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 Woosang Lim (임우상) (CV) 










About me

My current position is a postdoctoral fellow at Georgia Institute of Technology.
I am looking for a research scientist / post doc position starting this summer :)
Research Interests: efficient machine learning, representation learning and their applications. 
Keywords: low-rank approximation, manifold learning, sampling methods, multi-modal learning, neural networks, and topic modeling.
Academic Position

Aug. 2017 - Present
 - Postdoctoral FellowSchool of Computational Science and EngineeringGeorgia Tech, Atlanta, USA                     
 - Email: woosang.lim(at)cc.gatech.edu
 - Office: 1333, Klaus Advanced Computing Building, Georgia Tech, Atlanta, USA

Education

Spring, Fall 2016, Spring 2017
 - Visiting Ph.D. StudentSchool of Computational Science and EngineeringGeorgia Tech, Atlanta, USA 
 - Co-Advisor: Haesun Park
Sep. 2012 - Aug. 2017
 - Ph.D., School of ComputingKAIST, Daejeon, Korea
 - Efficient and Accurate Eigen-Decomposition of Large-Scale PSD Matrices via Sample Subspace Compression
 - Advisor: Doo-Hwan Bae
 - Co-Advisor: Haesun Park
Feb. 2011 - Aug. 2012
 - MS, Department of Mathematical ScienceKAIST, Daejeon, Korea 
 - Thesis: Fast Kernel k-Means and Kernel PCA via Subspace Approximation (Advisor: Kyomin Jung)
Mar. 2007 - Feb. 2011
 - BS, Department of Physics, Yeungnam University, Gyeongsan, Korea 
 - Summa Cum Laude
 - Double Major: Mathematics
 - Thesis: Application of Quaternion on Physics (Advisor:
Jin Hyuk Kwon)

Publications (International)

12.  Multi-scale Nystrom MethodW. Lim, R. Du, B. Dai, K. Jung, L. Song, and H. ParkAISTATS, 2018. (Oral Presentation, 4.8% acceptance rate)
      (Its previous version was presented at 
NIPS Workshop on Optimization for Machine Learning (OPT), 2017)
11.  CoDiNMF: Co-clustering of Directed Graphs via NMFW. Lim, R. Du, and H. Park, AAAI, 2018. 
10.  Unsupervised Phenotype Scoring, Perros, E. Papalexakis, E. Searles, W. Lim, H. Park, and J. Sun, In NIPS Workshop on Machine Learning for Health (ML4H), 2017.
9.  Hierarchical Ordering with Partial Pairwise Hierarchical Relationships on the Macaque Brain Data Sets, W. Lim, J. Lee, Y. Lim, D. Bae, H. Park, D. Kim, and K. Jung, PLoS One, 2017. [paper]  
8.  Hadamard Product for Low-rank Bilinear PoolingJ. Kim, K. On, W. Lim, J. Kim, J. Ha, and B. ZhangICLR, 2017. [paper] 
7.  Modeling Brain Hierarchical Structure using Graph-based Manifold Learning, W. Lim, J. Lee, Y. Lim, K. Jung, and D. Kim, Neuroscience, 2015. 
6.  Double Nystrom Method: An Efficient and Accurate Nystrom Scheme for Large-Scale Data Sets, W. Lim, M. Kim, H. Park, and K. Jung, ICML, 2015. [paper] [code] [slides] 
5.  Reward Shaping for Model-Based Bayesian Reinforcement Learning, H. Kim, W. Lim, K. Lee, Y. Noh, and K. Kim, AAAI, 2015. 
4.  Data/Feature Distributed Stochastic Coordinate Descent for Logistic Regression, D. Kang, W. Lim, K. Shin, S. Lee, and U. Kang, CIKM, 2014. 
3.  Optimizing Generative Dialog State Tracker via Cascading Gradient Descent, B. Lee, W. Lim, D. Kim, and K. Kim, SIGDIAL, 2014. 
2.  Hierarchical Analysis in the Human Brain Connectivity Networks, J. Lee, Y. Lim, W. Lim, K. Jung, and D. Kim, Neuroscience, 2012. 
1.  Scalable Kernel k-means via Centroid Approximation, B. Kang, W. Lim, and K. Jung, NIPS Workshop on Big Learning (BigLearn) 2011.

Publications (Domestic)

1.  소셜 네트워크 분석의 알고리즘적 접근, Y. Lim, W. Lim, and K. Jung, 컴퓨터이론연구회지, 2012

Awards & Honors


2016 - 2017           Google Ph.D. Fellow in Machine LearningGoogle 
                              Google Ph.D. Fellowship, USD 10,000
2015                       Spotlight PresenterMachine Learning Summer School (MLSS)
2015                       ICML 2015 Student Scholarship, International Machine Learning Society (IMLS)
2015                       Kim-Bo-Jung Fund Scholarship, First Prize in the Competition for Venture Research Program for Graduate Students, KAIST
                              Receiving Budget Support, KRW 40million (USD 36,300)
2010                       Bronze Medal, The 29th University Students Contest of Mathematics, Korean Mathematical Society 
2008                       Honorable Mention, The 27th University Students Contest of Mathematics, Korean Mathematical Society 
2011                       Distinguished Achievement Award, Y-Type Human Resources Who Brought Honor to Yeungnam University, Yeungnam University
2011 - Current        Government Scholarship Student, Korea
2009 - 2011            Government Scholarship, Project of Research of Green Energy, Korea
2007 - 2011            Department Scholarship, Yeungnam University
Fall 2011                Outstanding TA Award, Introduction to Linear Algebra, Department of Mathematical Sciences, KAIST

Academic Talks


Multi-scale Nystrom Method
Apr. 11, 2018           International Conference on Artificial Intelligence and Statistics (AISTATS) 
Dec.  8, 2017           NIPS Workshop on Optimization for Machine Learning (OPT)
Aug. 29, 2017         
Google, Mountain View, USA
CoDiNMF: Co-clustering of Directed Graphs via NMF  
Feb.  5, 2018           AAAI Conference on Artificial Intelligence (AAAI)
Memory-Efficient and Fast Prediction for Local Triangle Counting on Graph Streams
Mar. 27, 2016          FROGRAMS, Korea
Double Nystrom Method: An Efficient and Accurate Nystrom Scheme for Large-Scale Data Sets
 
Dec. 19, 2015          FROGRAMS, Korea
Sept.18, 2015         
NAVER LABS, NAVER, Korea
Aug. 25, 2015          Machine Learning Summer School (MLSS), Kyoto, Japan
July. 22, 2015          Seoul National University, Korea
July.   8, 2015          International Conference on Machine Learning (ICML)
Fast and Scalable Kernel PCA via Subspace Approximation
Jan. 31, 2015          The 9th ROSAEC Workshop, POSTECH, Korea

External Reviewer


2018                       IEEE Transactions on Knowledge and Data Engineering
2017                       IEEE Journal of Biomedical and Health Informatics
2016                       NIPS

Teaching Experiences

Spring 2014           CS570 Artificial Intelligence and Machine Learning, graduate course, Head TA, KAIST
Spring 2012           MAS101 Calculus 1, undergraduate course, TA, KAIST 
Fall 2011                MAS101 Introduction to Linear Algebra, undergraduate course, TA, KAIST