Junlin Han

Junlin Han
Undergraduate student at ANU
Research student, Data61-CSIRO & ANU
Visiting research intern at AIML, University of Adelaide

Australian National Univeristy (ANU)
Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Australian Institute for Machine Learning (AIML), University of Adelaide

Location: ~~Synergy Building, CSIRO Black Mountain Site, Acton ACT 2601, Australia~~
AIML Building, Lot Fourteen, Adelaide SA 5000, Australia
Profile | News | Research Interests | Education | Experience | Publications | Services | Skills | Awards|
Email: junlin.han@data61.csiro.au, junlinhcv@gmail.com
[GitHub] [Curriculum Vitae] [Google Scholar] [Twitter]

Profile

Greetings, welcome to my website!

I'm a 4th year undergraduate student at ANU. I work at Data61 (formerly known as NICTA) and ANU with Dr. Lars Petersson and Prof. Hongdong Li, and I'm currently visiting AIML, University of Adelaide, advised/hosted by Prof. Ian Reid.

[10.2022] Selected as a top reviewer in NeurIPS 2022!
[08.2022] The journal version of Contrastive Underwater Restoration (CWR) accepted to Remote Sensing.
[07.2022] Blind Image Decomposition (BID) accepted to ECCV 2022! A new low-level vision task that better adapts to complex real-world scenarios, check our project page for more.
[05.2022] You Only Cut Once (YOCO) accepted to ICML 2022! Check here for our work on how to perform data augmentation.
[12.2021] I joined Australian Institute for Machine Learning (AIML), University of Adelaide as a visiting research intern, hosted by Prof. Ian Reid!
[04.2021] DCLGAN (Dual Contrastive Learning) accepted to NTIRE (CVPRW) 2021 as oral presentation. The new SOTA method for unsupervised image-to-image translation.
[03.2021] Contrastive Underwater Restoration (CWR) accepted to IGARSS 2021 as oral presentation. HICRD dataset is also released.

My research interests lie in computer vision, deep learning, and artificial intelligence.
Specifically, I study visual machines from two perspectives:
(1) I am interested in building intelligent machines that may perceive, learn, and think more like humans, where such machines should be more robust and applicable in real-world environments.
(2) I explore the perception and cognitive properties of machines. I enjoy diving into questions like: How do machines see the world? What visual data do machines memorize?
These two programs are inseparable, for instance, having a deeper understanding of machines should advance the development of more powerful AI systems.

Undergraduate (02.2019 - 06.2023)

B.S. Information Technology (Honours), College of Engineering and Computer Science, ANU

Visiting Research Intern at AIML, University of Adelaide (12.2021 - ongoing)

Research Student at Data61-CSIRO & ANU (08.2020 - ongoing)

Top Reviewer, 2022
NeurIPS (Conference on Neural Information Processing Systems)
Second Best Presentation Award, 2021
AIM (Active Integrated Matter) Conference
Top-up Scholarship, 2021
for research work at Data61-CSIRO
Undergraduate Vacation Scholarship, 2020
for summer research at Data61-CSIRO