About Me

I am currently a Master Student in the Department of Electrical Engineering at National Tsing Hua University (NTHU), under the supervision of professor Min Sun. Additionally I am serving as a deep learning intern at MediaTek Research. I am proficient in several programming languages, including Python, C/C++, HTML/CSS, JavaScript, MySQL, Matlab, and Shell Script. Additionally, I am experienced with frameworks such as Linux, Git, GitHub, PyTorch, and LATEX.

My research at NTHU focus on data augmentation on panoramic images. I try to solve the scarcity issue of panoramic datas by implementing a brand-new data augmentation that not only fit panoramic images but also enhances dataset diversity. My new paper on this work was accepted by BMVC 2023.

As a deep learning intern at MediaTek Research, I was deeply involved in crafting applications that harness accessibility services within the Android platform and LLM. I was also dedicated to advancing an expansive Chinese language model alongside its related tasks. Furthermore, I collaborated with colleagues from the Cambridge research team to explore AI-driven methodologies for generating test cases in ASIC design verification.

As a machine learning intern at Roku, the leading streaming TV platform in America, I use AI to help improve picture quality setting based on different scenes. To be more specific, I generated a large set of images with new classes from Roku's internal dataset and trained and fine-tuned MobileNetV3 on the new data for scene classification. Additionally, I deployed the model on Roku TV to enable real-time content classification, with dynamic picture quality adjustments (contrast, clarity, color) based on the detected scenes.