A man wearing many hats. I am an accomplished technology executive and academic with extensive experience in leading data and software engineering teams and conducting cutting-edge research. With experience at leading companies such as Rakuten and Yahoo!, I have successfully contributed to reducing overstock rates, improving platform reliability, and building recommendation systems for enhancing customer satisfaction through my expertise in machine learning, forecasting, and backend development, among others. As Chief Technology Officer at Wavenet Inc., I am responsible for developing and delivering high-quality products, managing the development process, and ensuring that products are delivered on time and to the highest possible standard. As an associate professor at the Department of Management Information Systems, National Chung Hsing University, I conduct innovative and impactful research in the fields of intelligent traffic systems, AI-empowered Design, Fintech, spatiotemporal database, big data anayltics, deep reinforcement learning, data mining and artificial intelligence. I was served as a visiting professor at the Living Analytics Research Centre at Singapore Management University, where they conducted research on smart cities and developed valuable networks with scholars from around the world.

Contact Information

• E-mail: smalloshin[at]nchu.edu.tw
• Tel: +04-2284-0864#668
• Office: R688 College of Management, Department of Management Information Systems, National Chung Hsing University (145 Xingda Rd., South Dist., Taichung City 402, Taiwan)

Recruiting

• We are currently looking for both master’s and undergraduate students who are enthusiastic about learning data science, machine learning, deep learning, and interested in exploring the applications of AI in various fields such as intelligent transportation systems, smart cities, and AI-empowered design. If you are passionate about these areas and would like to join our team, please do not hesitate to email us to discuss potential opportunities.

What’s New

• Our paper A Lightweight and Accurate Spatial-Temporal Transformer for Traffic Forecasting is accepted by IEEE Transactions on on Knowledge and Data Engineering.