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Listen, the world is smiling!
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Yu (Hugo) Chen 陈宇, PhD
Senior Research Scientist, Meta AI
1 Hacker Way, Menlo Park, CA 94025, USA
Email: hugochan2013 at gmail.com
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Short Bio

Yu (Hugo) Chen is a Senior Research Scientist at Meta AI. He got his PhD degree in Computer Science from Rensselaer Polytechnic Institute, under the supervision of Prof. Mohammed J. Zaki. His research interests lie at the intersection of Machine Learning (Deep Learning) and Natural Language Processing, with a particular emphasis on the fast-growing field of Graph Neural Networks and Transformer-based Large Language Models. His work has been published at top-ranked conferences including but not limited to NeurIPS, ICML, ICLR, AAAI, IJCAI, ACL, NAACL, KDD, WSDM, ISWC, and AMIA. He was the recipient of the Best Student Paper Award of AAAI DLGMA’20. He was one of the book chapter contributors of the book "Graph Neural Networks: Foundations, Frontiers, and Applications". He delivered a series of DLG4NLP tutorials at NAACL'21, SIGIR'21, KDD'21, IJCAI'21, AAAI’22 and TheWebConf’22. His work has been covered in popular technology and marketing publications including World Economic Forum, TechXplore, TechCrunch, Ad Age and Adweek. He is a co-inventor of 4 US patents.

Previously, he earned his bachelor's degree in Telecommunications Engineering from the University of Electronic Science and Technology of China (UESTC) in Chengdu, China. In that short but cherished period of time, he exposed himself to programming, data science and all kinds of cool techniques. The great research experiences with Prof. Tao Zhou and Prof. Jie Shen encouraged him to continue his research journey.

In his spare time, he enjoy reading, writing, music, movie and photography. All of them make him discover and enjoy the beauty. He also likes to play various sports (e.g., soccer, badminton, tennis and table tennis).


Top News

  • We are very delighted to deliver a series of DLG4NLP tutorials at NAACL'21, SIGIR'21, KDD'21, IJCAI'21, AAAI'22 and TheWebConf'22. You are welcome to check out our DLG4NLP website for various learning resources, including graph4nlp library, survey, tutorials, and videos!

  • Please check out our book "Graph Neural Networks: Foundations, Frontiers, and Applications" at [SpringerLink] [Free e-book] [Chinese version].

News

  • [2023/05]   One paper is accepted by ACL 2023.

  • [2023/01]   The Chinese version of the GNN book (图神经网络中文城堡书) which I contributed a chapter to received the Epubit Bestseller Award 2022.

  • [2022/11]   The Chinese version of the GNN book (图神经网络中文城堡书) which I contributed a chapter to has been published by Post & Telecom Press and accepts order at JD.com.

  • [2022/06]   I am invited to serve as the chair of the NLP and Graph track and give a talk on Graph4NLP library at the Graph Machine Learning Summit 2022.

  • [2022/06]   I am invited to give a keynote talk on Graph Structure Learning for GNNs at IEEE AIIOT 2022.

  • [2022/05]   One paper is accepted by SIGKDD 2022.

  • [2022/05]   Our GNN4NLP survey is accepted by Foundations and Trends in Machine Learning journal.

  • [2022/04]   I am invited to give a position talk on Graph4NLP library at DLG4NLP@ICLR 2022.

  • [2022/01]   One paper is accepted by TheWebConf 2022.

  • [2022/01]   I am honored to contribute to the “Graph Neural Networks: Graph Structure Learning” chapter of the GNN book "Graph Neural Networks: Foundations, Frontiers, and Applications" recently published by Springer. The book is available for pre-order at Springer, Amazon, and JD.COM.

  • [2021/12]   Our tutorial titled "Deep Learning on Graphs for Natural Language Processing" is accepted by TheWebConf 2022.

  • [2021/11]   I am invited to give a talk on Graph4NLP library at CLIQ-ai.

  • [2021/11]   I am invited to give a guest lecture on DLG4NLP at UIUC.

  • [2021/09]   Check out our DLG4NLP website.

  • [2021/09]   Our tutorial titled "Deep Learning on Graphs for Natural Language Processing" is accepted by AAAI 2022.

  • [2021/06]   Check out our most recent survey paper, titled "Graph Neural Networks for Natural Language Processing: A Survey"! First comprehensive survey on GNNs for NLP!

  • [2021/06]   We are delighted to release our Graph4NLP library, which is the first library for the easy use of GNNs for NLP!

  • [2021/06]   We just delivered a very successful tutorial titled "Deep Learning on Graphs for Natural Language Processing" at NAACL 2021! Check out our slides!

  • [2021/05]   I am deeply pleased and honored to receive the Karen and Lester Gerhardt Prize (for outstanding PhD dissertation in engineering or science) and the Robert McNaughton Prize (for outstanding graduate student in computer science) from RPI.

  • [2021/05]   Our tutorial titled "Deep Learning on Graphs for Natural Language Processing" is accepted by SIGKDD 2021.

  • [2021/04]   Our tutorial titled "Deep Learning on Graphs for Natural Language Processing" is accepted by SIGIR 2021.

  • [2021/04]   One paper is accepted by Phys. Rev. Materials.

  • [2021/04]   Our tutorial titled "Deep Learning on Graphs for Natural Language Processing" is accepted by IJCAI 2021.

  • [2021/01]   One paper is accepted by ICLR 2021 and I will attend the conference.

  • [2020/12]   Our tutorial titled "Deep Learning on Graphs for Natural Language Processing" is accepted by NAACL 2021.

  • [2020/10]   One paper is accepted by WSDM 2021.

  • [2020/09]   One paper is accepted by NeurIPS 2020 and I will attend the conference.

  • [2020/09]   One paper is accepted by ISWC 2020.

  • [2020/09]   I join Facebook as a Research Scientist.

  • [2020/07]   One paper is accepted by AMIA 2020.

  • [2020/06/24]   I successfully defended my dissertation! Feel free to check out the Slides.

  • [2020/04]   One paper is accepted by IJCAI 2020.

  • [2020/04]   I am invited to give a talk on Question Generation at Amazon.

  • [2020/03]   I am invited to give a talk on Question Generation and Graph Learning at Tencent AI Lab America.

  • [2020/03]   I am invited to give a talk on Question Generation at Dataminr.

  • [2020/02]   Our paper on graph learning for GNNs received the Best Student Paper Award of AAAI DLGMA 2020.

  • [2019/12]   One paper is accepted by ICLR 2020 and I will attend the conference.

  • [2019/12]   One paper is accepted by AAAI DLGMA 2020 and I will attend the conference in New York, NY.

  • [2019/11]   I am invited to give a talk on Graph Learning at IBM Research in Yorktown Heights, NY.

  • [2019/10]   One paper is accepted by AMIA KRSWG 2019.

  • [2019/10]   One paper is accepted by NeurIPS GRL 2019 and I will attend the conference in Vancouver, BC, Canada.

  • [2019/07]   Two papers are accepted by ISWC 2019.

  • [2019/05]   One paper is accepted by ICML LRG 2019 and I will attend the conference in Long Beach, CA.

  • [2019/05]   I am invited to give a talk on KBQA for adaptive education at AIAED 2019 in Beijing, China.

  • [2019/05]   I am invited to give a talk on our KBQA work at IBM AI Horizons Seminar Series.

  • [2019/04]   One journal paper is accepted by IJPEM.

  • [2019/02]   One long paper is accepted by NAACL-HLT 2019 and I will attend the conference in Minneapolis, MN.

  • [2017/09]   One paper is accepted by IEEE SSCI 2017.

  • [2017/07]   I received the SIGKDD 2017 student travel award.

  • [2017/05]   One full paper is accepted by SIGKDD'17 and I will attend the conference in Halifax, NS, Canada.

  • [2017/01]   I am the TA for CSCI-4220: Network Programming, Spring 2017.

  • [2016/08]   I am the TA for CSCI-4390/6390: Data Mining, Fall 2016.

  • [2016/05]   One paper is accepted by CAD 2016.

  • [2016/02]   I begin to work with Prof. Mohammed J. Zaki.

  • [2016/01]   I am the TA for CSCI-2500 Computer Organization, Spring 2016.

  • [2015/08]   I am the TA for ECSE-4750 Computer Graphics, Fall 2015.

  • [2015/08]   I Join RPI as a PhD student in Computer Science.