學歷
2003 國立台灣大學電機工程系博士

研究專長
資料探勘
資訊檢索
機器學習

經歷
2004年8月~2011年7月 國立成功大學醫學資訊研究所助理教授
2011年8月~2014年7月 國立成功大學醫學資訊研究所副教授

Connyn Chang received the MSc degree in ICMA Centre, Henley Business School from University of Reading, U.K. She’s currently Treasury VP in Global Capital Market at CTBC Bank, as well as the Executive Director & CSO of Taiwan Artificial Intelligence Association (TAIA) and a PhD student in the Department of Computer Science & Information Engineering, NCU. She joined Taiwan AI Academy (AIA)’s Executive Program in Artificial Intelligence in 2019 and FinTech Program in 2022, organizing various events for all of the alumni since 2019. She also holds the certificate of Microsoft Certified Azure AI Fundamentals and the certificate in structured finance from UC Irvine.

As derivatives PM at the trading floor and top financial presentation/infographic designer, Connyn’s expertise is to convert and visualize big data in financial derivatives & global capital markets into useful info with aesthetics. In recent years, she leads many projects of TAIA, such as 2020 AI in Taiwan Hackathon, a series of AI Hub x AI Day events, etc. She has served as the moderator in Taiwan’s biggest AI forum - AI Academy Annual Conference, 2021 UK-Taiwan AI+ Smart Manufacturing International Online Conference, 2022 USA-Taiwan AI+ Smart Manufacturing International Online Conference, and the bilingual hostess in the Toastmasters D67 annual conference.

This research focuses on the challenges faced by Small and Medium Enterprises (SMEs) manufacturers in adopting AI technologies. Despite their successful decades-long operations, SMEs are seeking ways to leverage AI for enhancing product value and manufacturing efficiency. However, the lack of resources and collaborative development talent in AI technology presents a significant barrier.

To address these challenges, the study proposes a shared AI software platform where SMEs can utilize AI from design to operation, collaborate with each other, share resources through open-source, and add proprietary features for their businesses.

Specifically, the research aims to establish a lathe machining quality and tool damage diagnostic system using AI models. This system is expected to predict machining errors and tool damage, ensuring quality control without extensive manual inspection, reducing inspection costs, and increasing tool lifespan. The goal is to cater to the current machining demands of small batches with quick changeovers, overcoming the lack of versatility in existing technologies.

律師，專注於創新科技、開放資料、開放政府等數位治理議題及相關法律規範。2012 年以來持續參與 g0v 公民科技社群，從中習得「揪團打怪」技能：多方協作推動社會創新。

2017 年協助設立台灣人工智慧學校基金會，2021 年起擔任秘書長，推動課程轉型及開源 AI 平台「風火輪計畫」。

2020-2022 年擔任立法院開放國會委員會民間委員，推動完成台灣立法院首份「開放國會行動方案」。近來與台灣公民社群夥伴協作推動「數位公民素養」行動計畫作為台灣新世代社會基礎建設。