Brett A. Lovejoy, Ph.D.

Third parties have purchased many of the patents written by Brett, and others have been successfully enforced through litigation, or used as a basis for successful corporate fund raising.

Sample machine learning applications in the life sciences that Brett has worked on include application of support vector machines, neural networks, autoencoders, Markov chain models, tree-based algorithms, regression, and dimension reduction algorithms (e.g., principal component analysis, t-SNE).

Sample life science applications Brett has worked on include next generation DNA sequencing (including alignment, mapping, haplotyping and phasing), cancer classification, cancer detection, high throughput cell assays, and in silico high throughput screening (e.g., using molecular dynamics or convolutional neural networks, etc.) to name a few.

Prior to engaging in the practice of patent law in 1998, Brett worked as a researcher at UCLA, GlaxoSmithKline, and Roche, where he authored machine-learning software programs in various programming languages as part of his research. This work led to two first author Science publications on unrelated research: a Science article describing the X-ray crystal structure of an inhibitor bound to the active site of collagenase, and a Science report describing the X-ray crystal structure of a synthetic designer protein.