10/21 - Closing Plenary - Year in Review

Year in Review

Speakers

• Pytel, Melissa

  Entrada Therapeutics | Head of Intellectual Property

  Melissa Pytel is an attorney specializing in Intellectual Property with over 25 years of experience, both as in-house and outside counsel. With a focus on biotechnology, she offers strategic counsel on a wide range of IP matters, including patents, trademarks, trade secrets, licensing, and due diligence. Melissa's collaborative approach, working closely with researchers, scientists, and executives, enables her to develop comprehensive IP strategies that align with business objectives. Throughout her career, Melissa has had the privilege of working alongside exceptionally talented individuals, an experience that has been both enriching and rewarding.
• Mandel, Richard S.

  Cowan, Liebowitz & Latman P.C> | Shareholder

  Richard S. Mandel is a shareholder with Cowan, Liebowitz & Latman, P.C. in New York City. His practice focuses on intellectual property litigation, including copyright, trademark, unfair competition and Internet issues. Mr. Mandel earned his J.D. in 1985 from New York University School of Law, where he served as an editor on the Law Review, and his BA, summa cum laude, in 1982 from NYU College of Arts and Science, where he was Phi Beta Kappa. He is a member of the American Arbitration Association commercial panel of arbitrators and the Southern District of New York panel of court appointed mediators.
• Crouch, Dennis

  University of Missouri School of Law | Law Professor

  Dennis Crouch is a law professor at the University of Missouri School of Law, specializing in intellectual property and technology law. He is well known to the IP community as the founder and author of the popular site, Patently-O. Although a mechanical and aerospace engineer by training, Crouch has been involved with AI and software for decades. His Princeton University undergraduate thesis offered a novel model for neural network design that he termed fractal neural networks and offered an early example of using the massively parallel potential of the internet to facilitate machine learning.