After serving in the Polish Division of the British Army in World War II, he immigrated to the United States where he established a career in the field of signal processing, information theory, and communications.

[3] After his retirement, Bussgang volunteered in Warsaw and Kraków with the International Executive Service Corps to help privatize Polish industrial firms.

In 2011, President Komorowski presented Bussgang with the Knight’s Cross of the Order of Merit of Poland at The Polish Consulate in New York City for his activities promoting Polish-Jewish dialogue.

The company developed troposcatter modems, radio channel simulators, and a satellite system for measuring continental drift.

Over his career Bussgang earned six patents and maintained a top-secret security clearance for his contributions to defense technology.

[12] Bussgang also served as a consultant to Honeywell, Hughes Aircraft, Philco-Ford, IBM, Arthur D. Little, Raytheon Company, RCA, and Sperry Univac among others.

After retirement, Bussgang volunteered twice in Warsaw and once in Kraków with International Executive Service Corps to help privatize Polish industrial firms.

In 2011, President Komorowski presented Bussgang with the Knight’s Cross of the Order of Merit of the Republic of Poland at the Polish Consulate in New York City, for his activities promoting Polish-Jewish dialogue.

One is a monograph with David Middleton on Truncated Sequential Tests, the other is Signal Detection and Estimation; Problems and Solutions with Nicolas Johnson.

[16] These books, originally published by the Association of the Children of the Holocaust in Poland, contain testimonies by different authors highlighting experiences during World War II.

[20] While completing his graduate studies at the Massachusetts Institute of Technology (MIT), Bussgang formalized the theorem, which has since become an essential tool in understanding nonlinear systems affected by Gaussian processes.

The theorem simplifies the analysis of complex systems involving nonlinear operations by leveraging the statistical properties of Gaussian signals.

His theorem is used to model the behavior of systems where signals pass through nonlinear elements, enabling more efficient filter design.