Awards & Achievements
Recognition from national and international AI/ML competitions, showcasing innovative solutions across healthcare, security, and sustainability
4th Winner
4th Winner - GEMASTIK 2025 Data Mining Competition
Ministry of Higher Education, Science, and Technology
Placed 4th among 200+ teams nationwide by developing a Graph-of-Graphs Neural Network (GoGNN) integrated with TabPFN for cooperative business classification in the qualification phase, then live-coded an image preprocessing pipeline and ResNet18-based model for Javanese script (aksara Jawa) classification in PyTorch without internet access in the finals, demonstrating expertise in advanced graph neural networks, computer vision, and rapid deep learning implementation under constraints.
Semifinalist
Semifinalist - Health-themed AI Hackathon
National University of Singapore
Designed a two-stage EEG neurological events detection pipeline using EEG-DETR (EEG Detection Transformer), which incorporates Multimodal Convolutional Neural Network as the feature extractor for identifying neurological events in brain signal data. Competed against 200+ global teams.
Finalist
Finalist - AI Hackathon
Institut Teknologi Bandung and Telkomsel
Progressed past 330+ teams with TRACE: Traceable Real-time Adaptive Continual Explainable Deep Fake Detection System using Audio Visual Feature Fusion model, implemented with FastAPI web framework and PyTorch deep learning framework for large-scale video data processing.
1st Winner
1st Winner - Data Analysis Competition
Institut Teknologi Sepuluh Nopember
Placed first among 355+ teams across Southeast Asia by implementing data analysis and machine learning solutions, including AutoML modeling and feature engineering techniques for solar power output prediction.
Finalist
Finalist - Dataquest Competition
Universitas Airlangga
Developed an Intrusion Detection System using Gradient-Boosted Tree Model for multiclass network traffic classification with iterative feature engineering based on data analysis. Reached finals among 200+ nationwide teams.
3rd Winner
3rd Winner - RISTEK Datathon
RISTEK Fasilkom UI
Placed 3rd among 300+ international teams by developing a Bank Loan Fraud Detection System using Temporal Graph Neural Networks in the qualification phase, then developed an e-commerce Semantic Search Engine using Cross-Encoder architecture and Contrastive Learning in the finals, improving product search relevance for better customer experience.