Shubham Sharma

Title: Shubham Sharma: Innovator in Explainability and Fairness in AI

Introduction

Shubham Sharma is an accomplished inventor based in Austin, TX. He has made significant contributions to the field of artificial intelligence, particularly in the area of explainability and fairness of black-box trained classifiers. His innovative approach aims to enhance the understanding and reliability of AI systems.

Latest Patents

Shubham Sharma holds a patent for a groundbreaking invention titled "Framework for explainability with recourse of black-box trained classifiers and assessment of fairness and robustness of black-box trained classifiers." This patent describes a method, system, and computer-readable storage medium for performing a counterfactual generation operation. The operation involves receiving a subject data point, classifying it via a trained classifier, and identifying a counterfactual that results in a different outcome when provided to a model. This invention is crucial for improving the transparency and accountability of AI models.

Career Highlights

Shubham currently works at Tecnotree Technologies, Inc., where he applies his expertise in AI and machine learning. His work focuses on developing solutions that enhance the interpretability of complex models, making them more accessible to users and stakeholders. With a patent portfolio that includes 1 patent, he is recognized for his innovative contributions to the field.

Collaborations

Shubham collaborates with talented professionals in his field, including Joydeep Ghosh and Jessica Henderson. These partnerships foster a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Shubham Sharma is a notable inventor whose work in AI explainability and fairness is paving the way for more transparent and reliable artificial intelligence systems. His contributions are essential for the future of technology and its ethical application.