Nhu-Tai Do

Researcher at Pattern Recognition Lab - Chonnam Nat'l Univ.

From 2021 to now, I am Postdoc researcher in the Pattern Recognition Lab, Department of Artificial Intelligence Convergence, Chonnam National University, Korea. I received the B.S. degree in information system major from HCMC University of Foreign Language – Information Technology, Vietnam, in 2005, the M.S. degree in Information System Management from International University, Vietnam National University at HCMC, Viet Nam, in 2017, and the Ph.D. degree in Artificial Intelligence Convergence, Chonnam National University, South Korea, in 2021. From 2005 to 2017, I was a lecturer in the Faculty of Information Technology, HCM University of Foreign Languages and Information Technology, Vietnam. From 2017 to 09/2021, I am working in the Pattern Recognition Lab, Department of Artificial Intelligence Convergence, Chonnam National University, Korea. My research interests are pattern recognition, deep learning, computer vision, video understanding, and medical analysis.


Dec 24, 2021 :1st_place_medal: Aquaculture Artificial Intelligence Idea Contest 2021 (AQUA21) (Certificate) (Code). Team ADLER.
Nov 10, 2021 :1st_place_medal: Korean Emotion Recognition Challenge 2021 (KERC) (Certificate). Team ADLER.
Mar 15, 2020 Ranked 4th in Affective Behavior Analysis in-the-wild (ABAW) Challenge - IEEE 2020 Face & Gesture Conference. Team CNU_ADL.
Nov 9, 2019 :3rd_place_medal: Korean Emotion Recognition Challenge 2019 (KERC) (Certificate). Team ADLER.
Jun 12, 2019 Ranked 6th in Audio-video based emotion recognition - Seventh Emotion Recognition in the Wild Challenge (EmotiW) - 21st ACM International Conference on Multimodal Interaction 2019. Team ALDER.

Selected publications


  1. Diagnostics
    Multi-Level Seg-Unet Model with Global and Patch-Based X-ray Images for Knee Bone Tumor Detection
    Do, Nhu-Tai, Jung, Sung-Taek, Yang, Hyung-Jeong, and Kim, Soo-Hyung
    Diagnostics 2021
  2. Sensors
    Context-Aware Emotion Recognition in the Wild Using Spatio-Temporal and Temporal-Pyramid Models
    Do, Nhu-Tai, Kim, Soo-Hyung, Yang, Hyung-Jeong, Lee, Guee-Sang, and Yeom, Soonja
    Sensors 2021
  3. AACR 2021
    Abstract PO-024: Boosting up knee bone tumor detection from radiology and magnetic resonance imaging by using deep learning techniques
    Do, Nhu-Tai, Jung, Sung-Taek, and Kim, Soo-Hyung
    Clinical Cancer Research 2021


  1. FG 2020
    Affective Expression Analysis in-the-wild using Multi-Task Temporal Statistical Deep Learning Model
    Do, Nhu-Tai, Nguyen-Quynh, Tram-Tran, and Kim, Soo-Hyung
    In 2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020) 2020
  2. IEEE Access
    Image Colorization Using the Global Scene-Context Style and Pixel-Wise Semantic Segmentation
    Nguyen-Quynh, Tram-Tran, Kim, Soo-Hyung, and Do, Nhu-Tai
    IEEE Access 2020