Danny To Eun Kim

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I am a graduate researcher at UCL Web Intelligence Group, University College London (UCL), where I received an integrated Master's degree (M.Eng.) in Computer Science in 2022. Currently, I'm working with Prof. Emine Yilmaz and Dr. Aldo Lipani in the area of Conversational AI, Search, Question-Answering, and User Simulation. Also, I'm an active member of both Knowledge Graphs and NLP interest group at The Alan Turing Institute, where I regularly present and share my research.

During the summer of 2022, I interned at Vector.ai as a Machine Learning Engineer, automating the paperwork in freight forwarding industry by OCR and NLP.
From May 2021, I joined team Condita as a main developer to compete in the first Amazon Alexa Prize TaskBot Challenge, where I spent significant amount of time, constructing a real-time, multi-modal, knowledge-intensive, and interactive conversational assistant; our team has made to the quarterfinals.
Prior to that, I worked with Prof. Marianna Obrist at UCL (Human-Computer) Interaction Centre, finding ways to cluster text-based stories by authors' smell experience.

I love to spend my time teaching and socializing with like-minded researchers in various societies. For example, I served UCL Artifical Intelligence Society as a primary committee for 4 years. For more, you can take a look at my blog page or pictures!

Email  /  CV  /  Google Scholar  /  Blog  /  Twitter  /  GitHub

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Table of Contents  

Research  /  Publications  / 
Presentations & Workshops  / 
Teaching & Mentoring  / 

The ultimate goal of my research aims for a real-time conversational assistants. Therefore, I try to find better ways to encode human knowledge into computable forms, i.e., language models or graphs, and make the knowledge retrievable by (conversational) search systems.

Current Research:

  • Response Ranking/Selection with Conversational Look-Ahead that optimizes user satisfaction
  • Evaluation of Conversational System by User Simulation
  • Interactive Grounded Language Understanding - Asking Clarification Questions
  • Use of Knowledge Graphs in Conversational Search Systems
  • Extracting multimodal information from text: focusing on underresearched sense


A Multi-Task Based Neural Model to Simulate Users in Goal-Oriented Dialogue Systems
To Eun Kim, Aldo Lipani
SIGIR, 2022
paper / poster / code / bibtex

Conversational User Simulator that 1) generates user-side utterance, 2) predicts user's next action and 3) satisfaction level by multi-task learing. SOTA in Satisfaction and Action prediction in USS dataset

Condita: A State Machine Like Architecture for Multi-Modal Task Bots
Jerome Ramos*, To Eun Kim*, Z. Shi, X. Fu, F. Ye, Y. Feng, Aldo Lipani
* denotes equal contribution.
Alexa Prize TaskBot Challenge Proceedings, 2022
paper / bibtex

We present COoking-aNd-DIy-TAsk-based (Condita) task-oriented dialogue system, for the 2021 Alexa Prize TaskBot Challenge. Condita provides an engaging multi-modal agent that assists users in cooking and home improvement tasks, creating a memorable and enjoyable experience to users. We discuss Condita's state machine like architecture and analyze the various conversational strategies implemented that allowed us to achieve excellent performance throughout the competition.

Attention-based Ingredient Phrase Parser
Z. Shi, P. Ni, M. Wang, To Eun Kim, Aldo Lipani
ESANN, 2022
paper / arXiv / code / bibtex

Spin-off research from the Alexa Prize TaskBot Challenge. Assisting users to cook is one of these tasks that are expected to be solved by intelligent assistants, where ingredients and its corresponding attributes, such as name, unit, and quantity, should be provided to users precisely and promptly. To provide an engaged and successful conversational service to users for cooking tasks, we propose a new ingredient parsing model.

Presentations & Workshops
Personal Knowledge Graphs: Towards Better Conversational Assistants
Presented at the 5th Meet-up of Knowledge Graphs Interest Group
at The Alan Turing Institute.
27th October, 2022
A Multi-Task Based Neural Model to Simulate Users in Goal-Oriented Dialogue Systems
Presented at the SCAI: Search-Oriented Conversational AI Workshop
15th July, 2022
Recording / Slides

Teaching & Mentoring
Teaching Assistants (MSc courses)
  • CEGE0096: Geospatial Programming (Fall 2022)
  • CEGE0004: Machine Learning for Data Science (Spring 2023)
  • COMP0071 Software Engineering (Spring 2023)
  • COMP0189: Applied Artificial Intelligence (Spring 2023)
Transition Mentor
  • Helping 1st year CS students with programming (C, Java, Python, Haskell)
UCL Artificial Intelligence Society
A Founder, Maintainer, and Lecturer of Machine Learning Tutorial Series

You can know me better from my CV

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