Welcome

Listen, the world is smiling!
  My photo   
Yu (Hugo) Chen 陈宇, PhD
Co-founder and VP of Engineering, Anytime AI
Email: ychen at anytime-ai.com, hugochan2013 at gmail.com
Google Scholar, LinkedIn, Twitter, CV

Personal Highlights

Dr. Yu (Hugo) Chen is a distinguished scientist and entrepreneur in the field of artificial intelligence, with extensive industry experience and a profound academic background. Dr. Chen’s contributions to deep learning and natural language processing have received international recognition, with over 30 papers published at esteemed AI academic conferences such as NeurIPS, ICLR, AAAI, ACL, and KDD, accumulating more than 2,000 citations. He was awarded the NAACL 2024 Outstanding Paper Award and AAAI DLGMA’20 Best Student Paper Award for his exceptional research. He holds co-inventorship for 4 US patents. His technological innovations have been widely reported by over 20 media outlets including the World Economic Forum, TechCrunch, TechXplore, AI Era, and Synced.

Dr. Chen's global influence in the AI sector extends beyond his research and technological achievements to his contributions to the community. His contributions, through co-authoring the textbook "Graph Neural Networks: Foundations, Frontiers, and Applications" (which won the 2022 Epubit Bestseller Award and has been accessed online over 120,000 times), sharing tutorials/keynote speeches at premier AI conferences such as AAAI, IJCAI, NAACL, KDD, and IEEE AIIoT (attracting over 1,000 attendees cumulatively), and his Graph4NLP open-source project (garnering over 1,700 followers on GitHub), have significantly fostered academic and technological exchanges in the global AI field, enhancing his influence both within and outside the industry.

With over nine years of experience in AI research and development, Dr. Chen has demonstrated exceptional engineering development and management skills. As the co-founder and technical lead of Anytime AI, he has led a global technical team to apply cutting-edge Generative AI technology to the legal services sector, driving innovation and transformation in the industry. He has also demonstrated exceptional abilities in fundraising, actively attracting and engaging potential investors, and assisting the CEO in funding efforts.

Dr. Chen was awarded the 2024 AACYF Top U30 title and 2023 Data Intelligence Leader of the Year title. In summary, Dr. Chen's professional skills, leadership, innovative spirit, and positive societal contributions establish him as a true industry leader and innovator.

Top News

  • We are hiring! If you're interested in leveraging cutting-edge generative AI technologies to revolutionize the legal industry, we would love to hear from you. Learn more and apply today: Anytime AI Careers.

  • We launched our new AI product at Anytime AI to transform productivity and effectiveness in the world of Law and Orders.

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

  • We are very delighted to deliver the AIGC tutorial at AAAI'24. You are welcome to check out our AIGC Tutorial website for various learning resources!

  • 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!

News

  • [2024/08]   One paper is accepted by TMLR.

  • [2024/06]   Our paper "LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models" received Outstanding Paper Award at NAACL 2024!

  • [2024/03]   I was awarded the 2024 AACYF Top U30 title.

  • [2024/03]   One paper is accepted by NAACL 2024.

  • [2024/01]   I was awarded the 2023 Data Intelligence Leader of the Year title by DataFun.

  • [2024/01]   One paper is accepted by EACL 2024.

  • [2024/01]   One paper is accepted by ICLR 2024.

  • [2023/11]   I am happy to start my new journey as the Co-founder and Head of Machine Learning at Anytime AI.

  • [2023/10]   Our tutorial titled "Beyond Human Creativity: A Tutorial on Advancements in AI Generated Content" is accepted by AAAI 2024.

  • [2023/10]   One paper is accepted by EMNLP 2023.

  • [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.