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.

Reetu Das is an Assistant Professor at University of Michigan. Prior to this, she was a research scientist at Intel Labs, and the researcher-in-residence for the Center for Future Architectures Research. She received her PhD in Computer Science and Engineering from Pennsylvania State University, University Park. Some of her recent projects include in-memory architectures, fine-grain heterogeneous core architectures for mobile systems, and low-power scalable interconnects for kilo-core processors. Her research program has been funded by National Science Foundation, the Center for Future Architectures Research (C-FAR), Semiconductor Research Corporation and Intel Corporation. Reetu is an expert in computer architecture. She has authored over 45 papers, filed 7 patents and served on over 20 technical program committees. She has served as a track chair for Design Automation Conference for two consecutive years. Her research has been recognized by several awards. She has received outstanding research and teaching assistantship awards at Pennsylvania State University, an IEEE Top Picks award, an NSF CAREER award, CRA-W Borg Early Career Award, IEEE/ACM MICRO Hall of Fame award and was recently inducted to ISCA Hall of Fame. Her recent work on in-memory design named Compute Caches received the best Demo award in C-FAR and was selected from 50 projects from leading University research groups. She also serves as the CEO of a precision medicine start-up, Sequal Inc.

I am currently a Ph.D. Research Scholar with the School of IT, Indian Institute of Technology Delhi, New Delhi, India.
My current research interests span the areas of architecture design and acceleration techniques for computer vision and image processing applications, designing convolutional neural network accelerators, and machine learning applications to computer architecture.

Helena Caminal is a first-year Ph.D. student in the Computer Systems Lab at Cornell University, advised by Prof. José F. Martínez. She is generally interested in computer architecture and systems, with a focus on processing-in-memory.