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Akmal Yaasir fauzaan

@akmalyaasirfauzaan

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I build applied machine learning systems for vision, NLP, and recommendations.

Indonesia

Message

I'm building explainable career recommendation systems at BRIN, integrating academic and job data across institutions with semantic matching, cross-encoder reranking, XGBoost, SHAP, and skill extraction.

At Telkom University's MBC Laboratory, I research cervical cell segmentation with U-Net, U-Net++, SegNet, and Swin-UNet. My comparative work achieved an F1-score of 0.8868 and IoU of 0.7974 with Swin-UNet.

I've also developed computer vision, NLP, RAG, and AI recruitment projects—from flood mapping and drowsiness detection to Indonesian sentiment classification and secure FastAPI backends.

Experience

Work history, roles, and key accomplishments

Current

Research Intern

Current

National Research and Innovation Agency (BRIN)

Jun 2026 - Present (3 months)

Processed and integrated academic and job datasets for recommendation modeling. Developed semantic candidate-job matching using multilingual embeddings and Cross-Encoder reranking, and explainable recommendations using SHAP.

Python SQL Machine Learning NLP SBERT CrossEncoder SHAP Data Processing

Current

Research Assistant

Current

Telkom University

Sep 2025 - Present (1 year)

Conducted research on medical image segmentation using deep learning models including U-Net, U-Net++, Swin-UNet, and SegNet. Performed data preprocessing, training, and evaluation using metrics like Dice Score and IoU.

Deep Learning U Net Swin UNet SegNet Medical Imaging Image Segmentation Python PyTorch TensorFlow

Machine Learning Engineer Intern

Codecraft Infotech

Jun 2025 - Jul 2025 (1 month)

Analyzed customer-related datasets using classification and clustering techniques to identify behavioral segments. Generated insights from customer segmentation analysis to support marketing strategy discussions.

Python SQL scikit learn Classification Clustering data preprocessing EDA Model Evaluation

AI Developer Intern

Humic

Apr 2025 - Jun 2025 (2 months)

Analyzed medical imaging datasets to evaluate model performance and data quality, addressing class imbalance and recall-sensitive decision-making. Compared CNN-based models and presented findings to the technical team.

Python Medical Imaging CNN Model Evaluation Data Analysis Class Imbalance Recall