• ACL 2024 Tutorial: Watermarking for Large Language Models.
  
• NAACL 2024 Tutorial: Combating Security and Privacy Issues in the Era of Large Language Models
  
• ACL2021 Tutorial: Pre-training methods for Neural Machine Translation
• EMNLP 2019 Tutorial on Discreteness in NLP.
• CCF-ADL107/NLPCC 2019 Tutorial on Deep Generative Models for Text Generation. Dunhuang, China, 2019. by Hao Zhou and Lei Li.
• CCF-ADL/NLPCC 2016 Tutorial on Deep Learning for Question Answering. Kunming, China, December 2020. [Slides]
• 2014 PPAML Summer School Tutorial: Probabilistic Modeling using Bayesian Logic (BLOG) .
• KDD 2010 Tutorial on Time Series

• University of Massachusetts Boston Invited Talk: Towards Scaling Large Language Models to 1000 Languages - Challenges and Advances. Nov 4, 2024.
• Invited talk at MIT FutureTech Workshop on the Role of AI in Science: Watermarking and Detecting AI Generation. Nov 3, 2024.
• Univ. of Pittsburgh ISP Seminar: The Science of Evaluation and Alignment for Large Language Models. Oct 25, 2024. also delivered at Northeastern University. Nov 4, 2024.
• CMU LTI Colloquium: From Words to Molecules - Harnessing Generative AI for Breakthroughs in Language and Molecular Design. Sep 13, 2024.
• ACL 2024 Language+Molecule workshop: A Tale of Two Realms: Commonalities and Distinctions of Generating Language and Molecules. Aug 15, 2024.
• Michigan State University Guest Lecture: Assessing and Improving Large Language Models. 2024.4.1.
  
• CMU CyLab Seminar: Is it generated by AI? Attacks and Robust Watermarking for Generative AI. 2024.1.22 (a prior version was given at JHU CSLP Seminar in 2023.9 and NTU in 2023.12)
  
• Ohio State University TDAI's Foundations of Data Science and AI Speaker: Self-assisting and Cooperative Large Language Models. 2024.1.12 (also given at NUS in 2023.12)
  
• IEEE Central Coast Talk: Breaking Language Barriers with Neural Machine Translation. 2022.8.17
• CCMT 2021 Keynote: Efficient Machine Translation. [Slides]
• GAITC 2021 NLP Forum Invited Talk: Speech Translation from Research to Product Innovation. [Slides]
• GTC Talk 2020: Recent Advances in Machine Writing and Translation – Algorithms and Challenges. [Slides]
• NeurIPS 2020 Beijing Meetups: Scalable, Controllable, and Interpretable Machine Learning for Natural Language Generation. 2020.12.06 (30 mins).
• Constrained Text Generation - Monte Carlo Meets Neural Nets. Tsinghua University. IIIS. 2020.10.8 (1hr)
• Scalable, Controllable and Interpretable Machine Learning for Natural Language Generation. Tsinghua University, Guest Lectures at IIIS Undergrad class 2020.10.8. (1.5 hrs)
• ICLR 2020 Talk on Learning Deep Latent Models for Text Sequences. [Video] [Slides]
• BLOG language and compiled inference. Computer Science department, Stanford University, Tsinghua University, 2015.
  
• 2015 Invited Keynote at China Computer Federation Young Computer Scientists and Engineers Forum: Deep Learning – Towards More Intelligent Machines.
  
• 2013 TAMU Fish Bowl Seminar
• Parsimonious Linear Fingerprinting for time series, Machine learning lunch seminar, CMU, Nov, 2010. [ PPT ]
  
• Fast Algorithms for Mining Co-evolving Time Series. SMU, NUS, SJTU, Dec 2009. [ PPT ]
• Fast Algorithms for Mining and Summarizing Co-evolving Sequences, HKUST. 2009.[ Poster ]
• Machine Learning Lunch seminar, CMU, Oct 6, 2008. [ PPT ]