I work as a Lead Gen AI / ML Engineer at AMD. I got my Ph.D at Texas A&M University under the guidance of my advisor Dr. Peng Li. My research interest is focused on computer vision, time-series forecasting and reinforcement learning.
[IMAGE'24] Myung Seok Shim, Yogesh Nakhate, Suraj Pawar, Haron Abdel Raziq, David Thanoon, and Katy Wei , "Segment anything in seismic images"
[DCE'23] Myung Seok Shim, Christopher Thiele, Jeremy Vila, Nishank Saxena and Detlef Hohl, "Content-based image retrieval for industrial material images with deep learning and encoded physical properties", Data-Centric Engineering, 4, E21. doi:10.1017/dce.2023.16
[DAC’21] *Myung Seok Shim, Hanbin Hu and Peng Li, “Reversible Gating Architecture for Rare Failure Detection of Analog and Mixed-Signal Circuits,” Design Automation Conference, pp.901-906 , Dec 2021
[Arxiv] *Myung Seok Shim, Chenye Zhao, Yang Li, Xuchong Zhang, Wenrui Zhang, Peng Li, “Robust Deep Multi-Modal Sensor Fusion using Fusion Weight Regularization and Target Learning,” 2020
[IJCNN’17] *Myung Seok Shim, and Peng Li, “Biologically inspired reinforcement learning for mobile robot collision avoidance,” International Joint Conference on Neural Networks, pp. 3098-3105, May 2017
From TensorFlow to RTL in three months - Cadence Design Systems