- π€ Applied AI & Systems Engineer with a background in Computer Science and applied AI research.
- π§© Work at the intersection of Artificial Intelligence, Software Engineering, and Systems Development.
- ποΈ Background in Deep Learning and Computer Vision, especially object detection, instance segmentation, and pattern recognition.
- π§ Currently expanding into AI-powered applications, LLMs, RAG systems, developer tooling, Linux desktop systems, cross-platform software, and software architecture.
- π§ Enjoy experimenting with software and hardware, building productivity tools, exploring Linux, and turning ideas inspired by games and everyday problems into software projects.
- Design software systems that connect AI models with APIs, databases, user interfaces, and external services.
- Build back-end services and data pipelines for AI applications.
- Develop developer tools and productivity-oriented software.
- Explore Linux, desktop environments, system integration, and automation.
- Build cross-platform applications that communicate across devices and operating systems.
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- Develop and experiment with Deep Learning and Machine Learning systems.
- Work with Computer Vision, particularly object detection, image analysis, segmentation, and visual recognition.
- Explore LLM applications, Retrieval-Augmented Generation (RAG), and AI-assisted software systems.
- Experiment with model architectures, training workflows, evaluation methodologies, and deployment.
- Apply AI to domains including agriculture, medical imaging, and other real-world problems.
- Translate research ideas into reproducible software implementations.
- Investigate model architectures and compare their practical performance.
- Build datasets, experimentation pipelines, and evaluation workflows.
- Work on applied research involving agricultural AI, medical imaging, and computer vision.
- Bridge the gap between academic experimentation and usable engineering systems.
- Former Machine Learning Mentor at Bangkit Academy 2024 by Google, GoTo, and Traveloka, supporting more than 25 students throughout their ML learning path and projects.
- Served as a laboratory/teaching assistant at Universitas Mulawarman, Samarinda, Indonesia for subjects including Machine Learning, Deep Learning, Data Structures & Algorithms, and Object-Oriented Programming.
- Help students understand both the theoretical foundations and practical implementation of software and AI systems.
- Occasionally helped students to write undergraduate thesis by guiding the research flow implementation, programs development, and deliverables preparation.
- π Hold a Bachelor of Computer Science (B.CS. / S.Kom.) from Universitas Mulawarman, with a strong academic and research background in Applied AI, Deep Learning, and Computer Vision.
- πΎ My research includes agricultural AI and intelligent vision systems, with Scopus-indexed research publications involving Smart Agricultural Technology (Q1) and Artificial Intelligence in Agriculture (Q1).
- π§ My research portfolio also extends across Computer Vision, deep learning-based detection, image analysis, agricultural automation, and medical imaging.
- π¬ My research experience bridges academic research and practical engineering, focusing on developing, evaluating, and applying AI systems to real-world problems.
- π I am particularly interested in research that connects AI models, data, software systems, and domain-specific applications rather than treating machine learning models as isolated components.
| Tech Stack | Language/Tools/Frameworks |
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| Systems / Performance |
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| Scripting / Data |
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| Web |
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| Enterprise / JVM |
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| OS / Shell |
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| Editors / IDEs |
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| Terminal / Browsers |
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| Deep Learning |
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| Data / ML |
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| Compute / Infra |
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| Learn Code Here |
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