Lab Members

Elaine (Teng-Ting) Lim, Assistant Professor, AS4-1075
Elaine is passionate about understanding the genetic mechanisms of complex neurological diseases such as Alzheimer's Disease and autism. I completed my PhD training at Harvard University in quantitative genetics and genomics. During my post-doctoral training with George Church, I really enjoyed working at the intersection of computational methods development and technology development, with the aim of using novel methods development to understand complex diseases. I hope to train students and post-docs who are interested in cross-disciplinary training in human diseases, genetics, genomics and technology.

Yingleong (Rigel) Chan, Assistant Professor, AS4-1077, Lab webpage
Rigel runs his independent lab next to Elaine's lab, but helps with co-mentoring lab members in both groups. Rigel completed his graduate education in Genetics and Genomics at Harvard University under the supervision of Prof. Joel Hirschhorn. After graduating, he did his Postdoc research in Functional Genomics at Prof. George Church's Lab at the Department of Genetics at Harvard Medical School. Rigel has a deep interest in applying quantitative approaches using in-vitro models to further genetics research. His research is interdisciplinary encompassing both bioinformatics (Algorithm Design, Statistical Analysis, Data Processing, etc) as well as wet-lab experimental approaches (Tissue Culture, DNA and RNA sequencing, Gene Editing).

Julia Reichert, Research Associate, AS4-2071
Julia is interested in developing in-vitro models from induced pluripotent stem cells (iPSCs) to study human diseases. She is currently working to perform multiplex reprogramming of many human cells into iPSCs.

Pepper Dawes, Bioinformatician I, AS4-2071
Pepper is passionate about bioinformatics focusing on integrating different transcriptomics methods to create new techniques to better utilize the abundance of data we can derive from our experiments. She graduated from UT Austin with a background in computational biology and hopes to apply this to create tools for other researchers in the iPSC and transcriptomics spaces.