His contributions to jobs relevance include candidate selection in job search through multi-pass ranking and deploying generalized linear mixed models for reducing poor job recommendation impressions. Currently, he is focusing on the deployment of deep and wide models for job recommendations. He is a recent graduate of the University of California, Berkeley, where he received both his Master of Engineering and Bachelor of Science Degrees.