ECE Calendar

https://ece.ncsu.edu/seminar/architecting-hybrid-quantum-classical-computer-with-machine-learning/

Quantum Computing has the potential to solve classical intractable problems with higher speed and efficiency. To unlock its full potentials and enable practical applications, quantum components need to work with classical components which perform necessary parameter optimization, program compilation and error correction. The hybrid system also needs to be optimized with holistic awareness. On the...

Speaker: Hanrui Wang
MIT

Hanrui Wang is a fifth-year Ph.D. student at MIT EECS advised by Prof. Song Han. His research focuses on quantum computer architecture, machine learning for quantum systems, and efficient ML. His research has been recognized by ACM student research competition 1st place award, best poster award at NSF AI Institute, Best Presentation Award as a DAC Young Fellow, MIT homepage spotlight and appears in top computer architecture, design automation and ML conferences such as MICRO, HPCA, DAC, ICCAD and NeurIPS. His co-authored paper received ICML RL4RL Best Paper Award. He is the recipient of Qualcomm Fellowship, Unitary Fund, and Nvidia Fellowship Finalist. He is the creator of TorchQuantum library which has been adopted by IBM Qiskit Ecosystem and Nvidia cuQuantum Appliance. He is also the co-founder of QuCS lecture series for quantum education.