Computer Science Engineer, specializing in Hardware and Network Systems from SUNY Buffalo. Highly passionate about Research in the field of VLSI , Computer Architecture and Hardware Security. Also, I have a great interest in the field of Routers and Switches, MIMO technology and VLSI Digital Circuit designing. Along with my Master's I am also working as a Graduate Assistant in HPVSA Laboratory, in the Dept. of Computer Science Engineering , SUNY Buffalo. My current research is on design and optimization of Physically Unclonable Functions (PUF), which could act as a fingerprint for semiconductor devices.

Furthermore, I have obtained my Bachelor's degree in Electronics and Communication Engineering from SRMIST,Chennai,India. During my undergrad I sincerely worked under my Professor for the research project - on Tunnel Field Effect Transistor, which we presented at the National Conference Silicon'18. Our paper "Design Optimization of Tunnel Field Effect Transistor" was published in International Journal of Recent Technology and Engineering (IJRTE) in March 2019.

The amalgamation of Electronics, Computers and Communications have helped me to pave stronger base for the skills needed in the field of Computer Hardware and Computer Networks.

I am currently a senior systems engineer at Qualcomm working on mobile SoC performance analysis.

I received my PhD in 2020 from the ECE department of University of California, Santa Barbara under the guidance of Prof. Yuan Xie, and my Master's degree in 2015. I completed my undergraduate studies in the ECE department of University of Illinois at Urbana-Champaign in 2014. My PhD research explores the design space of the memory fabric in memory-centric system architectures, given the emerging memory technologies and integration trends, to identify bottlenecks and trade-offs and proposes scalable solutions.

Darya Mikhailenko is pursuing a PhD in Electrical and Computer Engineering at the University of Rochester under the supervision of Prof. Engin Ipek. Her interests cover areas of energy-efficient computer architectures, machine learning for computer vision applications, memory management, accelerators, and architecture modeling for emerging technologies. Darya worked as a research assistant at Nanoelectronics Research Laboratory (Purdue University, U.S.A.) and Bioinspired Microelectronics Systems Laboratory (Nazarbayev University, Kazakhstan) on the implementation of brain-computer architecture to actualize deep neural networks. Her recent work was dedicated to techniques to minimize data movement energy by exploiting asymmetric on- and off-chip interconnects. Currently, she researches microarchitecture level optimizations for AR/VR applications.

Darya is looking for internships in the field of AR/VR related but not limited to computer architecture and machine learning algorithms.

I'm a PhD student at Chalmers University of Technology in Gothenburg, Sweden. My current research focuses on scalable cache partitioning.