This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Insitro, Inc.. Active years: 2025.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025
Title: Peter Franklin Palmedo, Jr: Innovator in Microscopy Image Analysis
Introduction
Peter Franklin Palmedo, Jr. is a notable inventor based in San Francisco, CA. He has made significant contributions to the field of microscopy image analysis, particularly in the context of disease modeling. His innovative work has the potential to enhance the understanding and treatment of various diseases through advanced machine learning techniques.
Latest Patents
Palmedo holds a patent for "Microscopy image analyses for disease modeling." This patent encompasses systems and non-transitory computer-readable media designed for analyzing microscopy images. The technology aims to develop machine learning models that can effectively distinguish between healthy and diseased samples based on microscopy images captured from cells exhibiting different exposure response phenotypes (ERPs). This advancement in microscopy image analysis is crucial for improving disease modeling and diagnosis.
Career Highlights
Currently, Peter Franklin Palmedo, Jr. is associated with Insitro, Inc., a company focused on leveraging machine learning and data-driven approaches to transform drug discovery and development. His work at Insitro emphasizes the integration of advanced imaging techniques with machine learning to facilitate better healthcare solutions.
Collaborations
Palmedo collaborates with esteemed colleagues in the field, including Daphne Koller and Ajamete Kaykas. Their combined expertise contributes to the innovative research and development efforts at Insitro, Inc.
Conclusion
Peter Franklin Palmedo, Jr. is a pioneering inventor whose work in microscopy image analysis is paving the way for advancements in disease modeling. His contributions are vital for the future of healthcare and machine learning applications in medical research.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile