Career Notes

Chris Burges is currently self employed, having retired from the position of Principal Researcher and Research Manager at Microsoft Research at the end of 2016. While at MSR, which he joined 2000, Chris worked on image compression with neural nets; on audio fingerprinting for duplicate detection, audio thumbnail generation and music identification (his work is currently used in Xbox and Windows Media Player to identify music); on general machine learning research; on ranking (his ranking algorithm has been used now for several years by Bing for web search); and most recently, on how to make artificial intelligence scalable.

Before 2000, Chris worked at AT&T (then, Lucent) Bell Labs, which he joined in 1986 as a systems engineer, gradually morphing into a researcher.  There, he worked on the systems engineering of large communications networks for error robustness and network routing (AT&T still uses his algorithms to route several key networks); on neural networks for handwriting and machine print recognition (he worked on a system now used to read millions of checks daily, and in fact his long descent into machine learning was triggered by a particularly cool demo of a neural net recognizing handwritten digits in the early 90's); on a popular class of machine learning algorithms called Support Vector Machines (he was fortunate enough to work with one of SVM's inventors in the early days); and on speaker verification.

Prior to Bell Labs, Chris was a postdoctoral fellow at the Theoretical Physics Department at MIT, where he worked on topics in quantum gravity, and on the pretty much completely unrelated problem of fluid modeling using cellular automata.  Chris got his PhD in particle physics from Brandeis, where he also worked on cosmological models, and before that, he graduated with First Class Honors in Physics and Mathematics from Oxford.

Chris was Program Co-chair of Neural Information Processing Systems 2012 and General Co-chair of NIPS 2013.