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Seongjun Park
Also published under:
Affiliation
Department of Semiconductor Systems Engineering, Korea University, Seoul, Republic of Korea
Topic
2D Materials,Absorption Wavelength,Access Latency,Access Patterns,Buffer Size,CNN Model,Counter Value,Deep Neural Network,Deep Neural Network Layers,Deep Neural Network Model,Design Space Exploration,Digital Capture,Drain Current,Energy Consumption,Energy Efficiency,Fixed Time Window,Global Access,Graphene,Hardware Configuration,Hardware Overhead,Hardware Resources,High Energy Efficiency,Image Sensor,Inference Time,Input Matrix,Large Matrix,Load Data,Off-chip Memory,Optoelectronic Devices,Output Buffer,Parasitic Capacitance,Performance Degradation,Phototransistor,Pixel Level,Pulse Width,Readout Circuit,Scheduling Techniques,Semimetal,Short Time Window,Signal Processing,Systolic Array,Systolic Dimensions,Time-to-digital Converter,Transition Metal Dichalcogenides,Two-level Structure,Vision Transformer,Weight Matrix,
Biography
Seongjun Park received the B.S. degree from the School of Electronic and Electrical Engineering, Sungkyunkwan University, in 2023. He is currently pursuing the M.S./Ph.D. degree with the Department of Semiconductor System Engineering, Korea University. His research interests include neural network accelerator architectures and processing-in-memory architectures.