Environmental Mixtures Workshop

Traditionally, environmental health studies have focused on assessing risks related to a single pollutant at a time. This, however, does not reflect reality, since we are constantly exposed to multiple pollutants at once. Recently, there has been an increased interest in methods that allow researchers to assess exposures to many pollutants at a time. These methods are able to accommodate the high dimension of the exposure matrix, as well as the usually high correlation across exposures of interest.

This two-day intensive workshop will provide a rigorous introduction to multiple different techniques to analyze exposure to mixtures in environmental health. Led by a team of world experts in environmental health, epidemiology and statistics, many of whom have developed their own methods to analyze exposure to mixtures, the workshop will integrate seminar lectures with hands-on computer lab sessions to put concepts into practice. Emphasis will be given to supervised and unsupervised methods. Since the choice of method depends on the research question at hand, the workshop will conclude with a panel discussion on when each method presented is appropriate for use and for which research questions.

By the end of the workshop, participants will be familiar with the following topics:

• Principal Component Analysis (PCA)
• Factor Analysis (FA)
• Clustering
• Variable Selection (Lasso, elastic net)
• Bayesian Kernel (BKMR)
• Weighted Quantile Sum Regression (WQS)
• Emerging mixtures topics and novel extensions
• Tree-based methods

Summer 2026: The Environmental Mixtures Workshop is a live, in-person training taking place July 23-24, 2026 from ~9:00am - ~5:00pm at the Columbia University Irving Medical Campus in NYC. All training start and end times are in EDT.

More information on travel, lodging, and getting around NYC.

Investigators at 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:

1. Each participant must have an introductory background in statistics.
2. Each participant must be familiar with R.
3. Each participant is required to have a personal laptop/computer and a free, basic Posit Cloud (formerly RStudio Cloud) account.  All lab sessions will be done using Posit Cloud (formerly RStudio Cloud).

Knowing basic R platform and commands is required for the Boot Camp as noted in prerequisites above. This training will use Posit Cloud (formerly RStudio Cloud). If you are new to R or need a refresher, you can review the below tutorials to be well prepared:

• R Programming Tutorial - Learn the Basics(link is external and opens in a new window): A free datalab.cc class on R fundamentals
• Once you create your free, basic Posit Cloud (formerly RStudio Cloud) account for the training: Primers on Programming Basics and Visualization Basics(link is external and opens in a new window).
• SHARP Program RStudio Cloud Tutorial(link is external and opens in a new window): This self-paced tutorial from the Columbia SHARP Program walks through the Cloud Platform you will use at the training, as well as some basic exercises. We recommend this tutorial if you have not used the Cloud version of RStudio before, or if you are a beginner user of R.

If you have any specific questions about R and R studio in the context of the Environmental Mixtures Workshop, please email us(link sends e-mail).

Brent Coull, PhD, Harvard T.H. Chan School of Public Health, Harvard University.

Chris Gennings, PhD, Research Professor and Biostatistics Division Director, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai. Dr. Gennings’ research program includes the development of Weighted Quantile Sum (WQS) regression (joint work with a dissertation student), a method that is robust to confounding concerns based on complex correlations among exposure to environmental mixtures. She is currently developing methods for nutritional and environmental exposures that estimate and evaluate regulatory guideline values for mixtures.

Jeff Goldsmith, PhD, Associate Professor, Department of Biostatistics, Columbia University Mailman School of Public Health. Dr. Goldsmith's statistical research focuses on high-dimensional data, with particular emphasis on dimension reduction methods, and modeling health outcomes. In addition to environmental health, he works on physical activity quantification using accelerometers, and on motor control experiments involving kinematic data.

Marianthi-Anna Kioumourtzoglou, ScD, Professor, Department of Epidemiology, Brown University School of Public Health. Dr. Kioumourtzoglou is an environmental engineer and environmental epidemiologist by training, with a research emphasis on air pollution exposures. Her research focuses on statistical issues related to environmental epidemiology, such as assessing exposure to environmental mixtures (chemical and non-chemical) in health studies, and quantifying and correcting exposure measurement error.

Ander Wilson, PhD, Assistant Professor, Department of Statistics, Colorado State University. Dr. Wilson's research program focuses on developing statistical methods for environmental health research, including estimation of health effects of exposure to environmental mixtures, effect estimate heterogeneity, Bayesian methods, machine learning, and others.

Training scholarships are available for the Environmental Mixtures Workshop.

"This workshop is a great way to become familiar with novel methods for environmental mixtures research. The instructors were thorough in their explanations and facilitated meaningful discussion, making the workshop even more valuable." - Postdoc at Northeastern University, 2025

"It was taught at the right level for someone who is not a statistician but uses statistics all the time. I understood the concepts without getting lost in the mathematics." - Staff Member at the CDC, 2025

"This was easily the best workshop I have ever attended. The instructors break down difficult concepts in easy-to-understand lectures and provide real-life examples of how to apply the concepts." - Assistant Researcher at The George Washington University, 2025

"This workshop is a fantastic resource for those looking to better understand and implement modern mixtures methods in environmental health research. It is also a wonderful opportunity to learn from world-class instructors and network with other researchers." - Graduate Research Assistant at Northeastern University, 2024

"This training was great and provided a very good introduction to the methods and how they might be used. Going through the theory of the methods first and looking at R code for the methods second solidified the concepts after they were introduced, and provided me with practical tools to implement these approaches in my own research." - Doctoral Student at University of North Carolina at Chapel Hill, 2024

"The workshop was extremely informative and clear for someone who has not utilized mixture methods in the past, while still providing in-depth information and code that I am sure I will dip back into time and time again." - Postdoctoral Fellow at University of Michigan, 2023

"An excellent introduction to an emerging field of increasing importance. Would recommend." - Student at New York University Grossman School of Medicine, 2023

"Great overview of the status quo of environmental mixtures research methods. Instructors mapped research questions by theme and introduced methods accordingly, which was extremely helpful!" - PhD student at University of California, Berkeley School of Public Health, 2023

Registration Fee is based on your category and includes course material, breakfast, and lunch on training days. Course material will be available to all attendees during and after the workshop. Lodging and transportation are not included.

2026 Registration Category Rates: 

• Student/Postdoc/Trainee: 
  • Early-bird rate: $1,195 
  • Regular rate: $1,395 
• Faculty/Academic Staff/Non-Profit Organizations/Government Agencies: 
  • Early-bird rate: $1,395 
  • Regular rate: $1,595 
• Corporate/For-Profit Organizations: 
  • Early-bird rate: $1,595 
  • Regular rate: $1,795 

$200 early-bird discount is automatically applied if you register before the May 15 deadline.  

• $200 Early-bird Discount: This is automatically applied if you register before the May 15 early-bird deadline.  
• 10% Columbia Discount: This is valid for any active student, postdoc, staff, or faculty at Columbia University. If paying by credit card, use your Columbia email address during the registration process to automatically have the discount applied. If paying by internal transfer within Columbia, see below.  
• 10% Mailman Alumni Discount: This is valid for any individual who graduated from the Columbia University Mailman School of Public Health. To access the Mailman Alumni discount and receive a registration code, please email sharp_program@cumc.columbia.edu your graduation year and degree.  
• Group discounts are available for organizations sending 5+ participants. Please contact us directly at sharp_program@cumc.columbia.edu for more information. 

If paying by internal transfer within Columbia, submit this Columbia Internal Transfer Request form (link to form coming soon) to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.

If you would prefer to pay by invoice/check, please submit this Invoice Request form (link to form coming soon) to receive further instructions. Please note: filling out this form is not the same as registering for a training and does not guarantee a training seat.

Cancellation notices must be received via email at least 30 days prior to the training start date in order to receive a full refund, minus a $75 administrative fee. Cancellation notices received via email 14-29 days prior to the training will receive a 75% refund, minus a $75 administrative fee. Please email your cancellation notice to Columbia.Mixtures@gmail.com. Due to workshop capacity and preparation, we regret that we are unable to refund registration fees for cancellations less than 14 days prior to the training.

If you are unable to attend the training, we encourage you to send a substitute within the same registration category. Please inform us of the substitute via email at least one week prior to the training so we can include them on attendee communications, gather registration details, and provide materials.Should the substitute fall within a different registration category (e.g., you are a faculty member and they are a postdoc), the credit card on file will be credited/charged respectively. Please email substitute inquiries to Columbia.Mixtures@gmail.com. In the event Columbia must cancel the event, your registration fee will be fully refunded.