Sui Academic Research Award New Round Results Announced: Top Universities Worldwide Participated, 17 Projects Received Over $420,000 in Funding

Recently, the Sui Foundation announced the winners of the latest round of academic research awards. The program aims to fund research that promotes the development of Web3, with a particular focus on breakthroughs in blockchain networks, smart contract programming, and technologies related to products built on Sui.

In the past two phases, a total of 17 proposals from internationally renowned universities have been approved, with a total funding amount of $425,000. Participating universities include the Korea Advanced Institute of Science and Technology, University College London, École Polytechnique Fédérale de Lausanne, and the National University of Singapore, among others.

Awarded Project Overview

Research on the Diversity of Decentralized Autonomous Organizations ( DAO )

Professor Ari Juels from Cornell University will explore the nature of decentralized organizations, establish metrics to measure the degree of decentralization of DAOs, and propose practical methods to enhance decentralization within organizations.

Adaptive Secure Asynchronous DAG Consensus Protocol

Dr. Philipp Jovanovic from University College London proposed the development of an asynchronous directed acyclic graph ( DAG ) protocol to enhance attack resistance and adapt to changing adversaries. The protocol aims to provide better security and adaptability while maintaining performance levels close to partially synchronous models.

Sui Smart Contract Audit Based on Large Language Models

Professor Arthur Gervais from University College London plans to improve the auditing process of Move smart contracts using large language models such as GPT-4-32k and Claude-v2-100k. The project will expand on previous research on Solidity contracts, focusing on the security assessment of Sui smart contracts.

Research in the Field of Consensus Protocols

Professor Christopher Cachin from the University of Bern will conduct a comprehensive investigation into the current consensus field, providing new insights for cryptographic consensus protocols, which will help to better understand existing algorithms and offer new ideas for designing distributed protocols.

decentralized oracle protocol verification framework

Dr. Giselle Reis from Carnegie Mellon University and Dr. Bruno Woltzenlogel Paleo from the Djed Alliance will create a framework to rigorously analyze and verify blockchain oracles through formal methods, ensuring the accuracy and fairness of external data in smart contracts.

Identifying blockchain scalability bottlenecks

Professor Roger Wattenhofer from ETH Zurich will study the bottlenecks arising from design flaws in smart contracts, aiming to enhance the parallelization potential of blockchain applications and explore the impact of transaction fee adjustments on parallelization.

Bullshark Protocol Mechanized Verification

Professor Ilya Sergey from the National University of Singapore will use modern computer-aided verification tools to formally verify the Bullshark protocol, advancing the understanding of DAG-based consensus protocols and providing the first mechanically verified model.

Blockchain Benchmarking Standard Framework

Professor Henry F. Korth from Lehigh University proposed the creation of a standardized format for blockchain benchmarks to fairly compare layer one blockchains and layer two scaling solutions, providing users and developers with transparent insights into chain performance.

Build a scalable and decentralized shared sorting layer

Professor Min Suk Kang of the Korea Advanced Institute of Science and Technology will explore the possibility of using Bullshark/Mysticeti as a shared sorter algorithm, studying the operational mechanisms of multiple Rollups that use Sui as a sorting layer.

Optimal Congestion Pricing for Local Fee Markets

Professor Abdoulaye Ndiaye from New York University will study the local fee market to optimize congestion pricing, establish an effective pricing mechanism that reflects the state of network congestion, and achieve optimal resource allocation.

Sharded Automated Market Maker ( SAMM )

Professor Ittay Eyal from the Technion - Israel Institute of Technology is developing the concept of sharded contracts, utilizing multiple contracts to enhance concurrency. This research aims to adjust the incentive mechanisms for liquidity providers and traders, maintaining multiple AMM shards to achieve fully parallelizable sharded AMMs.

Private Information Disclosure in Competitive Mechanisms

Professor Andrea Attar from the University of Roma Tor Vergata will explore new approaches to market mechanism design, examining the impact of designers privately disclosing information to agents on market outcomes and strategic interactions, providing insights into modern market dynamics and competition.

Use large language models to generate Sui smart contracts

Professors Ken Koedinger and Eason Chen from Carnegie Mellon University will fine-tune large language models using Move code and Sui-specific prompts to address the challenges of current models in generating Move language smart contracts.

COMET: Move language transition comparison framework

Professor George Giaglis from the University of Nicosia will conduct a comprehensive comparative analysis between Solidity and Move, promoting a deeper understanding of the functionalities and capabilities of Move, and developing a framework to help developers easily transition to Move development.

DeFi Optimization: Deep Learning Methods

Professors Rachid Guerraoui and Walid Sofiane from the École Polytechnique Fédérale de Lausanne will develop a hybrid deep learning model for optimal range prediction in the Sui DeFi protocol, combining enhanced recurrent neural networks and deep reinforcement learning, while integrating social media sentiment analysis.

Assessment of SUI Volatility Prediction Capability

Professor Stavros Degiannakis of the Open University of Cyprus will investigate the effectiveness of the SPEC algorithm in predicting the volatility of Sui assets, focusing primarily on SUI using high-frequency price data, and validating it across various blockchain assets.

low-memory post-quantum transparent zkSNARKs

Brett Falk and Dr. Pratyush Mishra from the University of Pennsylvania are dedicated to developing scalable zkSNARKs while addressing the three major obstacles of prover time complexity, space complexity, and SRS size, providing deployable scalable cryptographic proof solutions for various applications in blockchain technology.