The genealogy process is typically the most time-consuming part of — and a limiting factor in the success of — forensic investigative genetic genealogy, which is a new approach that is transforming the way that law enforcement is solving violent crimes. Given a list of distant relatives of the unknown criminal, which is obtained from two databases (GEDmatch and Family Tree DNA), we construct an algorithm that attempts to find the criminal as quickly as possible. Using simulated versions of 17 cases (eight solved, nine unsolved) from the nonprofit DNA Doe Project, we estimate that our algorithm can solve criminal cases 25 times faster than a benchmark strategy. We also describe our recent use of the algorithm to attempt to solve stalled cold cases with genealogist Barbara Rae-Venter, who solved the Golden State Killer case.
Bio: Lawrence M. Wein is the Jeffrey S. Skoll Professor of Management Science at the Graduate School of Business, Stanford University, where he was a Senior Associate Dean of Academic Affairs during 2018-2024. He received a B.S. in operations research and industrial engineering at Cornell in 1979, a Ph.D. in operations research at Stanford University in 1988, and was a professor at MIT’s Sloan School of Management from 1988 to 2002. His research interests are in operations management and public health. He was Editor-in-Chief of Operations Research from 2000 to 2005. He has been awarded a Presidential Young Investigator Award, the Erlang Prize, the Koopman Prize, the INFORMS Expository Writing Award, the Philip McCord Morse Lectureship, the INFORMS President’s Award, the Frederick W. Lanchester Prize, the George E. Kimball Medal, a best paper award from Risk Analysis, and a notable paper award from the Journal of Forensic Sciences. He is an INFORMS Fellow, a M&SOM Fellow and a member of the National Academy of Engineering.
This event is a University Lecture and Data Science Distinguished Lecture co-sponsored with the Center for Data Science for Enterprise and Society, the SC Johnson College of Business, and the School of Operations Research and Information Engineering.