Prof. Choi (on behalf of SAIL members) received the appreciation award for the research project with POSCO. POSCO applied our AI (time series deep learning) method to control their blast furnace automatically for the first time. Thanks POSCO for the prestigious… Continue Reading →
We invite motivated applicants for postdoc, researcher and PhD (including MS/PhD) studies. [Vacancies] A Postdoc position The Statistical Artificial Intelligence Laboratory (SAIL) at Ulsan National Institute of Science and Technology (UNIST) invites applications for postdoctoral positions in various areas… Continue Reading →
We welcome a new researcher, Soonjae Kwon! Soonjae recently finished his master’s degree with deep learning based natural language understanding at Sogang university.
Our team composed of Giyoung, Donyeon, Sehyun and Jaesik ranked 190 (9.17%) out of 2071 teams participated. https://www.kaggle.com/c/two-sigma-financial-modeling/leaderboard
We are pleased to hold the 2016 SAIL UNIST Workshop! http://sail.unist.ac.kr/wp-content/uploads/2016/11/SAIL_workshop_2016_GE.v.png
We are pleased to announce the release of demo SW server to public: http://saildemo.unist.ac.kr/ Currently the server includes the following demos: “Automated Time-Series Analysis” – The Relational Automatic Statistician “Semantic Image Segmentation” – Global Deconvolutional Network “Pedestrian Detection” – RCNN… Continue Reading →
Our lab currently has some open positions for Grads, Postdocs and Researchers to solve some of the World’s Greatest Problems in AI! If you are interested in joining our lab, please contact Prof. Jaesik Choi at firstname.lastname@example.org with your CV and… Continue Reading →
Our paper, “Global Deconvolutional Networks for Semantic Segmentation” written by Vladimir, Janghoon and Jaesik is accepted BMVC-16. We show that simple but innovative ways to incorporate global context information to improve deep learning based semantic segmentation. We also demonstrate that the… Continue Reading →
Our undergrad intern, Madi, participates Google summer internship program at Mountain View, CA. Patrick Patolla (from Hamburg University of Technology, Germany) and Nikola Markovic (University of Belgrade, Serbia) visit our lab as summer graduate interns.
Our paper, “Novel Data Reduction Based on Statistical Similarity” written by Dongeun and Jaesik is accepted at SSDBM-2016. This is a joint work with our collaborators, Alex Sim and John Wu, in the Berkeley Lab. The data reduction method is… Continue Reading →