For Researchers
I am open to collaborations with researchers in academia, clinical settings, and industry, including pharmaceutical and biotechnology companies, who are interested in applying my statistical and computational methods to their research.
Researchers do not need to have detailed knowledge of my methods or their mathematical and computational foundations before contacting me. This is particularly relevant for clinical, experimental, and biological researchers who may have less experience with computational methods. I generally ask that researchers have a specific scientific question, a reasonable understanding of why a particular method may be applicable, and a very strong interest in applying it to their data. I am happy to assist with the technical details, including assumptions, implementation, troubleshooting, and interpretation.
Areas in which I may be able to assist include:
Method selection and application: Discussing which of my methods may be appropriate for a particular dataset or research question, including their assumptions, implementation, and interpretation.
Troubleshooting and modifications: Addressing implementation questions, unexpected results, or difficulties applying a method due to the nuances of a particular dataset. I am also open to discussing modifications that may be needed for specific research applications.
Clinical and experimental data analysis: Applying my methods to randomized controlled trials, treatment-response data, and other experimental or clinical datasets.
Genomic and molecular data analysis: Applying my methods to genetic, genomic, transcriptomic, and other omics data, including studies of disease mechanisms, therapeutic targets, and clinically relevant phenotypes.
Industry research: Collaborations involving drug discovery, therapeutic target identification, clinical development, treatment-response analysis, and related areas of pharmaceutical and biotechnology research.
When contacting me, please provide a description of the scientific question, the available data, the method you intend to apply, and why you believe it is suitable for your research.