A paper co-authored by EECS Ph.D. student Naveed Mahmud and his advisor, Assistant Professor Esam El-Araby, was recognized at the 32nd IEEE International System-on-Chip Conference (SOCC’19) in September 2019.
The paper “Dimension Reduction for Efficient Pattern Recognition in High Spatial Resolution Data Using Quantum Algorithms” was nominated for the Best Paper Award at SOCC’19 and received second place. SOCC has been the premier forum for more than 30 years for publishing the latest advancements in System-On-Chip (SoC) architectures, systems, logic and circuit design, process technology, test, design tools and applications. “I am proud of my student’s hard work and I am pleased that the quality of our results have been recognized by this conference,” Professor El-Araby said.
Photo from left to right: senior Bailey Srimoungchanh, Ph.D. student Naveed Mahmud, junior Nolan Blankenau, Assistant Professor Esam El-Araby, senior Bennett Haase-Divine, senior Annika Kuhnke, and junior Apurva Rai.
Because of the immaturity and the high-cost of existing quantum technologies, El-Araby’s research group has focused on developing a cost-effective and reconfigurable emulation platform that can be used for interfacing classical-to-quantum (C2Q) and quantum-to-classical (Q2C) data conversions between classical and quantum systems, and evaluating the performance of quantum algorithms for practical real-world quantum machine learning (QML) and cybersecurity applications. Their emulation platform architecture uses advanced field-programmable gate array (FPGA) technology for scalable, high performance, high throughput and highly accurate emulation of quantum algorithms and systems. Compared to existing state-of-the-art FPGA emulators, this emulation framework is the highest scalable, most accurate, and achieves highest throughput, as demonstrated by encouraging experimental results.