About Prof.

Yan-Ling Yang is an assistant professor in the Department of Chemical Engineering at National Taiwan University of Science and Technology. He received his PhD under the supervision from Profs. Yu-Jane Sheng and Heng-Kwong Tsao from the Department of Chemical Engineering, National Taiwan University in 2018. During his doctoral studies, he developed a custom parallelized mesoscale NPT dissipative particle dynamics algorithm to investigate the structural and mechanical properties of biomimetic membranes using molecular simulations. (楊延齡博士是國立臺灣科技大學化學工程系助理教授。 2018 年在國立臺灣大學化學工程系於諶玉真教授和國立中央大學化學工程與材料工程學系曹恆光教授共同指導下獲得博士學位。博士研究期間，開發了一種客製化的平行化中尺度 NPT 耗散粒子動力學的分子模擬演算法，研究仿生膜的結構和力學性質。)

  After completing his PhD, Dr. Yang pursued postdoctoral research from September 2018 to July 2020. During this period, he taught himself deep learning and atomic-scale molecular dynamics, applying these techniques to predict water-hydrocarbon and water-alcohol interfacial tensions and design biodegradable materials. (2018 年 9 月至 2020 年 7 月期間從事博士後研究。在此期間，深入研究深度學習和原子尺度的分子動力學，並將這些技術應用於預測水-烴和水-醇的界面張力以及設計可生物分解的材料。)

    In August 2020, Dr. Yang joined the Department of Chemical and Materials Engineering at Tamkang University. From 2020 to 2023, he collaborated with Professors Hsuan Chang and Yih-Hang Chen to develop artificial intelligence applications in process systems engineering. Beginning in 2022, he worked with Professor Liao-Ping Cheng on polymer thermodynamics and mass transfer theory, and the fabrication of PES, PLA, PVDF, and cellulose acetate membranes. (2020 年 8 月，加入淡江大學化學與材料工程學系。2020 年至 2023 年間，與張烜教授和陳逸航教授合作開發人工智慧在程序系統工程中的應用。自 2022 年起，與鄭廖平教授合作研究高分子熱力學和質量傳輸理論，以及 PES、PLA、PVDF 和醋酸纖維素膜的製備。)

    Since August 2023, Dr. Yang has been teaching in the Department of Chemical Engineering at the National Taiwan University of Science and Technology. His research interests include deep learning, deep reinforcement learning, physics-informed neural networks, symbolic regression, and large language model applications in chemical engineering, the development of machine learning force field-based molecular simulation algorithms combined with polymer membrane experiments applied to solid-state lithium batteries, separation processes, and biomedical materials.

(自 2023 年 8 月起，任教於國立臺灣科技大學化學工程系。研究領域包括深度學習、深度強化學習、物理資訊神經網路、符號迴歸和大型語言模型在化學工程、機器學習作用力場分子模擬演算法開發結合高分子薄膜實驗應用於固態鋰電池、分離程序與生醫材料。)