I am a PhD student in the School of Electrical and Computer Engineering at Purdue University. I received my Bachelors (2018) in Electronics and Communication Engineering (with honors) from Indian Institute of Technology Roorkee, India. I was a recipient of the IITR Heritage Excellence Award, INSA-NASI-IASc Summer Research Fellowship, and ENCORE Scholarship Award for outstanding performance in academics and curricular during my time at IIT Roorkee. Subsequently, I worked for Texas Instruments for one year on standard cell design and methodologies in collaboration in EDA team. I joined my PhD program in Fall 2019 and since have been a part of Nanoelectronics Research Lab. My research interests include computer architecture, hardware accelerators for Machine Learning applications using emerging technologies, and design of processing in/near memory based architectures. In my free time, I like to play badminton, dance, go for running, or listen to music.

Rujia Wang joined Illinois Institute of Technology in Fall 2018. She earned her Ph.D. and M.S degree from Electrical and Computer Engineering Department at the University of Pittsburgh and her B.E. from Zhejiang University. Her research experience spans across multiple areas in computer engineering, including novel memory architecture, secure computing architecture, system reliability, and high-performance computing, and her work has been published in top conferences in computer architecture area.

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.

Aninda Manocha received her Ph.D student in Computer Science at Princeton University. She was advised by Professor Margaret Martonosi in the broad area of Computer Architecture. More specifically, she worked on the design of reconfigurable hardware to accelerate a variety of software applications with a focus on the application and compiler interface. She also worked on memory hierarchy designs and operating system techniques tailored to irregular, memory-intensive graph applications. She received her B.S. in Electrical and Computer Engineering as well as Computer Science from Duke University in 2018. She now works at Rivos.