Mahopac, NY, United States of America

Young-Suk Lee

USPTO Granted Patents = 1 

Average Co-Inventor Count = 8.0

ph-index = 1


Company Filing History:


Years Active: 2025

where 'Filed Patents' based on already Granted Patents

1 patent (USPTO):

Title: Young-Suk Lee: Innovator in Graph Predictions

Introduction

Young-Suk Lee is an accomplished inventor based in Mahopac, NY (US). He has made significant contributions to the field of machine learning, particularly in the area of graph predictions. His innovative work has led to the development of a unique software solution that enhances the blending of graph predictions generated by various machine learning models.

Latest Patents

Young-Suk Lee holds 1 patent for his invention titled "Blending Graph Predictions." This software performs several key operations, including receiving a set of graph predictions corresponding to an input text. These predictions are generated by different machine learning models. The software blends these predictions to create multiple candidate blended graphs. Each graph's nodes and edges are assigned selection metric values, which are generated using a selection metric function that meets a minimum threshold. Ultimately, the software selects the candidate blended graph with the highest total combination of selection metric values as the output.

Career Highlights

Young-Suk Lee is currently employed at International Business Machines Corporation, commonly known as IBM. His role at IBM allows him to work on cutting-edge technologies and contribute to advancements in machine learning and artificial intelligence.

Collaborations

Throughout his career, Young-Suk Lee has collaborated with talented individuals, including Thanh Lam Hoang and Gabriele Picco. These collaborations have fostered a creative environment that encourages innovation and the sharing of ideas.

Conclusion

Young-Suk Lee's contributions to the field of graph predictions exemplify the impact of innovative thinking in technology. His work at IBM and his patented software demonstrate his commitment to advancing machine learning solutions.

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