FNAI LAB
Food & Nutrition
Artificial Intelligence Laboratory
"Make Food Computable"
We explore
Food-related Data Science
Recommendation Systems
NLP applications
News
🥳 Feb. 2024: Donghyeon Park (Professor)'s paper, "CookingSense: A Culinary Knowledgebase with Multidisciplinary Assertions" has been ACCEPTED to the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) to be held in Torino (Italia) on 20-25 May, 2024.
🥳 Dec. 2023: Eunyoung Bae (M.S. Student)'s paper, "The analysis of foreigner reviews for restaurants in Jung-gu, Seoul: Based on reviews from TripAdvisor", has been published to the International Journal of Tourism and Hospitality Research (KCI Journal)
☃️ Oct. 2023: Five poster papers have been presented to Korea Software Congress 2023
Jaesung Hwang (M.S. Student)'s paper,
Nilufar Khodzhaeva (M.S. Student)'s paper,
Hoon Park (Undergrad Student)'s paper,
Taeho Kim (Undergrad Student)'s paper,
Sungbeom Park (Undergrad Student)'s paper,
🥳 Aug. 2023: Donghyeon Park (Professor)'s paper, "KitchenScale: Learning to Predict Ingredient Quantities from Recipe Contexts" has been published in Expert Systems with Applications, one the most recognized journals with an impact factor of 8.665 (2022). This paper is based on collaborative work with Sony Research and Korea University.
🥳 Oct. 2022: Donghyeon Park (Professor)'s paper, "RecipeMind: Guiding Ingredient Choices from Food Pairing to Recipe Completion using Cascaded Set Transformer" has been accepted at CIKM 2022, one of the top-tier conferences in Information and Knowledge Management domain. This paper is a fruitful result of collaborative work among our FNAI Lab, DMIS lab (Korea University) and Sony AI (Tokyo, Japan) which aims to promote creative cooking in food industry.
About Us
The main focus of FNAI Lab is to utilize and leverage artificial intellignece (AI) and machine learning (ML) to solve problems in Foodinformatics, AI gastronomy, Recipe recommendation, Personalized diet prescription, Precision nutrition. In order to diversify and strengthen its arsenal, FNAI Lab also conducts research in other areas such as natural language processing (NLP), recommendation systems, and graph ML in order to uncover more-refined techniques to carry out its larger mission.
For more detailed explanations, check out our on-going research.
We are now hiring new members including undergraduate, master, Ph.D. students.