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WELCOME TO MY PAGE 👋👋👋

My name is Xuan-The Tran (Eric). I am an PhD student in Computer Science, majoring in Artificial Intelligence and Neuroscience. I am interested in the following topics: Deep Learning in Brain Imaging, Computer Vision and NLP.

My Github Activity

My Repository's Stats

📫 How to reach me:

Linkedin LinkedIn GitHub GitHub Youtube Youtube

Frameworks I worked with

ML/DL Framework

Pytorch scikit_learn tensorflow pytorchlightning sklearn keras

WEB/API Framework

django fastapi drf

Others

Heroku Heroku MySQL PostgreSQL selenium YouTube Channel Subscribers

Competetions I Participated

Natural Language Processing

OffenseEval2020: Classification of offensive language in Arabic, Turkish, Greek, Danish and English language.
PAN2021: Profiling Hate Speech Spreaders on Twitter in English and Spanish language.

Image Processing

ODIR2019: Multi-label classfication challenge to diangose both eye's disease simultaneously.
RIADD-ISBI-2021 Multi-label classfication challenge to diangose eye disorder upto 35 classes.
ISIC19 Skin cancer identification.
Chest XR COVID-19 Covid Diagnosis from chest Xray. Got 18th position.
PerCovid-19 Covid-19 Infection Percentage Estimation from CT-scan. Got 3rd and 2nd position in public and private leaderboard.

Publications

Journal Papers

  • Remote Diagnosis and Triaging Model for Skin Cancer Using EfficientNet and Extreme Gradient Boosting link Scopus: Q1
  • Using a Deep Learning Model to Explore the Impact of Clinical Data on COVID-19 Diagnosis Using Chest X-ray link Scopus: Q1
  • Citrus Plant Disease Identification using Deep Learning with Multiple Transfer Learning Approaches link
  • Machine Learning Based Real-Time Diagnosis of Mental Stress Using Photoplethysmography link
  • Vehicle Make and Model Recognition Using Mixed Sample Data Augmentation Techniques (accepted IJ-AI)

Conference Papers

  • A Machine Learning approach for Recognizing Intellectual Development Disorder using EEG. link
  • Deep learning based diagnosis of COVID-19 using chest CT-scan images link
  • Effect of Image Augmentation on ECG Image Classification using Deep Learning link
  • Beef quality assessment using AutoML link
  • A Generic Approach for Classification of Psychological Disorders Diagnosis using EEG link
  • Comparison of Loss functions and Optimizers for Multi-class X-ray Bone Segmentation link

Workshop Papers

  • TAC at SemEval-2020 Task 12: Ensembling Approach for Multilingual Offensive Language Identification in Social Media. link
  • Identify Hate Speech Spreaders on Twitter using Transformer Embeddings Features and AutoML Classifiers link
  • COVID19 Diagnosis using AutoML from 3D CT scans link

The Tran (Eric)'s Projects

apache-airflow icon apache-airflow

Code base for airflow training series Getting easy with Apache Airflow

autonomous-ai-drone-scripts icon autonomous-ai-drone-scripts

State of the art autonomous navigation scripts using Ai, Computer Vision, Lidar and GPS to control an arducopter based quad copter.

crewai icon crewai

Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.

dl4cvstarterbundle icon dl4cvstarterbundle

Edited code examples from the book 'Deep Learning for Computer Vision - Starter Bundle' by Adrian Rosebrock

flowise icon flowise

Drag & drop UI to build your customized LLM flow using LangchainJS

football_analysis icon football_analysis

This repository contains a comprehensive computer vision/machine learning football project that uses YOLO for object detection, Kmeans for pixel segmentation, optical flow for motion tracking, and perspective transformation to analyze player movements in football videos

haim icon haim

This repository contains the code to replicate the data processing, modeling and reporting of our Holistic AI in Medicine (HAIM) Publication in Nature Machine Intelligence (Soenksen LR, Ma Y, Zeng C et al. 2022).

made-with-ml icon made-with-ml

Learn how to responsibly develop, deploy and maintain production machine learning applications.

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