I graduated from UC Irvine in June 2021, majoring in Business Information Management, a major that focuses on both business and IT aspects. I landed a job as an Operation Specialist at JustFoodForDogs, focusing on on-time delivery of raw materials.
The one year of real-world exposure to business problems showed me how data could bring real, positive impacts to a company. This had led me to pursue my Master’s Degree at UC Irvine in Business Analytics, developing my analytical skills, data management, and statistical expertise within the realm of business.
I love to dig into customer problems and solve them with accessible modern technology. A great degree of familiarity with agile methodologies, software engineering processes, and data exploration techniques allows me to execute and lead a process that entails product planning, scheduling, and controlling.
A plethora of business and IT backgrounds from both my Bachelor’s and Master’s Degree, as well as my willingness to continue learning from other people’s perspectives on future technology help me to be more adaptive in this fast-changing world.
Supporting Skill
Preferred Job
Supporting Skill
Being aware that product releases cover tech, business, and UX aspect of a product, I constantly learn new skills in my own time and in school, from hardware, such as Raspberry Pi and Arduino, to software, such as Python Packages and Android Studio.
I learned business aspect of a product mostly from school. Related courseworks, including Lean Startup, Management of Information Technology, and Business Analytics Introduction, prepare myself in product research and release.
During my studies, I was first introduced to object-oriented programming through C++ and Python. After few years in university, I started to learn information retrieval and visualization through MySQL and R (ggplot2 library). In my own time, I sharpen my coding skills by signing up for online Data Scientist Python certification and developing side projects, such as an Android app.
Besides, I learned UX design processes while pursuing my study, including wire framing and UI design.
This is a project that was completed during my university time in IN4MTX 113 subject at University of California, Irvine. In this project, we first interviewed the Teacher Assistants (who acted as if they were the stakeholders) to know better what was expected in the product. From the gathered information, we summarized it in the specification. The specification included use cases and scenarios, as well as the functional and non-functional requirements of the app.
This project was part of CS 121 subject at University of California, Irvine. It was programmed with Python and other external libraries to index a local corpus and then allowed users to search documents through the search box in the desktop GUI application. BeautifulSoup was used to parse the HTML content and NLTK was used to tokenize and lemmatize each word. Term Frequency-Inverse Document Frequency (TF-IDF), HTML tag rating, and PageRank algorithm were used to rank the HTML pages, leading the search engine to be one of the fastest and most accurate search engine in the class.
This project was created in my leisure time to be used in a company. The Android app and the Arduino were used as means of upgrading the motorized gate to a smart gate lock where employees could simply open the gate with their smartphones. The Android app was developed using Android Studio. Firebase Realtime Database was used to establish the connection between the app and the Arduino unit. The company, as a result, had the gate operator work on something more important (boosting the company’s productivity by a bit).
This was IN4MTX 133 subject's project, allowing a user to keep track their sleep habit using iOS or Android smartphones. The sleep tracker app had the ability to log the overnight sleep and log sleepiness during the day. It was developed using Ionic and Angular to achieve a cross-platform mobile application using a single codebase.
This is a project from IN4MTX 143 subject where US financial summaries of each candidate in the US Federal Election Commission dataset were visualized through different visual representations. ggplot2, an R library, was used to generate the visual representations that were used to discover stories that might verify or refute the given hypotheses.
This project was created in my leisure time to build my online presence in this technology-driven world. The UI was first designed and planned with Adobe XD. The prototype from Adobe XD was then implemented with HTML and CSS to produce a static website.