Ahmad L.

Key Skills

Software

LabelImg

Label Studio

Roboflow

CVAT

Top Subject Matter

Computer Vision

Masked face detection on edge devices (YOLOv4)

Edge AI inference optimization

Top Data Types

Image

Video

Text

Top Task Types

Object Detection

Data Collection

Classification

Bounding Box

Polygon

Segmentation

Freelancer Overview

Research Assistant - AMIKOM University. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, AMIKOM University Yogyakarta (2025). AI-training focus includes data types such as Image, Computer Code, and Programming and labeling workflows including Object Detection, Evaluation, and Rating.

Labeling Experience

Research Assistant - AMIKOM University

ImageClassificationObject Detection

As a Research Assistant, you conducted real-time object detection research using edge devices to classify masked face scenarios. You worked with a research team under faculty guidance to build and improve an on-device YOLOv4-based application. The role required strong skills in computer vision, dataset handling, and deploying inference pipelines on embedded hardware. • Conducted research on real-time object detection (YOLOv4) for masked/wrong masked/no masked face classification • Collected and curated a dataset of 4,000+ images for training and evaluation • Implemented the real-time detection application using NVIDIA Jetson Nano and Raspberry Pi 3B • Tuned performance to improve processing speed by about 3x

2022 - Present

Research Assistant — Edge inference optimization (Nov 2022 - Present)

Other

Collaborated on optimizing hardware performance of NVIDIA Jetson Xavier NX for deep learning inference under an advisor team. Supported research focused on improving efficient edge inference through model and runtime optimization activities. Contributed as an undergraduate research assistant to enable evaluation and iteration of inference performance on target hardware. • Hardware performance optimization for edge deep learning inference • Jetson Xavier NX deployment/evaluation workflow • Supported ongoing research collaboration with external professors • Participated under MoECRT ACE Open Research program support

2022 - Present

IoT Engineer — Automation and IoT system development (May 2025 - June 2026)

OtherData Collection

Maintained and developed industrial automation systems, including building smart IoT devices that interface with machine controls and user inputs. Developed a smart locker using ESP32 and a resistive touchscreen as an HMI and created a card gacha machine using RFID with a web app interface. Although not explicitly described as AI training or labeling, these activities support data acquisition and automation pipelines used in intelligent system operation. • Maintenance of industrial automation machinery systems • Built IoT smart locker with ESP32 and touchscreen HMI • Built card gacha machine with RFID and Angular web interface • Developed interfaces supporting operational data collection for downstream AI use

2025 - 2026

Research Assistant — Real-time object detection dataset curation and edge inference (May 2022 - May 2023)

OtherImageObject Detection

Performed real-time masked face classification and object detection research using YOLOv4 to identify masked, wrong-masked, and unmasked faces from camera input on edge devices. Built and curated a dataset of over 4,000 face images for model development. Validated inference performance by deploying and running detection pipelines on embedded platforms for faster real-time throughput. • Dataset curation of masked vs. unmasked face images • Real-time object detection workflow for edge deployment • Use of NVIDIA Jetson Nano and Raspberry Pi 3B for inference • Improved detection/application speed by approximately 3x

2022 - 2023

Education

Work History