Sui New Round of Academic Research Awards Announced: Top Global Universities Participate, 17 Projects Awarded $420,000 in Funding

Recently, the Sui Foundation announced the winners of the new round of academic research awards. This program aims to fund research projects that promote the development of Web3, particularly in areas such as expanding technological boundaries in blockchain networks, smart contract programming, and products built on Sui.

A total of 17 research proposals from internationally renowned universities have received funding in this round, with a total amount of 425,000 USD. The participating universities include the Korea Advanced Institute of Science and Technology, University College London, École Polytechnique Fédérale de Lausanne, and National University of Singapore, among others.

The following is a brief introduction to some of the award-winning projects:

1. Research on Diversity of DAO Voting Groups (Cornell University) The project aims to establish metrics for measuring the degree of decentralization of the decentralized autonomous organization (DAO) and to explore practical methods for enhancing decentralization within the organization.

2. Adaptive Secure Asynchronous DAG Protocol Consensus (University College London) Develop an asynchronous Directed Acyclic Graph ( DAG ) protocol to enhance attack resistance and adapt to the constantly changing adversarial environment.

3. Sui Smart Contract Audit Based on Large Language Models (University College London) Improve the auditing process of Move smart contracts using large language models like GPT-4, and extend it to the security assessment of Sui smart contracts.

4. Research in Consensus Protocols (University of Bern) By investigating the current consensus field, new insights are provided for cryptographic consensus protocols, aiding in a better understanding of existing algorithms.

5. High Confidence Verification Framework for Decentralized Oracle Protocols (Carnegie Mellon University) Create a framework to rigorously analyze and verify blockchain oracles through formal methods, ensuring the accuracy and fairness of external data in smart contracts.

6. Blockchain Scalability Bottleneck Identification (ETH Zurich) Identify bottlenecks arising from smart contract design flaws to enhance the parallelization potential of blockchain applications.

7. Bullshark Protocol Mechanized Verification (National University of Singapore) Use modern computer-aided verification tools to formally verify the attributes of Bullshark, advancing the research on DAG-based consensus protocols.

8. Blockchain Benchmarking Standards Framework (Lehigh University) Create a standardized benchmark format for fairly comparing the performance of L1 blockchains and L2 scaling solutions.

9. Build a scalable and decentralized shared sequencing layer (Korea Advanced Institute of Science and Technology) Explore using Bullshark/Mysticeti as a shared sequencer algorithm to enable multiple Rollups to use Sui as the sequencing layer.

10. Local Fee Market Optimization Congestion Pricing (New York University) Study the local fee market to optimize the congestion pricing mechanism of the blockchain network for optimal resource allocation.

11. Sharded Automated Market Maker (Technion - Israel Institute of Technology) Develop the concept of sharding contracts, utilizing multiple contracts to enhance concurrency while addressing challenges such as liquidity fragmentation.

12. Private Disclosure in Competitive Mechanisms (Roma Tor Vergata University) Explore new methods for designing market mechanisms and study the impact of private information disclosure on market outcomes.

13. Generating Sui Smart Contracts Based on Large Language Models (Carnegie Mellon University) Improve the capabilities of large language models in generating smart contracts in Move language through fine-tuning.

14. Move Language Conversion Comparison Framework (University of Nicosia) Complete a comprehensive comparative analysis between Solidity and Move to facilitate the transition of developers to Move development.

15. DeFi Optimization: Deep Learning Methods (École Polytechnique Fédérale de Lausanne) Develop hybrid deep learning models to optimize liquidity and dynamic fees in the Sui DeFi protocol.

16. Assessment of SUI Volatility Prediction Ability (Open University of Cyprus) Study the effectiveness of the SPEC algorithm in predicting the volatility of Sui assets.

17. Low Memory Post-Quantum Transparent zkSNARKs (University of Pennsylvania) Develop scalable zkSNARKs to address issues such as prover time complexity, space complexity, and SRS size.

These research projects cover multiple cutting-edge areas of blockchain technology, from consensus mechanisms to smart contract security, from DeFi optimization to privacy protection. By supporting these academic studies, the Sui Foundation aims to promote innovation and development in blockchain technology, laying a solid foundation for the future of the Web3 ecosystem.