Recently, my works have been centered on:
Evaluating Large Language Models (LLMs):
I am developing methods to detect and reduce inaccuracies in AI-generated content, often referred to as "hallucinations." This involves analyzing model outputs and implementing techniques to ensure the information produced by AI systems is reliable and trustworthy.
Fiber Optic Leak Detection:
I work on systems that use fiber optic cables installed along pipelines to detect water leaks. These cables act as sensors, capturing data that can indicate changes such as temperature shifts or vibrations caused by leaks. By analyzing this data, we can identify and locate leaks more efficiently, helping to maintain and protect water infrastructure.
Climate Teleconnection Analysis:
I am involved in analyzing distant climate interactions using high-performance computing resources provided by NAIC. This project focuses on identifying and understanding how climate events in one region can influence conditions in another, contributing to more accurate climate predictions and better-informed environmental policies.
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Past Projects
During my Ph.D., I developed annotation tools for 3D point cloud data and applied deep learning techniques for object detection, assisting researchers in geospatial and forestry studies.
In earlier roles, I worked as a software developer and team lead on projects involving fraud detection, image analysis, and backend system development.
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Education
Ph.D. in Applied Informatics, Norwegian University of Life Sciences (2020)
Focus: Deep learning and 3D data annotation
M.Sc. in Informatics, Bandung Institute of Technology (2016)
Focus: Machine learning and software systems
B.Sc. in Computer Science, Sepuluh Nopember Institute of Technology (2011)
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Expertise
Machine Learning & Deep Learning Algorithms:
Building predictive models, neural networks, and AI systems for various data types.
Computer Vision & 3D Data Processing:
Specializing in point cloud classification, object detection, and developing smart annotation tools for large datasets.
Sensor Data Analysis:
Working with data from fiber optic sensors and LiDAR, with applications in environmental monitoring and autonomous systems.
Fraud Detection:
Applying natural language processing and anomaly detection techniques to identify fraudulent activities in text and transaction data.
Full-Stack Development:
Proficient in software architecture and development, enabling seamless integration of machine learning models into real-world applications.
Technical Project Management:
Experienced in leading interdisciplinary projects, coordinating technical teams, and delivering complex solutions on schedule.
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