A scientist turned patent agent
Daniel Thomas has handled patents in almost every area of intellectual property. As a patent agent at Patterson + Sheridan, Daniel focuses on patent preparation and prosecution, litigation and dispute resolution, and mergers and acquisitions. They also have experience in litigation analysis and conducting IP portfolio reviews.
Daniel’s technical focus areas include artificial intelligence and machine learning, biotechnology and pharmaceuticals, chemical applications, complex software and information technology, medical devices and procedures, nanotechnology and optics. Passionate about technology and pursuing the cutting edge, they particularly excel in information technology, cloud architecture and software patent development. They also enjoy using their chemistry and physics background when advising clients on life science, oil and gas, and chemical matters.
Prior to joining Patterson + Sheridan, Daniel developed and supported litigation for utility patents pertaining to life sciences, artificial intelligence and medical devices. They also leverage their vast knowledge of the oil and gas industry when working with clients, having previously worked as an asset manager and a global advisor for two energy services companies.
Knowledge as expansive as the universe
A trained physicist, Daniel often jokes that they “understand the universe and everything in it” when it comes to IP cases. They are a self-motivated learner who quickly picks up on new technologies and enjoys the challenge of distilling complex inventions into strong patent applications. Daniel prides themself on their attention to detail and consistent work quality, traits valued by their clients and colleagues alike.
Daniel holds a Bachelor of Science in both Physics and Chemistry with a Mathematics minor from the University of Texas at Arlington. While there, they researched magnetic materials as part of the theoretical condensed matter physics group. Daniel also conducted NASA-funded research on space plasmas and wrote computational models to calculate space weather predictions.
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