Executive Education Programmes designed to build capabilities in infocomm and digital business.
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We offer five practice-based graduate programmes focusing on information technology (IT) and data science.
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Meet the NUS-ISS Team and learn about our story and achievements.
Each year, the NUS-ISS Master of Technology (MTech) in Knowledge Engineering (KE) programme trains and graduates industry-ready software project managers and software architects.
Having taught in the programme for eight years, Member of Intelligent Systems at NUS-ISS, Dr Ding Li Ya, together with the rest of the MTech lecturers, has played a significant part in moulding Infocomm leaders in the region.
“I’m passionate about sharing my experience and knowledge with younger generation so as to help make their learning journey easier,“ shares Li Ya.
Li Ya (second from right), guiding the MTech students in a class
INNOVATE@ISS speaks to Li Ya to find out more about her.
1. Please tell us about your professional background
I have been in Computer Science and Artificial Intelligence areas since 1982. In 1990, I got my Ph.D. in Fuzzy Logic in Japan and joined ISS research in 1991. Thereafter, I worked as Project Leader in ISS under the Fuzzy Logic and Neural Networks Programme, and for the Neural Logic Networks project (international collaboration with Real World Computing Partnership, considered “6th generation computing”, founded by Japan government). I joined ISS MTech-KE teaching group in 1998, left ISS in 2002, served as Professor, Dean of school with two universities in Macau and rejoined ISS in 2011.
2. Could you share more about the modules/courses which you teach at NUS-ISS?
I teach the modules under the MTech KE programme – Intelligent Systems & Techniques for Business Analytics, Developing Intelligent Systems for Performing Business Analytics, and Computational Intelligence.
For executive education, I teach Predictive Analytics, which allows participants to learn how to utilise business data more effectively by deriving insights of trends and irregularities from data and apply them for forward-looking predictions.
3. Why did you choose to teach at NUS-ISS?
After nine years with two universities in Macau, I decided to come back to ISS. I like the working environment here with the understanding management, collaborative colleagues, close connection to industry, and hardworking students.
4. What do you enjoy most about your work?
Learning by teaching.
5. We understand that you recently contributed to the books “Knowledge-Based Information Systems in Practice”. Could you share more about that?
I have been working on “interval-valued confidence” for handling knowledge imperfection in intelligent systems since 2008. Last year, the book editors invited me to extend my previous papers to make a book chapter.
6. How do you keep up with the industry?
With my limited energy and time, my personal contact with the industry is limited. But through our student projects, I learn a lot about our local industry. So I enjoy discussions with students on understanding problems and modeling.
7. What are your favorite activities when you are not working?
I like to listen to classical music, cooking healthy food and cleaning the house as well!
8. Tell us something about yourself that very few people know.
My daughter’s name Yiling is “One Zero” in Chinese. In Fuzzy Logic, we use a value between 1 and 0 to indicate the truth and confidence for reasoning with knowledge imperfection.
Since its inception in 1996, the NUS-ISS Master of Technology (Knowledge Engineering) programme has been training IT professionals and domain experts in the concepts, techniques and methods of Intelligent Systems, and their application to the development of data analytics applications.
Applications for the January 2016 intake is now open. For more information on the programme, please visit our website here.