Chao Dai
About Chao Dai
Chao Dai is a Senior Scientist at Predicine Inc, specializing in high throughput sequencing data analysis and machine learning applications in genomics. He holds a Ph.D. in Computational Biology from the University of Southern California and has extensive experience in cancer research and liquid biopsy assays.
Work at Predicine
Chao Dai has been serving as a Senior Scientist at Predicine Inc since 2019. In this role, he focuses on the analysis of high throughput sequencing data and the application of machine learning techniques to genomic data. His work contributes to the development and clinical application of advanced genomic assays, including the PredicineBEACON next-generation minimal residual disease assay for genitourinary cancers. Dai's involvement in various projects emphasizes his expertise in liquid biopsy assays and genomic profiling.
Education and Expertise
Chao Dai holds a Bachelor of Science (BS) in Computer Science from Wuhan University, which he completed from 2000 to 2004. He furthered his education with a Master's degree in Computational Biology from the same institution, studying from 2004 to 2006. He then earned a Doctor of Philosophy (Ph.D.) in Computational Biology from the University of Southern California, where he studied from 2008 to 2013. Dai possesses advanced programming skills in R and Python, which he applies in his research.
Background
Before joining Predicine, Chao Dai worked as a Postdoctoral Associate at the University of Southern California from 2013 to 2016. He then transitioned to Stanford University, where he served as a Postdoctoral Researcher from 2016 to 2019. His academic and research background has equipped him with a strong foundation in computational biology and genomic data analysis, which he continues to leverage in his current role.
Research Contributions
Chao Dai has made significant contributions to various research initiatives in the field of genomics and cancer detection. He has been involved in the development of a rapid, highly sensitive cell-free RNA NGS assay for detecting gene fusion and splicing variants in cancers. His research also includes age-based assessments of cell-free DNA genomic profiles in metastatic castration-resistant prostate cancer and the development of a tumor-agnostic liquid biopsy assay for minimal residual disease detection. Dai has participated in research presented at the 2023 AACR conference.
Clinical Applications
Chao Dai has contributed to the clinical applications of genomic studies, particularly in bladder and prostate cancer. His work includes urine- and blood-based genome-wide copy number studies and the development of a novel urine cell-free DNA preservation method for molecular profiling in genitourinary tumors. Additionally, he has worked on blood-based tumor fraction estimation in cancer patients and the prognostic utility of DNA damage response aberrations in metastatic castration-resistant prostate cancer.