Member of the team which brought COzTERRA to life

• Conducted a trial at SPD Bedok to test ADAP Ball that enhances motor and cognitive skills of with children with autism with 9/10 teachers wanting to deploy it into their teaching curriculum • Awarded top 5 Finalist for AIT 100 Innovation Challenge Bangkok• Attained $10K from NUS Enterprise and $15k from raISE Singapore to continue development of products for children with autism• Awarded first place in Social Oven 2020 raISE Singapore and “Green lane” through raISE’s VFG Youth Funding• Redesigned our product into an extremely modular and robust IoT device and expanded its use cases to include assisting in remote physiotherapy and gym workout sessions with LAMP stack, Node-red and Grafana• Deployed IoT sensor solution to AWWA for trial• Built a PoseNet Joint detection model for workouts at https://awesome-glittery-ostrich.glitch.me

• Single-handedly designed, built and programmed an IoT weight-based system to track hospital inventory with positive user feedback which opened the door to a second trial• Successfully deployed IoT weight-based system and ran two successful trials at partner hospital with 90% accuracy • Successfully deployed Over-The-Air (OTA) firmware updates for ESP8266 microcontroller from an HTTP server, smarter sensing algorithms and programmed the microcontrollers to run a non-hardcoded programme to improve the accuracy and mass producibility of the system as well as to reduce future maintenance and manpower costs• Attained $4k funding for two successful trials from a partner hospital and $10k from NUS Enterprise to build an enterprise grade system for B2B deployment• Designed an embedded custom Printed Circuit Board (PCB) using Autodesk Eagle for IoT weight sensors for mass production to improve the reliability of the sensors • Designed and built a machine vision and weight fusion inventory management system to track hospital inventory to deploy for third and final trial at partner hospital• Secured a third trial with partner hospital to deploy fusion system witnessed by ALPS to allow Vision.ai to vie for a government tender such that Vision.ai’s system would be deployed in all Singapore public hospitals• Designed a suitable test-lab to conduct small scale internal trial and stress tests to improve and prepare machine vision and weight fusion system for real world scenarios and user habits

Top 3% selected for the programme. Entrepreneur First is the world’s leading talent investor. It invests time and money in the world’s most talented and ambitious individuals, helping them to find a co-founder, develop an idea, and start a company. So far, EF helped 2,000+ people create 300+ companies, worth a combined of almost $3bn.EF is backed by Reid Hoffman (founder of LinkedIn) and Greylock Partners, Mosaic Ventures, Founders Fund, Lakestar and some of the world's best entrepreneurs.

• Acquired Factory Assembly & Testing skills after building 3D printers from the ground up which translated into better designs for manufacturing and assembly as well as industry standard testing procedures • Performed deep system testing and analysis of how individual components affect the 3D printer to identify potential failure points and understand how components interact with one another • Spearheaded and designed a novel standardised modular light scanning system using CAD software to standardise light scanning and testing methodologies as well as long term reusability and interchangeability of inner templates • Spearheaded project to improve tension film assembly production yield to reduce the wastage of resources and increase overall manufacturing capacity

• Oversaw project technical direction, design decisions and execution of ideas in both years• Awarded Finalists with funding to develop solution further in both years• Spearheaded the problem statements by employing an empathetic approach and design thinking to build a user centric solution with high adoption rate• Built and tested a patient turning solution prevent formation of pressure ulcers and prevent nurses back injuries, tested solution in public hospital and reiterated design based on real user feedback (2017)• Revised a camera-based design over several iterations based off results of on-site testing and feedback from users, with the aim of eliminating medical inventory management problems in medical clinics (2018)• Demonstrated a final working prototypes and presented them to a panel of judges and end-users in both years