Elston Tan
Hi, I’m Elston Tan—a computing and AI enthusiast who loves turning ambitious ideas into real-world AI systems.
About
Hi, I’m Elston Tan—a computing and AI enthusiast who loves turning ambitious ideas into real-world AI systems. I’ve built end-to-end vision pipelines, SLAM research, and production-grade ML deployments for clients and researchers, with a track record of accelerating performance and delivering value. My work spans from research into open-vocabulary 3D segmentation to practical SDKs and data platforms.
I’m currently pursuing a Bachelor of Computing in Computer Science at the National University of Singapore, and I also completed a Diploma in Applied AI and Analytics at Singapore Polytechnic, along with a Nanodegree from Udacity. I lead and participate in AI-focused clubs, mentor teammates, and enjoy collaborating across disciplines to push the boundaries of what AI can do in industry.
- 4 years' experience
- Joined February 2026
Industry experience
- Software & Internet
- Media & Entertainment
- Professional Services
- Manufacturing
- Education
- Government
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Work experience· 9 roles
Collaborating on research attachments in SLAM and open-vocabulary 3D segmentation. Working under the Deputy Director in the Spatial Sensing and Machine Perception team.
Spearheaded and led development for an in-house research project; engineered an end-to-end vision pipeline using novel methods for Hyundai Steel as the sole research engineer and secured a contract. Researched state-of-the-art architectures and benchmarked with client datasets. Introduced ~15% increases in accuracy and mean-average-precision; sped pipelines by ~40% for real-time inference. Implemented custom loss functions and architecture modifications. Researched spatiotemporal methods for in-house licensing.
Spearheaded an in-house research project and built an end-to-end vision pipeline for Hyundai Steel as the sole researcher. Researched state-of-the-art architectures, benchmarked on client datasets, and achieved an average 15% increase in accuracy and mean average precision. Improved real-time inference by ~40% for client production use-cases. Implemented custom loss functions and architectural tweaks; studied spatiotemporal methods for in-house licensing.
Education· 6
Certifications and awards
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