I am Yu-Jhe (Jack) Li
M.S. student @ National Taiwan University
Scroll down to know more about me!
News
- Nov. 2018: One paper is accepted to AAAI 2019!
- Aug. 2018: Student Paper Award in CVGIP 2018!
- May. 2018: 2nd place in Nvidia GTC 2018 Poster Competition!
- May. 2018: One paper is accepted to ICIP 2018!
- Apr. 2018: One paper is accepted to CVPR 2018 Workshops!
- Oct. 2017: I joined Vision and Learning Lab (VLL)!
- Sep. 2017: Start seeking M.S. in National Taiwan University!
- Aug. 2017: One paper is accepted to PIMRC 2017!
- July. 2017: Summer Internship at TrendMicro inc.
About
I am now a graduate research student in Vision and Learning Lab (VLL) at National Taiwan University (NTU), supervised by Prof. Yu-Chiang Frank Wang. My research interests are in the areas of Machine Learning (ML) and Computer Vision (CV), particularly representation learning and transfer learning.
In past years, I graduated from National Tsing Hua University (NTHU) in three years and received my Bachelor of Science degree. Afterwards, I went to University of Minnesota, Twin Cities (UMN) to be non-degree seeking student, majoring in Computer Science for 5 months. I worked with Prof. Chih-Lin Chi for researching Bioinformatics and ML in UMN. After coming back to Taiwan, I had co-worked with Prof. Shou-De Lin researching ML before seeking Master degree in VLL at NTU. To obtain more details about me, here is my Curriculum Vitae.
Contact information:
Email address: r06942074 [AT] ntu.edu.tw
Timeline
Master of Science
National Taiwan University
Sep. 2017 - Present (Graduation expected Feb. 2019)
Exchange Student
University of Minnesota, Twin-Cities
Aug. 2016 - Jan. 2017
Bachelor of Science
National Tsing Hua University
Sep. 2013 - Jun. 2016 in Taiwan
Summer 2014 in Beijing
Publications
Anonymous Title (Double Blind) Under Review
Under review ...
Learning Resolution-Invariant Deep Representations for Person Re-Identification
Paper and Code are coming soon ...
Deep Reinforcement Learning for Playing 2.5D Fighting Games
[ArXiv]
Adaptation and Re-Identification Network: An Unsupervised Deep Transfer Learning Approach to Person Re-Identification
[ArXiv] [CVF open]
Deep Learning for Malicious Flow Detection
[ArXiv] [IEEE Xplore]
Co-work projects
Person re-identification
Mar. 2018 - PresentDetails: Instance segmentation and re-identification for surveillance system
Adversarial Attack for Malware
Sep. 2017 - Feb. 2018Details: Utilized Reinforcement Learning and Generative Adversarial Network for attacking the antivirus software. Supervised by Prof. Shou-De Lin.
Malicious Net-Flow Detection
Feb. 2017 - Aug. 2017Details: Integrated Artificial Intelligence and Cyber Security on un-decrypted(TLS) malicious netflow detection.