Multi-Aspect Learning: Methods and Applications

Richi Nayak is a Professor at the School of Computer Science and Leader of the Complex Data Analysis Program at the Centre of Data Science at Queensland University of Technology, Brisbane Australia. She has gained international recognition for her expertise in machine learning, data mining and text mining. Her research has resulted in significant advancements in clustering, deep neural networks, social media mining, recommender systems, multi-view learning and tensor/matrix factorization. She is highly passionate about addressing societal issues by applying her machine learning and AI innovation and fundamental research. She regularly consults with private, public and government agencies on various machine learning projects, many of which have been commercialised. Her research contributions have led to novel solutions for problems in Digital Marketing, K-12 Education, Digital Agriculture and Digital Humanities. She has authored more than 250 high-quality refereed publications that have been cited over 4000 citations, with an h-index of 33. She has been recognized for her research leadership with several best paper awards and nominations at international conferences, QUT Postgraduate Research Supervision awards, and the 2016 Women in Technology (WiT) Infotech Outstanding Achievement Award in Australia. She also serves as a Steering committee member of the Australasian Data Mining and Machine Learning Conference and as the editorial chief of the International Journal of Data Mining and Digital Humanities. She holds a PhD in Computer Science from the Queensland University of Technology and a Masters in Engineering from the Indian Institute of Technology Roorkee, India.

Khanh Luong obtained her PhD in Computer Science specializing in Data Science from Queensland University of Technology (QUT) in 2019. Afterwards, she worked as a Postdoctoral Researcher in Data Science at the QUT Centre for Data Science, where her research focused on addressing the challenges of dealing with multiple aspect data. Her research has made significant contributions to the fields of machine learning and data mining by developing innovative methods ready to be deployed on real-world datasets, ranging from text, image, sound, video, and bioinformatics data. Her methods apply to diverse problems, such as clustering, classification, anomaly detection, community discovery, and collaborative filtering, with a novel multi-aspect outlook. She has an impressive track record as an active member of the Organizing Committee of the Australasian Data Mining Conference for several years. Additionally, she has established herself as a highly regarded reviewer for several top-tier journals, including IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Transactions on Knowledge Discovery from Data (TKDD), IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), IEEE Transactions on Audio, Speech and Language Processing (TASLP), and Information Sciences. Recently joining Charles Sturt University as a research fellow, she is currently working on Cyber Security projects and collaborating with Data61 to develop practical approaches for detecting and reacting to attacks using various data sources.

Richi Nayak 是昆士蘭科技大學（Queensland University of Technology）計算機科學學院的教授及數據科學中心的複雜數據分析計畫負責人，位於澳大利亞布里斯班。她因在機器學習、數據挖掘和文本挖掘方面的專業知識而獲得國際認可。她的研究在聚類、深度神經網絡、社交媒體挖掘、推薦系統、多視角學習以及張量/矩陣分解等領域取得了顯著進展。她對於通過應用機器學習和人工智慧創新及基礎研究來解決社會問題充滿熱情。她定期與私營部門、公共機構和政府機構就各種機器學習項目進行諮詢，其中許多項目已實現商業化。她的研究貢獻為數位行銷、K-12 教育、數位農業和數位人文等領域的問題提供了新穎的解決方案。她已發表超過 250 篇高品質的同行評審論文，這些論文的引用次數超過 4000 次，h-index 為 33。她因其研究領導力而獲得多個最佳論文獎和國際會議的提名、昆士蘭科技大學研究生指導獎，以及 2016 年澳大利亞女性科技（WiT）資訊科技傑出成就獎。她還擔任澳大拉西亞數據挖掘與機器學習會議的指導委員會成員，以及《國際數據挖掘與數位人文期刊》的主編。她擁有昆士蘭科技大學的計算機科學博士學位，以及印度羅爾基印度理工學院的工程碩士學位。

Khanh Luong 於 2019 年在昆士蘭科技大學（QUT）獲得專攻數據科學的計算機科學博士學位。之後，她在 QUT 數據科學中心擔任數據科學的博士後研究員，研究重點是解決處理多方面數據的挑戰。她的研究對機器學習和數據挖掘領域做出了重要貢獻，開發了可在現實世界數據集上部署的創新方法，這些數據集涵蓋文本、圖像、聲音、視頻和生物信息學數據。她的方法適用於多種問題，如聚類、分類、異常檢測、社群發現和協同過濾，並具有新穎的多方面視角。她在澳大拉西亞數據挖掘會議的組織委員會中活躍多年，擁有令人印象深刻的成就。此外，她已成為多本頂級期刊的高度評價的審稿人，包括 IEEE 知識與數據工程期刊（TKDE）、IEEE 數據知識發現期刊（TKDD）、IEEE 神經網絡與學習系統期刊（T-NNLS）、IEEE 音頻、語音與語言處理期刊（TASLP）以及資訊科學期刊。最近，她加入查爾斯斯圖特大學擔任研究員，目前正在從事網絡安全項目，並與 Data61 合作，開發使用各種數據來源檢測和應對攻擊的實用方法。