I am a fifth-year PhD student in electrical engineering at Stanford advised by Mark Horowitz. I received my B.S. in Electrical Engineering and Business, Economics, and Management from Caltech in 2019 and my M.S. in Electrical Engineering from Stanford in 2021. My research is supported by the Quad Fellowship (2023 to 2024) and Stanford's Knight-Hennessy Graduate Fellowship (2019 to 2022).

I am broadly interested in hardware design for cryptography and machine learning applications. I am curious about the security implications of enabling faster execution of cryptographic protocols and worked on designing a fast extended GCD algorithm and accelerator for constant-time modular inversion and verifiable delay functions. On the machine learning side, I am working on dynamically adapting the execution of state-of-the-art models for use in real-time systems and am working on accelerating dynamic transformer models for computer vision in an ongoing collaboration with NVIDIA. I previously worked on building a flexible memory generator as part of an agile software-hardware co-design flow with Stanford's Agile Hardware (AHA) Project. As part of my research, I have worked on taping out chips in SKY130nm, TSMC16nm, and GF12nm. During the summer, I have interned with Meta Reality Labs, NVIDIA's Architecture Research Group, Apple, Microsoft, and Intel.

Hoda Naghibijouybari is an Assistant Professor in the Computer Science Department at Binghamton University. She received her Ph.D. in computer science from the University of California, Riverside in 2020, working with Professor Nael Abu-Ghazaleh. Her primary research interests are in the area of computer architecture, and security. Her current research focuses on architecture support for security, microarchitectural attacks, GPU security, and heterogeneous systems. Her research has resulted in the discovery of new attacks that have been disclosed to GPU companies and received coverage from technical news outlets. Her paper on GPU security (published in CCS-2018) was selected for Top Picks in Hardware and Embedded Security in 2019.

Anne Bracy is a Senior Lecturer in Computer Science at Cornell University. Prior to teaching at Cornell, Dr. Bracy was a Principal Lecturer and Coordinator of Undergraduate Research in Computer Science at Washington University in St Louis. She was also a Research Scientist at the Microarchitecture Research Lab at Intel in Santa Clara, California.

Dr Bracy received her PhD from University of Pennsylvania for her work on instruction fusion under the supervision of Amir Roth. Prior to her doctoral studies she was a student at Stanford University, where she was inducted into the Phi Beta Kappa honor society.