Bikal Lamichhane
Papers
1
Total Citations
24
H-Index
1
About
Bikal Lamichhane is a researcher at the forefront of brain-inspired computing and cybersecurity, with a focus on memory-efficient machine learning. His most-cited work, "SpamHD: Memory-Efficient Text Spam Detection using Brain-Inspired Hyperdimensional Computing" (2021, 24 citations), introduces a novel approach that leverages hyperdimensional computing (HDC)—a paradigm that mimics the brain’s use of high-dimensional, holographic vectors for robust and efficient pattern recognition. Lamichhane’s key contribution lies in demonstrating how HDC can achieve competitive accuracy in spam detection while drastically reducing memory and computational overhead compared to traditional deep learning models. This work highlights his expertise in designing lightweight, hardware-friendly AI systems for real-world applications. By bridging neuroscience and practical machine learning, Lamichhane’s research offers a promising path toward energy-efficient, on-device intelligence, making him a notable voice in the emerging field of hyperdimensional computing. His achievements underscore the potential of brain-inspired algorithms to address critical challenges in data security and resource-constrained environments.
Research Focus
Key Achievements
Top Papers
- 1