The new winners of the Sui Academic Research Award have been announced: Top universities around the world actively participated, with 17 projects receiving $420,000 in funding.

The Sui Foundation recently announced the winners of the latest round of the Sui Academic Research Awards. This program aims to fund research that promotes the development of Web3, with a particular focus on blockchain networks, smart contract programming, and cutting-edge 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.

Highlights of Award-winning Projects

Research on Decentralized Autonomous Organizations

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

Asynchronous DAG Protocol Consensus

The team led by Philipp Jovanovic at University College London is dedicated to developing an asynchronous DAG protocol aimed at enhancing attack resistance and adapting to dynamic adversarial environments. This protocol will provide superior security and adaptability while maintaining high performance.

Large Language Model Assisted Smart Contract Auditing

The team led by Arthur Gervais from University College London will utilize large language models such as GPT-4-32k and Claude-v2-100k to enhance the auditing efficiency of Move smart contracts. They previously identified vulnerabilities in 52 Solidity DeFi smart contracts that led to nearly $1 billion in losses and now plan to expand their research into the Sui smart contract domain.

Research in Consensus Protocol Field

Professor Christopher Cachin from the University of Bern will conduct a comprehensive investigation into the current field of consensus, providing new insights into cryptographic consensus protocols, aiding in a deeper understanding of existing algorithms, and offering new ideas for designing distributed protocols.

Decentralized Oracle Verification Framework

Dr. Giselle Reis from Carnegie Mellon University and Bruno Woltzenlogel Paleo from the Djed Alliance will create a framework to rigorously analyze and verify blockchain oracles through formal methods. The project will utilize the Coq proof management system to develop a comprehensive library of definitions and proof strategies.

Scalability Bottleneck Identification

Professor Roger Wattenhofer's team at ETH Zurich will focus on identifying bottlenecks arising from design flaws in smart contracts to enhance the parallelization potential of blockchain applications. They will also 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 properties of Bullshark, advancing research on DAG-based consensus protocols. This will be the first mechanically verified DAG consensus protocol model in the field of distributed systems.

Blockchain Standardization Framework

Professor Henry F. Korth from Lehigh University aims to create a standardized benchmarking format for blockchain to fairly compare L1 blockchains and L2 scaling solutions, providing users and developers with transparent insights into chain performance.

Scalable Shared Sequence Layer Construction

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

Local Fee Market Optimization

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

Research on Automated Market Makers for Sharding

The team led by Professor Ittay Eyal at the Technion - Israel Institute of Technology is developing the concept of "sharded contracts" to enhance concurrency using multiple contracts. They will focus on how to adjust the incentive mechanisms for liquidity providers and traders to maintain multiple AMM shards, achieving fully parallelizable sharded AMMs.

The role of private disclosure in competitive mechanisms ###

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

Large Language Model Generates Sui Smart Contract

Ken Koedinger and Eason Chen from Carnegie Mellon University are committed to addressing the challenges of smart contract generation using the Move language. They plan to enhance the performance of large language models in Sui smart contract generation by collecting Move code examples, improving prompt engineering, and implementing fine-tuning.

Research on Move Language Transition Framework

Professor George Giaglis from the University of Nicosia will conduct a comprehensive comparative analysis between Solidity and Move, exploring the functionalities and capabilities of Move in depth, and building a framework to assist developers in transitioning smoothly to Move development.

DeFi optimization deep learning methods

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. The model combines enhanced recurrent neural networks, deep reinforcement learning, and social media sentiment analysis, aiming to improve the DeFi protocol's responsiveness to market changes.

SUI volatility prediction capability assessment

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

low-memory post-quantum transparent zkSNARKs

Brett Falk and Pratyush Mishra from the University of Pennsylvania will focus on developing scalable zkSNARKs while addressing the three major obstacles of prover time complexity, space complexity, and SRS size, providing deployment-ready scalable cryptographic proof solutions for various applications in blockchain technology.

These research projects cover multiple cutting-edge areas of blockchain technology, from consensus mechanisms to smart contract security, from DeFi optimization to privacy protection. Their results are expected to bring significant breakthroughs to the Sui ecosystem and the entire blockchain industry, promoting further development of Web3 technology.