About
The Forensic Data Science Laboratory conducts research to develop methods for evaluation of forensic evidence that are based on relevant data, quantitative measurements, and statistical models; methods that:
- are transparent and reproducible;
- are intrinsically resistant to cognitive bias;
- use the logically correct framework for interpretation of evidence (the likelihood-ratio framework); and
- are empirically validated under casework conditions.
In order to develop methods that provide solutions for real forensic-evaluation problems, solutions that have a high probability of actually being adopted in casework, members of the Laboratory conduct research in collaboration with researchers and practitioners who have expertise in particular branches of forensic science.
Members of the Laboratory also conduct research on calibration and validation of forensic-evaluation systems, and on communication of forensic science to courts, research whose results are applicable across many branches of forensic science.
In addition to research, members of the Laboratory provide training in forensic inference and statistics to forensic practitioners and to lawyers, and contribute to the development of standards and guidelines for forensic science.
For more information about the lab's activities, please visit the Forensic Data Science Laboratory website.