學者及大學教授 / Academic / professor
大字係領域（由已登記職業／領域派生），唔係姓氏。
YUE Xiangyu
領域：學者與科學家
據官方名冊嘅逐人紀錄：學位：BEng (NJU), MSc (Stanford), PhD (UC Berkeley)。
According to the official record in cuhkFaculty: Degrees: BEng (NJU), MSc (Stanford), PhD (UC Berkeley).
呢句係由下面〈官方紀錄〉嘅欄位直接串成，冇加入任何推斷；完整欄位同原文連結見該節。
繁體中文
岳翔宇現為香港中文大學訊息工程學系助理教授。他二○一四年於南京大學自動化系取得工程學士學位，二○一六年在美國史丹福大學取得電機工程碩士，之後於加州大學柏克萊分校電機工程與計算機科學系取得博士學位，並獲該系頒發 Lotfi A. Zadeh 獎——此獎用來表揚博士畢業生嘅傑出表現。他先後在 Google Research、Google [X] Robotics、百度人工智能實驗室同騰訊人工智能實驗室從事研究工作。他的研究橫跨機器學習、遷移學習、標籤效率學習同電腦視覺，應用場景包括自動駕駛、機械人同醫學影像。機器學習模型依賴大量標註數據，但醫療影像等領域嘅標註成本特別高；遷移學習嘅做法係把一個任務學到嘅知識轉移到另一個任務，標籤效率學習就進一步減少所需標註。他在 Google、百度、騰訊等機構嘅研究經歷，涵蓋自動駕駛同機械人兩個應用場景；柏克萊嘅 Zadeh 獎以模糊集理論創始人 Lotfi Zadeh 命名。現時他在中大訊息工程學系任教，研究延續標籤效率學習同視覺應用。
English
Xiangyu Yue is an assistant professor in the Department of Information Engineering at The Chinese University of Hong Kong. He took a bachelor's degree in automation at Nanjing University in 2014, a master's degree in electrical engineering at Stanford University in 2016 and a PhD from the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, where he received the Lotfi A. Zadeh Prize for outstanding doctoral graduates. He has carried out research at Google Research, Google [X] Robotics, the Baidu AI Lab and the Tencent AI Lab. His research spans machine learning, transfer learning, label-efficient learning and computer vision, with applications in autonomous driving, robotics and medical imaging.
下列欄位逐字抄自官方名冊／院校紀錄嘅逐人頁（抓取日期 2026-10-29）：https://www.ie.cuhk.edu.hk/people/xyyue.shtml。本站只列官方寫過嘅欄位，冇加任何推斷。
BEng (NJU), MSc (Stanford), PhD (UC Berkeley)
Fields above are copied verbatim from the official record linked here; the site adds no interpretation.
Assistant Professor
資料整理日期 / Compiled: 2026-10-14
在史丹福大學取得電機工程碩士學位。
Completed a master's degree in electrical engineering at Stanford University.
在柏克萊取得博士學位，並獲 Lotfi A. Zadeh 獎。
Completed his PhD at Berkeley and received the Lotfi A. Zadeh Prize.
加入香港中文大學訊息工程學系。
Joined CUHK's Department of Information Engineering.
繁體中文
岳翔宇嘅研究解決機器學習「標籤不足」嘅現實問題：遷移學習同標籤效率學習都係為了令模型在少量標註資料下仍然可靠，並應用於自動駕駛同醫學影像等領域。
English
Yue's work addresses the practical shortage of labels in machine learning: transfer learning and label-efficient learning both aim to keep models reliable when annotated data are scarce, with applications from autonomous driving to medical imaging.
仲有 192 位同界別人物未列出；睇晒 學者及大學教授 全部名單 →
Chinese University of Hong Kong - Faculty Members · 香港中文大學 · 查閱日期 2026-10-14
CUHK Department of Information Engineering - Faculty Profiles · 香港中文大學訊息工程學系 · 查閱日期 2026-10-23
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