Title: Scalable Applied Quantum Computing with HPC -Addressing challenges of Quantum Computing in the NISQ Era
Speaker: Dr. Debanjan Konar
Venue: Seminar hall, second floor, IEOR Building
Day, Date, Time: Monday, 26th August 2024, 11:30AM-12:30PM
Abstract: Recently, Quantum Computing (QC) has been leveraged for intelligent systems (AI/ML) with the hope that the uncertainty in QC can be a great advantage for stochastic- based modeling in AI/ML, inspiring new research for Noisy Intermediate Scale Quantum (NISQ) devices. Thus, while classical AI/ML systems with HPC have demonstrated effective applications in decision-making, signal processing, and image recognition tasks, their implementation has been limited to deterministic digital systems due to scalability issues with QC. In this presentation, I will start the discussion with the fundamentals of Quantum Computing, and various logic gates that are essential for quantum computations will be discussed. I will be discussing primarily quantum machine learning, quantum optimization, hybrid classical quantum neural networks, quantum-inspired tensor networks with a direct application on computer vision, material science, etc., and with a special emphasis on Gate-based Quantum Neuromorphic Computing. Finally, I briefly discuss the future plan for the exploration to understand the information processing similarity between Quantum Neural Networks (QNN) and complex brain functionalities with some light into a series of Quantum ML algorithms that I developed and their feasibility for large-scale applications in the future.
Brief Bio: Debanjan Konar completed his Ph.D. from the Indian Institute of Technology Delhi (IITD), New Delhi, India. Recently, Dr. Konar joined as a Senior Chief Engineer and Head of Quantum Computing at Samsung Research & Development Institute Bangalore (SRIB), India. He was a Fulbright-Nehru Postdoctoral Fellow (Quantum Computer Sc.) at Purdue University. Prior to that, he was a Postdoctoral Research Scientist at Helmholtz Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany. He also worked as a Lead Research scientist (Quantum Computing) at BosonQ Psi Pvt. Ltd. (Bangalore), India. He was a Helmholtz Visiting Fellow (Quantum Computing) at the Steinbuch Center for Computing (SCC), Karlsruhe Institute of Technology (KIT) in Karlsruhe, Germany. His research interests include quantum machine learning, quantum computing, quantum-inspired optimization algorithms, hybrid classical-quantum algorithms, etc. Dr Konar has authored articles in topnotch AI and Quantum journals and conferences. He is a Fulbright Fellow, a senior member of IEEE, an ACM member, Euro-Science member.