Reliable VLSI Design Lab
Research Field
Prof. Ching-Hwa Cheng is currently a full professor of electronic engineering at Feng-Chia University. He is a 20-years IEEE senior member. His studies have included theoretical model analysis, design flow development, cell library generation, physical chip implementation and full system validation. His work differs from that of other researchers in this field is that most of his research designs are silicon proven by a practical system. 20+ years' experience in image-guiding surgery and low-power designed chip by multi-voltage. /p
Our Lab takes semiconductors, components/memory, strongintegrated circuit design/strong and strongsystem development/strong, strongLiDAR/strong applications, and AIoT-related electronic semiconductor industry technology as the main development direction./p
Autonomous vehicles rely on LiDAR (Light Detection and Ranging) and camera technologies to navigate and perceive their surroundings. Our research interests include image-point-cloud fusion , noise-tolerant Lidar system design, AI-based image process and there related application issues, e.g., object-segment in image and point cloud. Currently, we focus on a reliable LiDAR system implemented in an embedded system. However, LiDAR and Image data can be significantly affected by adverse weather conditions such as heavy rain, snow, fog, or dust storms. These weather conditions can lead to reduced visibility and accuracy in the LiDAR data, posing a significant challenge to the safe and efficient operation of autonomous vehicles. To address these issues, the project statement focuses on developing a system or algorithm to enhance autonomous vehicle LiDAR-Camera data by filtering out the adverse effects of weather conditions and improving the reliability and safety of autonomous driving in challenging environmental conditions. These challenges and goals not only present opportunities for innovation but also align with our project's overarching mission to create a cutting-edge solution in the field of semantic segmentation for objects. First is to increase the efficiency and accuracy of the existing system. The second is to execute the algorithm using embedded system. The third is to reduce computational complexity. Finally, our research work needs can be well demonstrated in a real environment (e.g. heavy raining conditions).
PI has honored with many competition awards, published more than 45 journal papers, 155 conference papers, developed two design automation tools and has been invited to serve as reviewer for many system and VLSI field journals/conferences.
PI received an M.S.E.E degree from Chung Hwa University, Taiwan, in 1993, and a Ph.D. degree in Computer Science and Information Engineering from National Chung Cheng University, Taiwan, in 2000. He is currently a full professor of electronic engineering at Feng-Chia University./p
2 Vacancies
Job Description
- This is a research-oriented internship; it need to motivate yourself and focus within this short duration to raise your capability in advanced technologies
- Your algorithm should be efficient and can be executed in an embedded system (e.g., Jetson Nano or Raspberry boards)
- Hardware environment: PC, embedded system (Jetson nano, Raspberry Pi)
- You need to FOCUS on your research only; no part-time job allowed. You need to cover your expenses here by yourself.
- Normal working hours are from AM8-9-to-PM5-6, 5 days/week
- Meeting 2 times/week, to present/demonstrate your working status.
- The Outcome-1, a feasible algorithm with real system demonstration. The Outcome-2, one paper/technical report
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Preferred Intern Education Level
- Under/Master (prefer)/PhD (prefer)
- Come from departments of computer-science/computer engineering/electronic-electric engineering
Skill sets or Qualities
Pure development by software. Programming Technique may on C, C++, Python, Matlab, OPENCV language, Linux OS (Ubuntu), AI CNN-RNN (Pytorch)