• Designed & delivered a reinforcement learning (RL) product enabling no-code RL training & evaluation workflows• Implemented RL algorithms and custom PyTorch model components for effective multi-agent RL• Developed end-to-end retrieval augmented generation (RAG) solutions for LLM applications, includingmultimodal PDF extraction, retrieval / reranking and document management / data annotation workflows

• Established a weak-supervision workflow to train machine learning models with limited labelled data• Conducted text clustering and topic modelling with BERTopic to decipher user and content patterns• Worked with stakeholders to support ad-hoc data analytics for minimising platform content risk

• Optimised paid ads promotions to improve ads revenue uplift by 32% & program ROI by 13%• Built dashboards & automation pipelines with SQL, Python (Pandas) & Excel• Conducted root-cause analysis on business metrics to inform business strategy

[A*STAR Research Internship Award] Robot Active Learning with Human-in-the-loop Reinforcement Learning• Researched Human-in-the-loop Reinforcement Learning (HRL) & Imitation Learning techniques• Designed & implemented sample-efficient HRL methodologies in PyTorch• Built a human-in-the-loop interface for reinforcement learning with PySimpleGUI

• Developed 6 TinyML & IoT projects, increasing customer engagement• Produced over 79 articles for the Seeed Studio blog, improving SEO traffic and sales• Completed as part of NUS Overseas Colleges (NOC) Shenzhen

• Corresponded with contractors and suppliers for the maintenance operations of Jurong Rock Caverns• Surveyed the feasibility of a industrial waste treatment facility on Jurong Island using transponder data• Streamlined data management protocols for JTC customer engagement reports