Profile | JaeHyun Lim
Transcription
Profile | JaeHyun Lim
JAE HYUN LIM [email protected] [email protected] Contact Address Positioning/Navigation Technology Research Section Electronics and Telecommunications Research Institute (ETRI), 218 Gajeongno, Yueseong-gu, Daejeon, Korea 305-700 Tel +82 42 860 5415 Mobile +82 10 8225 1401 Homepage http://jhlim.com (personal) http://kr.linkedin.com/in/jaehyunlim (linkedin) EDUCATION Korea Advanced Institute of Science and Technology M.S. Candidate, Electrical Engineering 2012.Feb – 2014.Feb Advisor: prof. Dae-Shik Kim Daejeon, Korea Korea Advanced Institute of Science and Technology Bachelor of Science, Bio-Brain Engineering, Magna Cum Laude 2008.Feb - 2012.Feb Daejeon, Korea Korea Science Academy (high school) 2005.Mar - 2007.Feb Busan, Korea RESEARCH INTERESTS • Deep Learning • Representation learning and probabilistic generative models for vision • Machine learning • Computer vision • Bayesian methods and Bayesian brain • Computational neuroscience RESEARCH PROJECTS / WORKING EXPERIENCE Researcher at ETRI 2014.Aug-current I started a researcher position at Electronics and Telecommunications Research Institute (ETRI), a national research center in Korea. I’m participating in a project to develop indoor navigation and human pose estimation systems with multimodal sensors. Kaggle National Data Science Bowl competition I participated in a data science competition, called Kaggle National Data Science Bowl competition, classifying images of plankton. I finished 22nd position out of 1049 teams with small difference from the winning solution. My approach and codes: https://github.com/lim0606/ndsb Competition site: https://www.kaggle.com/c/datasciencebowl 2015.Jan2015.Mar Kaggle Dogs vs Cats competition I join a team to implement deep learning algorithms for large scale image classification. During the project I and my colleague just ranked 6th in Dogs vs Cats kaggle competition, using deep convolutional neural network. We obtained 6th place against 215 other teams with 98.1% accuracy. http://www.kaggle.com/c/dogs-vs-cats/leaderboard 2014.Jan2014.Feb DARPA Robotics Challenge, Team KAIST, Vision group leader (Advisor: Prof. DaeShik Kim) As part of a team of team KAIST, which consists of several laboratories in KAIST and participates in DARPA Robotics Challenge in Dec. 2013, I am leading the group of people dedicating to design vision system for our robot (visit homepage). SLAM via Structure from Motion Sparse coding based 2d image tracking Stereo vision with dense SIFT matching Unsupervised 2d Image segmentation via deep learning and Bayesian nonparametric Project page: http://drc.kaist.ac.kr 2012-2014.Jan Multiple kernel learning with hierarchical feature Representations (Advisor: Prof. Dae-Shik Kim) [1] In this project, we suggest multiple kernel learning (MKL) with hierarchical feature representations. Using MKL, we tried to find the best combination of different levels of features learned by deep Boltzmann nets. 2013.Jan.2013.Oct Learning spatio-temporally invariant representations from video (Advisor: Prof. DaeShik Kim) [2] In this study, I designed an algorithm to discover individual identities from a video clip that shows faces in motion displayed in random order. The idea behind this stems from the possibility that ambiguity of different objects in data space can be elucidated by temporal relationships corresponding to how data appear to the system. 2011.June– 2012.July Predictive coding strategies for developmental neurorobotics (Advisor: Prof. DaeShik Kim) [3] In this work, we conducted neurorobotics experiments to illustrate that even minimalist prediction error-based strategies replicate key features observed during the emergence of infant learning behaviors, such as action sequence generation, object permanence, and imitation. 2011. Sept – 2012.May Active learning using entropy measure based on Gaussian Process classifier (Advisor: Prof. Soo-Young Lee) The research suggested explicit probabilistic measures of uncertainty model, mainly in the context of Gaussian process classification, including measure of entropy and expectation of posterior distribution with Markov Chain Monte Carlo approximation. (pdf) 2011.Feb– 2011.Dec 17th LG Global Challenger (Advisor: Prof. Doheon Lee) “LG Global Challenger” is the first and major overseas expedition program for undergraduates with the competitive rate of 21:1. My excellent results and active participation in Prof. Daeheon Lee's Bio Data Engineering course led me to be selected amongst a group of students for visiting world leading institutes. I had the opportunity to visit Microsoft's health group division in Seattle, Stanford University, patientlikeme.com's headquarters, Google research center as well as Harvard Medical School. (homepage, report) 2011 Self-segmentation (Advisor: Prof. Dae-Shik Kim) [4] In this work, I conducted neurorobotics experiments to demonstrate that prediction errorbased strategies replicate key features observed during the emergence of infant learning behavior, e.g. self-awareness behavior. 2010.Sept – 2011.June Internship program at Keio University (Advisor: Prof. Yasuyo Minagawa) The internship focused on research topics related to language developmental processes of human infants and language ability of human. It let me know how to deal with NIRS, functional MRI and other imaging tools for studying cognitive neuroscience. 2010.Jan.06 – 2010.Feb.07 A study on the role of thalamus in language processing with computational analysis, 2010 Winter/Summer URP Program (Advisor: Prof. Soo-Young Lee) This study was to validate cortico-thalamo-cortico systems as a hypothesis of human language processing with computation models cognitive experiments with functional magnetic resonance imaging (fMRI). (pdf) 2009.Oct– 2010.May KAIST Formula SAE Team Marketing Team Captain As part of a team of academic formula racing car research group called K-alpha, designed and tested our car to participate in the Formula SAE program. As a marketing manager, 2008-2009 I was in charge of arranging meetings with colleges and related institutions, making promotion materials, advertising, and as well as accounting. (potfolio) PUBLICATIONS [1] J. Lee, J. H. Lim, H. Choi, and D.-S. Kim, “Multiple Kernel Learning with Hierarchical Feature Representations,” in Neural Information Processing SE - 64, vol. 8228, M. Lee, A. Hirose, Z.-G. Hou, and R. Kil, Eds. Springer Berlin Heidelberg, 2013, pp. 517–524. (pdf) [2] J. H. Lim, H. Choi, J.-C. Park, J. Y. Jun, and D. Kim, “Learning spatio-temporally invariant representations from video,” Neural Networks (IJCNN), The 2012 International Joint Conference on. pp. 1–6, 2012. (pdf) (IJCNN was be held jointly with the FUZZ-IEEE and the IEEE CEC as part of the 2012 IEEE World Congress on Computational Intelligence (IEEE WCCI), June 10-15, 2012, Brisbane) [3] J.-C. Park†, J. H. Lim†, H. Choi, and D.-S. Kim, “Predictive coding strategies for developmental neurorobotics.,” Front. Psychol., vol. 3, p. 134, 2012. (†J.-C. Park and J. H. Lim have contributed equally to this work.) (pdf) [4] J. H. Lim, J. H. Yoo, S.-Y. Lee, D.-S. Kim, “Self-segmentation Based on Predictability Measure in Multimodal Autonomous System”, accepted for poster session in Neural Networks (IJCNN), The 2012 International Joint Conference on, San Jose, California (United States), July 31-5 2011 (pdf) TEACHING EXPERIENCE EE538 Introduction to Brain IT (Graduate course) This course discussed the key differences in architecture and algorithms between conventional information processing systems (e.g. von Neumann machines) and biological brains. As a teaching assistant I provided general background knowledge about brain-like information processing system, from single cell level neuron models to probabilistic neural networks and to state-of the art machine learning technologies. Assistant Teacher, International Students Science Fair 2006 The International Students Science Fair was initiated for the purpose of facilitating international exchange and interaction in science education, based on science project presentations delivered by high school students from all over the world. Designed the class named “Introduction to robot soccer for young scientist” as an official extracurricular activity of the fair. SKILLS MATLAB programming, C/C++ Programming Cuda programming in C/C++ Basic level web programming and database management Java Programming HONORS AND AWARDS National Research Fund Scholarship in KAIST KAIST Magna Cum Laude Korea Advanced Institute of Science and Technology KAIST Honor Program Academic course transition program REFERENCES Prof. Dae-Shik Kim ([email protected]) Prof. Soo-Young Lee ([email protected]) Prof. Doheon Lee([email protected]) Prof. Kyung Dae Kim ([email protected]) Spring 2013 Summer 2006 Feb 2012 present Feb 2012 2010 Sept – 2013 Aug