Personal Experience

David A. Neal is an Associate of Beus Gilbert McGroder PLLC, a premier boutique law firm concentrating on High Stakes Litigation, Real Estate and Zoning Law, and Plaintiffs Catastrophic Injury & Wrongful Death. Mr. Neal is a member of the firm’s Commercial Litigation practice.

Mr. Neal previously worked as an associate at an intellectual property law firm, where he prepared and prosecuted patents in bioinformatics, artificial intelligence, machine learning, image processing, cloud networking, and fintech.  He also has experience performing invalidity searches, preparing invalidity claim charts, and drafting clearance opinions.

During law school, Mr. Neal worked as an intern for the Honorable Kathleen O’Malley at the U.S. Court of Appeals for the Federal Circuit and the Honorable Kent A. Jordan at the U.S. Court of Appeals for the Third Circuit.

Before law school, Mr. Neal worked as an engineer for almost a decade.  Some of his areas of focus include designing electronic packaging for RF components and participating in the testing of ordnance for solid rocket motors.  His master’s work was focused on error correction coding and his Ph.D. dissertation focused on the temperature-emissivity separation of hyperspectral images.  During his Ph.D. candidacy, he also worked on projects related to MIMO tracking systems and random number generators.

Admissions

Arizona

Virginia

Washington D.C.

Education

Rose-Hulman Institute of Technology – B.S., Mechanical and Electrical Engineering

Utah State University – M.S., Electrical Engineering

Utah State University – Ph.D., Electrical Engineering

Reuben Clark Law School – J.D.

Publications

Utilizing Correct Prior Probability Calculation to Improve Performance of Low Density Parity Check Codes in the Presence of Burst Noise, David A. Neal, Master’s Thesis, 2012.

Correlated Maximum Likelihood Temperature/Emissivity Separation of Hyperspectral Images, David Neal, Todd Moon, Jake Gunther, and Gus Williams, in 2015 49th Asilomar Conference on Signals Systems, and Computers, November 2015.

Performance of Maximum Likelihood Temperature/Emissivity Separation of Hyperspectral Images with Correlated Gaussian Downwelling Radiance, David Neal, Todd Moon, Jake Gunther, and Gus Williams, in 2016 50th Asilomar Conference on Signals, Systems, and Computers, November 2016

Maximum Likelihood Temperature/Emissivity Separation of Hyperspectral Images with Gaussian Distributed Downwelling Radiance, David A. Neal, Dissertation, 2017.

Community and Philanthropy

Mr. Neal served as a missionary for the Church of Jesus Christ of Latter-Day Saints in St. Petersburg Russia, where he learned to speak Russian.