GTM for online courses in Asia Pacific

Tested the hypotheses of entering different markets with online courses. Tested different kinds of monetization, identified the paying segments, target audience and product positioning.

Tackled the learning issue by implementing various personalized learning styles and improved the product checkout process by decreasing the clicks required for payment from 4 to 2 through A/B testing. This streamlined the checkout process, making it more efficient and user-friendly.

As part of my role at Time Research & Innovation, I Ied creation of World Health Aid (WHA), a multilingual real-time health advice platform designed to support disadvantaged individuals. WHA is a comprehensive solution that facilitates telemedicine services, bridging the gap between healthcare providers and underserved populations. It combines live patient and clinician-facing decision support systems, offering a range of paid and free services, including self-diagnosis screening through video and voice chat, multilingual instant translation, voice-command symptom search, real-time messaging, and secure record keeping.

PROBLEM: There was a problem that web2 users could not onboard easily on web3 platform because of the complexity with the process at Fly wallet SOLUTION: Not a lot of travelers are web3 enthusiasts which kind of created a segmented market for FlyWallet. So I created documents and flowchart that will enable users that have Google account, Facebook account and Apple ID to onboard easily and save for travels ahead. Created multiple integration partners and monitored the API wrappings by the engineers. This created a diverse customer base for the web3 travel tech company.

As a computer vision expert, I was consulted to address the challenge of facial pore recognition for a beauty application. The problem involved accurately identifying and measuring individual pores on various skin types and tones. To tackle this, I designed an algorithm that could adaptively capture high-resolution images and extract relevant features. Leveraging machine learning, I trained a model on a comprehensive dataset that I helped gather, comprising different face images under various lighting conditions. The resulting algorithm could recognize and measure individual pores with high precision, providing personalized skincare recommendations to users, and thereby enhancing the app's user experience.