AI and Quantum Research Center
Research Field
Dr. Ka-Lok Ng earned his PhD in physics at Vanderbilt University in the United States. Currently, he is a distinguished professor in the Department of Bioinformatics and Medical Engineering at Asia University, Taiwan, where he also serves as the Vice Director of the AI and Quantum Research Center (AIQRC).
Dr. Ng has authored over 100 articles in scientific journals and conferences, along with two monographs in bioinformatics. These articles cover topics such as next generation sequencing (NGS) data analysis, multi-omics computational systems biology, network biology, DNA data hiding, high energy physics, and polarization of cosmic microwave background radiation. His current research centers on applying quantum machine learning (QML) techniques to identify cancer biomarkers, develop algorithms for solving network isomorphism problems, explore the use of LLMs for generating quantum programs, and tackle the issue of quantum-induced DNA mutations.
Since December 2009, Dr. Ng has served on the editorial boards of several scientific journals. He was the Editor-in-Chief of the WSEAS Transactions on Biology and Biomedicine from September 2010 to February 2014. He also has experience organizing international renown conferences, including the IEEE International Conference on Bioinformatics and BioEngineering (BIBE) and serve as the keynote speaker at the IMECS conference.
Our lab integrates Artificial Intelligence, Quantum Computing, and advanced computational methods to accelerate biomedical discoveries and solve complex biological network problems.
[1] Accelerate cancer drug discovery using AI and Quantum Machine Learning (QML).
Approach: Integrate single-cell RNA-seq with biomarker-guided multi-modal data (QSAR, ADMET, molecular dynamics).
Innovation: Apply Variational Quantum Algorithms (VQA) for high-dimensional feature extraction and predictive modeling.
Novelty: Combines quantum computing, AI-driven analytics, and multi-omics integration for precision oncology.
Impact: Enables accurate biomarker identification, improves drug candidate screening, and reduces development time.
[2] Data Fusion for Metastasis Gene Regulatory Module Ranking
Approach: Combine multiple features using data fusion algorithms for gene module prioritization.
Innovation: Integrates heterogeneous biological data into a unified ranking framework for metastasis-related modules.
Novelty: First to apply data fusion for systematic metastasis gene module prioritization across multiple data sources.
Impact: Enables precise identification of metastasis drivers, accelerating targeted cancer therapy development.
[3] Large Language Models for Quantum Programming
Approach: Utilize LLMs to auto-generate optimized quantum computing code for NVIDIA platforms.
Innovation: Bridges AI-driven code synthesis with quantum programming.
Novelty: Pioneering use of LLMs for generating quantum algorithms tailored to GPU-based quantum simulators.
Impact: Reduces development time and democratizes access to quantum programming expertise.
[4] Quantum and Deep Learning for Medical Imaging
Approach: Combine IBM Qiskit-based quantum circuits with ResNet and QCNN for image classification.
Innovation: Hybrid quantum-classical architecture enhances feature extraction in complex medical imaging tasks.
Novelty: First integration of QCNN with deep learning for diagnostic imaging in healthcare.
Impact: Improves accuracy and efficiency in early disease detection using quantum-enhanced models.
[5] Graph Theory for Biological Network Analysis
Approach: Apply advanced algorithms to solve digraph isomorphism for regulatory network comparison.
Innovation: Introduces scalable graph-theoretic solutions for analyzing upstream-downstream signaling relationships.
Novelty: Novel application of digraph isomorphism to biological signal transduction networks.
Impact: Facilitates discovery of conserved pathways and therapeutic targets in complex biological systems.
Selected Student Achievements Under My Supervision
2025 IEEE AIxMHC Conference – Best Paper Award
Student: Aninda Astuti (Ph.D student, Asia University, AI & Quantum Research Center)
Paper: Awarded Best Paper at the Second International Conference on Artificial Intelligence for Medicine, Health, and Care (AIxMHC), October 15, 2025.
2025 Student Quantum Computing Annual Conference – Poster Competition, First Place
Student: Aninda Astuti
Poster Title: “Enhancing Quantum Support Vector Classifier Performance and Speed through Neural Quantum Embedding and Tensor Networks.”
Date: August 23, 2025.
NTU-IBM Quantum System 2024 User Conference & Qiskit Hackathon Taiwan – Enterprise Special Award
Student: Aninda Astuti
Achievement: Won the Enterprise Special Award in the Quantum Computing Hackathon, 2024.
2023 IAENG International Conference on Bioinformatics – Best Paper Award
Students: Nguyen Manh Cong, Hsueh-Chuan Liu, Venugopala Reddy Mekala, Efendi Zaenudin, Ezra Bernardus Wijaya
Paper Title: “Identify Gene-Gene Regulatory Modules for Patients with Renal Clear Cell Tumor Metastasis.”
NTU-IBM Quantum System 2023 User Conference & Qiskit Hackathon Taiwan – Enterprise Special Award
Student: Aninda Astuti
Achievement: Won the Enterprise Special Award in the Quantum Computing Hackathon, 2023.
Dr. Ka-Lok Ng earned his PhD in physics at Vanderbilt University in the United States. Currently, he is a distinguished professor in the Department of Bioinformatics and Medical Engineering at Asia University, Taiwan, where he also serves as the Vice Director of the AI and Quantum Research Center (AIQRC).
View the following link for more, https://ppiddi.wixsite.com/klng.