Research Partner
Hack VCCheck size: Not disclosed and not inferable. Peyman is listed as a Research Partner, so founders should treat him as a domain expert and technical thesis contributor unless Hack VC confirms participation in a specific investment decision.
Peyman treats confidentiality as market infrastructure rather than an abstract right. His research uses identity-based encryption and distributed decryption to prevent front-running with dramatically lower communication overhead, while later work combines encryption and auctions for decentralized intent pricing. He argues privacy wins when it improves execution, protects commercial information, enables compliance and creates economically valuable products without extra user friction.
Cryptography that changes economic outcomes—better prices, less leakage, fairer auctions or safer data use—while remaining fast, composable and accessible inside existing applications. His work favors rigorous protocols with measurable overhead reductions, incentive alignment and use cases where users or institutions will pay for confidentiality.
His writing rejects privacy as a slogan without economic value, systems that add onboarding cost or complexity, centralized RFQ or relay designs vulnerable to manipulation, transparency that leaks strategy before execution, and cryptography whose communication or latency overhead makes it impractical for real markets.
Approach as a technical research conversation, not a generic fundraise. Specify the leakage or fairness failure, adversary and trust model; compare MPC, IBE, FHE, TEE and ZK tradeoffs; quantify bandwidth, latency and execution impact; show developer integration; and identify the economic beneficiary who will adopt or pay for confidentiality.
Identify the money, risk or market quality lost through information leakage and make confidentiality improve that economic outcome rather than existing as a costly optional feature.
Compare MPC, IBE, FHE, TEE, threshold encryption and ZK systems across trust, latency, bandwidth, composability, verification and failure assumptions for the target workflow.
Define who sees an order, vote, intent or strategy before finalization, how that party can censor or exploit it, and the precise condition under which decryption becomes safe.
Confidentiality reaches adoption when it protects execution, commercial data, regulatory exposure or AI value in ways that measurably improve user welfare and business economics.
Identity-based encryption, MPC and leaderless sealed-bid auctions can provide competitive intent pricing while reducing front-running, censorship and centralized price-discovery risk.
Identity-based encryption can decrypt batches after transaction ordering with committee-sized rather than transaction-times-committee messaging, sharply reducing the overhead of front-running protection.
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Peyman Momeni is a Research Partner at Hack VC focused on decentralized and privacy-preserving AI and financial systems. He is the founder of Fairblock and previously worked across applied cryptography and AI research at the University of Waterloo, ZKM, Snapp, HKUST, and Sharif University.