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Innovation and Intellectual Property Management (IIPM) Laboratory

This project aims explore and predict potential disruptive innovation opportunity. The disruptive innovation opportunity means potential and promising technology and innovation to penetrate and reshape mainstream as well as niche market. In other words, we find answer the questions – first, which technology will penetrate new market? Second, how is this disruptive technology implemented as business?

 

 

The main technique to solve these questions are machine learning and deep learning. Deep learning is a technique for learning and inference based on big data and it can solve hard problem in practice without information loss. Especially, it provides ‘right’ insights through iterative learning with high performance improvement. Machine learning and deep learning support are well-suited to deal with various type of data – both structured and unstructured data as coming of big data age.

 

This project serves as an ex-ante forecasting while considering existing technological paradigm because we will use both unsupervised learning and deep learning such as semi-supervised learning. It enables to early detection and forecasting by accumulating newly generated data not evaluating and classifying after implementing technology.

 

Project team: Dr Yujin Jeong, Leonidas Aristodemou, Frank Tietze

 

Related publications

 

Yujin Jeong, Leonidas Aristodemou, Frank Tietze (2019). Exploring disruptive innovation opportunity using deep learning. The R&D Management 2019 Conference, Paris, France.

News & Blog articles

IIPM annual review

20 December 2024

We have summarized some of the key events and achievements of the Lab and our members from 2024 in a first ever edition of our annual review, which is available for download iipm-ctm_annual_review_2024.pdf iipm-ctm_annual_review_2024.pdf .

ALPS team meeting in Cambridge

13 December 2024

It was a pleasure to welcome most the ALPS team to Cambridge. Having worked for some many months together mostly remotely, it was good to see everyone again together in-person. The team works on the Automated Licensing Payment System (ALPS) project currently exploring options to commercialize the technology platform. The...

ECNU guest lecture and alumni meeting in Shanghai

12 December 2024

Following the days at Tongji University, Prof. Tietze provided a guest lecture to students at the East China Normal University (ECNU) as part of the module run by Dr. Aocheng Tang , Assitant Professor at ECNU's Department of Economics and Management and IIPM Lab alumni. This year, at ECNU he started teaching the first ever...