1.1 Information for Applicants
- 19 master students per year - 12 students (from recommendation and screening) + 7 students (from entrance examination):
(1) Recommendation and Screening: Application materials 50% + Interview 50%
- Qualification:The applicant is required to have the basic ability of at least one programming type (such as Python, C/C++/C#, Java, R or Matlab, etc.).
- Application materials:
- Transcripts (with proof of ranking)
- Two reference letters (with the format from NCKU admission system)
- Autobiography (must contain evidence of interdisciplinary ability or
- Study plan (must include application motivation, relevant background or experience, interdisciplinary research expected to invest, future development or employment planning, etc.)
- Reports, portfolios or other helpful documentation (If the work is a collaboration of more than one person, please indicate the name of the collaborator and the part and responsible percentage).
(2) Entrance Examination：Examination 30% + Application materials 30% + Interview 40%
- Examination: Programming
2021 Examination(in Chinese)
- Application materials: same as above
- For international student’s application, please visit OIA, NCKU
1.2 Information for Students
- Students need to find an advisor (full time or adjunct professor), and discuss with their advisors about their interdisciplinary topic, then find a co-advisor (or more) for interdisciplinary research.
- Students will work together on their interdisciplinary research with their advisors and co-advisors.
- Scholarships will be provided to students based on their performance.
1.3 Concepts for the Interdisciplinary Research
- The core idea of the program is the AI robotics applications.
- The goal is to cultivate talents with interdisciplinary and dual- competency expertise (in AI computing and robotics applications).
- The program emphasizes team work, which can train students with system integration ability.
- Interdisciplinary courses will be linked to industrial practices.
- Part of the courses will cooperate with the industry and invite relevant teachers for cooperation.
2.1 Modularization Courses：Credits and Faculty
- Graduation requirement
- Elective courses for 24 credits, with the maximum 6 credits from course waiver.
- Required course: Seminar (0 credit). Before graduation, students must need to complete Seminar (1) (2) (3) (4).
- With agreement from advisors, students are allowed to enroll 6 credits courses from other departments.
- Each modularization course is 1.5 credits (3 hours per week *9 weeks).
- Each modularization course will include term project to enhance students' practical ability.
- The interdisciplinary faculty consists of 28 professors with rich practical experience in the field of AI or/and robotics.
- The interdisciplinary faculty are from CSIE, EE, ME, IMI and Institute of Data Science
2.2.1 5 Modularization Courses：the relationship between SOC and research centers
2.2.2 5 Modularization Courses：the relationship with AIoT –Computing ABCD
2.3.1 5 Modularization Courses：Course Map – Course Fields
2.3.2 5 Modularization Courses：Course Map(Download)
2.4 5 Modularization Courses：Courses and Credits
1. Artificial Intelligence Computing Modularization Courses
|1||Introduction to AI Robotics||1.5||CSIE Prof. Jenn-Jier James Lien|
|2||Artificial Intelligence: Computing and Application||1.5||CSIE Prof. Wei-Ta Chu|
|3||Deep Learning: Computing and Application||1.5||ME Prof. Torbjörn Nordling, instructed in English|
|4||Evolutionary Computation*||1.5||CSIE Prof. Shu-Mei Guo|
|5||Special Topic on Game AI||1.5||CSIE Prof. Wen-Yu Su|
|6||The Application of Deep Learning for Internet of Things||1.5||CSIE Prof. Kun-Chan Lan|
|7||Implementing Applications of Cyber Physical Systems*||1.5||CSIE Prof. Pei-Hsuan Tsai|
|8||Implementing Applications of Cyber Physical Systems*||1.5||CSIE Prof. Pei-Hsuan Tsai|
2. Learning-Based Computer Vision Modularization Courses
|1||Image Processing and Robot Vision: Fundamental and Design||1.5||SOC Prof. Jin-Yi Wu|
|2||Image Processing and Robot Vision: Computing and Application||1.5||SOC Prof. Jin-Yi Wu|
|3||Image Processing and Geometric Data Analysis: Fundamental and Design||1.5||EE Prof. Chia-Hsiang Lin|
|4||Image Processing and Geometric Data Analysis: Computing & Application||1.5||EE Prof. Chia-Hsiang Lin|
|5||Deep Learning for Medical Image Processing||1.5||CSIE Prof. Ming-Long Wu|
|6||Deep Learning for Computer Vision||1.5||CSIE Prof. Jenn-Jier James Lien|
|7||Artificial Intelligence to Sports Analytics||1.5||Institute of Physical Education, Health &Leisure Studies Prof. Kuangyou B. Cheng|
|8||Application of Deep Learning for Human Skeleton||1.5||CSIE Prof. Kun-Chan Lan|
3.Human-Robot Interaction Modularization Courses
|1||Natural Language Communication between Humans and Robots||1.5||CSIE Prof. Wen-Hsiang Lu|
|2||Deep Learning for Recommender Systems||1.5||Institute of Data Science Prof. Cheng-Te Li|
|3||Deep Learning for Speech Recognition*||1.5||TBD|
|4||Interaction with Chatbots||1.5||SOC Prof. Shao-Man Lee|
|5||Value-Infused Interaction with Chatbots||1.5||SOC Prof. Shao-Man Lee|
|6||Learning-Based Human-Robot Interaction： Fundamental and Design*||1.5||SOC Prof. Jin-Yi Wu|
|7||Learning-Based Human-Robot Interaction： Computing and Application*||1.5||SOC Prof. Jin-Yi Wu|
4.AMR and ROS Modularization Courses
|1||AMR Having RGB-D Camera and LiDar: Computing and Application*||1.5||TBD|
|2||Applications of Autonomous Driving Technologies||1.5||EE Prof. Jyh-Chin Juang*|
|3||SLAM（Simultaneous Localization and Mapping): Computing and Application*||1.5||TBD|
|4||Programming for the Robot Operating System*||1.5||CSIE Prof. Ching-Chun Huang|
|5||Programming for the Robot Operating System*||1.5||CSIE Prof. Ching-Chun Huang|
|6||Embedded Software*||1.5||CSIE Prof. Da-Wei Chang|
|7||Parallel Computing for___*||1.5||CSIE Prof. Chia-Heng Tu|
|8||Implications and Forecasting of Automation Technology||1.5||ME Prof. Torbjörn Nordling|
5.Robot and Robot Arm Modularization Courses
|1||Vision-Based Control: Computing and Application||1.5||EE Prof. Ming-Yang Cheng|
|2||Mobile Robot System: Computing and Application||1.5||EE Prof. Tzuu-Hseng S. Li|
|3||Mobile Robot Arm Control: Computing and Application||1.5||EE Prof. Jason Sheng-Hong Tsai|
|4||Introduction to Design, Analysis and Control of Robotic System||1.5||ME Prof. Tsing-Iuan James Tsay|
|5||Intelligent Robot Control: Computing and Application||1.5||ME Prof. Tsing-Iuan James Tsay|
|6||Introduction to Networked and Mobile Robotic System*||1.5||ME Prof. Chao-Chieh Lan|
|7||Introduction to Networked and Mobile Robotic System*||1.5||ME Prof. Yen-Chen Liu|
|8||Soft Robot: Design, Analysis and Application||1.5||ME Prof. Chih-Hsing Liu|
|9||Robot Gripper Design: Computing、System Integration and Application||1.5||ME Prof. Chih-Hsing Liu|
|10||Advanced Control: Robotic and Complex Systems*||1.5||ME Prof. Yen-Chen Liu|
|11||Advanced Dynamics : Robotic and Complex Systems*||1.5||ME Prof. Chao-Chieh Lan*|
|12||Robot Law: Introduction*||1.5||SOC Prof. Shao-Man Lee|
|13||Robot Law: Social Bot*||1.5||SOC Prof. Shao-Man Lee|
|14||Robot-Aided Smart Construction*||1.5||TBD|
|15||Artificial Intelligence to Bionic Hand Control*||1.5||TBD|