Editor’s Note
This profile of NTU PACE graduate Robin Yap illustrates how a foundational passion for learning can fuel a remarkable career pivot. His journey from educator to innovator at the crossroads of AI and gemology highlights the transformative power of continuous education in an evolving technological landscape.
Robin Yap, a graduate of the NTU PACE (SCTP) Advanced Professional Certificate in Software Engineering, views learning not just as a professional requirement but as the lens through which he understands the world. This mindset has guided his career from teaching physics and mathematics in a Singaporean secondary school to his current role at the intersection of AI and the gemstone industry.
His career took a turn when he joined A*STAR as a research engineer, working on projects that combined mechanical engineering with emerging AI applications. This experience sparked his interest in intelligent systems. Driven by this fascination, he pursued further studies, earning a Master’s in knowledge engineering and robotics, which laid the groundwork for his eventual PhD focus on robotics and AI.
Robin’s curiosity led him to pursue a Doctor of Engineering in robotics and artificial intelligence at the Tokyo Institute of Technology in Japan. This period was a significant turning point, immersing him in a culture that valued precision and discipline.
The experience broadened his perspective on how culture shapes engineering practices and innovation.
Upon returning to Singapore, Robin transitioned into the finance sector as a machine learning engineer. To strengthen his foundational skills, he enrolled in the Software Engineering SkillsFuture Career Transition Programme.
Today, Robin is an AI and computer vision engineer at Porolis Technologies, a startup in the gemstone and jewellery industry. His team developed a proprietary photomicrography device called KROMA™ that captures detailed images and videos of gemstones for AI analysis.
The goal is to provide jewellers and traders with reliable, high-quality images to enhance transparency and trust in the trade. The work involves unique challenges, as gemstone grading lacks universally accepted industrial benchmarks. Progress requires collaboration with domain experts and careful review of academic research to align their models with the best available knowledge.
A typical day involves software validation for the startup’s hardware systems, capturing gemstone images, testing AI models for accuracy, and refining results through comparisons with expert assessments. The team is also exploring patent opportunities for both the hardware and software components of their system.