Work

- Undergraduate Teaching Assistant of Deep Learning (CSCI 1470). Managed logistics of the course by holding office hours, online help, and grading. - Head Teaching Assistant of Computational Linguistics (CSCI 1460). Involved in designing a new curriculum for the course based on deep-learning methodologies, as well as holding office hours, online help, and grading.

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- Developing an artificial-intelligence-backed application that aims to provide recommendations of posts and photos to a specific person to post on social media. - Tackles the question of modeling a specific person's "characteristics" through a new evaluation metric named the Impostor Test.

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- Researched and developed classification and object detection deep learning models (of above 90% accuracy for classification), to identify large-vessel occlusions in brain CTA scans. Used Python and the Keras framework. - Developed an artificial intelligence platform, using React and Flask, to enable Rhode Island Hospital radiologists and residents in rapidly developing machine learning experiments. - Recipient of the Karen T. Romer Undergraduate Teaching and Research Awards. Abstract was accepted to SIIM Conference on Machine Intelligence and RSNA Machine Learning Showcase.

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Working under the FAST Integrity: Discovery team in the Feed and Stories group of the company. The team focuses on improving news feed quality and reducing the negative experiences of users.

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- Using C, built a RocksDB engine wrapper for the Arcus Cache Cloud, adding support for relevant data structures (List, Set, Map, B+Tree). - Designed a REST API and relevant algorithms for the Arcus Cache Cloud to store an retrieve GIS data.

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- Implemented the front-end web platform for the social network, using React and Node.js, and using the design specifications as reference. - Suggested UI/UX changes for the web and mobile design, which was approved by the project manager. - Heavily refactored the back-end (using Express and MongoDB) to make the code cleaner, robust and more secure, while maintaining the API interface to support the existing mobile platform.

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Developed an online store for the HKIS Parent Faculty Organization (PFO) to sell apparel for the 2016 Chinese New Year. Managed the website during the sales period, making changes to functionality where necessary.

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I have analyzed the mobile game industry within the Korean, Japanese and English markets, utilizing various research data to understand what each market favours in mobile games (in regards to gameplay, business / monetization methods, artwork, and game progression), and what aspects and strategies make a mobile game more effective in generating revenue. Through analysis, I have ultimately formed various action plans for the company, including what to change or add in current games, and which direction to take for upcoming games. The internship opportunity was also a valuable experience in learning the work culture and customs of a mid-sized Korean company, learning the state of the video game industry, and learning industry-level frameworks and libraries.

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