Deep Learning for Polymer Discovery: Foundation and Advances
暫譯: 聚合物發現的深度學習：基礎與進展

Gang Liu is a 4th year Ph.D. student in the Department of Computer Science and Engineering at the University of Notre Dame. His research focuses on graph and generative learning for polymeric material discovery. He has over ten publications in top data mining and machine learning venues, including KDD, NeurIPS, ICML, DAC, ACL, TKDE, and TKDD. His methods have contributed to the discovery of new polymers, with findings published in Cell Reports Physical Science and secured by a provisional patent. He receives the 2024-2025 IBM PhD Fellowship for his work on Foundation Models.

Eric Inae is a 3rd year Ph.D. student in the Department of Computer Science and Engineering at the University of Notre Dame. He received his B.S. in Computer Science and B.S in Mathematics from Andrews University in 2022. His research emphasis is in graph machine learning with applications in material discovery and polymer science. He was awarded with the Dean's Fellowship from the University of Notre Dame.

Meng Jiang, Ph.D., is an Associate Professor in the Department of Computer Science and Engineering at the University of Notre Dame. He received his B.E. and Ph.D. from Tsinghua University. He was a visiting scholar at Carnegie Mellon University and a postdoc at the University of Illinois Urbana-Champaign. He is interested in data mining, machine learning, and natural language processing. His data science research focuses on graph and text data for applications such as material discovery, question answering, user modeling, online education, and mental healthcare. He received the CAREER Award from the National Science Foundation and is a Senior Member of ACM and IEEE.

Gang Liu 是聖母大學計算機科學與工程系的四年級博士生。他的研究專注於聚合物材料發現的圖形和生成學習。他在頂尖的數據挖掘和機器學習會議上發表了超過十篇論文，包括 KDD、NeurIPS、ICML、DAC、ACL、TKDE 和 TKDD。他的方法促進了新聚合物的發現，相關研究成果已發表在《Cell Reports Physical Science》上並獲得臨時專利。他因其在基礎模型方面的研究獲得了 2024-2025 年 IBM 博士生獎學金。

Eric Inae 是聖母大學計算機科學與工程系的三年級博士生。他於 2022 年獲得安德魯斯大學的計算機科學學士學位和數學學士學位。他的研究重點是圖形機器學習，應用於材料發現和聚合物科學。他獲得了聖母大學的院長獎學金。

孟江（Meng Jiang），博士，是聖母大學計算機科學與工程系的副教授。他在清華大學獲得了工程學士和博士學位。他曾是卡內基梅隆大學的訪問學者，並在伊利諾伊大學香檳分校擔任博士後研究員。他對數據挖掘、機器學習和自然語言處理感興趣。他的數據科學研究專注於圖形和文本數據，應用於材料發現、問題回答、用戶建模、在線教育和心理健康護理等領域。他獲得了國家科學基金會的 CAREER 獎，並是 ACM 和 IEEE 的資深會員。