Events

The Microbiome Data Analytics Boot Camp is a two-day intensive training of seminars and hands-on analytical sessions to provide an overview of 16S rRNA gene sequencing surveys including planning, generating and analyzing sequencing datasets. This two-day intensive workshop will provide a rigorous introduction to the theory and methodology underlying the design, generation, and analysis of Amplicon Sequence Variant (ASV) based investigations of microbial communities. The workshop will introduce state-of-the-art techniques using the R language and environment. A team of leading experts in microbiome data analytics and statistics will offer a hands-on experience in learning how to implement these techniques by integrating publicly available data and R packages to explore and understand some of the pitfalls and information drawn from 16S rRNA data analysis. This workshop specifically trains participants in the use of the R programming environment for the analysis of microbiome sequence data, including the implementation of the DADA2 and phyloseq software packages. By the end of the workshop, participants will be familiar with the following topics: The theoretical basis underpinning 16S rRNA investigations Methodologies for generating 16S rRNA sequence data 16S sequence data quality control Amplicon sequence variant inference Taxonomic annotation Biodiversity estimation Principal Component Analysis and PERMANOVA Taxon-covariate correlation and regression modeling Introduction to machine learning in microbiome data Phylogenetic analysis Audience and Requirements Investigators from any institution and from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this workshop: Each participant must have an introductory background in statistics. Each participant must be familiar with R. Each participant must have a computer with either Chrome or Firefox installed (latest update). Instructors Maude David, PhD, Oregon State University.  Thomas Sharpton, PhD, Oregon State University. Additional Information Subscribe for updates on new Boot Camp details and registration deadlines. Contact the Microbiome Boot Camp team. Capacity is limited. Paid registration is required to attend.

Focus on Vision Science Join Us In-Person or Virtually for 1, 2, or All 3 Days CME Credits Available We invite you to attend the Precision Ophthalmology 2025, a one-of-a-kind conference focusing on the most up-to-date research in precision ophthalmology and is geared towards ophthalmologists, vision scientists, ophthalmic geneticists, and trainees of every level. It’s in our DNA to educate others, to provide superlative clinical care and to advance vision science.

The Statistical Analysis with Missing Data Workshop is a two-day intensive workshop of seminars and hands-on analytical sessions to provide an overview of concepts, methods, and applications for statistical analysis of health studies with missing data. This two-day intensive workshop integrates the principle concepts and methods commonly used in statistical analysis with missing data and their applications in surveys, longitudinal studies, and clinical trials. Led by a team of renowned experts in missing data research, this workshop will integrate seminar lectures with hands-on computer lab sessions and case studies to put concepts into practice. We will cover weighting, maximum likelihood, Bayes, and multiple imputation methods and use a wide variety of examples to illustrate the techniques and approaches. We will also discuss methods for missing not at random and the latest developments on missing data research. By the end of the workshop, participants will be familiar with the following topics: Missing data patterns and mechanisms Weighting methods Maximum likelihood methods Bayes and multiple imputation Approaches to missing not at random Missing data in surveys Missing data in longitudinal studies Missing data in clinical trials Audience and Requirements Investigators from all career stages are welcome to attend, and we particularly encourage trainees and early-stage investigators to participate. There are three requirements to attend this training: Each participant must be familiar with common methods of statistical analysis of complete data, such as multiple regression and logistic regression. Each participant must have experience with programming in R. Each participant is required to bring a personal laptop as all lab sessions will be done on your personal laptop. Each participant must have R downloaded and installed prior to attending the Workshop. Instructors Roderick J. Little, PhD, University of Michigan School of Public Health. Roderick J. Little is Richard D.  Qixuan Chen, PhD, Mailman School of Public Health, Columbia University. Qixuan Chen is Associate Professor of Biostatistics at Columbia University. Additional Information Subscribe for updates on new Training details and registration deadlines. Contact the Boot Camp team. Capacity is limited. Paid registration is required to attend.

Join us as we launch the Center for Innovation in Imaging Biomarkers and Integrated Diagnostics (CIMBID) CIMBID is a multidisciplinary research center designed to advance research, education, and clinical translation in AI-driven imaging biomarkers and integrated diagnostics. We bring together the brightest minds at Columbia University—spanning disciplines in medical imaging, computer science, biomedical informatics, bioengineering, systems biology, and public health—to conduct cutting-edge, rigorous, and impactful research. Through multidisciplinary collaboration, we aim to bridge the gap between technological innovation and clinical application, ensuring that our advancements translate meaningfully into real-world patient care. This event is aimed at highlighting the depth and breadth of the mission and activities of CIMBID and engaging the research community at Columbia University, as well as our partners, more broadly into a vibrant scientific ecosystem. We're excited to have you join us! More Information and Registration