Farah Ferdaus

I am an Assistant Professor in the Phillip M. Drayer Department of Electrical and Computer Engineering at Lamar University. Prior to joining Lamar, I was a Postdoctoral Researcher in the Mathematics and Computer Science (MCS) Division at Argonne National Laboratory (US Department of Energy, Office of Science). My research at Argonne focused on evaluating the energy efficiency of AI accelerators used in AI for science applications and HPC for AI. I worked on several projects that benchmarked the power and performance of deep learning models across different AI hardware platforms, which includes GPUs from Nvidia, AMD, and Intel, as well as specialized AI accelerators like Intel Habana Gaudi, Graphcore, Groq, and others.

I have published numerous scientific articles, including journal articles, conference papers, and book chapters on esteemed platforms. My research is showcased in premier ACM/IEEE journals and conferences, such as the SC Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis, IEEE International Symposium on Cluster, Cloud, and Internet Computing (CCGrid), IEEE Transactions on Information Forensics and Security (TIFS), ACM Journal on Emerging Technologies in Computing Systems, IEEE Transactions on Computers (TC), and IEEE Transactions on Very Large Scale Integration (VLSI) Systems (TVLSI). My research interests include quantum computing, high-performance computer architecture, energy-efficient computing, hardware security, cybersecurity, and memory systems. My PhD research specifically focused on hardware security and emerging memory technologies.

Education

  • Ph.D. in Electrical and Computer Engineering
    Florida International University, December 2022

  • M.Sc. in Electrical and Computer Engineering
    University of New Hampshire, December 2018

  • B.Sc. in Electrical and Electronic Engineering
    Bangladesh University of Engineering and Technology (BUET), September 2015

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