Hi there, I'm Elston 👋

AI Research Lead (Oct 2026 - Present)

Leading in AI research for client projects.

Engineer (Jun 2026 - Present)

Working with both hardware and software. Classified.

Advisor and Outreach (May 2026 - Present)

Partnered with multiple factories/companies in China, Middle-East, Southeast-Asia and Europe. Helping organisations to architect, integrate and deliver operational security systems in air, land and sea.

Advising the company in security and tech related matters and connecting with organisations as well as military leaders.

Chief Technology Officer (Aug 2026 - Present)

Managing product execution and technology

Acting Chief Executive Officer (Sep 2026 - Nov 2026)

Previous CEO left so I had to overtake overall business operations for a period of time

Founding ML Lead (March 2026 - Present)

Leading the machine learning and research team.

• Hiring manager for ML team
• Managed client relations and prototyping for early-phase client projects
• Leading two research teams

Air Defence Weapon Specialist

Posted to the 3rd Divisional Air Defence Battalion as a sergeant. Trained to shoot anything flying down.

Cross-trained on two weapon systems.

• 4th LBAD Spyder Conversion Course (Mar 2026 - May 2026)
• Coordinated band contigent for National Day Parade 2026
• Developing autonomous force protection solutions

Air Defence Weapon Specialist Trainee

Trained under the Air Warfare Training Institute, graduating top 5 in the class.

• 11th AFSCT (Air Force Specialist Cadet Training) Term (Dec 2025 - Feb 2026)
• 111th ADSS (Air Defence Specialist School) (Feb 2026 - Mar 2026)

Researcher (Aug 2025 - Present)

Collaborating with the German Research Center for Artificial Intelligence under Dr Jason Raphael Rambach (Deputy Director) in the department of Spatial Sensing and Machine Perception

• Working on SLAM integrated with 3d open-vocabulary semantic segmentation

Chief Technology Officer (Jun 2025 - Jun 2026)

Responsible for leading a multinational development team with members from the US, London, Italy and Singapore.

• Scaled our platform and introduced an increase of ~83.7% CMAU to 90 in less than a week
• Collaborated with external organizations, managed the team and logistics for the collaborations and introduced a 2x increase in userbase during one conference
• In-charged of infrastructure and handled cyber attacks and data breaches
• Built monitoring pipeline which tracked drop-off rates and user-side bugs/errors

Founding Technical Lead (Apr 2025 - Jun 2025)

Responsible for leading a multinational development team of 5 from the US and Singapore to ensure flawless execution of pilot sessions across multiple schools in Singapore

• Lead the development for a pilot sessions at CHIJ, SAJC and BuildingBlocs
• Accumulated over 700 users on our live waitlist
• Handled traffic and website for serving over 100 concurrent users on live production site
• Implemented model/technology changes
• Responsible for deployment of production site with continuous integration and development methods
• Handled technology costs and maximized for cost-efficiency
• Spearheaded collaboration efforts with clubs in Singapore Polytechnic and BuildingBlocs

Research Engineer (Jan 2025 - July 2025)

Full-time contracted AI Engineer for A*STAR ARTC Intelligent Product Verification (IPV) department reporting under the Deputy Group Manager.

• Ported models to TensorRT engine and onnx for C++ runtime
• Implemented model compression and sped models up by ~40% through methods like quantization etc
• Developed and documented an SDK (Software Development Kit) in C++ for model deployment
• Rapidly developed proof-of-concept solutions for managers and clients
• Improved model performances by ~15% through optimization
• Led the development and ensured the success of three client projects
• Secured funding for projects
• Led the development and closed multiple projects worth ~170k each with high customer satisfaction/feedback
• Collected and annotated datasets from clients
• Crafted comprehensive reports for group managers and clients
• Undertook research, prototyping and finetuning of SOTA VLMs for real-world use-cases for multiple clients
• Developed a full-stack data platform and containerised for usage by clients (converted frontend/backend code into machine code and containerised using podman)
• Prototyped and researched Monocular Depth Estimation as well as light microscopy reconstruction with Physics Informed Diffusion Models

AI Research Engineer Intern (Mar 2024 - Jan 2025)

• Doing research into state of the art models and architectures and reproducing papers for client projects as well as in-house research projects for ARTC IPV (Intelligent Product Verification).
• Created end-to-end pipelines and models for clients and created proof-of-concept solutions for in-house research projects.
• Created proof-of-concept defect detection solution that met KPIs for Hyundai Steel and managed to secure a contract and funding for the project.
• Reproduced and modified state-of-the-art papers for in-house research project on spatial-temporal defect detection and presented to the whole group.
• Created an AI-automated manufacturing-based labelling tool as a webapp and containerized with Docker for IPV.

Research Intern (IHPC) (Nov 2022 - Jul 2024)

• Interned at IHPC (Institute for High Performance Computing) as an AI Research Intern under the department of SCC (Social and Cognitive Computing)
• Co-authored in a paper titled “CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes” that got accepted to NeurIPS 2024
• Helped develop a dataset for visual reasoning and benchmarking a VQA (Visual Question Answering) model
• Worked ad-hoc on 3 projects under Dr Paritosh Parmar on the topic of visual reasoning
• Helped co-author and publish an open VQA dataset benchmarked againt other current VQA datasets to NeurIPS 2024

Project Intern (I2R) (Sep 2022 - Jan 2023)

• Worked in the Institute for Infocomm Research (I2R) Visual Intelligence division as a Student Researcher and Project Intern
• Developed, tested and analysed two methods of detecting blurred images
• Cleaned and modified datasets for testing and training purposes (e.g. gaussian blurring images, reformatting images)
• Researched different edge operators and developed feature engineering paired SVM model for classification task
• Tested various CNN architectures for optimized performance on this specific problem (e.g MobileNetV2)
• Made detailed reports on developments in research every week and presented report to supervisor (worked with numbers and graphs)