I worked on a research project, funded by Offchain Labs, that investigated the performance of Timeboost, Arbitrum’s new transaction ordering policy, and its impact on user behavior. A research paper detailing these findings is currently in preparation.
Orakle is an academic society of KAIST dedicated to studying blockchain and networking with local/global builders. I have been a member for many years and have conducted some research with my colleagues. Below are some of the records of my activities.
I worked as a research intern while investigating our competitors’ products and the demands of our main
customers, such as searchers and builders. In addition, with my supervisors, I designed 2 new auction
mechanisms: 1) for sequencing transactions in rollups that maximize profit while protecting retail users
from malicious tactics such as frontrunning and sandwich attacks, and 2) for enabling atomic execution of cross-chain bundles and fairly distributing the revenue across various L2s.
I designed and proposed the overall structure of an AMM-based prediction market, along with the incentive mechanisms that support it. Notable works include:
The adoption of a Dutch auction for proposing new market topics, enabling semi-permissioned market creation with guaranteed passive liquidity until expiration. This results in the rapid creation of markets related to the most viral issues at the time.
Enabling native support for multiple-outcome markets by separating AMMs for each outcome, along with optimal routing logic. This approach overcomes the limitations of approximating a multiple-outcome market using many binary markets and mitigates the guaranteed loss of liquidity providers (as LPs can choose specific outcomes to provide liquidity, if they have provided liquidity to the AMM for the correct outcome, then PnL is positive).
In addition, I contributed to the design of other incentive mechanisms, including tokenomics, and wrote blog articles explaining the protocol. See also: SynStation Whitepaper and SynStation Blog.
Fugazi is an AMM-based dark pool. Unlike many other dark pool implementations, Fugazi operates without oracles or centralized operators. All actions related to trading—such as pool creation, liquidity provision (LPing), and swaps—are entirely permissionless. While users may experience delays after submitting orders due to batching and high computational load, Fugazi’s user experience is nearly identical to that of other AMMs like Uniswap, Curve, and Balancer.
We introduced and elaborated on the additional features of FM-AMM, as outlined in [CF23]. We modeled the interaction between CEX-DEX arbitrageurs competing for arbitrage profits on the FM-AMM and derived the pure-strategy Nash equilibrium for this game. Furthermore, we calculated the asymptotic LVR of FM-AMM in theoretical scenarios and compared its performance to that of the Uniswap V2-style CPMM with fixed-rate fees through numerical simulations. Our findings showed that performance is significantly affected by factors such as price volatility, transaction costs, and liquidity pool size, with FM-AMM demonstrating lower losses to arbitrageurs under certain conditions.