Name: Zahra Ahmadi
Type: User
Company: Leibniz University Hannover
Bio: "Human-centered AI" group leader at PLRI, MHH.
Senior researcher at L3S Research Center, LUH.
PhD from Johannes Gutenberg University Mainz, @kramerlab .
Location: Hannover
Blog: https://orcid.org/0000-0003-1110-4756
Zahra Ahmadi's Projects
Inductive Link Prediction for Criminal Network Analysis
MANDO is a new heterogeneous graph representation to learn the heterogeneous contract graphs' structures to accurately detect vulnerabilities in smart contract source code at both coarse-grained contract-level and fine-grained line-level.
The resource applied Graph Learning on smart contract vulnerability detection in bytecode form.
MANDO-GURU, a deep graph learning-based tool, aims to accurately detect vulnerabilities in smart contract source code at both coarse-grained contract-level and fine-grained line-level.
MANDO-HGT is a framework for detecting smart contract vulnerabilities. Given either in source code or bytecode forms, MANDO-HGT adapts heterogeneous graph transformers with customized meta relations for graph nodes and edges to learn their embeddings and train classifiers for detecting various vulnerability types in the contracts' nodes and graphs.
SoChainDB framework facilitates obtaining data from blockchain-powered social networks.
Crawl & visualize ICLR papers and reviews
Implementation of Random Compression Method for Online Multi-label Streams