Research Experience
The Structure of Knowledge: Skeleton Tree & Knowledge Entropy , 09/2018 to 07/2019
Independent Research, supervised by Professor Luoyi Fu and Xinbing Wang (IIOT, SJTU)Extract and measure the complex structure composed by knowledge entities from both qualitative and quantitative perspectives.
Proposed the concept of Skeleton Tree, along with the extraction algorithm that efficaciously preserves the main skeleton structure of different academic citation networks.
Introduce the concept of ”Knowledge Entropy” based on the Skeleton Tree to measure the value of the knowledge contained in academic entities. item Quantify the influence and novelty of each academic paper via the newly proposed Subtree Entropy and Node Entropy index.
Bitcoin Network De-anonymization via IP Matching method , 03/2018 to 09/2018
Independent Research, supervised by Professor Luoyi Fu and Xinbing Wang (IIOT, SJTU)Proved that the Bitcoin network follows the power-law distribution.
Proposed a heuristic de-anonymous approach that suits the profit-oriented characteristics of Bitcoin traders in Bitcoin trading market.
Derived an algorithm that leverages the adjacency matrix and transition probability matrix which makes it possible to apply clustering to the IP matching method.
Established the de-anonymous method that matches the activity information of the IP with the transaction records in Blockchain.
Verify the IP matching de-anonymous method on real Bitcoin trade data between 07/21/2018 to 08/14/2018, which is scraped down and consists millions of transactions and even more addresses.
Data Transmission and Privacy Conservation in Social Networks, 12/2016 to 03/2018
Independent Research, supervised by Professor Luoyi Fu and Xinbing Wang (IIOT, SJTU)Extract and measure the complex structure composed by knowledge entities from both qualitative and quantitative perspectives.
Proposed the concept of Skeleton Tree, along with the extraction algorithm that efficaciously preserves the main skeleton structure of different academic citation networks.
Introduce the concept of ”Knowledge Entropy” based on the Skeleton Tree to measure the value of the knowledge contained in academic entities. item Quantify the influence and novelty of each academic paper via the newly proposed Subtree Entropy and Node Entropy index.
Projects
Academic Title Graph based on Stereoscopic Accurate Portrait , 09/2018 to Present
Funded by National Natural Science Foundation of China (NSFC), data, figures and system from Acemap Developed IIOT, SJTUDescription: In this project, my major work is to realize some functions including data cleaning, visualization and derivation of some models (including the Knowledge Entropy Model above).
Collecting, processing and analysis on the academic relation data of over 30GB.
Visualization of the academic networks that reveals relations between different academic titles of China.
Construction of part of the Website (mainly on Web back-end database and the interface for front-end).