Ahmed Imteaj, an assistant professor in the School of Computing at Southern Illinois University Carbondale, has been awarded a prestigious $167,500 grant from the National Science Foundation’s Computer and Information Science and Engineering Initiation Initiative (CRII). This initiative aims to provide crucial resources for early-career researchers like Imteaj, who is dedicated to advancing the field of AI-driven crime analytics. His research focuses on developing a federated learning framework tailored specifically for enhancing crime analytics across interconnected networks of law enforcement agencies.
Imteaj’s innovative approach utilizes federated learning, also known as collaborative learning, to address critical challenges in AI crime analytics. Unlike traditional methods that involve transferring sensitive data, federated learning allows multiple agencies to collaborate on model training without compromising individual data privacy. This method not only ensures the security of sensitive information but also promotes efficient teamwork and timely decision-making among law enforcement entities.
The framework proposed by Imteaj encompasses three phases. Initially, it prioritizes data labeling and model rebalancing to mitigate bias, ensuring fair outcomes across diverse datasets and communities. By integrating equitable data from various sources, Imteaj aims to prevent algorithms from perpetuating historical prejudices that could lead to unfair targeting of specific neighborhoods or demographics.
In the subsequent phases, Imteaj’s research focuses on combining data from multiple interconnected networks to enhance the depth and accuracy of AI-driven decision-making tools for law enforcement. This includes strategies to optimize computational efficiency while safeguarding against potential security threats and unauthorized access. By bolstering the security of model training processes, Imteaj’s work not only strengthens the reliability of AI crime analytics but also safeguards sensitive crime-related data from potential breaches.
Beyond his current NSF grant, Imteaj’s commitment to advancing AI applications in law enforcement is evident through his previous collaborations and grants. His efforts underscore the growing importance of integrating cutting-edge technologies with criminological insights to develop state-of-the-art training modules and educational programs. Through these initiatives, Imteaj aims to equip law enforcement professionals with advanced tools for proactive crime prevention and informed decision-making in an increasingly AI-driven landscape.
