Hassan Sajjad

Hi!

I am Hassan - applied machine learning and deep learning researcher with a focus on natural language processing . I like to work on interesting NLP problems, specially looking at them from the angle of their practical application. I enjoy reading books and love spending time with my family.

Since you ended up on this page and if you are wondering where to go next, here are a few pointers:

To know more about me but in a summarized form, check out About me!

To see my deep learning and NLP courses, check out Teaching

Here is a link to my resume

If you would like to reach out to me for:

  • an interesting problem, drop a line here: hasaan.sajjad+nlp@gmail.com
  • my courses, drop a line here: hasaan.sajjad+coach@gmail.com
  • else: hasaan.sajjad+general@gmail.com

Recent News

  • Keynote: Hidden Linguistic in Deep NLP Models, Symposium on Natural Language Processing, University of Moratuwa, Sri Lanka (March 2019)
  • Deep learning for NLP: Fun teaching at International Spring School in Advanced Language Engineering, University of Moratuwa (March 2019)
  • Talk: Machine Translation in Real World, King’s College London, UK (March 2019)
  • Talk: Analyzing Individual Neurons in Deep NLP Models, University of Melbourne, Australia (February 2019)
  • Accepted @NAACL 2019: “One Size Does Not Fit All: Comparing NMT Representations of Different Granularities”
  • Accepted @NAACL 2019: “Highly Effective Arabic Diacritization using Sequence to Sequence Modeling”
  • Media coverage: Our work on NeuroX - Analyzing and Controlling Individual Neurons is featured at MIT news and several AI blogs.
  • Accepted @ICLR 2019: “Identifying and Controlling Important Neurons in Neural Machine Translation”
  • Accepted @AAAI 2019: “What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models”
  • Accepted @AAAI 2019: “NeuroX: A toolkit for Analyzing Individual Neurons in Neural Network”
  • Best Innovation Award @ARC’18 for our Speech Translation System, see media coverage
  • Deep learning for NLP: I will be delivering an intensive course on deep learning for NLP at the University of Duisburg-Essen, Germany in the second week of April 2018
  • Accepted @NAACL 2018: Incremental decoding and training methods for simultaneous translation in neural machine translation
  • Media coverage: Our work on understanding Neural Machine Translation has made it to MIT news and been picked by several channels like ScienceBlog, ScienceDaily
  • Accepted @IWSLT 2017: Neural Machine Translation Training in a Multi-domain Scenario
  • Deep learning for MT: I had great fun in teaching deep learning for machine translation at the DGfS-CL Fall School. Course material is available here.
  • Accepted two papers @ACL 2017
  • Read my post about What does Neural Machine Translation Learn about Morphology

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