Chair
Deepika Saxena, The University of Aizu, Japan
The inherent advantages of quantum computing (QC) technology, particularly regarding security, privacy, scalability, and efficiency, have opened new frontiers in information technology and Quantum computing systems. This track focuses on quantum technology and machine learning. The topics of interest include, but are not limited to, the following:
- Machine Learning and Quantum-inspired machine learning
- FPGA controller for Quantum Computers
- Quantum computing systems
- Quantum algorithms for ML tasks
- Learning and optimization with hybrid quantum-classical methods
- Quantum learning theory
- Quantum-enhanced robustness in machine-learning models
- Machine learning for experimental quantum information
- Learning and optimization with hybrid quantum-classical methods
- Fuzzy logic for quantum ML
- Quantum machine learning applications
TPC Members
- Sumit Sharma, National Institute of Technology Kurukshetra, India
- Monika Poriye, Kurukshetra University Kurukshetra, India
- Priti Maratha, Central University of Haryana, India
- Smruti Rekha Swain, National Institute of Technology Kurukshetra, India
- Abhisek Sharma, National Institute of Technology Kurukshetra, India
- Satender Kumar, National Institute of Technology Kurukshetra, India
- Jatinder Kumar, National Institute of Technology Kurukshetra, India
