講者

Taiwan's Opportunities in the AI-First World

簡立峰 / 總經理 / Google Taiwan
Lee-Feng Chien is Managing Director and Engineering Site Director for Google Taiwan. He leads the operation and development of Google's engineering effort in Taiwan, and is an engineering lead of ChromeOS Product Area for APAC. He is also known for his work on Chinese search and language processing, and has researched Chinese parsing systems, language models, dictation machines, and search engineering technology for many years. Prior to Google, he was research fellow and deputy director of the Institute of information Science, Academia Sinica, Taiwan, and also jointly appointed as a professor of the Information Management Department of National Taiwan University. He received his Ph.D. in CS&IE from National Taiwan University in 1991.

Representation Learning on Big and Small Data

張智威 (Edward Y. Chang) / President / HTC Research & Healthcare

Edward Chang currently serves as the President of Research and Healthcare (DeepQ) at HTC. Ed's most notable work is co-leading the DeepQ project (with Prof. CK Peng at Harvard), working with a team of physicians, scientists, and engineers to design and develop mobile wireless diagnostic instruments. Such instruments can help consumers make their own reliable health diagnoses anywhere at any time. The project entered the Tricorder XPRIZE competition in 2013 with 310 other entrants and was awarded second place in April 2017 with 1M USD prize. The deep architecture that powers DeepQ is also applied to power Vivepaper, an AR product Ed's team launched in 2016 to support immersive augmented reality experiences.

Prior to his HTC post, Ed was a director of Google Research for 6.5 years, leading research and development in several areas including scalable machine learning, indoor localization, social networking and search integration, and Web search (spam fighting). His contributions in parallel machine learning algorithms and data-driven deep learning (US patents 8798375 and 9547914) are recognized through several keynote invitations and the developed open-source codes have been collectively downloaded over 30,000 times. His work on IMU calibration/fusion (US patents 8362949, 9135802, 9295027, 9383202, and 9625290) with project X was first deployed via Google Indoor Maps (see XINX paper and ASIST/ACM SIGIR/ICADL keynotes) and is now widely used on mobile phones and VR/AR devices. Ed's team also developed the Google Q&A system (codename Confucius), which was launched in over 60 countries.

Prior to Google, Ed was a full professor of Electrical Engineering at the University of California, Santa Barbara (UCSB). He joined UCSB in 1999 after receiving his PhD from Stanford University. He is a recipient of the NSF Career Award and Google Innovation Award. He is also an IEEE Fellow for his contributions to scalable machine learning.

AlphaGo-深度學習與強化學習的勝利

黃士傑 / Research Scientist / Google DeepMind
AlphaGo 首席工程師。畢業於國立台灣師範大學資訊工程研究所,現在是 Google DeepMind 的資深研究員。

Big Data Visualization

馬匡六 / Professor / University of California at Davis
馬匡六,現任美國加州大學戴維斯分校電腦工程系教授兼研究所主任,並領導一個 25 名研究員的團隊 (VIDI Labs)。 馬教授於 1993 年在美國猶他大學獲得電腦科學博士學位後,加入美國太空總署 Langley 研究中心擔任研究員,1999 年成為加州大學副教授。馬教授的研究興趣廣泛,主要在可視化,高性能計算,交互式技術之開發,整合及應用。 他因為在研究方面的傑出貢獻,於 2000 年獲得美國總統青年科學家獎 (PECASE),2012 年獲選美國電子電機工程師協會院士,又於 2013 年獲頒可視化研究領域最高榮譽的計術成就獎。 他目前是台大資工的客座教授,交大資工的榮譽教授,並参與中研院的研究計劃。

Detecting Rumors and Fake News Online

Meeyoung Cha / Associate Professor / KAIST School of Computing
Meeyoung Cha is an associate professor at School of Computing in KAIST. Her research interests are in the analysis of complex network systems including online social networks with emphasis the spread of information, moods, and user influence. She received the best paper awards at ACM IMC 2007 for analyzing long-tail videos in YouTube and at ICWSM 2012 for studying social conventions in Twitter. Her research has been published in leading journals and conferences including PLoS One, Information Sciences, IJCAI, WWW, and ICWSM, and has been featured at the popular media outlets including the New York Times websites, Harvard Business Review’s research blog, the Washington Post, the New Scientist. Dr. Cha has worked at Facebook's Data Science Team as a Visiting Professor for a year.

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