Mahdi Ghelichi

Title: Mahdi Ghelichi: Inventor in Explainable Machine Learning

Introduction

Mahdi Ghelichi is an inventor based in Toronto, Canada, associated with The Toronto-Dominion Bank. His patent work addresses the monitoring of explainability in machine-learning processes operating within distributed computing environments.

Latest Patents

Ghelichi is named on 1 patent: “Dynamically Monitoring Variations in Process Explainability Within a Distributed Computing Environment.” The disclosed system compares explainability data from different time intervals to measure changes in a machine-learning process. If the measured variation meets specified exception criteria, the system can gather additional measurements and modify a process parameter or the composition of the input dataset.

Career Highlights

Ghelichi’s listed invention focuses on detecting changes in how machine-learning processes can be explained and enabling responsive adjustments. This work connects explainability monitoring with operational controls in distributed computing.

Collaborations

Ghelichi’s listed coworkers include Talieh Tabatabaei and Julie R. Melanson. The available information identifies his association with The Toronto-Dominion Bank but does not specify the coworkers’ roles in the patent.

Conclusion

Mahdi Ghelichi’s patent highlights an approach to monitoring machine-learning explainability over time and responding to significant changes in distributed computing environments.