Dr. Benjamin (Ben) Hoar is a patent agent in the Century City office of Wilson Sonsini Goodrich & Rosati, where he focuses patent work related to software, artificial intelligence, clean energy technology, and applications of artificial intelligence in the biotech and medical device domains.
Ben obtained his Ph.D. in chemistry from UCLA in 2023 for research into applications of machine learning in electrochemistry. His work spanned the electrochemical device and process optimization, computer vision, natural language processing, education, and clean tech fields.
Prior to UCLA, Ben gained experience in biosensing at the University of Miami. He has published in each of these fields while also having studied photocatalysis UT Austin.
Dr. Benjamin (Ben) Hoar is a patent agent in the Century City office of Wilson Sonsini Goodrich & Rosati, where he focuses patent work related to software, artificial intelligence, clean energy technology, and applications of artificial intelligence in the biotech and medical device domains.
Ben obtained his Ph.D. in chemistry from UCLA in 2023 for research into applications of machine learning in electrochemistry. His work spanned the electrochemical device and process optimization, computer vision, natural language processing, education, and clean tech fields.
Prior to UCLA, Ben gained experience in biosensing at the University of Miami. He has published in each of these fields while also having studied photocatalysis UT Austin.
- Ph.D., Chemistry, University of California, Los Angeles, 2023
- M.S., Chemistry, University of California, Los Angeles, 2020
- B.S., Chemistry, University of Miami, 2018
- U.S. Patent and Trademark Office
- Ph.D., Chemistry, University of California, Los Angeles, 2023
- M.S., Chemistry, University of California, Los Angeles, 2020
- B.S., Chemistry, University of Miami, 2018
- U.S. Patent and Trademark Office
Select Publications
- Co-author with R. Ramachandran, M. Levis-Fitzgerald, E.M. Sparck, K. Wu, and C. Liu, “Enhancing the Value of Large-Enrollment Course Evaluation Data Using Sentiment Analysis,” Journal of the Chemical Education, 2023
- Co-author with W. Zhang, S. Xu, R. Deeba, C. Costentin, Q. Gu, and C. Liu, “Electrochemical Mechanistic Analysis from Cyclic Voltammograms Based on Deep Learning,” ACS Measurement Science, Au, 2022
- Co-author with Y. Chen, J. Wang, and C. Liu, “Machine Learning-Based Inverse Design for Electrochemically Controlled Microscopic Gradients of O2 and H2O2,” PNAS, 2022
- Co-author with S. Lu, and C. Liu, “Machine-Learning-Enabled Exploration of Morphology Influence on Wire-Array Electrodes for Electrochemical Nitrogen Fixation,” The Journal of Physical Chemistry Letters, 2020
- Co-author with S.K. Karma, M. Micic, S. Li, S. Paudyal, E.M. Zahran, and R.M. Leblanc, “Conjugation of Carbon Dots with β-Galactosidase Enzyme: Surface Chemistry and Use in Biosensing,” Molecules, 2019
Select Publications
- Co-author with R. Ramachandran, M. Levis-Fitzgerald, E.M. Sparck, K. Wu, and C. Liu, “Enhancing the Value of Large-Enrollment Course Evaluation Data Using Sentiment Analysis,” Journal of the Chemical Education, 2023
- Co-author with W. Zhang, S. Xu, R. Deeba, C. Costentin, Q. Gu, and C. Liu, “Electrochemical Mechanistic Analysis from Cyclic Voltammograms Based on Deep Learning,” ACS Measurement Science, Au, 2022
- Co-author with Y. Chen, J. Wang, and C. Liu, “Machine Learning-Based Inverse Design for Electrochemically Controlled Microscopic Gradients of O2 and H2O2,” PNAS, 2022
- Co-author with S. Lu, and C. Liu, “Machine-Learning-Enabled Exploration of Morphology Influence on Wire-Array Electrodes for Electrochemical Nitrogen Fixation,” The Journal of Physical Chemistry Letters, 2020
- Co-author with S.K. Karma, M. Micic, S. Li, S. Paudyal, E.M. Zahran, and R.M. Leblanc, “Conjugation of Carbon Dots with β-Galactosidase Enzyme: Surface Chemistry and Use in Biosensing,” Molecules, 2019
Cytovale’s IntelliSep test is the first and only U.S. Food and Drug Administration (FDA)-cleared cellular host diagnostic indicated for use in hospital emergency departments, where over 80 percent of sepsis cases present. The test, which takes only approximately eight minutes, provides clinicians with a first-ever look into the biology that causes sepsis, enabling care teams to quickly and confidently identify the proper diagnosis and deliver appropriate, patient-centered care. Cytovale will use the proceeds from the financing to build upon its early clinical success and accelerate commercial expansion of IntelliSep to more hospital emergency departments and health systems nationwide.
The Wilson Sonsini team that advised Cytovale on IP matters related to the financing includes Matt Bresnahan, Maysam Pessian, Nicholas Tiee, and Ben Hoar.
For more information, please see Cytovale’s news release.
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