Akanksha Tyagi
Researcher
Also affiliated: Indian Institute of Technology Hyderabad (2024)
Graduate Student Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
Akanksha Tyagi's research focuses on the application of machine learning techniques, specifically reinforcement learning, to address complex problems in computer science and engineering. Her recent work includes developing a reinforcement learning approach for multi-parametric input mutation to enhance fuzzing techniques, a method used for software testing. She has also investigated the use of reinforcement learning to improve lane-level dynamics for electric vehicle traversal. Tyagi has published three papers and has a citation count of two, with an h-index of one. Her collaborators include Qinghua Li and Marie Louise Uwibambe from the University of Arkansas at Fayetteville, with whom she has co-authored one publication each.
Metrics
- h-index: 1
- Publications: 3
- Citations: 2
Selected Publications
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Graph-Based and Ensemble Anomaly Detection for Smart Water Treatment Systems (2026)Journal of the Arkansas Academy of Science OpenAlex
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A Reinforcement Learning Approach to Multi-Parametric Input Mutation for Fuzzing (2025)
Collaboration Network
Top Collaborators
- A Reinforcement Learning Approach to Multi-Parametric Input Mutation for Fuzzing
- A Reinforcement Learning Approach to Multi-Parametric Input Mutation for Fuzzing
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