CHIV Kimchhor
About
PhD student specializing in Quantum Machine Learning, with a foundation in Quantum Computing, Quantum Error Mitigation, and advanced machine learning. Holding a Master's degree from Pukyong National University, her research focuses on bridging the gap between theoretical quantum algorithms and their deployment in practical, real-world applications.
Academic Background
- Current: PhD in Big Data, Chungbuk National University (CBNU)
- Master's Degree: AI Convergence, Pukyong National University (PKNU)
- Bachelor's Degree: Computer Science, Royal University of Phnom Penh, Cambodia (2022)
Research Focus
Her research focuses on Quantum Machine Learning, with emphasis on bridging theoretical quantum algorithms and their practical applications. She explores how quantum computing principles can enhance machine learning capabilities for real-world deployment.
- Quantum Machine Learning: Bridging theoretical quantum algorithms with practical, real-world applications
- Quantum Error Mitigation: Techniques to improve quantum computation reliability and accuracy
- 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 (KICS Fall Conference 2024), November 2024 - View Conference
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 - View Conference
Research Interests
Her research explores Quantum Machine Learning, investigating how quantum computing can enhance traditional machine learning approaches for real-world applications. She is particularly interested in variational quantum algorithms and their applications in optimization problems, quantum error mitigation techniques, and efficient quantum circuit design and transpilation.