CHIV Kimchhor
Academic Background
- Current: Integrated MS and PhD in AI Convergence, Pukyong National University, Busan, South Korea
- Bachelor's Degree: Computer Science, Royal University of Phnom Penh, Cambodia (2022)
Research Focus
Chiv Kimchhor's research focuses on the cutting-edge intersection of quantum computing and machine learning, exploring how quantum algorithms can enhance computational capabilities for complex optimization and learning tasks.
- Quantum Machine Learning: Applying quantum computing principles to machine learning algorithms
- Deep Learning: Advanced neural network architectures and optimization techniques
- Quantum Computing: Variational quantum algorithms and quantum circuit optimization
Conference Publications
Using Zero-Noise Extrapolation to Improve Variational Quantum Eigensolver for Portfolio Optimization
Authors: Kimchhor Chiv, Chansreynich Huot, Myeongseong Go, Youngsun Han
Conference: 2024년도 한국통신학회 추계학술대회, November 2024
Efficient Transpilation of Quantum Circuits to Quantum Intermediate Representation
Authors: Sengthai Heng, Nagyeong Choi, Kimchhor Chiv, Youngsun Han
Conference: 24th Asian Quantum Information Science Conference (AQIS 2024), August 2024
Research Interests
Her research explores the emerging field of quantum machine learning, where she investigates how quantum computing can revolutionize traditional machine learning approaches. She is particularly interested in variational quantum algorithms and their applications in optimization problems, as well as efficient quantum circuit design and transpilation techniques.
Collaboration with AICLab
As a collaborating researcher with AICLab at Chungbuk National University, Chiv Kimchhor brings expertise in quantum computing and deep learning to complement the lab's research in applied AI and computer vision. This collaboration bridges quantum computing research at Pukyong National University with applied AI initiatives at AICLab.