Hi, I'm Haikal Ardikatama

AI & Data Professional

AI & Data Professional crafting end-to-end AI solutions that power growth, optimize performance, and redefine what's possible.
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Haikal Ardikatama - AI Engineer and Data Professional specializing in computer vision and machine learning

About Me

I'm a passionate AI & Data Professional with over 3 years of experience developing and deploying end-to-end AI solutions across cloud and edge environments. I specialize in transforming complex business challenges into scalable, high-performance AI systems that deliver measurable results.

My expertise spans Python, C++, PyTorch, OpenCV, and cloud platforms, with a strong focus on architecture scalability, performance optimization, and data-driven decision-making that translates directly into business value.

Python
C++
PyTorch
OpenCV
AWS
GCP
Docker
TensorFlow
Git
MLOps

Work Experience

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RnD Engineer

Digital Place Vision Pte Ltd

Tangerang, Indonesia

  • Led R&D for AI-driven planogram compliance solution achieving <2min processing time per shelf
  • Designed lightweight product detection models achieving 95% mAP on 70+ SKUs
  • Developed lightweight open-set product recognition model achieving 85% TPR@FPR0.1% on low-quality cropped product images
  • Developed feed recommendation system reducing feed consumption by 30% using Bayesian Optimization
  • Enhanced supply chain simulation and routing optimization engine improving delivery efficiency
Mar 2022 - Dec 2023

AI Engineer

PT. Nodeflux Teknologi Indonesia

Jakarta, Indonesia

  • Designed multi-stage FIQA pipeline reducing poor-quality face registrations by 50%
  • Developed head detection model using YOLOX achieving mAP >85% for crowd estimation
  • Enhanced helmet detection accuracy by 25% for traffic violation verification
  • Optimized streaming pipeline increasing throughput from 18 to 50 concurrent streams
  • Developed TrainingOps and DataOps frameworks accelerating model iteration by 50%
Aug 2021 - Jan 2022

AI Engineer Intern

PT. Nodeflux Teknologi Indonesia

Jakarta, Indonesia

  • Developed multi-label facial attribute recognition model achieving 93% mAP@K
  • Deployed model as RESTful API on Azure Cloud using Flask and Docker Compose
  • Implemented occlusion-related attribute detection for KYC face recognition systems

Education

Bachelor's Informatics Engineering / Computer Science

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Gunadarma University

Depok, Indonesia | GPA: 3.78

Thesis: Developed a COVID-19 classification system using ConvNeXt (CNN) on X-ray images, achieving over 96% across accuracy, precision, recall, and F1-score. Packaged as a Dockerized API for deployment.

View on GitHub

Machine Learning Track Awardee

Jan 2021 - July 2021

Bangkit Academy

Virtually

Capstone Project: Kikuma – an AI-based solution for acne diagnosis using MobileNetV2, integrating machine learning, cloud computing, and mobile development.

View on GitHub

Certifications: Math for ML Specialization, Google IT Automation & Support, TensorFlow Developer, and TensorFlow Data & Deployment by DeepLearning.AI.

Skills & Tools

Hard Skills

AI Engineering Software Engineering MLOps Computer Vision Version Control System AI System Architecture AI Optimization for Edge Devices Cloud Platform (GCP and AWS)

Soft Skills

Project Management Agile Development Critical Thinking and Problem Solving Communication

Programming Languages

Python C++ Java SQL

AI Development Libraries

PyTorch Hugging Face TensorFlow Scikit-learn NumPy Pandas Ultralytics

Tools & Platforms

OpenCV ONNXRuntime TensorRT MLFlow Docker Git AWS GCP Azure

Public Speaking

Pengembangan Inovasi AI di Indonesia

National Webinar – Universitas Dinamika

June 2023

How to Create Effective Training Pipelines using TensorFlow

Google I/O Extended Depok 2023

July 2023

Unleashing the Power of AI: Shaping the Future Together

Tech Talk – ML/AI, GDSC Gunadarma

July 2023

Inovasi Teknologi AI: Peluang dan Tantangan di Era Society 5.0

National Webinar – Universitas Lambung Mangkurat

November 2023

Utilizing FiftyOne as a Computer Vision Tool for DataOps

Internal Dev Session – DSI 2

October 2023

View on GitHub

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