Quantum Economics AI Lab
Research and incubation at the intersection of economics, artificial intelligence, quantum-inspired methods, and deep technology.
A Dataset of Early Blockchain-Registered AI Agents on Ethereum
As autonomous AI agents begin to hold wallets and transact on public blockchains, their earliest on-chain footprints form a unique record of machine economic behaviour. This paper assembles and documents a curated dataset of the first AI agents registered on Ethereum, providing a foundation for empirical research on the emerging agentic economy.
Liu, Y. · Nature: Scientific Data · forthcoming
Hover over a card to expand it.
Empirical Analysis of EIP-1559: Transaction Fees, Waiting Times, and Consensus Security
Examines how Ethereum’s EIP-1559 fee-market redesign changed transaction pricing, waiting times, and miner incentives. Finds the new base-fee mechanism improves fee predictability without weakening consensus security.
Liu, Y., Lu, Y., Nayak, K., Zhang, F., Zhang, L., & Zhao, Y. (2022)
Proc. 2022 ACM SIGSAC Conf. on Computer and Communications Security
DOI: 10.1145/3548606.3559341 ↗Deciphering Bitcoin Blockchain Data by Cohort Analysis
Applies cohort-analysis methods from population science to Bitcoin’s UTXO ledger. Produces reusable indicators of transaction age and lifespan that support future economic research on Bitcoin.
Liu, Y., Zhang, L., & Zhao, Y. (2022)
Nature: Scientific Data, 9(1), 136
DOI: 10.1038/s41597-022-01254-0 ↗Cryptocurrency Valuation: An Explainable AI Approach
Introduces the Price-to-Utility ratio, a blockchain-native fundamental valuation measure for Bitcoin. Shows it predicts long-run returns better than existing on-chain metrics and powers an explainable trading strategy.
Liu, Y., & Zhang, L. (2023)
Intelligent Computing, Proc. 2023 Computing Conference, Springer
DOI: 10.1007/978-3-031-37717-4_51 ↗SoK: Blockchain Decentralization
Surveys and unifies existing measures of blockchain decentralization across consensus, network, governance, wealth, and transaction dimensions. Proposes a new entropy-based index to quantify transaction-level decentralization.
Zhang, L., Ma, X., & Liu, Y. (2022)
Working Paper, arXiv:2205.04256
arXiv: 2205.04256 ↗The Economics of Blockchain Governance: Evaluate Liquid Democracy on the Internet Computer
Models the Internet Computer’s liquid-democracy governance system as a cooperation game among token-holders. Simulations show the staking reward multiplier is key to aligning short-term incentives with a DAO’s long-term growth.
Liu, Y., & Zhang, L. (2024)
Proc. IEEE 24th Int. Conf. on Software Quality, Reliability and Security Companion (QRS-C)
DOI: 10.1109/QRS-C63300.2024.00038 ↗Blockchain Network Analysis: A Comparative Study of Decentralized Banks
Compares the transaction networks of four leading DeFi lending protocols using core-periphery analysis. Finds meaningful differences in structural decentralization across MakerDAO, Compound, Aave, and Liquity.
Zhang, Y., Chen, Z., Sun, Y., Liu, Y., & Zhang, L. (2023)
Intelligent Computing, Proc. 2023 Computing Conference, Springer
DOI: 10.1007/978-3-031-37717-4_67 ↗Bitcoin Gold, Litecoin Silver: An Introduction to Cryptocurrency’s Valuation and Trading Strategy
Tests the popular analogy likening Bitcoin to gold and Litecoin to silver using on-chain lifespan and utility metrics. Builds a Price-to-Utility trading strategy that outperforms simple buy-and-hold benchmarks.
Yu, H., Sun, Y., Liu, Y., & Zhang, L. (2024)
Future of Information and Communication Conference, Springer
DOI: 10.1007/978-3-031-54053-0_39 ↗A Dataset of Early Blockchain-Registered AI Agents on Ethereum
Builds a reproducible dataset of the first AI agents registered under the ERC-8004 standard on Ethereum, combining on-chain identity, reputation, and feedback records. Supports empirical research on agent trust and the emerging agentic economy.
Liu, Y. (2026)
Working Paper, arXiv:2604.22652
arXiv: 2604.22652 ↗EconAgentic in DePIN Markets: An LLM Approach to the Sharing Economy of Decentralized Physical Infrastructure
Introduces an LLM-agent framework simulating stakeholder behavior in token-based DePIN markets. Compares AI-driven and heuristic decision-making across efficiency, inclusion, and stability outcomes.
Liu, Y., & Schweitzer, M. (2025)
Working Paper, arXiv:2508.21368
arXiv: 2508.21368 ↗Dr. Yulin Liu
Dual academic background in physics and economics, with a Master's in Quantum Physics and a Ph.D. in Macroeconomics from ETH Zurich, followed by academic appointments and visiting positions at ETH Zurich, HUST, DKU, NYU Shanghai etc. His research has been published in leading journals across economics, computer science, and the Nature Portfolio.
Industry roles include Senior Economist at the DFINITY Foundation, Senior Economic Advisor at Chainlink, Visiting Economist at the Bank of Finland, and Chief Economist at Liquity — mechanisms of his design have secured over USD 10 billion in live on-chain systems. He currently serves on the board of the Swiss DEF Foundation and as topic editor for several academic journals.
We work with students in economic modeling, AI, and financial systems across several formats:
- 01Research internships for undergraduates
- 02Master’s dissertation supervision and research collaboration
- 03PhD-level research projects and incubation opportunities
We primarily work with Zurich-based students, alongside a limited global cohort. Outstanding students may continue as research fellows.
We also support external PhD researchers working on related topics.
Supporting founders from the Zurich research ecosystem
We are building long-term relationships with professors and research groups working on semiconductors, AI, and embodied intelligence across ETH Zurich, UZH, and neighbouring institutions — to identify and support students and researchers who want to spin their work into a company.
Founder Mentorship
Hands-on guidance from research to venture — positioning, strategy, early execution.
Funding Opportunities
Direct investment from our own capital, complemented by access to our network of venture capital firms, strategic investors, and grant programs across deep tech.
From an early research idea to a growing startup, we help incubate and scale your venture. Get in touch!