Hi ~ I’m Le-Anh Tran, PhD, an AI Researcher/Engineer fascinated by neural networks - what makes them so cool, how they do surprisingly clever things, and why they are occasionally stupid. I enjoy turning ideas into experiments and making AI not only smarter, but genuinely useful in the real world.
My work focuses on Image Enhancement & Understanding, where I spend most of my time teaching machines to see a little better (though I explore other areas as well). I enjoy the full journey from a questionable idea to an algorithm that actually works. I read papers, write papers, and occasionally discover that someone else had already had the exact same idea three years earlier.
I'm also a big fan of 3-cushion billiards and soccer. I spend my free time trying to convince balls to go where I want them to.
Email: tranlevision@gmail.com
Profiles: ResearchGate |
GoogleScholar |
MyResume
Projects | Blogs: Github |
Medium
3/2021 – 2/2024
Myongji University, South Korea
3/2019 – 2/2021
Myongji University, South Korea
9/2014 – 8/2018
HCMC University of Technology and Engineering (HCMUTE), Vietnam
1/2026 – Now
DeltaX Co., Ltd., Seoul, South Korea
4/2020 – 5/2025
MindinTech, Inc., Seoul, South Korea
7/2019 – 9/2019
OCST Co., Ltd., Seoul, South Korea
3/2018 – 2/2019
FPT Software, Ho Chi Minh City, Vietnam
2/2017 – 1/2018
Faculty of Electrical and Electronics Engineering, HCMUTE, Vietnam
LA Tran
Pattern Recognition, 2026
LA Tran, DC Park
Neural Computing and Applications, 2025
LA Tran, DC Park
The Visual Computer, 2024
LA Tran, DC Park
The Visual Computer, 2024
LA Tran, D Kwon, HM Deberneh, DC Park
Intelligent Data Analysis, 2024
LA Tran, NC Tran, DC Park, J Carrabina, D Castells-Rufas
GECOST 2024, IEEE
LA Tran, D Kwon, DC Park
Procedia Computer Science, 2024
LA Tran, HM Deberneh, TD Do, TD Nguyen, MH Le, DC Park
IWIS 2022, IEEE
LA Tran, S Moon, DC Park
Procedia Computer Science, 2022
LA Tran, MH Le
ICSSE 2019, IEEE
Each data has different importance.
When traditional computer vision and deep learning conjugate.
What is the key to the success of Vision Transformers?
Learn from different perspectives.
Prevent your model from overfitting.
Everything in the universe is connected.
When fog is beneficial.
Guide a student to learn a teacher’s behavior.
*More posts can be found at my Medium page.