I am an Assistant Professor of the Computer Science Department at Virginia Tech, where I lead the Natural Language Processing Lab. At VT CS, I'm also a member of the Sanghani Center for Artificial Intelligence and Discovery Analytics.

Prior to VT, I received my Ph.D. in Computer Science from UIUC where I worked with Heng Ji. I have also worked at Singapore Management University, Microsoft Rsearch Asia, IBM Watson Research, and Allen Institute AI (AI2). I am a recipient of the 2019 AI2 Fellowship, 2021 Amazon Research Award, 2023 VT-Amazon Initiative Research Award, 2023 Department Rising Star Award and 2023 NSF CAREER award. My research has been recognized with the awards including ACL'2023 Outstanding Paper Award and SIGIR'2023 Best Paper Award Honorable Mention.

My research focuses on Natural Language Processing, Machine Learning and Artificial Intelligence. I'm interested in building efficient models and benchmarks that can encourage machines to perform human-level intelligence. My current research interests include information extraction, language understanding and generation, conversational AI and multimodal.

I'm always looking for highly motivated students to work with me on broad NLP and Multimodal research. Please feel free to reach out and apply!

News and Highlights

  • (10/08/23) : Three papers accepted by EMNLP'2023. Congrats to Jingyuan, Zhiyang, Ying and Minqian.

  • (10/06/23) : Congrats to Ying on being selected as an Amazon Fellow!

  • (10/06/23) : We are grateful to receive a grant from the Amazon–VT Initiative to support our research on conversational AI (VT News Article).

  • (9/12/23) : HokieBot team won the Third Place on Scientific Competition (awarded $25,000) for the Amazon Alexa Prize SocialBot Grand Challenge 5! Check out our report and news announcement from Amazon Science.

  • (8/20/23) : Serving as an Area Chair of EACL'2023 and SPC of AAAI'2023.

  • (7/28/23) : Super excited and honored to receive the Best Paper Award Honorable Mention from SIGIR'2023! Welcome to check out our Multimodal Fact Checking and Explanaton Generation paper and Github repo!

  • (7/12/23) : Serving as a publication committee co-chair of NAACL'2024!

  • (7/10/23) : Super honored to share that our MultiInstruct work received the Outstanding Paper Award from ACL'2023! Welcome to check out our project page.

  • (7/6/23) : We are very grateful to receive a new grant from DARPA for the ECOLE program!

  • (5/1/23) : We have 5 papers accepted by ACL'23! Congrats to Zhiyang, Ying, Minqian, Sijia and all collaborators!

  • (3/28/23): Very grateful to receive the NSF CAREER Award!

  • (3/10/23): Congrats to Zhiyang, Minqian and Ying on receiving internship offers from Amazon Alexa AI, AWS Research Lab (NYC) and Apple Research.

  • (12/18/22): Serving as a publication committee co-chair of ACL'2023, SAC of ACL'2023, AC of EMNLP'2023, and SPC of IJCAI'2023.

  • (10/28/22): We are grateful to receive a gift fund from Google and Intuit.

  • (10/26/22): Our team - HokieBot is selected as one of the 9 university teams for the Alexa Prize SocialBot Grand Challenge 5. We are grateful for all the support from Amazon Alexa.

  • (9/30/22): Talk at USC AI Seminar: "Towards Open World Event Extraction with Weak Supervision".

  • (8/15/22): Our work on Incremental Prompting for Continual Event Detection is accepted by COLING'22. Congrats to Minqian!

  • (8/1/22): Serving as Area Chair (AC) for COLING'2022.

  • (6/22/22): Initiated workshop "Indirect, Weak and Self Supervision for Knowledge Extraction" accepted by AKBC2022. Call For Papers!

  • (6/21/22): We are very grateful to receive a new grant from Meta AI to support our research on multimodal entity linking.

  • (3/31/22): Recent talks at UNC Greensboro, STR, and Data Intelligence Workshop on Transferable and Scalable Event Extraction

  • (3/8/22) : Our SimBot team (to advance Embodied AI) is featured on the VT News today!

  • (12/15/21): Will give a tutorial on New Frontiers of Information Extraction at NAACL'2022.

  • (12/10/21): Very excited to receive a new grant for the DARPA KMass program.

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