Computational Forensics and Investigative Intellience


Units: 12

Description: This course covers the use of computational methods in crime investigation (forensics) and prevention (intelligence). In almost all areas of forensics and intelligence, computational methods continue to aid, and sometimes entirely replace, human expertise in tracking crime. This is desirable since automation can address the problems associated with scale and global crime linkage through diverse data computational tools can potentially overcome and surpass human capabilities for crime investigation. This course is of a cross-disciplinary nature. It amalgamates knowledge from criminology, forensic sciences, computer science, statistics, signal processing, machine learning, AI, psychology, medicine and many other fields. Students from all departments and schools are welcome to take this course. Instruction: This is an instruction-based course. There will be 26 lectures, two per week, each of 80 minutes. Prerequisites: • Prerequisites for CS students – CMU CS 15-112 (Fundamentals of programming) or Equivalent – CMU CS 21-241 (Matrix Algebra) or Equivalent – CMU CS 36-217 (Probability and Random Processes) or Equivalent • Prerequisites may be waived for some students at instructors discretion

Learning Outcomes: The course aims to: • Build awareness of global crime, global intelligence, and global investigative and law-enforcement practices. • Expose the students to pre-emptive intelligence methodologies used in a-priori crime detection and prevention • Show how different kinds of evidence are analyzed , emphasizing the role of computational methods of deduction – Show how these methods can be leveraged to address investigative challenges in multiple branches of forensics – Train students to imbibe the scientific methodology required to create new computational tools for forensic deduction from different kinds of evidence. • Teach students how to leverage large volumes of data from diverse sources, for the analysis and interpretation of evidence. The focus will be on pattern discovery and information linkage. • Apprise students of – Legal requirements that must be fulfilled for forensic evidence to be acceptable in courts of law across the world. – Requirements for engaging in legally actionable intelligence practices.