Research Areas
Biography and Research Information
OverviewAI-generated summary
Akanksha Tyagi's research focuses on the application of machine learning techniques, particularly reinforcement learning, to address complex computational problems. Her work includes developing methods for improving lane-level dynamics for electric vehicle traversal, utilizing reinforcement learning to enhance decision-making and navigation in dynamic environments. Tyagi also investigates the use of reinforcement learning for multi-parametric input mutation, a technique applied to fuzzing for identifying software vulnerabilities. Her scholarly output includes two publications, with a total of two citations and an h-index of 1. She has collaborated with Marie Louise Uwibambe on one shared publication at the University of Arkansas.
Metrics
- h-index: 1
- Publications: 2
- Citations: 2
Selected Publications
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A Reinforcement Learning Approach to Multi-Parametric Input Mutation for Fuzzing (2025)
Collaboration Network
Top Collaborators
- Improving Lane Level Dynamics for EV Traversal: A Reinforcement Learning Approach
- Improving Lane Level Dynamics for EV Traversal: A Reinforcement Learning Approach
- 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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