Professor Jiun-In Guo

Distinguished Professor, Institute of Electronics, National Yang Ming Chiao Tung University

Background: Ph.D Electronics Engineering, National Chiao Tung University
Research Interests: VLSI, IP/SOC, Intelligent Vision System, Embedded Deep Learning Technology, ADAS/Autonomous Driving System

Professional Experience:

• Distinguished Professor, Institute of Electronics, NYCU (2017/6~)
• Deputy Dean of ECE College, NYCU (2017/02-2022/08)
• Founder, eNeural Technologies Inc. (2022/05~)
• PI, MOST Moon-Shot Semiconductor Research Program (2018/05-2022/06)
• Director, SoC Center, NYCU (2016/8-2019/7)
• Director, Institute of Electronics, NYCU (2012/8-2015/7)
• PI, MOST National SoC Program (2011/1-2015/12)

Major Awards and Honors:

• MOST Outstanding Technology Transfer Award (2020)
• MXIC Best Advisor Award (2020)
• MOST AI Innovation Project Program Best Worthy Investment Team Award (2019)
• MOST Future Tech Award (2018)
• MOST Outstanding Technology Transfer Award (2017)
• MOST Best Industrial Academia Consortium Award (2016)
• MOST Outstanding Research Award (2016)
• Chinese Institute of Engineers (CIE) Outstanding Engineering Professor Award (2014)
• National Invention Silver Award (2012)
• The Chinese Institute of Electrical Engineering (CIEE) Outstanding Engineering Professor Award (2010);
• The Chinese Institute of Electrical Engineering (CIEE) Middle Taiwan Outstanding Engineering Professor Award (2008);

Publication:

[1]	Hung-Wei Lin, Vinay M. Shivanna, Hsiu Chi Chang, and Jiun-In Guo,” Real-Time Multiple Pedestrian Tracking with Joint Detection and Embedding Deep Learning Model for Embedded Systems,” accepted by IEEE Access, April 9th, 2022. (SCI, IF=4.48, H-index=127, JCI Rank=58/223 in Engineering, Electrical and Electronics)
[2]	Tzu-Hsien Sang, Kuan-Yu Tseng, Feng-Tsun Chien, Chia-Chih Chang, Yi-Hsin Peng, and Jiun-In Guo, “Deep Learning-based Velocity Estimation for FMCW Radar with Random Pulse Position Modulation,” accepted by IEEE Sensors Letters, March 1st, 2022 (SCI, IF=2.36)
[3]	Yu-Shu Ni, Vinay Malligere Shivanna, Jiun-In Guo,” iVS Dataset and ezLabel: A Dataset and a Data Annotation Tool for Deep Learning based ADAS Applications,” Remote Sensing, 2022, 14, 833. (SCI, IF=4.848), https://doi.org/10.3390/rs14040833
[4]	Chia-Chi Tsai and Jiun-In Guo,” IVS-Caffe – Hardware-Oriented Neural Network Model Development,” IEEE Transactions on Neural Networks and Learning Systems (Early access), pp. 1-15, July 26th, 2021. (SCI, IF=12.51)
[5]	Chun-Yu Lai, Bo-Xun Wu, Vinay M. Shivanna, and Jiun-In Guo,” MTSAN: Multi-Task Semantic Attention Network for ADAS Applications,” IEEE Access, vol. 9, pp. 50700-50714, 2021. (SCI, IF=4.48)
[6]	Zohauddin Ahmad, Yan-Min Liao, Sheng-I Kuo, You-Chia Chang, Rui-Lin Chao, Naseem, Yi-Shan Lee, Yung-Jr Hung, Huang-Ming Chen, Jyehong Chen, Jiun-In Guo, and Jin-Wei Shi, “High-Power and High-Responsivity Avalanche Photodiodes for Self-Heterodyne FMCW Lidar System Applications,” IEEE Access, vol. 9, pp. 85661-85671, 2021. (SCI, IF=4.48)
[7]	Tzu-Hsien Sang, Feng-Tsun Chien, Chia-Chih Chang, Kuan-Yu Tseng, Bo-Sheng Wang, and Jiun-In Guo,” DoA Estimation for FMCW Radar by 3D-CNN,” Sensors, vol. 21, no. 16, Aug. 2021, (SCI, IF=3.576)
[8]	Yu-Ting Li, Paul Kuo and Jiun In Guo, “Automatic Industry PCB Board DIP Process Defect Detection System based on Deep Ensemble Self-Adaption Method,” IEEE Transactions on Components, Packaging and Manufacturing Technology, vol. 11, issue 2, pp. 312-323, Feb. 2021. (SCI, IF=2.31)
[9]	Wen-Chia Tsai, Jhih-Sheng Lai, Kuan-Chou Chen, Vinay M. Shivanna and Jiun-In Guo, “A Lightweight Motional Objects Behavior Prediction System Harnessing Deep Learning Technology for Embedded ADAS Applications,” Electronics, Electrical and Autonomous Vehicles session, special issue Autonomous Vehicles Technology, vol. 10, issue 6, pp. 692, 2021. (SCIE, IF=2.412)
[10]	Jiun-In Guo, Chia-Chi Tsai, Jian-Lin Zeng, Shao-Wei Peng, and En-Chih Chang,” Hybrid Fixed Point/Binary Deep Neural Network Design Methodology for Low Power Object Detection,” IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS), vol. 10, no. 3. pp. 388-400, September 2020. (SCI, IF=4.643)
[11]	Guan-Ting Lin, Vinay Malligere Shivanna, and Jiun-In Guo, “A Deep Learning Model with Task-Specific Bounding Box Regressors and Conditional Back-Propagation for Moving Object Detection in ADAS Applications,” Sensors, special issue on “Sensor and Communication Systems Enabling Autonomous Vehicles”, vol. 20, no. 18, pp. 1-21, Sept. 2nd, 2020. (SCIE, IF=3.275)
[12]	Jin-Wei Shi, Jiun-In Guo, Manabu Kagami, Paul Suni, and Olaf Ziemann, “Photonic technologies for autonomous cars: feature introduction,” Optics Express, vol. 27, no. 5, pp. 7627-7628, March, 2019. (SCI, IF=3.356, ranked 1st out of 94 journals)
[13]	Chia-Chi Tsai, Cheng-Yen Lin, and Jiun-In Guo, “Dark channel prior based video dehazing algorithm with sky preservation and its embedded system realization for ADAS applications,” Optics Express, vol. 27, no. 9, pp. 11877-11901, April 2019. (SCI, IF=3.356, ranked 1st out of 94 journals)
[14]	Vinay M. Shivanna, Kuan-Chou Chen, Bo-Xun Wu, and Jiun-In Guo,” A Comparison of Traditional and CNN Based Computer Vision Sensors for Detection and Recognition of Road Signs,” the Open Access book, “Vision Sensors” edited by Dr. Francisco J. Gallegos-Funes, July 13, 2021. (SCI) @ IntechOpen Book Chapter.