Samuel Chung Hoffman

Title: Innovations of Samuel Chung Hoffman

Introduction

Samuel Chung Hoffman is a notable inventor based in New York, NY (US). He has made significant contributions to the field of molecular optimization and drug discovery. With a total of 3 patents, his work focuses on enhancing the efficiency of drug development processes.

Latest Patents

One of his latest patents is titled "Query-based molecule optimization and applications to functional molecule discovery." This invention introduces a query-based generic end-to-end molecular optimization (QMO) system framework. The QMO framework is designed to optimize molecules, particularly for accelerating drug discovery. It effectively decouples representation learning and guided search, applying to any plug-in encoder-decoder with continuous latent representations. The framework incorporates evaluations based on chemical modeling, analysis packages, and pre-trained machine-learned prediction models for efficient molecule optimization.

Another significant patent is "Combinatorial black box optimization with expert advice." This invention outlines a method, computer program product, and system for optimizing results in combinatorial optimization problems. The method involves processors receiving a black-box model and learning a multilinear polynomial surrogate model using an exponential weight update rule. This innovative approach optimizes the learned model and applies the black-box model to the optimized solution.

Career Highlights

Samuel Chung Hoffman is currently employed at International Business Machines Corporation (IBM). His work at IBM has allowed him to explore advanced methodologies in molecular optimization and drug discovery.

Collaborations

He has collaborated with notable coworkers, including Payel Das and Kalapriya Kannan, contributing to the advancement of innovative solutions in his field.

Conclusion

Samuel Chung Hoffman is a distinguished inventor whose work in molecular optimization and drug discovery has led to significant advancements in the field. His innovative patents reflect his commitment to improving drug development processes and enhancing the efficiency of molecular evaluations.