Singapore
Advised the incoming junior team on the planning and execution of CPIC, supporting leadership transition and helping ensure the long-term sustainability and continuity of the course. Provided guidance on trainer recruitment, syllabus design, lecture and contest preparation, logistics, sponsorship outreach, and participant management. Mentored the organizing team on sustainable event operations and programme planning, enabling CPIC to continue serving future batches while maintaining its mission of providing accessible competitive programming education.
Scaled CPIC from its inaugural run into a larger 200+ participant programme, supported by 20+ trainers. As Head Trainer, managed trainer recruitment, role allocation, and coordination, while refining the syllabus and maintaining the quality of lectures, practice materials, problem sets, and contests. As Organizer, oversaw the expanded course operations, including venue planning, sponsorship outreach, catering, logistics, participant coordination, and event execution. Helped grow CPIC into a larger and more structured programme while preserving its accessibility as a free introductory course for competitive programming.
Launched and led the first run of CPIC, establishing it as Singapore’s largest free introductory competitive programming courses. Built the course from the ground up, bringing together over 100 participants and 10+ trainers. Designed the initial course structure, syllabus, and training model, while also preparing lecture and contest materials. Recruited and coordinated trainers, allocated teaching responsibilities, and delivered selected lectures. Oversaw overall course execution, including participant coordination, logistics, communications, and operations, ensuring a strong learning experience for the inaugural cohort.
Conducted research on AI-guided simulated annealing for automated gene editing design, exploring how machine learning and large language models can improve the optimisation of gene, mRNA, and CRISPR guide RNA sequences. Developed a framework that combines heuristic search with adaptive AI-based scoring to evaluate candidate biological sequences more efficiently across large combinatorial search spaces. Worked on feature extraction, model-based sequence scoring, simulated annealing optimisation, and validation using CRISPR guide RNA datasets. Implemented a traditional machine learning pipeline using Gradient Boosting Regression to predict guide RNA quality from biological sequence features such as GC content, positional nucleotides, homopolymer runs, dinucleotide patterns, and sequence complexity. Also explored the use of LLM-driven scoring to support context-aware and personalised sequence evaluation.
Led the training programme for Singapore NOI competitive programming preparation. Oversaw trainer coordination, curriculum delivery, logistics, and session execution, while also delivering selected lectures on algorithms, problem-solving techniques, and competitive programming strategies. Ensured trainers were well-supported and that students received consistent, high-quality preparation for national-level informatics competitions.