Cornelius Justin Satryo Hadi

About Me

A highly motivated and ambitious professional with a strong educational background in Mathematics, specialized in Artificial Intelligence. Possessed a deep understanding of data science, machine learning, and deep learning, also have gained valuable experience through various projects, competitions, academic research, and organizations. Known as a person with strong work ethic, adaptability, and problem-solving abilities, Thrived in dynamic and challenging environments and a collaborative team player with excellent attention to details and a proactive mindset.

Education

Bachelor's Degree - Mathematics 2020 - present

Universitas Indonesia

GPA: 3.77 / 4.00

Machine Learning Cohort 2023

Bangkit Academy

● Accepted as one of 5010 participants with over 67k applicants. ● Learned various end-to-end deep learning techniques using Tensorflow.

Work & Experience

Laboratory Assistant

Deparment of Mathematics, Universitas Indonesia

09/01/2022 - 07/02/2023

Laboratory Assistant of Algorithm and Programming Class (2022) ● Taught Python programming language basics to intermediate material, including data types, loops, functions, and NumPy library, to more than 150 students. Laboratory Assistant of Data Science Class (2023) ● Taught various data science, machine learning, and deep learning implementation technique using Python programming language to more than 50 students. ● Created a module focusing on data visualization using Seaborn and Matplotlib. ● Introduced students to deep neural networks using TensorFlow-Keras. Laboratory Assistant of Numerical Differential Equation Class (2023) ● Taught Octave programming language for numerical differential equations to more than 50 students.

Skills

Machine Learning
85%
Deep Learning
85%
Python
95%
Tensorflow
90%
SQL
70%
Microsoft Excel
90%

Awards

3rd Winner of Healthkathon 2022 - Machine Learning Category 2022
In October 2022, my team was named the 3rd winner in the Healthkathon 2022 Machine Learning Category. The aim of the project was to build a classification model for the inefficiency of BPJS Kesehatan (Indonesia government health insurance) participant claims, specifically focusing on fraud detection using XGBoost.