I recently graduated from Penn State University. My research at Penn State was focused on memory and storage architecture. I worked on NAND flash solid state drives on cloud and enterprise environments. I also did an internship at Memory Solution Lab in Samsung Semiconductor where I worked on open channel solutions for SSD storage architectures. I am now a Software Engineer at Google platform team working on system drivers for cloud storages.

Hai “Helen” Li is currently Clare Boothe Luce Associate Professor of Electrical and Computer Engineering Department at Duke University, USA. She received the B.S. and M.S. degrees from Tsinghua University, China, and the Ph.D. degree from the Department of Electrical and Computer Engineering, Purdue University, USA. Her current research interests include memory design and architecture, neuromorphic architecture for brain-inspired computing systems, and architecture/circuit/device cross-layer optimization for low power and high performance. Dr. Li is a distinguished member of ACM, a distinguished speaker of ACM (2017-2020), and a distinguished lecture of IEEE CAS society (2018-2019).

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.

Amila received her Bachelor's and Master's Degrees from the University of Sarajevo in Electrical Engineering within Computer Science and Informatics Department in 2006, 2009, respectively. In academic year 2007/2008 she received Fulbright Visiting Student Award and joined Embedded Systems and Architectures Lab at University California, Riverside as Junior Researcher. In 2010, she spent 1 month at Faculty of Electrical Engineering, University of Ljubljana as a visiting academic. Then, she received MEXT scholarship in 2010 and spend 3 and half years in beautiful Tokyo, where she completed her Ph.D. at Keio University in 2013.

Her primary area of interest is Computer Architecture, including Reconfigurable Architectures, High Performance Computing and Heterogeneous Computing. Her past research mainly focused on finding new ways to accelerate compute-intensive parts of an algorithm by means of offloading it to an FPGA. The challenge is to take advantage of knowledge about an architecture and adapt the algorithm to the architecture rather than the other way around. Her PhD research focused on developing architectures and methodologies that help to reduce the execution time of Cyclic Redundancy Check algorithms, particularly those implemented using FPGAs, and iSCSI protocol implementation.

In recent years, she has expanded her research to include Digital Signal Processing, Computer Vision, Image Segmentation, Machine Learning to name a few.