Stanford's FIGGsolver Helps Investigators Solve Cold Cases Through Mathematical Genealogy

A mathematical algorithm developed at Stanford University is helping forensic genetic genealogists investigate long-unsolved crimes by identifying more efficient ways to navigate complex family trees. The system, called FIGGsolver, was highlighted in forensic news coverage on November 9, 2026, following a Stanford University report describing its application to actual criminal investigations.

Developed by Lawrence Wein, professor emeritus at Stanford Graduate School of Business, with researcher Malo Sommers, FIGGsolver uses probabilistic analysis and mathematical optimization to guide investigative decisions.

Forensic investigative genetic genealogy combines DNA profiles recovered from evidence with genealogical databases and historical records to identify possible relatives of an unknown individual.

Unlike conventional forensic DNA matching, which searches for matching profiles, genetic genealogy can use distant biological relationships to reconstruct family connections.

However, investigations become particularly challenging when available genetic matches are distant relatives or when family records are incomplete.

FIGGsolver addresses this problem by recommending which branches of a family tree investigators should examine next.

The algorithm uses stochastic dynamic programming to evaluate possible investigative actions under uncertainty. It helps genealogists decide whether to research a genetic match's ancestors, investigate descendants of potential common ancestors, or pursue another available lead.

The system does not independently identify suspects or replace genealogists. Researchers must still examine genealogical records, establish family relationships, and assess the relevance of potential leads.

One reported application involved a decades-old sexual assault investigation in Cleveland, Ohio.

Investigative genetic genealogist Barbara Rae-Venter and her team had struggled to identify the perpetrator despite extensive genealogical research.

After applying FIGGsolver's recommendations, investigators pursued a previously overlooked ancestral connection.

The resulting investigation identified a deceased individual whose involvement was subsequently confirmed by law enforcement using DNA from a close relative.

According to Stanford, the case was resolved in approximately 10 days after the algorithm was introduced.

The research team has since reported assisting with 14 additional cold cases.

Earlier mathematical research involving the DNA Doe Project also demonstrated that optimized genealogical strategies could substantially reduce investigative effort compared with conventional approaches in simulated case analyses.

However, those simulation results should not be interpreted as a guaranteed improvement in every real investigation.

FIGGsolver has limitations. Its mathematical framework does not directly incorporate geographical information, surnames, ethnicity, or certain complex patterns of shared ancestry.

Incomplete historical records and limited genetic matches can also prevent investigators from reaching a conclusion.

Importantly, identifying a genealogical lead does not establish criminal responsibility. Independent forensic confirmation and appropriate investigative procedures remain essential.

The developers are working to make FIGGsolver more widely available to forensic genetic genealogists.

The research illustrates how mathematical decision-support tools may reduce investigative workload while preserving the central role of human expertise in interpreting genetic relationships and confirming identities.