Gregory Urbanchuk Joins Grassi as Head of IP Services
New York, N.Y., September 22, 2023 – Grassi, a leading provider of advisory, tax and accounting services, has announced that Gregory J. Urbanchuk, MSc., CVA has joined the firm’s Forensic, Litigation and Valuation Services group as a consulting principal. In this role, he will lead the firm’s litigation support and valuation services for intellectual property matters.
Urbanchuk has more than 20 years of experience providing forensic accounting, dispute resolution, business valuations and intellectual property consulting services in the United States and Europe. He serves as an expert witness in complex commercial litigation in the areas of intellectual property, commercial damages and valuation. Urbanchuk has evaluated damages and testified in cases claiming patent, trademark and copyright infringement, the misappropriation of trade secrets, and breach of contract. He has qualified and testified as an expert witness in U.S. federal and state courts.
Urbanchuk also values public and privately held business and intellectual property in connection with mergers and acquisitions, financial reporting, taxation and estate planning.
Prior to joining Grassi, Urbanchuk was founder and managing director of Countermark Group, LLC, a boutique consulting firm specializing in intellectual property, economic damages and valuation advisory services.
Urbanchuk has a Master of Science by Research with Distinction in International Business degree and a Post Graduate Certificate in Economics from the University of London. He holds a Bachelor of Science in Accounting degree from Saint Joseph’s University and the Certified Valuation Analyst (CVA) designation awarded by the National Association of Certified Valuators and Analysts. He is a Dispute Resolution Arbitrator with the Financial Industry Regulatory Authority (FINRA).
Urbanchuk sits on the Board of Directors for the Demining Research Community, a non-profit organization that researches and develops innovative uses of remote sensing and machine learning to improve the efficiency and safety of landmine and unexploded ordinance detection.
