Research

Criminological theories explain crime and victimization through the experiences they were built on, and some populations were missed in that foundation. In this area, I examine how distinct cultural and social contexts shape strain, coping, and harm. The larger goal moves beyond explanation: understanding how these contexts should inform theory, measurement, and institutional practice, so that the people they describe are protected by and integrated into the systems built to serve them.

Emerging technologies create new forms of victimization faster than data and law can adapt. My work to date has examined stalking, cyberstalking, deepfake abuse, and other forms of online harm, showing that aggregate statistics conceal distinct patterns of victimization and coping. I am now extending this line in two directions: tracing how online harm translates into offline violence, discrimination, and public perceptions, and identifying the routes through which victims come to seek help. Because these harms cross borders by design, my work in this area is built on international and interdisciplinary collaboration.

Documenting victimization showed me a second problem: many victims struggle to report harm or to be recognized when they do. In this area, I examine how law can protect victims and, through that protection, enhance public safety. My work follows legal responses across their life course: how statutes are written and interpreted, how courts sentence, and how governments respond when new forms of abuse outgrow existing law. A growing strand turns to statutory language itself, because protection often hinges on how the same ambiguous terms are read by the public, by legal practitioners, and increasingly by AI systems. I am also extending this work comparatively, asking what jurisdictions can learn from one another as harm increasingly crosses borders. The aim is law that victims can actually reach: legible statutes, consistent enforcement, and institutions that respond before harm escalates.

Artificial intelligence is transforming how the justice system documents, predicts, and interprets. Rather than replacing traditional criminology, I pair established theories and methods with AI and machine learning to test where each adds value and where each reaches its limits, across policing, risk prediction, and legal interpretation. This work treats AI as both a research tool and a research subject to enhance accuracy, fairness and public safety. The goal is integration with safeguards proportionate to what is at stake.