P. Kanisius Bagaskara

Machine Learning Engineer (Student)

Jakarta, Indonesia

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KANISIUS
BAGASKARA
Google Student Ambassador
Jakarta, Indonesia • Machine Learning Engineer
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Selected Work

Featured Projects

Production-ready ML systems with real-world impact. Each project includes problem analysis, technical implementation, and measurable results.

01

F1 2025 Analytics Dashboard

Real-time telemetry & ML-powered strategy predictions

Live DemoCode
The Problem

F1 fans struggle to understand race strategies. Existing tools lack real-time ML predictions for tire degradation and optimal pit stops.

My Solution
  • →Interactive telemetry visualization using FastF1 API
  • →XGBoost model predicting optimal pit windows (92% accuracy)
  • →Driver performance comparison across 23 race tracks
  • →Weather integration affecting strategy recommendations
Impact
92%
Model Accuracy
<50ms
API Response
50+
Active Users
Challenges Solved
  • •Handled missing telemetry data with interpolation algorithms
  • •Optimized API fetching within rate limits
  • •Built mobile-responsive UI for live race viewing
PythonStreamlitFastF1XGBoostFastAPI
02

IEEE-CIS Fraud Detection

Binary classification for financial transaction security

Code
The Problem

Financial fraud detection requires handling imbalanced datasets and complex transaction patterns.

My Solution
  • →XGBoost classifier with comprehensive feature engineering
  • →Transaction pattern analysis & anomaly detection
  • →Handled class imbalance with SMOTE
  • →ROC-AUC optimization for fraud detection
Impact
0.94
ROC-AUC
590k+
Dataset
400+
Features
Challenges Solved
  • •Extreme class imbalance (3.5% fraud cases)
  • •Feature engineering from anonymized data
  • •Time-based validation to prevent leakage
XGBoostPandasScikit-learnSeaborn
03

Deep Dive into ML

Machine Learning algorithms implemented from scratch

Code
The Problem

Understanding the inner workings of core algorithms to build robust and optimized AI systems.

My Solution
  • →Implemented classic ML algorithms purely in NumPy
  • →Built custom optimization engines (Gradient Descent, Adam etc.)
  • →Mathematical derivations for backpropagation and loss functions
  • →Compared performance against enterprise libraries (Scikit-Learn)
Impact
10+
Algorithms
Core Math
Focus
Mastery
Goal
Challenges Solved
  • •Deriving complex calculus for backward passes
  • •Optimizing matrix multiplications without frameworks
  • •Handling numerical instability (vanishing gradients)
PythonNumPyMatplotlibJupyterMath
View More on GitHub

Tech
Stack

Python
01

Python

Primary

Claude AI
02

Claude AI

LLM Integration

Scikit-Learn
03

Scikit-Learn

ML Algorithms

FastAPI
04

FastAPI

Backend APIs

Pandas
05

Pandas

Data Manipulation

NumPy
06

NumPy

Numerical

Codex / OpenAI
07

Codex / OpenAI

Code Generation

Python
01

Python

Primary

Claude AI
02

Claude AI

LLM Integration

Scikit-Learn
03

Scikit-Learn

ML Algorithms

FastAPI
04

FastAPI

Backend APIs

Pandas
05

Pandas

Data Manipulation

NumPy
06

NumPy

Numerical

Codex / OpenAI
07

Codex / OpenAI

Code Generation

Matplotlib
11

Matplotlib

Plotting

Seaborn
12

Seaborn

Statistical Viz

Plotly
13

Plotly

Interactive

Docker
14

Docker

Containers

GitHub Actions
15

GitHub Actions

CI/CD

GitLab CI
16

GitLab CI

DevOps

VS Code
17

VS Code

Editor

Google Colab
18

Google Colab

Cloud

Jupyter
19

Jupyter

Notebooks

Streamlit
20

Streamlit

Data Apps

Matplotlib
11

Matplotlib

Plotting

Seaborn
12

Seaborn

Statistical Viz

Plotly
13

Plotly

Interactive

Docker
14

Docker

Containers

GitHub Actions
15

GitHub Actions

CI/CD

GitLab CI
16

GitLab CI

DevOps

VS Code
17

VS Code

Editor

Google Colab
18

Google Colab

Cloud

Jupyter
19

Jupyter

Notebooks

Streamlit
20

Streamlit

Data Apps

By The Numbers

The journey so far

8+
Open Source Repos
Top 100
GSA Rising Star
35+
Tech Skills
100+
Students Trained
Track Record

By The Numbers

Quantifiable impact through code, education, and continuous learning.

8+
Repositories
200+
GSA Top Rank
35+
Tech Stack
4
Major Projects

Technical Impact

8+Open Source Projects

ML and data science tools

50+GitHub Stars

Across all repositories

92%Model Accuracy

F1 tire degradation predictor

Education & Teaching

Top 100GSA Rising Star

Fully funded graduation invite

5+AI Workshops

Conducted for students

100+Students Trained

In AI and data science

Recognition

StanfordML Specialization

3 courses completed

GoogleGemini Certified

Educator & Student

IBMData Science

Professional certificate

My Journey

The Path So Far

From watching Iron Man to becoming a Google Ambassador—every step counts.

2025

Started ML Journey

November 2025 - Inspired by Iron Man's JARVIS, began learning Python and ML fundamentals

First Classification Model

Built Iris dataset classifier using scikit-learn

Joined Data Science Club

Jakarta, Indonesia - started community learning

2025

IBM Python for Data Science

Completed professional certificate (after November)

Google Student Ambassador

Awarded Rising Star Top 100 & Fully Funded Invitation for Graduation

First ML Workshop

Conducted workshop for 50+ students

F1 Analytics Dashboard

Launched real-time telemetry analysis tool

Google Gemini Certified

Both Educator and Student certifications

2026

Stanford ML Specialization

Completed 3-course program with honors

Deep Dive into ML

Implemented 8 CS229 algorithms from scratch

Currently Building

F1 tire degradation predictor with weather integration

Now

“The journey of a thousand miles begins with a single step”

— And a lot of Python debugging

Continuous Learning

Certifications

Every certificate here was earned to solve a real problem — not just to collect badges. Stanford for the math, Google for the tools, IBM for the foundations.

Jan 2026
Click individual courses to verify
IBM

Python for Data Science

"The foundation. Where it all started."

Aug 2025
Verify
Google for Education

Gemini Certified Educator

"Bridging AI tools with real teaching impact"

Sep 2025
Verify
About Me

Turning Data Into Racing Insights

Machine Learning Engineer focused on building production-ready ML systems and real-time analytics. Currently developing an F1 tire degradation predictor with weather integration using Python, FastF1 API, and XGBoost.

As a Google Student Ambassador Rising Star + Top 100, I've conducted AI workshops for 100+ students, making complex AI concepts accessible through hands-on learning.

My approach combines rigorous data research analysis with First Principles Thinking inspired by Elon Musk—stripping complex problems down to their fundamental truths before building scalable ML architectures.

Kanisius Bagaskara
GSA '25

Official Representation

GSA Rising Star + Top 100
Stanford ML Specialization
8+ Open Source Projects
100+ Students Trained

Core Expertise

Claude AI, OpenAI Codex, LLM Prompting

AI Integration

First Principles Thinking, Statistical Modeling

Data Research

Docker, CI/CD, Model Deployment

MLOps

FastF1 API, Version Control, Pipelines

Data Engineering

Google Student Ambassador, Tech Overviews

Leadership

Open for Opportunities

ML Engineering internships & freelance projects

Random Facts

How I Got Here

01

The Iron Man Thing

Honestly? I got into Data Science because of Iron Man. Watching JARVIS talk, analyze data in real-time, help Tony make decisions—I thought, "Damn, I wanna build something like that." Started learning Python, fell into ML, and now I'm stuck here (in a good way).

02

From Bedroom to Stage

Used to be just some kid coding alone in my room. Next thing I know, I'm a Google Student Ambassador. I was the guy who got nervous talking to 5 people. Now I can teach workshops with 100+ people. Didn't see that coming, but turns out teaching is fun—it actually makes me understand stuff better.

03

The Stubbornness

I never aim to be the best. I just know that when I have a target, I chase it until I get it. Like F1—it's not about being perfect, it's about improving every single lap. Code broke? Fix it. Algorithm failed? Try again. Just keep moving forward.

I'm not perfect, but when I have a goal,
I DON'T STOP UNTIL I GET IT.

Too stubborn to quit
Always LearningToo Stubborn To QuitF1 > Football
Message from Kanisius

"I build high-performance data pipelines and intelligent systems with the same precision and relentless pursuit of speed found in motorsport. Always pushing the limits, always optimizing for the win."

Live

Currently

Recent Win

Completed Stanford ML Specialization (3 courses)

Last updated: February 2026

This section auto-updates with my latest activities

Get In Touch

Let's Build Something

Currently open to opportunities. Usually respond within 24 hours.

Open For

ML Engineering internships
Freelance data science projects
F1 analytics collaboration
Guest speaking at tech events
Start a ConversationDownload CV
Usually respond within 24 hours
Email
kanisius@novar.me
LinkedIn
linkedin.com/in/kanisiusbagas1212
GitHub
github.com/maxvyquincy9393
Twitter
@maxquincy18