Knowledge-augmented Methods for Natural Language Processing - Bill Yuchen Lin

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Résumé :
Dr. Meng Jiang is currently an assistant professor at the Department of Computer Science and Engineering in the University of Notre Dame. He obtained his B.E. and Ph.D. from Tsinghua University. He spent two years in UIUC as a postdoc and joined ND in 2017. His research interests include data mining, machine learning, and natural language processing. He has published more than 100 peer-reviewed papers of these topics. He is the recipient of the Notre Dame International Faculty Research Award. The honors and awards he received include Best Paper Finalist in KDD 2014, Best Paper Award in KDD-DLG 2020, and ACM SIGSOFT Distinguished Paper Award in ICSE 2021. He received NSF CRII Award in 2019 and CAREER Award in 2022. Bill Yuchen Lin is a postdoctoral young investigator at Allen Institute for AI (AI2), advised by Prof. Yejin Choi. He received his PhD from University of Southern California in 2022, advised by Prof. Xiang Ren. His research goal is to teach machines to think, talk, and act with commonsense knowledge and commonsense reasoning ability as humans do. Towards this ultimate goal, he has been developing knowledge-augmented reasoning methods (e.g., KagNet, MHGRN, DrFact) and constructing benchmark datasets (e.g., CommonGen, RiddleSense, X-CSR) that require commonsense knowledge and complex reasoning for both NLU and NLG. He initiated an online compendium of commonsense reasoning research, which serves as a portal for the community. Dr. Shuohang Wang is a senior researcher in the Knowledge and Language Team of Cognitive Service Research Group. His research mainly focuses on question answering, multilingual NLU, summarization with deep learning, reinforcement learning, and few-shot learning. He served as area chair or senior PC member for ACL, EMNLP, and AAAI. He co-organized AAAI'23 workshop on Knowledge Augmented Methods for NLP. Dr. Yichong Xu is a senior researcher in the Knowledge and Language Team of Cognitive Service Research Group. His research focuses on the combination of knowledge and NLP, with applications to question answering, summarization, and multimodal learning. He led the effort to achieve the human parity on the CommonsenseQA benchmark. He has held tutorials on knowledge-augmented NLP methods in ACL and WSDM. Prior to joining Microsoft, Dr. Xu got his Ph.D. in machine learning from Carnegie Mellon University. Wenhao Yu is a Ph.D. candidate in the Department of Computer Science and Engineering at the University of Notre Dame. His research lies in language model + knowledge for solving knowledge-intensive applications, such as open-domain question answering and commonsense reasoning. He has published over 15 conference papers and presented 3 tutorials in machine learning and natural language processing conferences, including ICLR, ICML, ACL, and EMNLP. He was the recipient of Bloomberg Ph.D. Fellowship in 2022 and won the Best Paper Award at SoCal NLP in 2022.He was a research intern in Microsoft Research and Allen Institute for AI. Dr. Chenguang Zhu is a principal research manager in Microsoft Cognitive Services Research Group, where he leads the Knowledge and Language Team. His research covers knowledge-enhanced language model, text summarization, and prompt learning. Dr. Zhu has led teams to achieve human parity in CommonsenseQA, HellaSwag, and CoQA, and first places in CommonGen, FEVER, ARC, and SQuAD v1.0. He holds a Ph.D. degree in Computer Science from Stanford University. Dr. Zhu has published over 100 papers on NLP and knowledge-augmented methods. He has held tutorials and workshops in knowledge-augmented NLP in conferences like ACL, AAAI, and WSDM. He has published the book Machine Reading Comprehension: Algorithm and Practice published in Elsevier....

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