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*The A*STAR Computing and Information Science Scholarship was renamed to A*STAR Graduate Scholarship (Computing) in 2025

Sometimes, a single nudge can redefine one's path. For Xen, this came as an unexpected suggestion, propelling her from the Philippines to Singapore, and into the realm of cutting-edge technology.

Xen’s life would be a lot different had she not decided to leave Philippines to pursue Computer Engineering at Temasek Polytechnic in Singapore. Xen had always planned on doing a PhD, but much later in life. Taking inspiration from her grandfather who hoped to grow a better coconut so farmers could make more money and have a better life. She hoped her work will also bring technologies that make life better for others.

A*STAR came knocking through its Scholarship talks at Temasek Polytechnic and offered her scholarships, twice. First, she took the Undergraduate Scholarship to study Computer Engineering at the National University of �����(NUS); and then for a PhD under the A*STAR Computing and Information Science (ACIS) Scholarship, also at NUS.

Her decision to do an Industrial PhD put her on a different path from her peers. In addition to her supervising professor at NUS, she was also attached to one of A*STAR’s Research Institutes, the A*STAR Institute for Infocomm Research (A*STAR I²R) where she worked with another supervisor on industry projects. She was stationed at various locations to conduct field tests and worked with A*STAR I²R's engineers and system scientists to develop workable solutions for immediate operational challenges.

Her area of research is the application of machine learning to indoor localization - or a sort of GPS for indoor spaces. An Indoor Positioning System (IPS) differs from GPS in various ways. Firstly, GPS does not work well inside buildings because satellite signals can be obscured by walls and ceilings, so an IPS would need to use other wireless technologies such as Bluetooth or Ultra-Wideband instead. Secondly, indoor positioning can require more precision and consistency to track assets in real time, which can be a challenge when objects and devices block or interfere with wireless signals. Her PhD thesis centres around using machine learning to overcome such challenges and enhance localization accuracy in practical settings.

Xen seeks to improve workflow efficiency on factory floors and manufacturing facilities. For example, in an assembly line, workers often share tools, which means the tools sometimes get misplaced. Or a worker may have moved a work trolley to another part of the factory and forgot to return it. The workers next needing the tool or trolley would have to locate the item before they can start work. This kind of delay can be minimized if there were systems to always know where the assets in the factory are – which the use of an IPS may be able to fix. The technology she is working on is transferable into many applications, for example, in eldercare. An elderly person can be given an IPS tag equipped with fall detection sensors or an SOS button, so caregivers can offer quick and immediate assistance in the event of an emergency. While the convenience of locating misplaced tools might seem minimal, the broader applications of Xen's research, like aiding eldercare with immediate emergency responses, hold the potential to save lives.

A trajectory she had not planned for when she was 16. She could still be living in the Philippines or working as a computer engineer while planning a later dive into the PhD track; not quite where she is today. In her twenties, stepping into a career as a scientist, and already with a patent to her name (S. Krishnan and R. X. M. Santos, "Identification Tag," Patent WO/2021/17307 Patent Appl. PCT/SG2021/050086, 2021) for her work using computer vision in the robust identification of tags, especially after abrasive treatments, is a testament to her innovation and dedication. Despite her young age, Xen has already made a lasting mark in her field.