The University of Macau welcomes the 2025 graduation season. Among the hundreds of graduates from the Faculty of Science and Technology, Gong Ying from the Department of Electromechanical Engineering (EME) at the Faculty of Science and Technology stood out for his outstanding academic achievements, innovative research projects, and active campus involvement. He was honored with the “Best Master’s Student Award” by his department. Gong credited his success to both the innovation and practical value of his research, as well as UM’s strong research infrastructure and experimental support.
Advancing Intelligent Systems
His research focuses on robot learning, particularly a diffusion prior strategy guided by pre-trained models. By replacing Gaussian noise with prior information, he reduced model inference steps, significantly speeding up robotic policy learning. This approach also shows promise in autonomous driving and smart manufacturing—areas requiring fast, efficient decision-making. When asked why he chose UM, Gong emphasized the university’s strong faculty, international research perspective, and rapidly growing global reputation, which together provided him with an ideal academic platform.
Excellence in Research and Campus Contribution
During his studies at UM, Gong consistently embraced a spirit of diligence and innovation, actively participating in various academic competitions and practical activities. At the 18th “Challenge Cup” National College Students Extracurricular Academic Science and Technology Works Competition—often referred to as the “Olympics” of student scientific innovation—he and his team stood out among over 400,000 entries nationwide and won the Grand Prize Award, marking the best result for the Department in nearly 18 years.
In addition, he successfully published a journal paper, demonstrating his solid foundation in scientific research. Beyond academics, he remained committed to giving back to the campus community by assisting in the organization of the UM Open Day, showcasing the university’s research capabilities and educational achievements to the public and promoting technological innovation.
Learning and Personal Growth
Reflecting on his time at UM, Gong praised the high-quality facilities, diverse campus culture, and supportive professors. When facing language barriers, he overcame them through discussions and asking questions. The biggest challenge, he said, was proposing novel improvements and designing rigorous experiments—an experience that sharpened his critical thinking and appreciation for collaboration.
Future Goals and Advice
Looking ahead, Gong will continue his studies as a Ph.D. student at UM. and to explore new frontiers in science and technology. He also shared some advice for future students, “Complete your studies successfully, build a strong network, plan early, develop hobbies, and stay healthy. A balanced life helps you go further.” Gong Ying’s journey is a testament to perseverance and passion in science. His story inspires others to embrace challenges, grow through experience, and strive for excellence.
澳門大學迎來2025年畢業季,而在科技學院數百名畢業生中,機電工程系碩士生龔穎憑藉卓越的學術成果、創新的研究計畫以及積極的校園參與,榮膺「學系最優秀碩士生獎」。回顧這段求學之旅,龔穎表示,他的研究及學習的成功不僅得益於其研究項目的創新性與應用潛力,更離不開澳大完善的科學研究體系與系統化的實驗支持。
為智能應用注入新動能
龔穎的研究聚焦於機器人學習領域,探討預訓練模型引導下的擴散先驗策略。通過利用先驗信息替代高斯噪聲,他的研究旨在減少模型推理步數,從而加速基於擴散的機器人策略學習。這一框架不僅對機器人操作任務有效,還能應用於自動駕駛、智能制造等領域,對於需要實時決策和高效執行的場景具有重要意義。談到選擇澳門大學的原因,龔穎表示,澳大雄厚的師資力量、國際化的科研視野以及近年來快速提升的全球聲譽,為他提供了理想的學術平台。
力爭佳績,不忘回饋校園
在澳大求學期間,龔穎始終秉持著勤奮、創新的科研精神,積極參與各類學術競賽與實踐活動。在被譽為大學生科技創新「奧林匹克」的第十八屆「挑戰盃」全國大學生課外學術科技作品競賽中,他和團隊成員從全國40萬多份作品中嶄露頭角,斬獲全國特等獎,創下機電工程系近18年來的最佳成績。此外,他也成功發表期刊論文,展現了紮實的科學研究功底。學術之外,他也不忘回饋校園,連續兩年協助澳大開放日活動,向大眾展示學校的科學研究實力與教育成果,推廣科技創新成果。
學習與個人成長
回顧兩年的碩士生涯,龔穎特別提到澳大優質的硬體設施、多元的校園文化以及教授們的悉心指導。即便在遇到困難時,如語言障礙導致的理解問題,他也通過積極提問和討論找到了解決方案。而研究上最大的挑戰,莫過於提出創新性的改進方向並設計全面實驗來驗證方法的有效性。這些經驗不僅培養了他獨立思考和主動學習的能力,也讓他深刻體會到團隊協作與學術交流的價值。
未來規劃與建議
展望未來,龔穎計劃繼續攻讀博士學位,目前已收到澳大博士錄取通知書,將繼續深耕科研領域,探索未知的科學疆界。最後,他也寄語即將踏入澳大校園的學弟學妹們,他表示: 「首先確保學業順利完成;其次要主動拓展社交圈,結識志同道合的朋友;盡早規劃未來目標,培養長期興趣愛好,並注重身體健康。唯有全方位提升自己,才能行穩致遠。」龔穎的經驗激勵著那些渴望在學術上取得成就的學生,展示了如何克服挑戰,實現自我價值,並為未來鋪設更多可能。