Chung was awarded a M.S. in 1972 and a Ph.D. two years later. By this time, she was married and had already given birth to her first child. The same year she received her Ph.D. and started working for the Mathematical Foundations of Computing Department at Bell Laboratories in Murray Hill, New Jersey. The position at Bell Laboratories was an opportunity to work with other excellent mathematicians, but also it contributed to her mathematical world powerfully. She has published many impressive mathematical papers, and published many joint papers with Ron Graham. Bell Laboratories In 1974, Fan Chung graduated from the University of Pennsylvania and became a member of Technical Staff working for the Mathematical Foundations of Computing Department at Bell Laboratories in Murray Hill, New Jersey. She worked under Henry Pollak. During this time, Chung collaborated with many leading mathematicians who work for Bell Laboratories such as Ron Graham. In 1975, Chung published her first joint paper with Graham, On multicolor Ramsey numbers for complete bipartite graphs, which was published in the Journal of Combinatorial Theory (Series B). In 1983 the Bell Telephone Company was split up. Since Pollak joined and became head of a research unit within a new company, he asked Chung to become Research Manager. She supervised many mathematicians in the unit. In 1990, she was one of the first to receive a Bellcore university fellowship, a sabbatical she spent at Harvard university. Later career After twenty years of work at Bell Laboratories and Bellcore, Chung decided to go back to the University of Pennsylvania to become a professor of mathematics. In 1998, she was named Distinguished Professor of Mathematics at the University of California, San Diego. Beyond her contributions to graph theory, Chung has used her knowledge to connect different fields of science. As she wrote in "Graph Theory in the Information Age", “In the past decade, graph theory has gone through a remarkable shift and a profound transformation. The change is in large part due to the humongous amount of information that we are confronted with. A main way to sort through massive data sets is to build and examine the network formed by interrelations. For example, Google’s successful Web search algorithms are based on the WWW graph, which contains all Web pages as vertices and hyperlinks as edges. There are all sorts of information networks, such as biological networks built from biological databases and