QuantaML: Next Generation Machine Learning

Mohali

December 6, 2025

C-DAC Mohali successfully conducted a Two-Week Residential Professional Training Programme on "QuantaML: Next Generation Machine Learning" from November 24th to December 05th, 2025. The programme was sponsored by the Department of Science and Technology (DST), Government of India, and was organized for 24 Group - A Scientists, Technologists, and Academicians working in the Government and Public Sector.The training programme aimed to provide participants with a foundational as well as applied understanding of quantum computing and quantum machine learning, with emphasis on quantum-enhanced learning models and hybrid quantum–classical frameworks. Participants were equipped to conceptualize and evaluate quantum machine learning approaches for addressing emerging scientific and technological challenges.

Overview

The programme introduced participants to the core concepts of quantum computing, including quantum bits, quantum gates, quantum circuits, and key algorithms such as Grover’s algorithm, Shor’s algorithm, Quantum Support Vector Machines (QSVM), Variational Quantum Circuits (VQC), Quantum Principal Component Analysis (QPCA), Quantum Approximate Optimization Algorithm (QAOA), and Quantum Neural Networks (QNNs).Alongside conceptual understanding, participants gained valuable hands-on experience using quantum simulators and Python-based frameworks. The sessions also encouraged meaningful discussions on practical limitations, current challenges, and future directions of quantum machine learning, with applications spanning optimization, cybersecurity, materials science, and broader scientific research.

Programme Highlights

The first week focused on the Foundations of Quantum Computing and Machine Learning. Sessions covered fundamental quantum principles such as superposition and entanglement, quantum gates and circuits, Python programming essentials, and classical machine learning fundamentals. Participants received training on Qiskit, Pennylane, and quantum simulators, along with techniques for encoding classical data into quantum states using angle and amplitude encoding.The second week emphasized QuantaML as the Next Generation of Machine Learning, covering hybrid quantum–classical models, variational and parameterized quantum circuits, quantum neural networks, and quantum optimization techniques such as QAOA. The programme also included hands-on demonstrations of real-life quantum machine learning use cases. An industry visits to the IISER Mohali NMR Laboratory and an expert interaction session provided participants with exposure to real-world quantum research and development environments.

Programme Coordination and Delivery

The programme was organized under the esteemed guidance of Shri V. K. Sharma, ScientistG & Centre Head, C-DAC Mohali.Dr. Preeti Bali, Head (STD) provided overall leadership and strategic oversight, managing the end-to-end technical content delivery for the successful conduct of this high-end training programme.The programme featured expert-led sessions delivered by senior scientists and domain specialists from C-DAC, ensuring a strong integration of theoretical foundations and hands-on learning.

Dr. Gurmohan Singh provided academic leadership and delivered sessions on quantum computing fundamentals, basic quantum algorithms, and real-life quantum machine learning use cases.
Dr. Manjit Kaur conducted sessions on quantum gates and circuits, Bell states, quantum teleportation, and hands-on training using Qiskit.
ShriRohan Thakur delivered expert sessions along with hands-on exercises on Python fundamentals, relevant Python libraries, and quantum programming using Python-based frameworks.
ShriAmit Saxena, ScientistF, C-DAC Pune, delivered engaging sessions on HPC integration with quantum computing and quantum accelerators, providing insights into scalable quantum–classical workflows.
ShriVivek Nainwal, ScientistE, C-DAC Hyderabad, delivered an interactive session along with hands-on training on QSIM and Qniverse, India’s indigenous quantum simulation platforms.
ShriPeeyush Jain, ScientistE, delivered sessions on neural networks.
ShriTapas Saini, ScientistE, C-DAC Hyderabad, conducted in-depth sessions on Quantum Neural Networks (QNNs), explaining QNN architectures and guiding participants through hands-on implementation of quantum neural network models.
Advanced topics including quantum feature mapping, hybrid quantum–classical models, QSVM, QPCA, and quantum variational circuits were covered by Dr. Tarun Kumar.
The interactive session on Quantum Optimization using QAOA, along with corresponding hands-on exercises, was delivered by Shri Nagendra Singh, ScientistB, C-DAC CINE, and his team.

Additionally, two interactive brainstorming sessions were conducted with participants to discuss domain-specific challenges in their respective areas of work and to explore potential collaborative opportunities with C-DAC for addressing these challenges using quantum machine learning–based solutions.Collectively, these expert sessions equipped participants with a structured, application-driven understanding of QuantaML as the next generation of machine learning.

Valedictory Session and Conclusion

The training programme concluded with a valedictory session, during which participants shared their experiences and expressed appreciation for the well-structured curriculum, extensive hands-on learning, and the relevance of quantum-enhanced machine learning to future scientific and technological applications.Certificates were awarded to all participants upon successful completion of the training programme.