Denis Emelin

Denis Emelin

PhD Candidate / Post-Graduate Researcher in Informatics

University of Edinburgh, ILCC

Biography

Hello! I currently pursue a PhD at the University of Edinburgh, where I’m advised by Dr. Rico Sennrich and Dr. Ivan Titov. My research aims to explore and improve the extent of language understanding in neural machine translation.

Our work has demonstrated that NMT models rely on shallow heuristics when inferring the right sense of ambiguous words, and improved the ability of transformer models to represent lexical and contextual information. Related phenomena, such as co-reference resolution, discourse processing, and translation of figurative language are also among my varied research interests.

Recently, I completed an internship with the MOSAIC group at the Allen Institute of Artificial Intelligence, where I investigated commonsense reasoning abilities of state-of-the-art models of language.

In my spare time, I enjoy climbing, learning new things, and caring for my future orchard.

Interests

  • Machine translation and multilingual technologies
  • Grounded natural language understanding
  • Natural language generation
  • Commonsense, social, and moral reasoning
  • Interpretability and model bias

Education

  • PhD Informatics, 2021

    University of Edinburgh, United Kingdom

  • MSc Language Science & Technology, 2017

    Saarland University, Germany

  • BA German Studies (Linguistics Focus)

    University of Tübingen, Germany

News

Dec 2020 Published ‘Moral Stories: Situated Reasoning about Norms, Intents, Actions, and their Consequences’. Many thanks to my wonderful collaborators!
Nov 2020 Presented ‘Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks’ at EMNPLP 2020
Sep 2020 ‘Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks’ has been accepted as a long paper to EMNLP 2020!
Jun 2020 I started an internship with the MOSAIC group at AI2, advised by Ronan Le Bras and Yejin Choi! Working on goal-directed, commonsense reasoning.
Sep 2019 I attended WeCNLP2019 in Menlo Park, USA! Impressions: High industry representation, excellent speakers, engaging panel discussion. Definitely worth attending.
Jul 2019 I attended ACL 2019 and presented ‘Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts’ at the Fourth Conference on Machine Translation (WMT19)!
Jul 2019 I started an internship at the Information Sciences Institute (ISI), advised by Dr. Jonathan May! Working on translation of figurative language and commonsense resoning for NMT.
Sep 2018 I attended the 13th Machine Translation Marathon, hosted at Charles University, Czech Republic! Participated in lectures and workshops on recent developments in MT and implemented a hierarchical character-to-word decoder as part of the week-long hackathon.
Jul 2018 I attended the Microsoft Research AI Summer School 2018, hosted at Microsoft Research Cambridge, UK. Attended lectures and workshops at MSR Cambridge as one of 100 invited PhD students.
Mar 2018 I started my PhD at the University of Edinburgh, ILCC!

Work Experience

 
 
 
 
 

Research Intern

Allen Institute for Artificial Intelligence (AI2)

Jun 2020 – Sep 2020 Seattle, Washington, USA

Explored social commonsense reasoning capabilities of contemporary natural language understanding and generation models.

Accomplishments:

  • Crowd-sourced a high-quality dataset
  • Developed effective, task-specific neural decoding algorithms
  • Performed extensive experimentation and model analysis
 
 
 
 
 

Research Intern

University of Southern California, Information Sciences Institute (ISI)

Jun 2019 – Sep 2019 Los Angeles, California, USA.

Developed methods for improved translation of figurative language.

Accomplishments:

  • Constructed a novel, wide-coverage idiom explicitation corpus from web data
  • Evaluated the ability of NMT systems to translate non-literal, non-compositional expressions
  • Implemented initial strategies for improved translation of figurative language
 
 
 
 
 

Teaching Assistant, Tutor, Marker

University of Edinburgh

Apr 2018 – Feb 2020 Edinburgh, Scotland, United Kingdom

Assisted in preparing and teaching undergraduate courses on machine translation and natural language understanding.

Accomplishments:

  • Created and evaluated coursework submitted by several hundred students
  • Taught tutorials accompanying the primary lecture, helping students to develop a better understanding of theory and practical considerations