A virtual memorial service is set for 2 p.m. Tuesday through Hillier Funeral Home of College Station for the respected researcher, educator and mentor who came to Texas A&M in 1987 as an associate professor in the Department of Statistics and made a career out of applying his statistical expertise to chemistry, forensic science, medicine and related problems across multiple disciplines in broader service to society.
Spiegelman was renowned by colleagues at Texas A&M and throughout the nation for his comprehensive knowledge of statistics and its fundamental importance, his genuine nature and willingness to serve in any capacity, and his commitment to fairness, equity and accuracy in all matters, particularly science.
“Cliff was a person who voluntarily helped others,” said Texas A&M statistician Samiran Sinha. “He was there whenever the department needed someone, whether in presenting the department at the college level, talking with other departments, or improving or restructuring courses. I communicated with him last week regarding a paper review. He was truly a helpful person.”
Spiegelman was appointed in 2009 as a distinguished professor of statistics, Texas A&M’s highest honorific rank for faculty. He was designated a Regents Professor for 2018-19 in recognition of his exemplary contributions to The Texas A&M University System and the people of Texas. A senior research scientist with the Texas A&M Transportation Institute, he had served since 2017 as the inaugural Official Statistician of the Texas Holocaust and Genocide Commission as well as the statistical advisor to the Texas Forensic Science Commission. For many years he also was the key statistical advisor to the City of Houston’s crime lab.
Throughout his four-decade career, Spiegelman used his vast knowledge of statistics and forensic science to help free innocent people, reevaluate history and develop sharper analytical tools for society. In perhaps the most visible and pioneering example, his expertise was key as a member of a National Research Council committee tasked with evaluating the effectiveness of comparative bullet lead analysis (CBLA), a forensic method most notably used in the investigation of the 1963 assassination of U.S. President John F. Kennedy.
He was instrumental in the Federal Bureau of Investigation’s 2005 decision to stop using the widespread technique after he demonstrated it to be fundamentally flawed and also part of a related study that determined the same for evidence used to rule out a second shooter in the Kennedy assassination — work recognized with the 2008 American Statistical Association’s Statistics in Chemistry Award.
“Cliff’s passion was good and irrefutable statistical methodology in the absence of classical experimental design,” said Texas A&M statistician and interim head of Texas A&M Statistics Daren B.H. Cline. “He was a public face for statistics who demonstrated the relevance of our field to society and the importance of proper techniques and precise application.”
A native of Long Island, Spiegelman earned a bachelor’s in economics, math and statistics at The State University of New York at Buffalo in 1970, and both his master’s in managerial economics and doctorate in statistics and applied mathematics at Northwestern University in 1973 and 1976, respectively. Prior to coming to Texas A&M, he spent nine years in the Statistical Engineering Division at the National Bureau of Standards (now known as the National Institute of Standards and Technology) in Gaithersburg from 1978 to 1987 following one year as an assistant professor of statistics at Florida State University. He also held visiting faculty appointments at Northwestern (1982-1983), Johns Hopkins University (1986-1987) and Lamar University (1993-1996).
In addition to higher education, Spiegelman served as an adjunct investigator in the Biostatistics Branch of the National Cancer Institute (NCI) Division of Cancer Epidemiology Genetics (2005-2008) and as a consultant for the NCI Proteomics Program (2005-2009). For the past six years, he spent his summers in Washington, D.C., working with collaborators at the National Agricultural Statistical Service (2014-2019).
Spiegelman was a founder of the field of chemometrics, the science of using data to extract information from chemical systems by data-driven means to investigate and address problems in chemistry, biochemistry and chemical engineering. In 2017, the international journal he co-founded, Chemometrics and Intelligent Laboratory Systems, celebrated his 30-plus years of service to both the publication and the discipline he helped create with a virtual special issue in his honor. An active researcher and scholar, Spiegelman authored more than 200 refereed publications that have appeared in the Annals of Statistics and at least 20 other statistics journals. He also contributed to five books and dozens of conference proceedings, reviews and editorials.
Beyond traditional scholarly achievements, Spiegelman was equally driven by societal service, as evidenced by his body of work focused on problems of local, state, national and international importance, along with his desire to communicate the results to help audiences at all levels better understand its broader significance.
During the past two decades, he was quoted in many contexts by national media, most notably with regard to his research showing the statistical limitations of some of the forensic techniques commonly presented as evidence in the justice system, including bullet fragment analysis. He routinely testified in criminal matters related to various aspects of statistics, flawed forensic science, probability and the law — often in association with the Innocence Project, the national nonprofit legal clinic dedicated to exonerating wrongfully convicted people through DNA testing and other post-verdict methods. He was among a distinguished group of statisticians, legal scholars and scientists from other fields who regularly collaborated with the Innocence Project on amicus briefs to help educate the courts on the limitations of forensic techniques.
In 2017, he also offered his pro bono services as an expert witness in a two-day mock trial, State of Texas v. Lee Harvey Oswald, co-sponsored by the South Texas College of Law Houston and Citizens Against Political Assassinations (CAPA).
“Cliff was a leading applied statistician of his generation,” said Texas A&M statistician and fellow distinguished professor Valen E. Johnson, dean of the College of Science and former head of Texas A&M Statistics from 2014 to 2018. “Aside from his well-known work in chemometrics, he was one of the nation’s leading forensic statisticians and had a huge impact in reforming evidentiary standards in criminal prosecutions. For example, he was instrumental in excluding bullet lead and bite mark analyses. As a consequence of his work, a number of convictions based on misleading statistical claims were overturned. He also served as the official statistician of the Texas Holocaust and Genocide Commission and was the statistics advisor to the Texas Forensic Science Commission and Houston Forensic Science Center. Not only was he an outstanding statistician, but he was also an outstanding citizen.”
One of Spiegelman’s lifelong passions was using statistics to achieve justice for everyday citizens. For many years, he worked with judges and attorneys to broaden their understanding of statistics and the critical effect it often has on case outcomes and broader issues at hand. At the time of his death, he was working with colleagues and U.S. legislators to introduce potential bipartisan legislation that would enter existing forensic evidence collected at crime scenes during the civil rights era into forensic databases. He strongly believed such a watershed move would help pave the way for countless decades-long cold cases potentially to be solved.
“Cliff Spiegelman may have been unique among all the scientists I knew in my 25 years as a department head and dean,” said Texas A&M statistician and Dean Emeritus of Science H. Joseph Newton, former head of Texas A&M Statistics from 1990 to 1997 and former dean of science from 2002 to 2015. “He made fundamental contributions to his field of statistics, but his desire to communicate and apply his knowledge and experience were extraordinary. He helped found the field of applying statistics to chemistry problems, he helped make areas of forensics more meaningful from the view of what the data could really say, he worked with people in Holocaust studies, and he worked in many other areas. His passion for these things was legendary. I was fortunate enough to have many talks with him — sometimes being told I had made a mistake — and always came away with an even greater respect for the type of people I had the honor to work with. We will all miss him and his work very much.”
Spiegelman was a fellow of the American Statistical Association, the Institute of Mathematical Statistics and the American Association for the Advancement of Science as well as an elected member of the International Statistical Institute. A two-time recipient of the ASA Statistics in Chemistry Award for best paper, he also received the 2007 Jerome Sacks Award for Outstanding Cross-Disciplinary Research recognizing innovation in statistical science and the San Antonio Chapter of the ASA’s 2016 Don Owen Award for excellence in research, contributions to editorial activities and service to the statistical community. Most recently, he was honored with the Texas A&M chapter of Sigma Xi’s 2019 Outstanding Science Communicator Award.
“Cliff was a great colleague and a truly outstanding statistician,” said Texas A&M statistician Jeffrey D. Hart. “I don’t think I’ve ever known anyone as dedicated to his/her profession than was Cliff. He will be sorely missed.”
Spiegelman is survived by his wife Kathy and their two daughters, Lindsey and Abigail, and his daughter Rachel from a previous marriage.
In lieu of flowers or other offerings, memorials may be made to the Aggieland Humane Society, the Innocence Project or the Bryan Animal Center. Memories and tributes also may be shared online via Hillier Funeral Home’s website.