Autobiography

        My name is Kuang-Ting, Lee. I hold a master’s degree in the department of Computer Science, National Chung Hsing University. I am a member of Computer Vision and Multimedia Lab at National Chung Hsing University and specialize in the fields of deep learning and computer vision. During my period in graduate school, my advisor strictly asked us to survey IEEE Trans. journal papers and top conference papers appearing in CVPR, ICCV, and NIPS. We also presented reading reports of the papers in a weekly meeting. Thus, I am good at systematically studying academic papers and efficiently figuring out new ideas to support my research.  

        During my graduate study, I attended International ICT Innovative Services Awards twice, which is the most well-known ICT application competition for university and college students in Taiwan held by the government. As a presenter, I learned the skill of making a clear and structural presentation. As a team leader, I assigned the tasks based on the specialty of my teammates. Finally, our team won second prize in 2019 and further won first prize in 2020 among hundreds of teams from 8 countries in the Asia-Pacific area. Besides, my advisor had submitted part of our research to the International Computer Symposium 2020 in Taiwan and assigned me to present it in an oral session. Attending the international conference to defend our research against scholars from different countries is an exciting and challenging experience. I learned how to claim novelty concisely and make a persuasive presentation in a limited time. Therefore, I am confident that having the skills of effective communication and team cooperation are my advantages.      

        The topic of my master thesis is “Learning Contrastive Features for One-class Novelty Detection.” To identify novel samples from target class samples, I proposed a novel deep learning framework based on contrastive learning to improve the discriminability of image features. For the purpose of collecting information from a target class, I further leveraged sparse dictionary learning to build a one-class model.  According to our experimental results, the proposed method outperforms state-of-the-art methods reported in CVPR and NIPS. In addition to the publication at International Computer Symposium in 2020, the rest of my research has been submitted to IEEE Transactions on Image Processing.

        With the 2-year experience in academic research, I did my work cautiously and proactively. To maintain the quality of my research, I periodically reported the estimated task completion time to my advisor and finished my task as soon as possible. There is a motto in our laboratory which I always keep in my mind. “Every job is a self-portrait of those who did it. Autograph your work with quality.” I hope I can work and grow with your company. I look forward to having an opportunity for an interview. Thank you for reading my resume.