Learning Engineer Front End

Le Duc Cam R ********@*****.***

Ho Chi Minh City, Viet Nam Cam-Duc-Le

Ó+84-969****** ï Le Duc Cam

TECHNICAL SKILLS

Computer Languages: C/C++, Python, JavaScript, PHP, Java(basic), SQL. Libraries/Tools: Numpy, Pillow, Sklearn, Keras, Tensorflow, Pytorch(basic), Pandas, PySpark, Seaborn, Matplotlib, Imbalanced-Learn ReactJS, NodeJS, FastAPI(basic).

DBMS: MySQL, Oracle

Office: Microsoft Office, Latex

Research Focus: Machine Learning/Deep Learning/Computer Vision. EDUCATION

Ho Chi Minh University of Technology - Vietnam National University Ho Chi Minh City, Viet Nam 2019 – 2023

Computer Science - CGPA: 8.13

Le Quy Don High School for the Gifted, Vung Tau, Vietnam 2016 – 2019 Specilized in Mathematics

ACHIEVEMENTS

- Provincial excellent students in Mathematics contest for 3 consecutive years (2016-2019) LANGUAGE

- English: Working proficiency (IELTS: 7.0)

WORK EXPERIENCE

CyberLogitec Vietnam (CLV) 6/2022 - 5/2023

Machine learning engineer (RnD team) Vietnam

· Pet’s Style project (11/2022 - 5/2023):

- Successfully trained a generative model which helps to turn a dog/cat face into Disney, comic, Ghibli style. The system is developed based on the GANsNRoses model, with the support of StyleGan and comprises 2 versions: a "full" model running on PC’s GPU and a quantized model for mobile devices (click to see an example).

- Developed a generative model based on StarGAN-v2 that blends a pet’s face and a human’s face together. (click to see an example).

· Predict Booking Cancellation project (6/2022 - 10/2022):

- Successfully developed ML models to predict the customer’s container booking cancel- lation rate using time-series based models (like: ARIMA, SARIMAX, regression algo- rithms) and an ensemble based classification model (RF, XGBoost, NB, etc). Techniques were used to deal with the huge volume, imbalance and ambiguity of data: re-sampling, target encoding, rule-based, combining internal data (from database) with external data

(news, covid-related indexes, industry indexes, marine logistics indexes). PERSONAL PROJECTS

· Remote Sensing Image Classification

- Successfully developed a deep learning model to detect the scene of a remote sensing image (link).

- Typical publications:

+ A Robust and Low Complexity Deep Learning Model for Remote Sensing Image Clas- sification - ICIIT 2023 (link).

+ A Light-weight Deep Learning Model for Remote Sensing Image Classification - EU- SIPCO 2023 (link).

· MDP-Weather

- Successfully developed a weather related website. In this project, I developed the front- end of the website using ReactJS,was in charge of database design and processing API calls, developed weather classification models (DTree, MLP, NB, etc), temperature pre- diction models (Moving Average, Linear Regression) and deployed using FastAPI. (link).

· Phone Selling

- Successfully developed a simple e-com website that sells mobile phones. (link).

· Sentiment Analysis

- Successfully developed a model to classify the emotion of a text sequence using LSTM and FastAPI, which achieved 80% accuracy on Sentiment140 dataset. (link).

· Job Portal

- Successfully developed a simple website using PHP and XAMPP that connects employ- ers and employees together (link).

· POS-System

- Developed a POS system’s front end using HTML, CSS, JS (link).

· Video Streaming

- Successfully implemented a simple Client-Server livestream app with Tkinter, socket, threading and cv2 library (link).

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