Publisher: University of Macau Chief Editor: Katrina Cheong Deputy Chief Editor: Ella Cheong Editors: Davis Ip, Debby Seng Translators: Winky Kuan, Bess Che Designer: Jack Ho Advisors: Li Defeng, Associate Dean, Faculty of Arts and Humanities / Distinguished Professor and Director, Centre for Studies of Translation, Interpreting and Cognition Lampo Leong, Distinguished Professor and Director, Centre for Arts and Design, Faculty of Social Sciences Timothy Simpson, Associate Professor, Department of Communication, Faculty of Social Sciences Tang Keng Pan, Professor Emeritus, Department of Chinese Language and Literature, Faculty of Arts and Humanities Address: Room G012, Administration Building (N6), University of Macau, Avenida da Universidade, Taipa, Macau, China Tel: (853) 8822 8833 Fax: (853) 8822 8822 Email: prs.publication@um.edu.mo Printing: Mindblowing Film Culture Co.,Ltd. ISSN: 2077‑2491 Certain images are sourced from Shutterstock Published biannually since 2009, UMagazine is one of the University of Macau’s official publications and aims to report innovative ideas and research breakthroughs of the University of Macau. It also showcases the latest developments and achievements of the university in teaching, research, and community services. 出版: 澳門大學 總編輯: 張惠琴 副總編輯: 張愛華 編輯: 葉浩男、盛惠怡 翻譯: 關詠琪、謝菀菁 排版: 何杰平 顧問: 人文學院副院長、翻譯傳譯認知研究中心主任 李德鳳特聘教授 社會科學學院藝術設計中心主任 梁藍波特聘教授 社會科學學院傳播系副教授 Timothy Simpson 人文學院中國語言文學系榮休教授 鄧景濱 地址: 中國澳門氹仔大學大馬路 澳門大學行政樓(N6) G012室 電話: (853) 8822 8833 傳真: (853) 8822 8822 電郵: prs.publication@um.edu.mo 印刷: 顱影像文化有限公司 國際刊號: 2077‑2491 部分圖片來自Shutterstock 《澳大新語》創於2009年，為澳門大學官方刊物之一， 每年出版兩期，旨在展示澳門大學的創見和突破、 報導教研和社會服務的最新發展和成果。 2023年|總第28期 Autumn/Winter 2023 | Issue 28
在大數據技術為全球各行各業帶來變革之際，澳門 大學培養數據專才，深化跨學科研究，並且推動數據 科學應用於日常生活和工作。我們引領讀者進入本 期精彩內容，將封面專題放在澳大協同創新研究院 數據科學中心與各學院的合作上，揭示它們如何推 進數據科學在人工智能應用、市場營銷分析、金融科 技、數據戰略與合規管理、精準醫學、計算語言學、教 學分析及智慧政務等八大領域的應用與創新。 在「專題探討」欄目，我們介紹澳大的澳門先進材料 研發中心，探討其如何推進澳門新材料產業邁向綠 色、低碳、精細及節約的未來，同時向讀者介紹四項 環保科研項目，展示澳大在可持續發展領域的努力。 本期也專訪了兩位教授，分別是藝術與設計系主任 李軍和英文系教授Nick Groom。李軍教授分享他對 藝術史及文藝復興時期藝術作品的獨特見解，Nick Groom教授則暢談他的文學研究心路歷程。 在「學術研究」投稿欄目，澳大學者探討中國投資者 在歐盟面臨的挑戰、機器人能否激勵人類，以及電子 皮膚技術的潛在應用，這些研究突出了澳大學者在 探索當今社會重要問題方面的努力。最後，我們帶領 讀者了解何鴻燊東亞書院和霍英東珍禧書院學生的 社會服務成果。 我們期待本期《澳大新語》為讀者帶來新的視野和啟 發，一起探索知識的無限可能。 In an era where big data technologies transform global industries, the University of Macau (UM) has made strides in cultivating data professionals, fostering interdisciplinary research, and integrating data science into both personal and professional spheres. In this issue of UMagazine, we spotlight the collaboration between UM’s Centre for Data Science and various faculties within the university, delving into their endeavours in artificial intelligence applications, marketing analytics, financial technology, data strategy and compliance, precision medicine, computational linguistics, analytics in teaching and learning, and smart governance. In this issue’s Topic Insight, our focus shifts to the Macao Centre for Research and Development in Advanced Materials at UM. We examine the centre’s role in shaping a more environmentally conscious and efficient new materials industry in Macao. In addition, we highlight four research projects that illustrate the university’s commitment to sustainable development. We have also interviewed two professors, Prof Li Jun in the Department of Arts and Design, and Prof Nick Groom in the Department of English. Prof Li talks about the captivating realm of art history and the Renaissance, while Prof Groom shares his experience in literary research. Within the pages of Academic Research, UM scholars unravel the challenges faced by Chinese investors in the EU, examine whether robots can inspire humans to do good deeds, and shed light on the potential applications of electronic skin technology. These studies not only showcase UM’s commitment to scholarly pursuits but also underscore its efforts to address some of the most pressing issues of our time. Lastly, we introduce the social services provided by the students of Stanley Ho East Asia College and Henry Fok Pearl Jubilee College. We believe this issue of UMagazine will provide fresh perspectives about timely social issues. Together, let us embark on a journey to explore UM’s contribution to the pursuit of knowledge. 編者的話 張惠琴 Katrina Cheong EDITOR’S WORDS
CONTENTS 目錄 2023年|總第28期 Autumn/Winter 2023 | Issue 28 封面專題 COVER STORY Weaving Innovation Roadmaps With Data 解讀數據 編織創新藍圖 數據科學推動社會進步 Improving Society Through Data Science 05 拓展人工智能應用 Applying AI in Novel Ways 11 數據引領精準營銷 Marketing to Minds With Data 13 釋放大數據的金融價值 Extracting Financial Value From Big Data 15 從數據合規建立信任 Building Trust Through Data Compliance 17 數據指引精準醫療 Crafting Tailored Cures Through Data 19 構築人與機器的共同語言 Developing a Common Language for Humans and Machines 21 數據科學推動個性化教育 Data Science Driving Personalised Education 23 運用數據提升公共服務 Leveraging Data to Enhance Public Services 25
專題探討 TOPIC INSIGHT Transforming Innovative Materials Into Life-Improving Products 將創新材料轉化成改善生活的產品 27 Fuelling Green Innovation With Pioneering Technology 嶄新科技推動綠色創新 33 人物專訪 EXCLUSIVE INTERVIEW 李軍：藝術是心與手構築的理想世界 Li Jun: Art is an Ideal World Crafted by Heart and Hands 39 Nick Groom：引領學生尋找經典文學的價值 Nick Groom: Leading Students to Discover the Value of Classic Literature 45 在歐盟戰略自主下，中國投資者將會面臨甚麼？ The European Union’s Strategic Autonomy: What Does It Mean for Chinese Investors? 51 WALL-E與現實：為何災難應對機器人不能激勵我們 WALL-E vs. Reality: Why Disaster Response Robots Don’t Inspire Us 55 電子皮膚——未來的可穿戴人機交互界面 Electronic Skin: Wearable Interactive Interface for the Future 59 學術研究 ACADEMIC RESEARCH 書院發展 RC DEVELOPMENT 何鴻燊東亞書院多元與持續性並重的社會服務 Diversity and Sustainability of Social Services at Stanley Ho East Asia College 63 愛的果實是服務，服務的果實是成長——霍英東珍禧書院服務學習項目 The Fruit of Love Is Service; the Fruit of Service Is Growth: Henry Fok Pearl Jubilee College’s Service-Learning Programmes 67
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 5 數據科學推動社會進步 Improving Society Through Data Science 文 / 葉浩男‧圖 / 何杰平、編輯部 Chinese & English Text / Davis Ip ‧Photo / Jack Ho, Editorial Board 在每次點讚、每筆買賣甚至每次心跳都可化為數據 記錄下來的今天，澳門大學的專家和學生正在將數 據化為實用見解，涵蓋人文、工商管理、教育、健 康科學、法學、科技和社會科學等領域，觸及全校 所有學院，不僅引發學術創新，也對澳門和其它地 區的進步有所貢獻。 以數據規劃未來 「現在的時間與過去的時間，或許皆是未來的時間。」 從詩人T·S·艾略特這句話，我們或可領略到數據的 關鍵之處。它們不只是歷史的殘跡，也是解讀當下和 規劃未來的要素。澳大協同創新研究院數據科學研 究中心主任余亮豪教授指出：「科技進步使數據能不 僅能反映事物和環境，也成為推動創新的重要力量。 無論是數字、文字、圖像、聲音或影像，各類數據都促 使我們取得了十年前難以想像的科技突破。」 余亮豪是電腦及資訊科學系副教授，研究專長包括大 數據處理與強化學習。他表示，數據科學家不斷開發 新方法來更有效地解讀數據，獲得新的洞見。「這個領 域融合統計、數據分析、機器學習與計算機科學，可在 我們日常生活與工作中廣泛應用。此外，機器學習與 數據科學密不可分。機器學習主要是指電腦算法通過 數據來學習，提升執行任務的效能，其進展也能反過 來提高收集和分析數據的效率。」 新一代數據科學家 數據科學研究中心與澳大七所學院合辦理學碩士學 位（數據科學）課程，是澳門首個跨學科大數據課程， 自2019年8月推出起報讀人數逐年攀升。學生須從
澳大新語 • 2023 UMAGAZINE 28 6 封面專題 • COVER STORY 八個專業範疇中選擇其一，分別是人工智能應用、市 場營銷分析、金融科技、數據戰略與合規管理、精準 醫學、計算語言學、教學分析和智慧政務。 學生須修讀由澳大科技學院開設的四門基礎科目，學 習數據科學編程、數據可視化、數據庫技術、機器學習 工具的知識與技能，並且選修四門屬於其專業範疇、由 相應學院開設的科目。他們亦會探討從數據使用與收 集而衍生的私隱、安全和倫理問題，研究數據科學技術 對社會各方面的影響。 余教授說：「每名學生畢業前要完成一個研究項目，融 會數據科學技巧與專業範疇知識。畢業生可望在各行 各業擔任數據工程師、分析師或科學家等。」 跨學科數據研究 除了促進教育，數據科學研究中心也是一個跨學科研 究平台，有16名來自各學院的成員參與研究。其中，該 中心聯合法律與資訊技術領域的專家，探究科技在私 隱保護上的角色、發展相應的科技和提出政策建議。 中心的學者還結合健康科學、科技和藥物方面的研 究，開發針對罕見疾病和常見癌症的精準療法。 在澳門積極發展現代金融業之際，數據科學研究中心也 扮演支持角色，透過數據分析和研究促進金融業發展， 包括以大數據技術開創嶄新的應用、流程、產品和商業 模式。該中心也協助澳大各學院在語言學、公共行政和 數據合規等領域應用數據科學。余教授指出：「新冠疫情 期間，我們中心的研究人員設計了澳門新冠疫情數據可 視化系統，協助市民了解和應對疫情變化。」 在教育與研究以外，中心也促進跨學科對話與合作， 例如曾舉辦關於跨境數據使用的圓桌會議和學生治 理數據分析比賽。2023年9月，中心還主辦「第一屆 澳門數據科學研討會」，匯聚大數據處理、市場營銷 分析、精準醫學、智慧政務等多領域的專家。 解讀和改善社會 社會現象複雜多變，過去缺乏全面和系統的預測方 法，但數據科學的進步正帶來轉變。社會科學學院副 院長、社會學系主任蔡天驥教授是數據科學研究 中心的成員，不斷開展計算社會科學研究：「我有兩 個主要研究方向，首先是運用數據科學來解決社會 問題，其次是將預測性分析融入社會科學研究。在數 據能實時更新的今日，我們也可實時驗證社會現象 預測的準確性。」 蔡教授說，數據與機器學習模型在提供及研究公共
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 7 服務上已不可或缺。例如，他在近年一項關於預測澳 門固體廢物量增長的研究中，開發了多種機器學習模 型，發現「廣義加性模型」的預測最為精確。「澳門固體 廢物來源眾多，受家庭結構、遊客流量和建築業發展 的影響，人均固體廢物量在世界前列，遠超香港、上海 和新加坡等地。」 蔡教授進一步指出，澳門家庭結構的變化與少子化不 僅會影響未來的廢物總量，亦會改變廢物種類的比例： 「一些小家庭，特別是沒有子女的家庭，可能常常點 外賣，而非在家裡煮飯，塑膠餐具用量因此增加。」他 期望開發更全面的模型，預測廢物總量及各類廢物的 數量，協助規劃廢物分類與處理設施。 探究傳播過程 數據科學也深化了我們對個人和群體溝通的認識。傳播 系講座教授、數據科學研究中心成員趙心樹致力運用大 數據分析方法探索傳播學議題。他說：「在網絡發達的 今日，人們可獲得豐富和即時的資訊，但也更容易只接 收到與自己觀點相符的資訊，這可能使大眾意見愈趨分 歧。研究這些問題時必須借助大數據作精確分析。」 趙教授進一步說，在社交媒體環境中，資訊的發佈、 接收和轉發都會形成「選擇螺旋」：「在我們研究的 內地社交媒體平台，帖文發佈者在初期的『選擇螺 旋』中較能主導螺旋的走向，但後來的螺旋會愈來 受點讚、轉發及讀者的偏好影響，形成網絡輿論的『 同音效應』。」 在近年一項研究中，趙教授等學者透過大數據技術 收集和分析社交媒體帖文，了解標題長度對點讀率 和點轉率的影響。研究發現，點讀群體偏好中等長度 的標題，約28字為最佳；但點轉群體傾向更短的標 題，最好不過20字。「這些發現有助我們理解內地網 絡輿論，也為市場推廣提供參考。」 各行各業應用數據科學 數據科學不僅串聯過去、現在和未來，也能連接不同 的人物和事物。余亮豪教授指出：「透過充分的跨學 科合作，數據科學研究中心正在培養新一代數據科 學家，並且廣泛開展跨學科研究，推動深度知識探索 和建立預測機制與模型，引導數據科學在生活各層 面的應用，提升新興科技產業發展，貢獻社會。」 澳大舉辦第一屆澳門數據科學研討會 UM hosts the 1st Macau Symposium on Data Science
澳大新語 • 2023 UMAGAZINE 28 8 封面專題 • COVER STORY In an era where every swipe, purchase, and heartbeat can be catalogued as data, the University of Macau (UM) is seizing this opportunity to transform data into actionable insights. Such efforts are evident across UM faculties, encompassing disciplines from the humanities to business, education, health sciences, law, social sciences and technology. By doing so, the university is not merely fuelling academic innovation but also contributing to social progress in Macao and beyond. Planning the Future Through Data ‘Time present and time past. Are both perhaps present in time future.’ These words from poet T.S. Eliot encapsulate the essence of data. Far more than a historical artefact, data can serve as a lens through which we interpret the present and shape the future. Prof U Leong Hou Ryan, head of the Centre for Data Science (CDS) at UM’s Institute of Collaborative Innovation (ICI), explains, ‘Technological advancements allow data not only to represent our world, but also to act as a catalyst for innovation. Whether it is numerical, textual, visual, auditory, or video-based, data has enabled technological leaps that were not imaginable at all just a decade ago.’ Prof U, associate professor in the Department of Computer and Information Science who specialises in big data processing and reinforcement learning, says that data scientists are developing new techniques to extract insights from data. ‘The field of data science is an amalgamation of statistics, data analytics, machine learning and computer science. It is widely used in our daily life and work,’ he says. ‘Moreover, data science and machine learning are closely related. The latter refers to the process in which algorithms learn primarily from data to enhance task performance. Therefore, advancements in machine learning have in turn improved our efficiency in data collection and analysis.’ The Next Generation of Data Scientists In collaboration with seven UM faculties, CDS offers a Master of Science in Data Science programme—the first interdisciplinary programme in big data in Macao. The programme has attracted increasing numbers of applications since its launch in August 2019. Students in this programme are required to specialise in one of these eight areas: artificial intelligence applications, marketing analytics, financial technology, data strategy and 余亮豪教授 Prof U Leong Hou Ryan compliance, precision medicine, computational linguistics, analytics in teaching and learning, and smart governance. The programme has four fundamental courses. They are delivered by UM’s Faculty of Science and Technology and equip students with skills in data science programming, data visualisation, database technology, and machine learning tools. In addition, students take four courses under their chosen specialisation offered by the related faculties. Throughout their studies, students may also explore the privacy, ethical, and safety issues arising from the collection and use of data, thereby delving into the broader impact of data science technologies on society. Each student must complete a research project that integrates data science with their area of specialisation before they can graduate. Prof U says, ‘Graduates are well-positioned to work as data engineers, analysts, and scientists in a variety of sectors.’ Interdisciplinary Data Research Beyond educational initiatives, CDS also serves as a platform for interdisciplinary research. Currently, the centre has 16 members from various UM faculties who engage in a wide range of research activities. For example, CDS collaborates with experts in law and information technology to study the role of technology in privacy protection, thus developing related technologies and offering
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 9 policy recommendations. As an interdisciplinary platform, members also integrate research in health sciences, technology, and pharmacology to develop precision medicine solutions for rare diseases and common cancers. As Macao develops a modern finance industry, CDS plays a supporting role by leveraging data analysis for the benefit of the industry. This includes using big data technologies to pioneer new applications, processes, products, and business models. Moreover, the centre has helped different UM faculties apply data science in fields such as linguistics, public administration, and data compliance. Prof U adds, ‘During the COVID-19 pandemic, our research team developed a data visualisation system which helped the Macao public better understand and adapt to the changing situation.’ Aside from its contributions to education and research, CDS also fosters interdisciplinary discussion and collaboration. For example, it has hosted roundtable discussions on cross-border data usage and organised data analysis competitions. Additionally, in September 2023, the centre hosted the 1st Macau Symposium on Data Science, which gathered experts from diverse fields including big data processing, market analytics, precision medicine, and smart governance. These initiatives have reinforced its role as a platform for interdisciplinary innovation and scholarly exchange. Deciphering and Improving Society Given the complexity of social phenomena, it is difficult to make comprehensive and systematic predictions about the future development of society. However, the rise of data science is changing this landscape. Prof Cai Tianji, associate dean in the Faculty of Social Sciences and head of the Department of Sociology, is a member of CDS. He is dedicated to research in computational social science. Prof Cai explains, ‘My research is twofold. First, I use data science to tackle social issues. Second, I integrate predictive analytics into social science research. With the availability of real-time data updates, we can now also verify the accuracy of predictions about social phenomena in real time.’ Prof Cai elaborates that data and machine learning models have become crucial in both the provision and study of public services. For example, in a recent research project focused on predicting the growth of solid waste in Macao, Prof Cai developed multiple machine learning models and found that ‘Generalised Additive Models’ made the most accurate predictions. He says, ‘Macao ranks among the top in the world in terms of per capita solid waste generation, outpacing Hong Kong, Shanghai, and Singapore. The sources of solid waste in Macao are varied and influenced by factors such as family structure, tourist influx, and construction activity.’ Prof Cai further explains how changes in family 數據科學研究中心於2019/2020學年起開設理學碩士學位（數據科學）課程 The Centre for Data Science introduced a Master of Science in Data Science programme in the 2019/2020 academic year
澳大新語 • 2023 UMAGAZINE 28 10 封面專題 • COVER STORY structure and the declining birth rate in Macao will affect the proportion of waste types, in addition to affecting the overall amount of waste. ‘For instance, smaller households, especially those without children, are more likely to order takeaway food than cooking at home, thereby increasing the use of plastic utensils,’ he notes. In view of this, Prof Cai hopes to develop more robust models to predict the overall amount of waste and the amount of each type of waste, which can help with the planning of waste sorting and processing facilities in Macao. Exploring Communication Processes Data science enhances our understanding of communication, whether between individuals or groups. Zhao Xinshu, chair professor in the Department of Communication and a member of CDS, employs big data analytics in communication studies. He says, ‘In today’s digital age, people have ready access to abundant real-time information. However, there’s a significant caveat: we are increasingly likely to only receive information that aligns with our viewpoints, which may lead to wider division among the public. Rigorous big data analytics is therefore essential for exploring these issues.’ Prof Zhao expands on the concept of ‘selective spiral’, which is formed as information is disseminated, received, and reposted on social media. ‘In our examinations of social media platforms in mainland China, post creators can mostly lead the selective spiral in the initial stage. However, as the spiral continues, it will be more heavily influenced by the preferences of people who like, share, and read the post, leading to the formation of an “echo chamber” in online public opinion,’ he explains. In a recent study, Prof Zhao and his team used big data technologies to collect and analyse Chinese-language social media posts, so as to understand the impact of headline length on click-through and share rates. The study shows that readers generally prefer medium-length headlines, with a length of around 28 characters as optimal. On the other hand, sharers favour shorter headlines, with an ideal length of no more than 20 characters. ‘Such findings not only shed light on online public opinion in mainland China but also provide guidance for marketing strategies,’ he concludes. Applying Data Science Across Industries Data science serves not just as a conduit between the past, present, and future, but also as a nexus among different communities and phenomena. It fosters innovation and new methodologies in different sectors. Prof U states, ‘Through rigorous interdisciplinary collaboration, CDS is cultivating a new generation of data scientists. The centre engages in extensive interdisciplinary research to promote in-depth knowledge exploration and create predictive models. Such endeavours facilitate the application of data science in all aspects of life, thereby supporting the development of emerging technologies and making contributions to society.’ 蔡天驥教授 Prof Cai Tianji 趙心樹教授 Prof Zhao Xinshu
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 11 拓展人工智能應用 Applying AI in Novel Ways 科學）課程中的「人工智能應用」專業範疇。該專業 範疇由協同創新研究院與科技學院合辦，涵蓋計算機 視覺、自然語言處理、網絡挖掘、大數據分析及深度 學習等。 楊教授是該專業範疇的課程統籌人。他說，很多學生 都運用人工智能作有趣而實用的嘗試，2022年就有學 生用深度學習模型分析星雲圖像，識別星雲的生命週 期。目前他有兩名學生運用大型語言模型，驗證知識 圖譜中資訊的可信度。 此外，在楊教授指導下，一名數據科學碩士課程 學生和一名計算機科學碩士課程學生開發了一個系 統，通過分析一個有多座公共設施的區域內連接無 線網絡的移動裝置的時間和位置，預測該區域的每 日人流動態。該系統近來更增添新功能，能推導突 人工智能技術湧現，滲透各行各業，背後多以大量數 據為推手，而拓展人工智能的應用和培養數據科學人 才，正是澳門大學科技學院電腦及資訊科學系副教授 楊丁奇等專家的目標。 無盡創新前景 楊教授說：「人工智能近年突破不斷，包括自動駕駛 車輛進一步發展和蛋白質折疊預測系統出現，但最受 公眾關注的，莫過於ChatGPT等大型語言模型。」 楊教授是大數據專家，其中一項課題是研究構建知識 圖譜，使之更精確地儲存複雜的知識，從而準確地預 測和推理。他也致力開發圖神經網絡模型，用來分析 複雜的圖數據。 過去數年，不少人士修讀澳大的理學碩士學位（數據 文 / 葉浩男‧圖 / 何杰平 Chinese & English Text / Davis Ip‧Photo / Jack Ho
澳大新語 • 2023 UMAGAZINE 28 12 封面專題 • COVER STORY 發情境（如部分入口封鎖或火災）時的人流，成果 獲知名學術期刊刊登。 培育數據科學思維 楊教授說，一些學生畢業後擔任數據科學家、數據工 程師或人工智能課程導師，也有不少修讀博士課程， 他們不僅精通程式語言和人工智能技術，而且具備出 色的分析思維能力。「我們的畢業生面對不同領域的 問題時，都能識別所需的數據，確立想取得的結果， 然後選用合適的機器學習模型將兩者連接起來。這就 是數據科學家的思考方式。」 A new wave of artificial intelligence (AI) technology driven primarily by vast data repositories is permeating almost every industry. Yang Dingqi, associate professor in the Department of Computer and Information Science in the Faculty of Science and Technology (FST) at the University of Macau (UM), is among experts committed to cultivating talent in data science and expanding the applications of AI. Boundless Prospects for Innovation ‘Recent years have seen many breakthroughs in AI, ranging from advances in autonomous vehicles to the development of systems that predict protein folding, not to mention large language models [LLMs] like ChatGPT, which has captured the most public attention,’ says Prof Yang. Prof Yang is an expert in big data, and one of his research interests is developing new schemas for knowledge graphs. This allows for accurate storage of complex knowledge, thereby supporting more accurate predictions and inferences based on such graphs. He is also devoted to the development of graph neural network models for analysing complex graph data. Over recent years, many people have enrolled in the Artificial Intelligence Applications specialisation under UM’s Master of Science in Data Science programme. This specialisation, jointly offered by the university’s Institute of Collaborative Innovation and FST, covers topics such as computer vision, natural language processing, web mining, big data analysis, and deep learning. As the coordinator of the specialisation, Prof Yang says that many students have conducted intriguing and practical experiments in AI. In 2022, one student used deep learning models to analyse images of nebulae and identify various stages of nebula formation. Two other students are using LLMs to verify the credibility of information stored in knowledge graphs. Furthermore, under Prof Yang’s guidance, a master’s student in data science and a master’s student in computer science developed an innovative data system. The system predicts crowd movements within an area that encompasses multiple large public facilities by analysing the spatiotemporal data from mobile devices connected to wireless networks. The system has been further upgraded to predict crowd movements in emergencies such as blocked entrances or fires. A paper detailing this project has been published in a reputable academic journal. Nurturing the Data Science Mindset ‘Some graduates have moved on to become data scientists, data engineers, or AI instructors, while others are pursuing doctoral degrees,’ says Prof Yang. ‘When faced with challenges across various sectors, they excel at identifying the relevant data, determining the desired outcomes, and linking the two through machine learning models. In essence, they think like data scientists.’ 楊丁奇教授 Prof Yang Dingqi
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 13 數據引領精準營銷 Marketing to Minds With Data 銷，沿用舊有營銷模式難免流失客戶，花費雖大卻 成效不彰。「澳門以旅遊等服務業為主，必須運用 科技了解旅客不斷變化的需要，才能保持競爭力。」 數據分析工具能讓我們了解市場現象，甚至建立模型 預測動向，但探究背後原因時仍需傳統的市場學調查 與實驗。由澳大協同創新研究院與工商管理學院合辦 的理學碩士學位（數據科學）課程中的「市場分析」 專業範疇正正兼重兩者。周教授是該專業範疇的課程 統籌人。她說：「先了解市場現況，再探索背後原 因，才能制訂高效營銷策略。」 周教授說，「市場分析」專業範疇的畢業生能將數 據科學活用於商業，最近一名學生與一個大型本地 電子商貿平台合作，分析數以十萬計客戶的數據， 識別新的競爭平台出現時可能流失的客戶群，針對 消費者一舉一動早已成為企業營銷的重要數據來源。 澳門大學工商管理學院管理及市場學系副教授周詠芝 表示，營銷成功除了取決於服務和產品質素，分析市 場數據的能力同樣不可或缺。 預測消費者行為 企業營銷過去大多借助大眾媒體廣告和推銷員的技巧與 人脈，前者缺乏針對性，後者難以規模化。在社交媒體 和電子支付盛行的今天，企業很容易收集大量數據，包 括客戶的購買記錄、上網習慣、付款方式和個人資料， 從而精確、大規模地分析和預測市場，向客戶精準推 廣。周教授說：「在瀏覽器尋找一個地名，你的社交媒 體程式可能立刻推送機票廣告。」 研究消費者和服務業前線員工行為的周教授說，澳 門大型的休閒旅遊企業均廣泛運用大數據模型作營 文 / 葉浩男‧圖 / 何杰平 Chinese & English Text / Davis Ip ‧Photo / Jack Ho
澳大新語 • 2023 UMAGAZINE 28 14 封面專題 • COVER STORY 他們的消費模式開展營銷。 善用數據開拓客源 對一些業界人士來說，運用大數據營銷需時學習和適 應，但這無疑已成業界的基本要求。周教授說：「因 應趨勢，我們不斷通過教學和研究，推動業界更有效 地收集和分析數據，協助他們鞏固和開拓客源。」 While data analytics tools can reveal ‘what’ is happening in the marketplace and assist in creating predictive models, traditional marketing research methods such as experiments and surveys remain indispensable for understanding the reasons ‘why’ consumers make particular choices. The Marketing Analytics specialisation under the Master of Science in Data Science, jointly offered by UM’s Institute of Collaborative Innovation and FBA, is unique in that it encompasses both approaches. ‘The first step is to learn about the current market situation, followed by analysing the underlying dynamics. This enables us to formulate effective marketing strategies,’ says Prof Chow, who also serves as the coordinator of this specialisation. Prof Chow says that graduates of the Marketing Analytics specialisation can apply their data skills to solve real-world business challenges. For instance, a recent graduate partnered with a leading local e-commerce platform to create a system that identifies the buying habits of customers at risk of switching to a new competitor. This analysis, encompassing hundreds of thousands of customer data points, paves the way for targeted marketing initiatives. Harnessing Data for Customer Growth ‘Big data tools are fast becoming the standard in marketing, even if there’s a learning curve for some,’ Prof Chow says. ‘Recognising these industry shifts, our focus remains on advancing both education and research in the field. Our goal is to equip industries with the data skills essential for customer retention and growth.’ 周詠芝教授 Prof Cheris Chow Every consumer swipe and click is a valuable source of data for businesses eager to sharpen their marketing strategies. According to Cheris Chow, associate professor in the Department of Management and Marketing of the Faculty of Business Administration (FBA) at the University of Macau (UM), while quality products and services matter, the effective use of data is just as crucial for marketing success. Predicting Consumer Behaviour Before the big data era, companies relied on untargeted mass-media advertisements and skilled salespeople, an approach that is not easily scalable. Today, the popularity of social media and the widespread use of e-payments enable companies to collect a varied array of data, including purchase history, browsing patterns, payment methods, and customer demographics. This rich dataset allows companies to accurately analyse consumer behaviour and create customised marketing campaigns. ‘Search for a city online through a search engine, and your next social media interaction could very well show you an advertisement for flights to that destination,’ says Prof Chow. Big data models are vital to the marketing efforts of top leisure and hospitality businesses in Macao, according to Prof Chow, a researcher specialising in consumer behaviour and frontline service staff. In contrast, companies clinging to traditional marketing methods not only risk losing customers but also face inefficiencies in their advertising expenditure. ‘In a service-based economy like Macao’s, which is focused on tourism, using technology to keep up with the ever-changing needs of visitors is essential for staying competitive,’ she notes.
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 15 釋放大數據的金融價值 Extracting Financial Value From Big Data 市場不景和消費下滑之間的關聯。 因應金融業變革，澳大協同創新研究院和工商管理學 院共同開設理學碩士學位（數據科學）課程的「金融 科技」專業範疇。李教授是該專業範疇的課程統籌 人。他表示：「發展現代金融業是澳門走向經濟適 度多元發展的關鍵一環，預期未來數年澳門對數據 分析、業務分析和金融分析等方面專業人才的需求 日益增多。」 李教授續說，該專業範疇涉及人工智能、區塊鏈、雲 計算和大數據在金融業的應用。在大數據方面，學生 不僅學習收集和清洗金融大數據，亦能掌握使用決策 樹和神經網絡等機器學習模型來分析數據。「一位畢 業生今年開發了一個系統，結合多種機器學習模型， 能相當精確地預測在點對點[P2P]借貸中，哪些借款 金融世界每分每秒產生大量數據。澳門大學工商管理 學院金融及商業經濟學系副主任李振國副教授指出， 這些數據經機器學習模型分析後能成為改善投資策 略、減低投資風險和開發嶄新金融產品的基石。 培育現代金融業人才 金融市場向來起伏不定，但疫情、戰爭和人工智能等 因素近年令市場更趨波動。面對這些挑戰，單靠傳統 的計量經濟學模型未必能精準地分析與預測金融市 場。李教授說：「憑藉基於大數據的機器學習模型， 金融機構不僅可制訂更佳的投資方案，也能洞察客戶 所需，提供合適產品。」 與此同時，經濟和金融學者也愈來愈多利用大數據 開展研究，如李教授曾收集和分析居民在社交媒體 上表達對金融和資產市場的情緒，研究金融和資產 文 / 葉浩男‧圖 / 何杰平 Chinese & English Text / Davis Ip‧Photo / Jack Ho
澳大新語 • 2023 UMAGAZINE 28 16 封面專題 • COVER STORY 人的違約風險較高。該模型在評估信用卡申請者的債 務違約風險上也表現突出，商業價值顯著。」 大數據引領金融業 正如航海者參考精確的氣象數據來決定航向，今日的 金融機構和投資者同樣需要先進的數據科學技術來推 測市場走向和擬定投資策略。李教授指出：「運用大 數據是金融業人士維持競爭力的關鍵，也是澳門現代 金融業發展的重要方向。」 Master of Science in Data Science programme. Prof Lei, who also serves as the coordinator of the specialisation, says, ‘Developing the modern financial services industry is crucial for Macao as the city moves towards economic diversification. We foresee a growing demand for specialists in areas like data analytics, business analytics, and financial analytics in the coming years.’ According to Prof Lei, the specialisation encompasses the application of artificial intelligence, blockchain technology, cloud computing, and big data in the financial domain. ‘In addition to data collection and cleaning, students learn to use machine learning models ranging from decision trees to neural networks,’ Prof Lei adds. ‘This year, a graduate developed a system that integrates various machine learning models to predict default risks among peer-to-peer [P2P] lenders. The model also has the advantage of evaluating the default risk of credit card applicants, which underlines its considerable commercial value.’ Big Data at the Forefront of Modern Finance Just as navigators rely on accurate weather data to determine their course, financial institutions and investors need advanced data technologies to decode market trends and formulate investment strategies. Prof Lei concludes, ‘Tapping into the vast potential of big data is important for finance professionals to stay competitive. It is also a promising direction for Macao’s modern financial services industry.’ 李振國教授 Prof Henry Lei An immense volume of data flows through the financial sector every second. Henry Lei, associate head of the Department of Finance and Business Economics in the Faculty of Business Administration (FBA) at the University of Macau (UM), emphasises that machine learning models, by harnessing this data, can enhance investment strategies, reduce investment risks, and contribute to the development of new financial products. Nurturing Modern Financial Professionals The recent pandemic, wars, and the rise of artificial intelligence have amplified the fluctuations in financial markets. Using traditional econometric models alone may fall short in providing accurate analyses and forecasts for today’s dynamic markets. ‘By leveraging machine learning models trained on big data, financial institutions can devise superior investment strategies,’ says Prof Lei. ‘More importantly, they can gain a deep understanding of client needs, allowing them to provide tailored products.’ Experts in economics and finance also increasingly rely on big data for their research. Prof Lei, for example, has explored sentiments on social media regarding financial and asset markets. This approach provides insight into the correlation between poor financial or asset market performance and declining consumption. Recognising the evolving needs of the financial sector, UM’s Institute of Collaborative Innovation, in collaboration with FBA, has introduced the Financial Technology specialisation under the university’s
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 17 從數據合規建立信任 Building Trust Through Data Compliance 研究院與法學院合辦了理學碩士學位（數據科學）課 程中的「數據戰略與合規管理」專業範疇。 身為該專業範疇的課程統籌人，Ramaswamy教授表 示，這個課程的教學團隊匯集不同法系的多語言國際 法律專家。「除了教授數據科學技術，該課程亦探討 在醫療保健、生物醫學研究和公共管理等領域運用和 保護數據，以及比較各地關於數據使用和人工智能程 式開發的法律和規定。」 過去數年，該專業範疇的學生開展了眾多研究項目，涉 及歐盟《一般資料保護規範》、澳門的個人數據保護標 準，以及粵港澳大灣區內不同司法管轄區的合規要求， 學生可提升其設計預防性合規策略的能力，將來能協助 機構降低處理數據時的法律風險，尤其是跨境數據傳輸 和使用不合規時可能面對的巨額罰款。 Ramaswamy教授指出，畢業生能在法律或爭議調解 領域發揮所長，也能在公私營機構找到許多其它職 業機會，亦有愈來愈多人有意攻讀博士課程，進一 步研究數據戰略與合規管理方面日新月異的跨學科 前沿課題。 在大數據科技盛行的今日，我們對數據擁有權和相關 權利的保護足夠嗎？澳門大學法學院環球法律學系副 教授Muruga Perumal Ramaswamy認為，社會亟待在 科技創新與法律考慮之間求取平衡。 數據使用的法律挑戰 大數據科技在商業活動和公共服務中早已不可 或缺，但也引發不少合規管理問題，涉及知識 產權保護、私隱、數據安全和爭議解決途徑 等。Ramaswamy教授表示：「良好的數據戰略不僅 要符合法規要求，亦應遵守自願制定的行業標準等 其它基準，從而降低法律風險，贏得數據使用者和 提供者的信任。」因此，他和法學院其他學者正開 展相關研究，涵蓋歐洲和澳門的數據保護、粵港澳 大灣區網絡安全、生成性人工智能規管、基因數據 保護和智能合同使用等。 培養融會法律與科技的人才 Ramaswamy教授說，對法律界人士而言，理解大數 據的收集、存儲和使用有助他們提供更適切的法律意 見和數據戰略；對科技業人士而言，理解相關法律框 架亦有助他們管理和使用數據。因此，澳大協同創新 文/葉浩男、資深校園記者古詠軒‧圖 / 校園記者梁鎮鴻 Chinese & English Text / Davis Ip, Senior UM Reporter Ku Weng Hin‧Photo / UM Reporter John Leung
澳大新語 • 2023 UMAGAZINE 28 18 封面專題 • COVER STORY In an era dominated by big data technologies, are we adequately safeguarding data ownership and other related rights? Muruga Perumal Ramaswamy, associate professor in the Department of Global Legal Studies in the Faculty of Law (FLL) at the University of Macau (UM), argues that there is a pressing need to strike a balance between technological innovation and legal considerations. Legal Complexities of Data Use Big data technologies are indispensable in both commercial activities and public services, yet they also present a myriad of compliance challenges, ranging from intellectual property protection and privacy to data security and recourse to dispute resolution. Prof Ramaswamy contends that an effective data strategy should extend beyond merely satisfying regulatory requirements; it should also align with voluntary industry standards. ‘Adhering to such standards not only mitigates legal risks but can also gain trust from data users and providers,’ he explains. In FLL, Prof Ramaswamy and his colleagues are engaged in research on data protection in Macao and Europe, cybersecurity in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), regulation of generative artificial intelligence, genetic data protection, and application of smart contracts. Cultivating Talent at the Intersection of Law and Technology ‘Understanding the collection, storage, and use of data is invaluable for legal professionals, equipping them to provide more tailored legal advice and data strategies. For tech professionals, a grasp of pertinent legal frameworks is equally beneficial when it comes to data management and use,’ says Prof Ramaswamy. Against this backdrop, UM’s Institute of Collaborative Innovation, in collaboration with FLL, has launched a Data Strategy and Compliance specialisation under the university’s Master of Science in Data Science programme. According to Prof Ramaswamy, the coordinator of this specialisation, the teaching team comprises multilingual international legal experts with extensive knowledge of various jurisdictions and legal systems. Students in this specialisation not only learn about data technologies but also explore how to apply and protect data in fields such as healthcare, biomedical research, and public administration. Moreover, students compare legal frameworks on data use and the development of artificial intelligence applications between jurisdictions. Over the past few years, students in this specialisation have undertaken various research projects, covering topics such as the General Data Protection Regulation in the European Union, personal data protection standards in Macao, and compliance requirements in various jurisdictions within the GBA. These projects have enhanced their ability to design preventive compliance strategies, which can help reduce legal risks associated with data processing faced by organisations. This is particularly important given the substantial penalties that may result from non-compliance in cross-border data transfer and use. Prof Ramaswamy adds that graduates of this specialisation are not only well-positioned to excel in the fields of law and dispute resolution but are also capable of securing a wide range of career opportunities in both public and private sectors. ‘A growing number of our graduates express interest in pursuing doctoral studies to delve further into advanced interdisciplinary topics in the rapidly evolving field of data strategy and compliance.’ Muruga Perumal Ramaswamy教授 Prof Muruga Perumal Ramaswamy
COVER STORY • 封面專題 2023 UMAGAZINE 28 • 澳大新語 19 數據指引精準醫療 Crafting Tailored Cures Through Data 的研究包括利用人工智能發現疾病標記物、區分患者亞 型和監測疾病狀況，以及開發多種高通化驗技術，從而 大規模和快速地分析血液和身體組織樣本。 精準醫學需求日增 隨著大眾對個人化醫療的需求日增，加上澳門近年積 極發展健康產業，學術界、醫療機構、藥廠及生物技 術開發行業需要愈來愈多精準醫學人才，不少學生修 讀澳大的理學碩士學位（數據科學）課程中的「精準 醫學」專業範疇。該專業範疇由澳大協同創新研究院 與健康科學學院合辦。 身為該專業範疇的課程統籌人，潘教授說：「該專業範 疇涵蓋從數據分析、機器學習到生物醫學等方面的廣泛 知識，包括以不同疾病為例，探討基礎生物學和人工智 能在醫療環境中的應用，以備學生應對各種醫療保健挑 戰，達致精準醫療。」該專業範疇的學生畢業前須完成 當癌症患者經多次化療仍然效果有限，失望之情難以 言喻。澳門大學健康科學學院副教授潘全威表示，常 規治療無法滿足個人需求時，借助機器學習與大數據 分析的精準醫學能提供新的治療方向。 分析多元健康數據 「精準醫學」是較為新興的臨床和研究領域。潘教授 說，開展精準醫學診療時，醫生除了進行常規檢查， 也會分析患者的基因，了解基因多態性／變異如何影 響疾病的形成，也可能進一步分析患者體內如蛋白質 分子、代謝物等各類能反映病情的「生物標誌物」。 透過整合這些數據，醫生能更準確地識別病症的亞 型，選擇合適療程。 潘教授指出：「機器學習與大數據分析在精準醫學中扮 演重要角色，尤其能相當精確地協助識別生物標誌物， 有助我們更深入地了解癌症、糖尿病等複雜疾病。」他 文 / 葉浩男‧圖 / 編輯部 Chinese & English Text / Davis Ip‧Photo / Editorial Board
澳大新語 • 2023 UMAGAZINE 28 20 封面專題 • COVER STORY 一個研究項目，將數據科學與生物醫學相結合，探討生 物醫學、醫學或醫療方面的實際問題。 潘教授指出，該專業範疇的學生以來自學界、醫院和 業界的大型數據集開展研究。近年的研究項目涉及眾 多主題，從解決與生命相關的基本生物學問題、建立 疾病模型、對發病機制的理解、藥物開發，以至人工 智能在醫學中的應用等均有涉獵。「憑藉數據科學與 生物醫學方面的專長，我們的畢業生能為社會帶來更 個人化的醫療服務。」 Growing Demand for Precision Medicine With the increasing demand for personalised healthcare and the active development of the health industry in Macao in recent years, there is a growing demand for precision medicine professionals in many fields, from academia and clinical settings to the pharmaceutical and biotechnology industries. Against this backdrop, many students have chosen the Precision Medicine specialisation under the university’s Master of Science in Data Science programme, jointly offered by UM’s Institute of Collaborative Innovation and FHS. ‘This specialisation equips students with a diverse skill set, from data analytics to biomedical sciences, preparing them to tackle a variety of healthcare challenges towards achieving precision medicine,’ says Prof Poon, who also serves as the coordinator of the specialisation. Before graduation, students are required to pursue a research project to solve a practical data science problem in the field of biomedical sciences, medicine, or healthcare. According to Prof Poon, students of the precision medicine specialisation conduct research using large datasets from academia, hospitals, and industries. Recent projects have ranged from solving fundamental biological questions related to life, disease modelling, understanding of disease pathogenesis, drug development and applications of AI in medicine. ‘With expertise in data science and biomedical sciences, our graduates have the ability to contribute to society with more personalised healthcare solutions,’ Prof Poon concludes. 潘全威教授 Prof Terence Chuen Wai Poon When a cancer patient still only has limited response after multiple chemotherapy treatments, the sense of despair can be crushing. Terence Chuen Wai Poon, associate professor in the Faculty of Health Sciences (FHS) at the University of Macau (UM), suggests that in such circumstances, precision medicine—enabled by machine learning and big data analytics—can serve as a compelling alternative to conventional therapies. Harnessing Multifaceted Health Data According to Prof Poon, precision medicine is an emerging clinical and research field that is gaining prominence in diagnosis and treatment of disease. Beyond routine check-ups, clinicians may examine patients' genetic profiles to discern how polymorphism/ mutations affect disease formation. They may also delve into other ‘biomarkers’—such as proteins and metabolites—to get a clearer picture of the patient’s health. By integrating these data, clinicians are better placed to identify disease subtypes, thus enabling more tailored treatment plans. ‘Machine learning and big data analytics play important roles in precision medicine. They are particularly adept at pinpointing biomarkers with remarkable accuracy. This enables us to have a deeper understanding of complex diseases like cancer and diabetes,’ explains Prof Poon. His research applies artificial intelligence for tasks like biomarker discovery, patient classification and disease monitoring. He has also been developing various high-throughput analytical technologies that allow swift and large-scale analyses of biological specimens such as blood and tissue.
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