Natural Language Processing 2020 [Discussion]

Leveraging deep learning as a workhorse, NLP is evolving rapidly. There is a popular opinion that the "ImageNet moment" has already arrived. We have invited experts with experience in academia and industry to speak about the latest achievements and challenges in NLP in 2020. We will discuss aspects of applying heavy DL models to solve NLP problems, the issues related to their explainability, and practical usage.

The discussion will be in English.

Moderator:

Artem Chernodub (Applied Research Scientist at Grammarly, GitHub, Facebook, Linkedin)

Experts:

  • Kyryl Truskovskyi (Machine Learning Software Engineer at BorealisAI (Canada), Twitter, GitHub)
  • Maria Nadejde (Applied Scientist at Amazon Web Services, Linkedin)
  • Nikita Lukianets (Founder and CTO at PocketConfidant AI, Twitter, GitHub, Linkedin)
  • Svitlana Galeshchuk (Data Scientist та Researcher in NLP at Starclay (France) and Université Paris Dauphine, Linkedin, Facebook)
Artem Chernodub
Grammarly
  • Applied Research Scientist at Grammarly
  • Teaches Deep Learning at Ukrainian Catholic University, Ph.D. degree in Artificial Intelligence
  • Has over 10 years of ML experience in industrial & academic domains. Previously worked for Postindustria, Samsung, US Air Forces
  • Interested in Deep Learning for NLP: Neural Machine Translation, Argument Mining, Grammatical Error Correction
  • GitHub, Facebook, Linkedin
Kyryl Truskovskyi
BorealisAI
  • Kyryl has over 7 years of experience in the field of Machine Learning
  • He currently holds the position of MLSE (machine learning software engineer) in the Canadian company BorealisAI
  • For the bulk of this career, he has helped build machine learning startups, from inception to product.
  • He has also developed expertise in choosing and implementing state of the art deep learning architectures and large-scale solutions based on them.
  • Twitter, GitHub
Maria Nadejde
Amazon Web Services
  • Applied Scientist at Amazon Web Services focused on researching and delivering solutions for expanding Amazon’s machine translation capabilities
  • Before joining Amazon, she was an Applied Research Scientist at Grammarly developing deep learning applications that improve written communication
  • Obtained a PhD in Informatics from the University of Edinburgh and an MSc from the Erasmus Mundus European Masters Program in Language and Communication Technologies (LCT)
  • Research interests: machine translation, grammatical error correction, domain adaptation
  • Linkedin
Nikita Lukianets
PocketConfidant AI
  • Founder and CTO at PocketConfidant AI, a self-coaching technology built on research from the fields of positive psychology, psychology of learning, and linguistics
  • Founder of Open Ethics, the non-for-profit initiative that aims to bring transparency standards to ML-powered products
  • 10+ years of experience in Human-Computer Interaction
  • MBA in innovation management from Politecnico di Milano School of Management
  • Microsoft alumni
  • Twitter, Github, Linkedin
Svitlana Galeshchuk
Starclay (France)
  • Data Scientist and Researcher in NLP at Starclay (France) and Université Paris Dauphine
  • Has earned her doctorate in Economics and Financial Analysis in Ukraine and has served as a Fulbright Scholar in machine learning visiting the USA. She has also acted as a Visiting Associate Professor at the Laboratory of Informatics, Université Grenoble Alpes (France)
  • Key areas of expertise in NLP: text classification, semantic similarity, question answering, interpretability across NLP tasks
  • Linkedin, Facebook, GitHub, dblp
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