Company Filing History:
Years Active: 2022-2023
Title: Innovations by Aaron Tietz in Machine Learning and Digital Threat Mitigation
Introduction
Aaron Tietz is an accomplished inventor based in San Francisco, CA. He has made significant contributions to the field of machine learning and digital threat mitigation. With a total of 2 patents, Tietz is recognized for his innovative approaches to optimizing automated decisioning workflows.
Latest Patents
Aaron Tietz's latest patents focus on systems and methods for enhancing machine learning-informed automated decisioning workflows. One of his notable patents describes a system and method for adapting an errant automated decisioning workflow. This includes reconfiguring digital abuse or digital fraud logic parameters in response to identifying anomalous shifts in efficacy metrics. The automated decisioning workflow comprises distinct routes that evaluate digital threats associated with target digital events. The system computes decisions based on the probability of digital fraud and simulates performance in a reconfigured state using historical digital event data. This innovative approach promotes an in-production state for the automated decisioning workflow, ensuring enhanced efficacy in digital threat evaluations.
Career Highlights
Aaron Tietz is currently employed at Sift Science, Inc., where he continues to develop cutting-edge solutions in the realm of digital security. His work focuses on leveraging machine learning to improve automated decision-making processes. Tietz's expertise in this area has positioned him as a key player in the fight against digital fraud.
Collaborations
Aaron collaborates with talented individuals such as Phani Srikar Ganti and Eduard Chumak. Their combined efforts contribute to the innovative projects at Sift Science, Inc., enhancing the company's capabilities in digital threat mitigation.
Conclusion
Aaron Tietz's contributions to machine learning and digital threat mitigation exemplify the impact of innovation in technology. His patents and work at Sift Science, Inc. highlight the importance of adapting automated decisioning workflows to combat digital fraud effectively.