Rate My Professor Shikha Anirban

Anirban earned her Doctor of Philosophy in Computer Science from Griffith University in 2023, with a thesis titled 'Compression techniques for reachability and shortest distance queries.' She holds a Master's degree and a Bachelor's degree in Computer Science and Engineering from Jahangirnagar University, Bangladesh. Her research specializations encompass graph data management, machine learning, graph neural networks, natural language processing, algorithm design, data analytics, and software engineering. Her work emphasizes leveraging vast data volumes from technological advancements to improve processing algorithm efficiency, data compression for reduced storage costs, and data analysis for informed decision-making across applications such as social networks, web graphs, and road networks. Key publications include 'Explainable Neural Subgraph Matching With Learnable Multi-hop Anchors' (IEEE Access, 2024, co-authored with Duc-Quang Nguyen et al.); 'Compression Techniques for 2-hop Labeling for Shortest Distance Queries' (World Wide Web Journal, 2022); 'Answering Binary Causal Questions: A Transfer Learning Based Approach' (IJCNN 2020, co-authored with Humayun Kayesh et al.); and 'Multi-level Graph Compression for Fast Reachability Detection' (DASFAA 2019, Best Paper Runner-up). She received the Jeffry Blee Memorial Award in 2019 and the Jeffrey Blee Memorial Prize in 2022 from Griffith University. In teaching, Anirban focuses on enhancing students' critical thinking and problem-solving skills to prepare them for future technological challenges.