Statistical Artificial Intelligence Lab@UNIST

Artificial Intelligence and Machine Learning Research

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[Grant] A ‘Development of AI Curling Robot’ is acknowledged (April 2017)

Great news! A 2-years long project for `Development of AI Curling Robot’ is acknowledged by the Korean government. Our lab is participating in the granted consortium led by Korea University [Total 5B KRW (our lab’s portion: 300M KRW), 2017/04/01 ~… Continue Reading →

[Grant] An `Autonomous Intelligent Digital Companion Framework’ project from IITP is acknowledged (April 2017)

Great news! A 4-years long project for developing `Autonomous Intelligent Digital Companion Framework’ is granted by the Korean government. Our lab is participating in the granted consortium led by Korea Electronics Technology Institute (KETI) [20B KRW (our lab’s portion: 600M… Continue Reading →

[News] Top 10% in Two Sigma Financial Modeling Challenge hosted by Kaggle

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

[News] 2016 SAIL UNIST Workshop

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  

[Demo SW] Release of Demo SW (October 2016)

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 →

[Open Positions] Grad students, Postdocs and Researchers

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 jaesik@unist.ac.kr with your CV and… Continue Reading →

[Paper] Our paper, “Global Deconvolutional Networks for Semantic Segmentation”, is accepted at BMVC-16 (July 2016).

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 →

[New Interns] Summer student exchanges (July 2016).

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.

[Paper] Our paper, “Novel Data Reduction Based on Statistical Similarity”, is accepted at SSDBM-16 (May 2016).

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 →

[Open Positions] Postdocs and PhD studentships

We invite motivated applications for Postdoc and PhD (including MS/PhD) studies.   [Vacancies] Postdoc positions The Statistical Artificial Intelligence Laboratory (SAIL) at Ulsan National Institute of Science and Technology (UNIST) invites applications for postdoctoral positions in various areas of machine… Continue Reading →

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