Darya Mikhailenko

Darya Mikhailenko is an experienced electrical and computer engineer with a robust background in research and engineering roles. Darya served as a Graduate Research Assistant at the University of Rochester, focusing on Granular Matrix Reordering to enhance energy efficiency in neural networks, and contributed to commutative data reordering techniques published in ISCA 2020. Darya's expertise includes working in various research laboratories and internships, such as at the Bioinspired Microelectronics Systems Lab and Google, where contributions to pre-silicon tools and power estimation for mobile AI applications were made. Darya holds a Master's degree in Electrical and Computer Engineering from the University of Rochester and a Bachelor's degree in Electrical and Electronics Engineering from Nazarbayev University.