演講者陣容

As the Engineering Director, Jason Ma oversees Google/ChromeOS Taiwan's growth, business management and development, as well as leads multiple R&D projects across the board. Before taking this leadership role at Google Taiwan, Jason was a Platform Technology and Cloud Computing expert in the Platform & Ecosystem business group at Google Mountain View, CA.  In his 15 years with Google, Jason has successfully led strategic partnerships with global hardware and software manufacturers and major chip providers to drive various innovations in cloud technology. These efforts have not only contributed to a substantial increase in Chromebook's share in global education, consumer and enterprise markets, but have also attracted global talents to join Google and its partners in furthering the development of hardware and software technology solutions/services.

Prior to joining Google, Jason served on the Office group at Microsoft Redmond, WA.  He represented the company in a project, involving Merck, Dell, Boeing, and the United States Department of Defense, to achieve solutions in unified communications and integrated voice technology. In 2007, Jason was appointed Director of the Microsoft Technology Center in Taiwan. During which time, Jason led the Microsoft Taiwan technology team and worked with Intel and HP to establish a Solution Center in Taiwan to promote Microsoft public cloud, data center, and private cloud technologies, connecting Taiwan's cloud computing industry with the global market and supply chain.

Before joining Microsoft, Jason was Vice President and Chief Technology Officer at Soma.com. At Soma.com, Jason led the team in designing and launching e-commerce services, and partnered with Merck and WebMD on health consultation services and over the counter/prescription drugs/services. Soma.com was in turn acquired by CVS, the second largest pharmacy chain in the United States, forming CVS.com, where Jason served as Vice President and Chief Technology Officer and provided solutions for digital integration.

Jason graduated from the Department of Electrical Engineering at National Cheng Kung University, subsequent which he moved to the United States to further his graduate studies.  In 1993, Jason obtained a Ph.D. in Electrical Engineering from the University of Washington, with a focus in the integration and innovation of power systems and AI Expert Systems.  In 1997, Jason joined the National Sun Yat-sen University as an Associate Professor of Electrical Engineering. To date, Jason has published 22 research papers and co-authored 2 books.  Due to his outstanding performance, Jason was nominated and listed in Who's Who in the World in 1998.

Heng-Tze Cheng is Research Director & Principal Research Scientist at Google DeepMind, Gemini Team, focusing on Large Language Models and Generative AI research. Heng-Tze has been leading a series of major leaps in Gemini Post-Training Research, Thinking, Reasoning, and Coding. Before Gemini, he led the LaMDA project, Google's breakthrough Conversational AI with high quality, factuality, and safety. He also co-founded Google Bard from Day 1, launched it within in 100 days, and helped grow it into Gemini App. Formerly on the Google Brain team, he founded and led Mixel Task-oriented Dialog Research, enabling 10+ new and improved dialog products in Duplex Assistant, Search, Maps, and Cloud. 

Previously, he founded and led Wide & Deep Learning, which was cited 4600+ times, open-sourced as an official model in TensorFlow and Google Cloud, and widely adopted across the industry. He also helped build large-scale end-to-end machine learning platforms, including Sibyl and TFX. Since 2015, he and his team have delivered 100+ product innovations and improvements through machine learning research across YouTube, Assistant, Google Play, Ads, and more. 

Prior to Google, he received his Ph.D. from Carnegie Mellon University in 2013, and B.S. from National Taiwan University in 2008.

Shuo-Yiin Chang is a Senior Staff Research Scientist at Google DeepMind. He leads Gemini Multimodal Video and Audio-Visual workstream. His work is centered on Google's core foundational large language models, Gemini, and the universal AI assistants, Astra and Gemini Live. He received the IEEE Signal Processing Society Best Paper Award in 2024. Prior to Google, Shuo-Yiin completed his Ph.D. in EECS at the University of California, Berkeley.

 Kuang-Huei Lee is a Staff Research Scientist at Google DeepMind, focusing on reinforcement learning, agentic systems, and generative models. His research drives significant advancements in Google's robotics, TPU, and Veo projects. Before joining Google in 2019, he was a computer vision researcher at Microsoft. His work is widely published in top-tier conferences in machine learning (NeurIPS, ICML, ICLR), robotics (RSS, CoRL, IROS), computer vision (CVPR, ECCV), and NLP (EMNLP), including a CoRL Special Innovation Award and an IROS Best Paper Finalist. He has also been serving as area chair for ICLR and NeurIPS. Kuang-Huei earned his graduate degree from Carnegie Mellon University and his undergraduate degree from National Taiwan University.

研究專長：語言理解、對話系統、機器智慧、自然語言處理 

Chen was born in Taipei, Taiwan. She earned a Ph.D. degree in the Language Technologies Institute (LTI) of School of Computer Science (SCS) at Carnegie Mellon University (CMU) in 2015. Chen also holds an M.S. degree in Language Technologies from CMU SCS, and B.S. and M.S. degrees in Computer Science & Information Engineering (CSIE) from National Taiwan University (NTU).

Chen's research interests mainly focus on spoken language understanding, machine intelligence, spoken dialogue system, multimodal application, natural language processing, and deep learning. She fortunately received Google Faculty Research Award, AWS Machine Learning Research Awards, Best Student Paper Awards at IEEE ASRU 2013 and IEEE SLT 2010, a Best Student Paper Shortlist at ISCA INTERSPEECH 2012, and the Distinguished Master Thesis Award from ACLCLP. 

個人網站：https://www.csie.ntu.edu.tw/~yvchen/

研究領域：Machine Learning、Deep Learning、Computer Vision、Signal Processing

Chien-Yao Wang received the Ph.D. degree in Computer Science and Information Engineering from National Central University, Zhongli, Taiwan, in 2017. He is currently an Assistant Research Fellow with the Institute of Information Science, Academia Sinica, Taiwan. His research interests include signal processing, deep learning, and machine learning. Currently, his research focuses on multi-task representation learning for multi-modal signal. 

個人網站：https://wongkinyiu.github.io/