Mehdi Poursoltani is a patent attorney at UTULAW PC, where he focuses on prosecuting patent applications across a wide range of technology sectors. Drawing on his experience in both patent prosecution and intellectual property litigation, Mr. Poursoltani also represents clients in patent, trademark, and trade dress disputes before federal courts in California and across the United States.
Before entering private practice, Mr. Poursoltani served as a patent examiner at the United States Patent and Trademark Office (USPTO), where he worked within the biomedical engineering art group. His experience at the USPTO has given him valuable insight into the patent examination process, which enhances his ability to navigate complex patent applications and effectively advocate for clients.
In addition to his legal career, Mr. Poursoltani spent over a decade working in the engineering field. His technical background includes roles as an R&D manager and senior full-stack engineer, where he gained hands-on experience with a wide range of technologies. These include vehicle communication protocols, digital signal processing, biological signal processing, artificial intelligence, machine learning, embedded systems, circuit design, and more. This extensive engineering experience allows him to better understand the technical aspects of patent law, providing clients with informed and strategic legal counsel.
Mr. Poursoltani combines his legal expertise with a strong technical foundation to offer comprehensive services in patent prosecution, litigation, and portfolio management.
Education
- University of San Diego School of Law, San Diego, CA
- Juris Doctor, Concentration in Intellectual Property & Technology Law, 2019
- Master of Science, Biomedical/Bioelectrical Engineering, 2006
- Bachelor of Arts, Biomedical Engineering, 2003
Admissions
- United States Patent & Trademark Office (USPTO)
- California State Bar
- United States District Court for the Central District of California
Publications
- Mehdi Poursoltani, “Disclosing AI inventions.” Tex. Intell. Prop. LJ 29 (2021): 41.
- Mehdi Poursoltani, et al., “Comparing higher order statistics of three ICA methods in wavelets-based single-channel fetal ECG extraction.” 2006 International Conference on Biomedical and Pharmaceutical Engineering. IEEE, 2006.