MIT EECS - VMware Undergraduate Research and Innovation Scholar
Improving Genetic Programming in detecting high-order interaction of SNPs
Interactions of SNPs (Single Nucleotide Polymorphisms) are associated with various complex diseases such as sporadic breast cancer. Using Genetic Programming for association studies has proved effective in identifying high-order interactions of SNPs indicative of increased breast cancer risk. However, because SNP interactions are often of a high order and the number of SNPs in humans is huge (~1,400,000 SNPs), the methodology needs to be extended to be scalable. In this project, we will consider integrating additional biological factors and use these factors to propose new heuristics that may not only extend the methodology, but also yield better results in identifying important SNP interactions and classifiers.
I worked on a UROP with Prof. Jazayeri on a web-based acquisition system for studying time perception in humans. I had an internship at Athenahealth, Inc. designing and improving the regression testing. I double major in Biology and EECS.