab. Her research integrates applied mathematics, computational biology, and clinical oncology to address cancer evolution and screening strategies. Education: PhD in Applied Mathematics, University of Washington (2015) MS in Applied Mathematics, University of Washington (2011) BS in Mathematics, UCLA (2010) Research Interests: Mathematical oncology Cancer evolution modeling Epigenetic drift analysis Screening optimization Multiscale tumor dynamics Her work bridges disciplines to develop predictive tools for early cancer detection and personalized surveillance strategies. Publications: Recent work includes studies on metagenomic data bias (Nature Communications 2025), AI-driven cancer biomarker discovery (JCI Insight 2022), and computational models of Barrett's esophagus progression (Gut 2020). Her research emphasizes translational applications in clinical oncology and public health. Awards: Recognized with the 2024 Leah Edelstein-Keshet Prize, 2022 AGA Research Scholar Award, and 2018 MRC Rutherford Fellowship. Her work has been cited over 1,000 times across key oncology journals. Funding: Principal Investigator on NIH grants (R01CA270235, I01BX005958) supporting projects on Barrett's esophagus modeling and colitis-associated colorectal cancer surveillance optimization. Collaborates with clinicians, geneticists, and computational biologists to advance cancer control efforts. Labs/Teams: Leads the Quantitative Cancer Control Lab at UCSD, part of the Bioinformatics and Systems Biology division. Active in interdisciplinary initiatives like the Moores Cancer Center's Cancer Control Program.

Xiaolin ZhuView profile

Lecturer

• human genetics
• medical genetics
• cancer genetics
• +7 more

Xiaolin Zhu, MD, PhD is an Adjunct Lecturer in the School of Medicine at the University of California, San Francisco (UCSF), specializing in the Genitourinary Medical Oncology Program. His clinical focus is on prostate, bladder, and kidney cancers, while his research explores cancer evolution mechanisms through patient biospecimen analysis. He holds roles as Principal Investigator on grants from the Department of Defense, Prostate Cancer Foundation, and Conquer Cancer Foundation. Education: Bachelor of Medicine (MD equivalent) in Clinical Medicine, Shanghai Jiao Tong University School of Medicine (2011) PhD in Genetics and Genomics, Duke University (2017) Internal Medicine Residency, UT Southwestern Medical Center (2020) Hematology/Oncology Fellowship, UCSF (2024) Research Interests: Focuses on precision oncology, genomic profiling of treatment resistance, and translational research in prostate and urothelial cancers. Key areas include epigenetic evolution in cancer progression, biomarker discovery, and developing novel therapeutic strategies. Awards: ASCO Young Investigator Award (2022-2023) PCF Young Investigator Award (2022-2025) Department of Defense Physician Research Award (2024-2028) Grants: Investigating SSTR1 as a novel biomarker for advanced prostate cancer (DOD, 2024-2028) Resistance mechanisms to androgen receptor inhibitors (PCF, 2022-2025) Genomic profiling of metastatic castration-resistant prostate cancer (ASCO, 2022-2023) Labs/Teams: Active in UCSF's Genitourinary Oncology research teams and collaborates with the West Coast Prostate Cancer Dream Team.

• Statistical genomics
• Big omics data analysis
• Multivariate analysis
• +5 more

Dr. Lin Chen is a tenured Professor of Biostatistics in the Department of Public Health Sciences at The University of Chicago, where they have been faculty since 2010, progressing from Assistant Professor (2010-2017) to Associate Professor (2017-2024) and now Professor (2024-present). Previously, they completed postdoctoral research at Fred Hutchinson Cancer Research Center (2008-2010) under Drs. Ross L. Prentice and Li Hsu, and at Princeton University (2008) under Dr. John D. Storey. Dr. Chen earned their Ph.D. in Biostatistics from the University of Washington in 2008 under Dr. John D. Storey, following a B.S. in Economics from Peking University (2002). Their research focuses on developing advanced statistical methods for statistical genomics , big omics data analysis , multivariate analysis , missing data analysis , and mixed-effects models . Their work has significantly advanced methodologies in Mendelian randomization, multi-omics integration, and genetic association studies. Dr. Chen's recent publications reveal a strong emphasis on integrative approaches that connect multiple layers of genomic data across different biological contexts. Their research demonstrates particular expertise in developing statistical frameworks that bridge genetic variation with molecular phenotypes and complex traits, often addressing critical challenges in causal inference and mediation analysis within genomic studies. The work consistently appears in top-tier journals including Nature Communications, Nature Genetics, and The American Journal of Human Genetics. The Best Paper in Genetic Epidemiology Award for the Year 2021 The Departmental Best Dissertation Award 2017-2018 (awarded to Jiebiao Wang) Dr. Chen actively mentors graduate students and postdoctoral fellows, with several former lab members now in faculty positions or industry roles at major pharmaceutical companies. Their lab currently has ongoing postdoctoral openings. They have developed multiple widely-used software packages including GMAC, Primo, mvMISE, ofGEM, MixRF, mixEMM, PEMM, Trigger, RHT, SNPath, and EigenR2, available through CRAN, GitHub, and Bioconductor. Dr. Chen teaches courses including Applied Regression Analysis, Introduction to Biostatistics, Statistical Analysis with Missing Data, and Introductory Statistical Genetics at the University of Chicago.

Xu ShiView profile

Associate Professor

• Biostatistics
• Causal Inference
• Healthcare Data Analysis
• +5 more

Xu Shi is an Associate Professor in the Department of Biostatistics at the University of Michigan. Previously, they held a postdoctoral fellowship at Harvard’s Data Science Initiative (2017) under Tianxi Cai and Eric Tchetgen Tchetgen. Their research focuses on statistical methods for administrative healthcare data, electronic health records (EHR), and causal inference. Key projects include developing scalable pipelines for EHR curation, causal inference methods for comparative effectiveness studies, and co-leading the FDA’s Sentinel Initiative Innovation Center’s Causal Inference Core. Education: Ph.D. in Biostatistics from University of Washington (201?), B.S. in Mathematics & Applied Mathematics from Zhejiang University, China. Research emphasizes harmonizing distributed EHR data, addressing unmeasured confounding in air pollution studies, and rare adverse event analysis through flexible propensity score methods. They also explore medical knowledge extraction from ICD code patterns and natural indirect effect estimation robust to measurement errors. Awards: None explicitly listed. Grants & Advising: No specific grants or students listed, but their work involves collaborative initiatives like the FDA Sentinel Program. Labs/Teams: Active in the Causal Inference Core and distributed healthcare data partnerships with institutions like Henry Ford Health System and Kaiser Permanente.

Abigail BighamView profile

Associate Professor

• Human Population Genetics
• Molecular Evolution
• Natural Selection in Human Genome
• +4 more

Abigail Bigham is an Associate Professor and Vice Chair for Undergraduate Studies in the Department of Anthropology at the University of California, Los Angeles (UCLA). Her research focuses on human population genetics, molecular evolution, and high-altitude adaptation, particularly in Andean and Tibetan populations. She holds a PhD in Anthropology from Penn State University (2008) and a BA in Anthropology from the University of Arizona (2001). Her team investigates genetic and epigenetic mechanisms underlying adaptation to hypoxia, diet, and infectious diseases. Key research areas include the genetic basis of altitude-related traits like hemoglobin concentration, pulmonary function, and metabolic adaptations. Her lab also explores the evolutionary impact of dietary changes (e.g., potato-rich diets in the Andes) and immune responses to pathogens such as HIV and dengue. Recent work includes epigenetic studies of high-altitude acclimatization and the functional validation of adaptive alleles. Dr. Bigham’s projects often involve interdisciplinary collaborations, integrating genomic data with physiological measurements and anthropological fieldwork. She has conducted field studies in Peru, Tibet, Guatemala, and Nepal, focusing on indigenous populations to understand how genetic variation contributes to survival in extreme environments. Her lab’s website (https://bigham-lab.anthro.ucla.edu/) provides access to datasets and research tools. Her academic contributions span over 50 peer-reviewed articles and grants addressing high-altitude physiology, evolutionary genetics, and global health. She actively advocates for ethical discussions on race and genetics, challenging simplistic biological determinism through public outreach and educational initiatives.

Kristen BrennandView profile

Professor

• Psychiatric Genomics
• Stem Cell Biology
• Neurogenetics
• +3 more

Kristen Brennand is the Elizabeth Mears and House Jameson Professor of Psychiatry and Professor of Genetics at Yale School of Medicine. She leads research at the intersection of genomic engineering, neuroscience, and stem cell biology to decode mechanisms underlying brain diseases. Her work focuses on translating genetic insights into medically actionable information for schizophrenia, autism, PTSD, and Alzheimer’s disease. Education: PhD in Molecular and Cellular Biology from Harvard (2008), Postdoc at Salk Institute Key research areas: Gene-environment interactions , neuronal circuit dysfunction , precision psychiatry , and reversible disease mechanisms Recent publications span single-cell transcriptomics , neurogenetic atlases , and computational psychiatry methods . Awards: Executive Leadership in Academic Medicine (ELAM) Fellowship (2025) Funded by NIH, New York Stem Cell Foundation, Brain Research Foundation, and Brain and Behavior Research Foundation Laboratory: Brennand Lab at Yale School of Medicine