Dr. Andy (Andrzej) Kudlicki joined MSBMI as an Assistant Professor within the UTHealth Biomedical Informatics Group Analytics Research Center (BIG-Arc) and the Department of Clinical and Health Informatics in June 2025. With background in physics and bioinformatics, he is working on extracting and interpreting EHR data, especially in the context of genomic information.
- Tell us about your research center and/or what research/work you are currently working on.
His current research focuses on the analysis of time-course data, methods of causal inference in biological networks, and the development of deconvolution algorithms. He is interested in novel regulatory elements, using them to optimize data compression and processing, and in understanding how they interact to drive the logic of complex diseases, including developmental and neurodegenerative disorders.
- What does the future of your research look like? What does the future of informatics look like?
In Dr Kudlicki’s opinion, one of the key elements of innovation in biomedical informatics lies in automated or semi-automated feature engineering. Identifying the parameter space that facilitates creating models optimal for a specific research question has been central to the success of his past research projects and he expects it to be even more important going forward.
Education
- Postdoctoral: UT Southwestern, Dallas, TX - Biophysics and Bioinformatics, 2001-2006
- Graduate Education: Polish Acad. Sci, Warsaw, Poland- Ph.D. / Physics; 10/1995 - 09/2000 Advisors: M. Ró?yczka, R. Juszkiewicz
- Undergraduate Education: University of Warsaw, Poland -M.S. / Physics / Astronomy; 10/1990 - 09/1995
Areas of Expertise
- Statistical models, Monte-Carlo methods, inference of causation
- Integration of genomic, proteomic and transcriptomic datasets with clinical data
- Transcriptional regulation in inflammation, cancer and neurodegeneration
- Genotype-to-phenotype mapping
- Epigenomics of development and disease
