Patrick Colangelo is an investor and entrepreneur with experience in private equity, capital markets, and entrepreneurship organizations. He is the co-founder of the Nesa Protocol, a Layer-1 blockchain network focused on decentralized AI execution. His career has included founding an investment firm and leadership roles in student-led investment and entrepreneurship initiatives at Harvard College. ^[1]

Career

Colangelo founded Black Diamond Capital Investors, LLC in April 2012 and has served as the firm's Founder and Chairman. The firm focuses on investment activities across areas including private equity, growth equity, mezzanine capital, and distressed investments. From 2012 to 2014, Colangelo served as President of the Harvard College Private Equity Group, where he was involved in leveraged buyouts, growth equity, mezzanine financing, and distressed investment strategies. During the same period, he served as President of the Harvard College Entrepreneurship Forum from 2011 to 2014, leading one of Harvard College’s entrepreneurship-focused student organizations. ^[2]

Panels

Bringing FHE to AI

At FHECon during TOKEN2049 Singapore in October 2024, Colangelo moderated a panel exploring the role of Fully Homomorphic Encryption (FHE) in the development of decentralized AI systems alongside Brendan Playford of Masa, Dr. Jennifer Dodgson of KIP Protocol, Allen Chak of Game Plus, and Liam Ren of Morphic. The discussion focused on how FHE and other privacy-preserving technologies could enable secure AI applications by allowing computation on encrypted data without exposing sensitive information. Playford discussed Masa’s decentralized data network and its approach to making large datasets accessible for machine learning applications, while Dodgson outlined KIP Protocol’s focus on Web3 infrastructure for AI development, including mechanisms to deploy and monetize AI assets while maintaining privacy. Chak highlighted opportunities in gaming, including leveraging decentralized data and AI-generated content to create more interactive experiences, while Ren discussed the technical challenges of implementing FHE alongside cryptographic approaches such as zero-knowledge proofs and trusted execution environments. The panel also examined barriers to wider adoption, including computational costs, privacy concerns, and the need for greater education around FHE, with participants noting that continued research and infrastructure development would be necessary for privacy-preserving technologies to become more practical for decentralized AI applications. ^[3]