Bahar Asgari is an assistant professor in the Department of Computer Science at the University of Maryland, Collage Park with a joint appointment in UMIACS. Before joining UMD in August 2022, she spent a year working at Google on its Systems and Services Infrastructure team. She received her Ph.D. in electrical and computer engineering from Georgia Tech in 2021, where she was advised by Dr. Sudhakar Yalamanchili and Dr. Hyesoon Kim. Bahar’s research interests include but are not limited to domain-specific architecture design, near memory processing, and reconfigurable computing. Her proposed low-cost hardware accelerators and hardware/software co-optimization that deal with essential challenges of sparse problems contribute to a widespread application domain from machine learning to scientific computing.

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 am an assistant professor at the department of computer science and Engineering at AUC. Before that, I did my Ph.D. studies as a CYD doctoral fellow at EPFL. I was working with Dr. Mirjana Stojilovic at the Parallel Systems Architecture (PARSA) laboratory led by Professor Babak Falsafi.

My research interests are focused on field programmable gate arrays (FPGAs) security. In particular, I look at the possible remote attacks on FPGAs. Furthermore, I am interested in the security of heterogeneous CPU-FPGA systems. I investigate possible attacks on and across system components. The goal is to find the vulnerabilities and design lightweight and effective countermeasures.

I am grateful to have received the CYD Doctoral Fellowship, the Google Generation Scholarship, and the EPFL EDIC Fellowship.

I'm a Ph.D. candidate at Department of Computer Science and Engineering, Indian Institute of Technology, Madras, advised by Prof. Chester Rebeiro. My research interests are broadly in the area of secure systems design, with a specific focus on micro-architecture level solutions against various attacks against cryptographic implementations, such as cache side-channel attacks. I'm also interested in exploring the applications of AI to help in building a more secure framework. I was one among the 12 candidates across the world to present my research at Lenovo AI Innovation Challenge Event at SuperComputing Conference 2017, Denver, Colorado. I was also one of the three-member team from IIT Madras that won the First Place in the CSAW Embedded Security Challenge 2016. We designed a secure implementation of an OpenRISC processor to detect and prevent buffer overflow attacks.