Home News & Events Research Seminars NLP@VinUni: Robust & Low-Resource Natural Language Processing

NLP@VinUni: Robust & Low-Resource Natural Language Processing

Despite some empirical successes, natural language processing (NLP) technology remains limited when it comes to practical applications, due to a lack of reliability and robustness, and very high memory and computational footprints. We plan to develop a strong research activity at VinUni centered around NLP, with a focus on three thrusts: a) low-resource and robust algorithms, b) Vietnamese and other languages that are outside the purview of most existing NLP models and c) industry or academic applications that are relevant to VinUni and Vingroup and Vietnam at large.

The talk  describes some of the salient features of modern NLP, outline a few use cases, and end with a call for participation to a few collaborators from CBM, CHS and FAS, to work with us on specific cases of interest.

About the Speakers:

  • Laurent El Ghaoui: Prior to his current appointment at VinUniversity, Prof. El Ghaoui taught at the Department of Electrical Engineering & Computer Science and Department of Industrial Engineering & Operations Research at University of California, Berkeley (ranked #32 worldwide according to the QS World University Rankings 2021). He also taught Data Science within the Master of Financial Engineering at UC Berkeley’s Haas Business School. Besides being a researcher and a lecturer, Prof. El Ghaoui is also a consultant and an entrepreneur. According to him, these experiences solving real-world problems have supplemented his research life tremendously.
  • Wray Buntine: Prior to his current appointment at VinUniversity, Wray Buntine was a full professor, foundation director of the Master of Data Science, and director of the Machine Learning Group at Monash University. Previously, he was conducting research projects at Helsinki Institute for Information Technology, NASA Ames Research Center, University of California, Berkeley, and Google. In the ’90s he was involved in a number of startups for both Silicon Valley and Wall Street. Professor Wray is known for his theoretical and applied work and in probabilistic methods for document and text analysis, social networks, data mining and machine learning. He is on several journal editorial boards and has been a senior program committee member for premier conferences such as IJCAI, UAI, AAAI, EMNLP, ICLR, ACML and NeurIPS. He has over 200 academic publications, several software products and two patents.

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