- An Efficient Method for Wide Area Event Detection and Prediction Using Regression Model
- Performance evaluation on the accuracy of the semantic map of an autonomous robot equipped with P2P communication module
- Incremental Learning for Autonomous Navigation of Mobile Robots based on Deep Reinforcement Learning
- Many-to-Many Voice Conversion based Disentangled Variational Autoencoder
- FlowVocoder: A small Footprint Neural Vocoder based Normalizing Flow for Speech Synthesis (Submitted to ICASSP 2022)
Research Experience
- AI Research Resident, VinAI Research. Project: Many-to-Many Voice Conversion. Mentor: Viet Anh Tran
- Big data engineer, VCCorp, Hanoi, Vietnam, Oct 2016 – Jul 2017.
Education
- M.S., Computer Engineering, Sunmoon University, Asan city, Korea, Sep 2019. Thesis: Autonomous Navigation for Mobile Robot Based on Reinforcement Learning.
- B.E., Computer Science, Posts and Telecommunication Institute of Technology, Hanoi city, Vietnam, May 2017. Thesis: Human Activity Recognition based on Support Vector Machine.
Background
Research interests: Robotics, speech processing, representation learning.
Miscellany
Communication skills: Vietnamese: Native; English: C1 (IELTS 7.0). Activities include organizing AIDAY 2020, Rising to the challenge, and being an instructor at U.S. Embassy in Hanoi, Vietnam, for Get-In-Tech series: Artifial Intelligence & Machine Learning.