Tj Bozada

Contributor   in
Emerging Technologies  

TJ Bozada, is the Chief Revenue Officer of ToxTrack, Inc -- a cheminformatics company. Founded in 2016, ToxTrack's team of computational scientists has a history of developing groundbreaking machine-learning applications. ToxTrack's biggest publication to date, Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility, was covered by Nature and Science. Since its inception, ToxTrack has been expanding its portfolio, offering new machine learning based solutions for the chemical industries. The latest, Chemchart Enterprise, combines machine learning techniques to offer a single solution for chemical data management.

As Chief Revenue Officer, Mr. Bozada manages all non-technical aspects of ToxTrack including higher level strategy, sales, and marketing activities. Mr. Bozada is also the Treasurer of the Atlantic Coast Chapter of the OpenTox Association, which seeks to promote openness and collaboration across the toxicological communities. Prior to ToxTrack, Mr. Bozada worked for a variety of machine learning startups. He received his dual Bachelors of Science degrees from The Johns Hopkins University in Biomedical Engineering and Applied Math & Statistics.

tags:   Big Data     Database     Machine Learning    

Disclaimer: All opinions, ideas, and thoughts expressed and posted by Contributors at platform are their own personal points of view, and do not represent neither Contributor's employers, nor

Posts by this author

Chemchart Enterprise: an Intelligent Platform for Chemical Data Management

Chemchart Enterprise: an Intelligent Platform for Chemical Data Management

Chemical data management is an important process to a number of industries, especially those engaged in manufacturing or research and development.  Unfortunately, chemical data is as unwieldy to manage as it is important.  This is for a variety of reasons, but the biggest contributing factor is the sheer amount of data available to the public and managed by an enterprise.  For decades, chemical data has been recorded in paper, and then excel sheets, and now databases.  While efforts have been made to homogenize, or at least centralize this data, there is not one single solution for indexing and searching the wide variety of data types, and sources, managed by an individual enterprise.  Chemchart Enterprise changes this paradigm by combining the flexibility of big data with the precision of machine learning, providing a single solution for managing the entire organization chemical space.