Jiaying Wu | Sharding Blockchain | Best Researcher Award

Ms. Jiaying Wu | Sharding Blockchain | Best Researcher Award

Master’s Degree at Yunnan Normal University, China

Summary:

Ms. Jiaying Wu is a dedicated researcher currently pursuing a Master’s Degree in Computer Science at Yunnan Normal University, maintaining a GPA of 3.89/4.0. She holds a Bachelor’s Degree in Software Engineering from Hunan University of Humanities, Science and Technology, where she graduated with a GPA of 3.78/4.0. Her research focuses on blockchain scalability, sharding techniques, and cross-shard transaction security mechanisms. Ms. Wu has published several papers in renowned journals, contributed to key blockchain projects, and earned numerous academic and competition awards, showcasing her expertise and commitment to technological innovation.

Profile:

Education:

Ms. Jiaying Wu is currently pursuing a Master’s Degree in Computer Science at Yunnan Normal University, where she maintains an outstanding GPA of 3.89/4.0, having started her program in August 2022. Prior to this, she completed her Bachelor’s Degree in Software Engineering at Hunan University of Humanities, Science and Technology from September 2018 to June 2022, graduating with a GPA of 3.78/4.0. Her solid academic foundation is complemented by her focus on advanced topics such as blockchain scalability, sharding techniques, and cross-shard transaction security mechanisms.

Professional Experience:

Ms. Jiaying Wu has gained significant professional experience through her research work in blockchain and Internet of Things (IoT) security. Since 2022, she has focused on addressing performance bottlenecks in traditional blockchains within IoT scenarios by developing a high-performance dynamic sharding model. This model enhances blockchain scalability and cross-domain data access. From August 2022 to May 2024, she designed an attribute-based access control model aimed at improving flexibility in data decryption and public search functionalities. Additionally, she has contributed to major scientific projects in Yunnan Province and played a key role in establishing the Yunnan Provincial Key Laboratory of Blockchain and IoT Security.

Research Interests:

Ms. Jiaying Wu’s research interests lie in the areas of blockchain technology and its scalability, with a particular focus on sharding techniques and cross-shard transaction security mechanisms. She is also deeply interested in optimizing blockchain performance for Internet of Things (IoT) applications, working on solutions to improve scalability and efficiency in edge computing scenarios. Her work explores dynamic sharding models, secure cross-domain access, and blockchain-based access control systems, aiming to enhance both security and flexibility in decentralized networks. These research interests highlight her commitment to advancing blockchain technology in real-world applications.

Skills:

Ms. Jiaying Wu possesses a diverse set of professional skills that are highly relevant to her research in blockchain and computer science. She is proficient in programming languages such as C, Python, and Go, and has extensive experience with blockchain platforms like Hyperledger Fabric and Ethereum. Ms. Wu is skilled in writing blockchain smart contracts using Go and Solidity, allowing her to implement complex functionalities within decentralized systems. Additionally, she has a strong background in blockchain project development, particularly in system design and performance optimization. Her technical expertise extends to network technology, as evidenced by her Computer Level Certificate – Level 3 Network Technology.

Concution:

Considering Ms. Jiaying Wu’s academic performance, groundbreaking research contributions, and numerous awards, she is a highly deserving candidate for the Research for Best Researcher Award. Her work in blockchain scalability and IoT security, coupled with her technical expertise, places her at the forefront of innovation in her field.

Publication Top Noted:

A sharding blockchain protocol for enhanced scalability and performance optimization through account transaction reconfiguration

  • Authors: J. Wu, L. Yuan, T. Xie, H. Dai
  • Journal: Journal of King Saud University – Computer and Information Sciences
  • Year: 2024
  • Volume: 36(8)
  • Article: 102184
  • Status: In Press

Ciphertext Fuzzy Retrieval Mechanism with Bidirectional Verification and Privacy Protection

  • Authors: T. Xie, L. Yuan, Q. Zhang, J. Wu, F. Ren
  • Journal: IEEE Internet of Things Journal
  • Year: 2024
  • Status: In Press