Heikichi Hayashi
← Adrasteia LabsAnd, behold, there are last which shall be first, and there are first which shall be last.
καὶ ἰδοὺ εἰσὶν ἔσχατοι οἳ ἔσονται πρῶτοι, καὶ εἰσὶν πρῶτοι οἳ ἔσονται ἔσχατοι.
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Founding Director and Department Coordinator · Adrasteia Labs; Research Assistant at The University of Hong Kong
I am Heikichi Hayashi, also known as Tingyi Lin. I started Adrasteia Labs with friends and colleagues, and over a few years it has grown into a distinguished student research group in China. My research sits where FinTech meets EconCS: algorithmic game theory and mechanism design for blockchain, cryptocurrency, and decentralized finance, backed by empirical work in economics.
I earned two bachelor's degrees, in economics and in business, at the Central University of Finance and Economics. Along the way I visited the University of Illinois Urbana-Champaign and worked as a research assistant at The University of Hong Kong.
My research has been presented or will be presented at the AEA, the Federal Reserve Board Summer Workshop on Money, Banking, Payments, and Finance (Gerzensee, Switzerland), the Bank of Italy, the Yale Tobin Center, Tsinghua PBCSF, the KOF Swiss Economic Institute at ETH Zurich, Cornell University, Google Research, Tsinghua SEM, the Peking University National School of Development, and HKU Business School, etc.
FinTech · Economics and computation · Algorithmic game theory · Mechanism design · Tokenomics · AMMs and MEV · Empirical economics
Research
Much of my research is about tokenomics. A token bundles cash-flow claims, governance rights, and access, and its supply and allocation decide who gets paid for growing the protocol. I want to know when these incentives actually work, when they tip into pure speculation, and why token markets stay full of lemons even though every contract sits in the open.
I also study decentralized exchange. On AMMs I work on liquidity provision and pricing; on MEV I treat transaction ordering as an auction, where randomized priority rules can soften wasteful races and block builders end up taxing informed trading.
On the empirical side, I use causal inference to trace how on-chain shocks reach conventional markets.
Accepted
Accepted at the ICML 2026 Workshop on AI for Math
Presented at: EC'26 Workshop on AI-Driven Research in EconCS (oral contributed talk); Can AI Do Theory? Workshop at STOC TheoryFest 2026 (Google Research); AEA Annual Meeting 2027 (scheduled)
AI for Social Science
Under Review
Kilts Center at Chicago Booth Marketing Data Center Paper
Presented at: Bank of Italy ToDeFi 2026*; CCER Summer Institute (* presented by coauthor)
Game Theory & Information Economics
Presented at: EC'26 Workshop on Online Learning and Economics; 12th Tsinghua University SEM Graduate Workshop (Outstanding Presentation Paper Award); EEA-ESEM*; ESIF Economics and AI+ML Meeting (Cornell University)*; KOF Swiss Economic Institute at ETH Zurich*; Peking University National School of Development (* presented by coauthor)
Game Theory & Mechanism Design
Working Paper
Working Paper
Presented at: Yale Pre-Doctoral Economics Conference (Yale Tobin Center); Asia Meeting of the Econometric Society, China (HKU Business School); FMA International European Conference*; 5th Annual Hong Kong Conference on FinTech and AI in Finance (City University of Hong Kong) (* presented by coauthor)
Empirical Economics
Working Paper
Presented at: Federal Reserve Board Summer Workshop on Money, Banking, Payments, and Finance (Gerzensee, Switzerland); China Financial Research Conference (Tsinghua PBCSF); Asia Meeting of the Econometric Society, China (HKU Business School); 38th Asian Finance Association Conference* (* presented by coauthor)
Game Theory & Mechanism Design
Projects
We are working hard to advance verifiable AI workflows for economic research.
We are also building large panel datasets across blockchain, DeFi, and other areas we find interesting. See projects →