An instinctive problem solver, Ming combines his science and engineering prowess to find ways that algorithms, scalable analysis platforms and interactive visualizations can empower scientists and accelerate research.

Ming creates solutions that are scalable, usable and address the needs of researchers, scientists and innovators. He currently specializes in computational mass spectrometry with applications to proteomics, metabolomics and natural product discovery.

Obtaining a PhD from UC San Diego, Ming completed his graduate education with Prof. Nuno Bandeira and went on to create Ometa Labs LLC. Using high-throughput untargeted tandem mass spectrometry to detect and quantify thousands of molecules in biological samples, he applies machine learning algorithms to infer the relationship between molecules and the biological and environmental context in which they are found.