About

Liang He is a Software Engineer at Databricks with expertise in developing and designing serverless and highly elastic cloud services. He excels in removing operational complexity while ensuring reliability and cost efficiency at scale. Liang has a Doctor of Philosophy in Physics from Purdue University, where he also worked as a Research Assistant. He holds a Bachelor of Science in Physics from the University of Science and Technology of China. During his time at Purdue University, Liang self-implemented a MapReduce system to analyze large scale data in binary format. He designed a data structure with constant time and space-efficient implementation using a 3-level column NoSQL idea. The data structure saved 100x disk space and achieved speed-up by 10x, and the software is used by researchers in this area. Liang also trained a classifier for very weak Physics signal on data-driven Monte Carlo simulation using boosted decision trees. Optimized features improved the performance of signal identification by a factor of 200%. Prior to joining Databricks, Liang worked as a Period Coordinator at Brookhaven National Laboratory. He had the responsibility of oversight and continuity of the STAR experimental scientific program on a day-to-day, week-to-week basis during a two-week "tour of duty." He was also responsible for calling and leading meetings required for the coordination of regular shift crew in carrying out the near-term scientific program. Liang's technical expertise includes software engineering, research science, MapReduce, and NoSQL. With 4.96 years of relevant experience, he is a highly skilled and accomplished professional.