I'm Gelara, a forward-thinking computer architecture master's student from Iran. My focus lies in Approximate Computing, Bio-inspired Computing, and Brain Interface Computing.

Hi, I am Nayana, a final year Ph.D. candidate at Princeton University, advised by Prof. David August. My research interests are in the field of computer architecture and hardware/software co-design, with more focus on performance improvement at the Datacenter scale. I interned for two consecutive summers with Google Wide Profiling team at Google. Before joining Princeton, I was working as a Verification Engineer at AMD, Bangalore, India.

Sabrina M. Neuman is an Assistant Professor of Computer Science at Boston University. Her research interests are in computer architecture design informed by explicit application-level and domain-specific insights. She is particularly focused on robotics applications because of their heavy computational demands and potential to improve the well-being of individuals in society. She received her S.B., M.Eng., and Ph.D. from MIT, and she was a postdoctoral NSF Computing Innovation Fellow at Harvard University. She is a 2021 EECS Rising Star, and her work on robotics acceleration has received Honorable Mention in IEEE Micro Top Picks 2022 and IEEE Micro Top Picks 2023. She holds the 2023-2026 Boston University Innovation Career Development Professorship.

I am a PhD student at the University of California, San Diego, majoring in Computer Science and Engineering. My research interests lie in the intersection of Computer Architecture and Computational Genomics. I am a part of Turakhia Lab under the supervision of Professor Yatish Turakhia, where I work on solving computational challenges and developing efficient hardware for genomic data analysis. I completed my undergraduate in Electronics and Telecommunication Engineering from IIEST Shibpur, West Bengal, India.

As a computer science researcher specializing in computational genomics, I am dedicated to advancing the field through the development of optimized hardware+software accelerated tools. My research focuses on devising fully automated and scalable methods to accelerate error-prone phylogenetic estimation techniques. By doing so, I aim to contribute significantly to evolutionary biology studies and help unravel the complexities of the tree of life. In parallel, I am engaged in a fascinating project leveraging an HLS-based framework to accelerate dynamic programming-based algorithms, mainly focusing on sequence alignment algorithms. This project aims to help bioinformaticians customize their algorithms and port on FPGA with less effort, bringing significant advancements in computational genomics research.