Papers
1
Total Citations
8
H-Index
1
About
Jiguang Wan is a leading researcher in big data storage systems, with a primary focus on erasure coding and efficient data management for large-scale, cold data environments. His most cited work, "Robot: An efficient model for big data storage systems based on erasure coding" (2013, 8 citations), addresses the critical challenge of storing explosive data growth by proposing a novel coding-based solution that optimizes reliability and space efficiency. This contribution has provided a foundational framework for reducing storage overhead in data centers and cloud infrastructures, directly impacting how industry and academia handle massive, infrequently accessed datasets. Wan’s research bridges theoretical coding techniques with practical system design, offering scalable and cost-effective strategies for modern storage challenges. His work is particularly notable for its emphasis on balancing performance and fault tolerance, a key concern in big data ecosystems. With a career dedicated to advancing storage technologies, Jiguang Wan continues to influence the evolution of resilient, high-capacity storage systems, making his contributions essential reading for students and researchers exploring the frontiers of data engineering and distributed storage.
Research Focus
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Top Papers
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