SOC

Workshop on Future Computing (WFC)

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The continuous advances in computing are reshaping the entire education system, and eventually all disciplines and industries worldwide, under the rapid development in machine learning algorithms, AI and neuromorphic computing, quantum computing, etc.

Workshop on Future Computing invites experts and leaders from academia, industry, and the public sector to share, elaborate, and discuss critical issues, developments, breakthroughs and new perspectives in future computing, including theories, methodologies, architectures, systems, applications, social implications, etc. The annual WFC is organized by Miin Wu School of ComputingSOC, NCKU, and the 1st WFC was held last year and very well received by attendees.

Topics of the workshop this year include Computing Architecture, high-performance & memory-centric computing, AI Robotics, Computational Biomedicine, AI-Assisted Healthcare, AI and Intelligent Mobility, Splendid AI Applications, and visions on future computing.

Summer Summit

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Miin Wu School of Computing aims to cultivate interdisciplinary and innovative talents with specific domain knowledge and computing expertise. Accordingly, these talents can use advanced computing technology both to solve major social problems and to benefit our nation. Hence, in order to encourage outstanding scholars to lead interdisciplinary research teams and cooperate with SOC, we launched  the 2021 NCKU Miin Wu School of Computing AI Summer Summit. The research fields of this summit 2021 focus mainly on Future Computing, AI Robotics, and Computational Biomedicine. 

Highlights

Launching Ceremony of National Intercollegiate Athletic Games 2021
MOU Signing Ceremony between NCKU and NITKC
Pre-College Party for MS on AI Robotics Students

近期活動

2022 05.20
領航網通科技,賦能人工智慧
闕院長將介紹與可擴展儲能架構及管理之發展相關的技術挑戰,並描述如何將成熟的計算機系統管理技術應用於這些挑戰。
2022 05.19
開創跨域整合應用的AI拓荒者—吳誠文特聘講座教授講座暨微論壇: "Fan Engagement in a 5G Stadium with AI-Based Technologies"
想像一個截然不同的觀賽體驗--入場後戴上AR眼鏡,球員就在你眼前,賽況分析即時發送到你的裝置上…這就是未來的人工智慧運動場館,既保留現場觀賞的刺激與共感,亦享有轉播才有的沉浸式觀看體驗。這樣的應用背後需要影像處理、5G網路、運算架構等技術,是非常龐大而複雜的跨域整合計畫,未來將可複製到演唱會、音樂劇、舞台劇等場景,實現沉浸式場館體驗。 此次演講,吳誠文講座將透過2021年全大運之案例,解構其背後縝密的技術,展示基於人工智慧之5G場館的未來與前景。
2022 05.06
引領多媒體科技發展 開拓AI應用探索家—孫明廷教授講座: 「研究經驗 突破自我」
孫明廷教授是美國華盛頓大學著名的華人學者,為影像處理領域成果傑出的研究人才,在該領域佔有極重要的地位。孫明廷教授是美國華盛頓大學著名的華人學者,為影像處理領域成果傑出的研究人才,在該領域佔有極重要的地位。
2022 04.28
享譽全球人工智慧領域 台灣AI發展推手—孔祥重院士談"Don't Sell Your Youth Cheap: Become a Thinker and Think Long Term"
AI潮流席捲全球,因前人的努力,當前臺灣人才得以佔有一席之地。然而對於未來科技發展,我們的人才是否已經做好準備?透過此次演講,孔祥重院士精煉數十年經驗,與年輕學子分享長遠思考的重要性與方法,勉勵成大師生養成深度思考的習慣,培養超越十年的長期競爭力。
2022 04.22
Seminar: Learning without Labeling for Visual Applications
Supervised training with deep Convolutional Neural Networks CNNs has achieved great success in various visual recognition tasks. However, it requires large amount of well-annotated data. Data labeling, especially for large-scale image dataset, is very expensive. How to learn an effective network without the need of training data labeling has become an important problem for many applications.
2022 04.15
一代宗師—從棒球國手到AI拓荒者 吳誠文講座談"人工智慧與運動科技發展"
隨著人工智慧與大數據發展成熟,近年來整體運動科技發展快速,自近年研究與應用成果,可以預見科技將推動賽事活動轉播、運動員訓練發展。2021年成大全大運運用以人工智慧強化之運動科技,展示多項前瞻運動科技運用,包括球路落點與軌跡分析、擴增實境AR應用於社群媒體影像串流、以5G及MEC實現3D實況轉播,以及基於人工智慧的運動數據分析等。在這場演講中,吳誠文講座將介紹運動科技相關技術、未來前景與挑戰。
2022 04.14
AI 趨勢跨域論壇II:Data-driven for fault detection and diagnosis
The development of information technology and process technology have been enhanced the rapid changes in high-tech products and smart manufacturing, specifications become more sophisticated. Large amount of sensors are installed to record equipment condition during the manufacturing process. In particular, the characteristics of sensor data are temporal. Most the existing approaches for time series classification are not applicable to adaptively extract the effective feature from a large number of sensor data, accurately detect the fault, and provide the assignable cause for fault diagnosis. This talk presents different methods for fault detection and diagnosis and also extends the topics related to prognostic and health management.
2022 03.17
AI 趨勢論壇 II:選擇權資金管理與量化策略建構
本研究基於資金管理概念,提出具固定停損或停利機制的選擇權賣方與價差交易策略,藉由停損機制對最大獲利及損失進行量化,降低產生超額虧損的風險。本研究透過傳統統計方法及隨機森林演算法對勝率進行估計,採用熱點圖對預測結果進行視覺化,同時考量勝率門檻及穩固 性擷取有利可圖的交易區間,並以混淆矩陣、Accuracy 及 Precision 等指標評估模型效能。實驗結果顯示,本研究建構之隨機森林預測模型對所提出交易策略擁有相當優秀的預測能力Precision 最高達 0.9,能夠有效達成資金管理及風險管理之目標。