Engineer Medical

The Institue of Cancer Research

** ******** ****, ******

Hoo-Chang Shin SM2 5NG, United Kingdom

H mobile +44 (0-75-403*-****

B ab87ll@r.postjobfree.com

PhD student web: www.beejion.com/khcs

Objective

To obtain a full-time researcher/engineer position in machine learning/computer vision

Summary

Unsupervised (feature) learning, supervised learning, deep learning, topic discovery, pat-

Machine

learning tern analysis, multi-modal data analysis.

Object detection, segmentation, object tracking, OpenCV, ITK/VTK, computer vision

Computer vision

library development for embedded systems (Xilinx XUP board).

Worked with datasets for drug development in a team composed of physicists, biologists,

Medical research

and chemists.

Performance analysis of HW/SW co-design on embedded systems of:

Embedded

systems – Software Defined Radio (SDR) - on Lyrtech SFF SDR board with FPGA and DSP

– Video-based driver assistance system - on Xilinx XUP boards

C, C++, Java, Python, Matlab, Simulink, Assembly, VHDL, JavaScript, JSP, SQL, etc.

Programming

Linux, Mac OS X, MS Windows, GPGPU (Nvidia CUDA), DSP (with TI Code Composer

Target platforms

Studio), FPGA (with VHDL and Xilinx System Generator and HDL Coder).

Eclipse Modeling Framework with UML and Java.

Prototype design

Development of an ROI-Engine for Clinical Purpose

Service-

Orienteed (Link to the project page can be found on my personal webpage ).

Architecture

Education

PhD in Artificial Intelligence in Medicine,

2009. Oct. -

expected end: The Institute of Cancer Research, University of London, London, United Kingdom.

2013. Sep. – Research on unsupervised feature learning, supervised learning, topic discovery and deep

learning, and their application to obeject detection and segmentation in high-dimensional large

heterogeneous patient dataset.

– Provisional thesis title: Object Detection and Segmentation in High-dimensional MR Images.

M.Sc. (Diplom Ingenieur) in Electrical Engineering,

2004. Oct. -

2008. Sep. Technical University of Munich, Munich, Germany.

– Course work concentration in Signal Processing and RF Engineering.

– Practical experiences in HW/SW co-design and performance analysis of computer vision/

communication systems on embedded systems.

– Master’s thesis: Performance Analysis and FPGA-DSP Based Implementation of GNU Radio

OFDM Transmitter.

– Bachelor’s thesis: Tunnel Entrance Recognition for Video-based Driver Assistance Systems.

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B.Sc. in Mechanical Engineering and Computer Science,

2000. Feb. -

2004. Feb. Sogang University, Seoul, Korea.

– Course works in control theory, artificial intelligence, and computer architecture.

– Bachelor’s thesis: Optimization of a DC Motor Control using Evolutionary Algorithm.

Professional Experiences

Internship, AUDI AG, Ingolstadt, Germany.

2009. May. -

2009. Aug. – Developed tool for fast prototyping of unit design module with Eclipse Modelling Framework

Internship and Master’s Thesis, BMW Research and Technology, Munich, Germany.

2007. Oct. -

2008. Oct. – Performance analysis and FPGA-DSP based implementation the open-source GNU Radio

OFDM transmitter for car-to-x communication system

Student Researcher, Institute for Integrated Systems, TU Munich, Munich, Germany.

2006. Dec. -

2007. May. – Development of Tunnel Entrance Recognition Engine and its real-time implementation on an

embedded system for a driver assistance system

– Developed a computer vision library of the algorithms used for an embedded system (Xilinx

XUP board)

(the link to the project can be found on my personal webpage)

Student Researcher, Institute for Electronic Design Automation, TU Munich, Munich,

2005. Mar. -

2005. Apr. Germany.

– Development of a data analysis automation tool for statistical timing analysis of analogue

circuits

Publications

Hoo-Chang Shin, Matthew Orton, David Collins, Simon Doran, Martin Leach, Stacked

Journal Article

Autoencoders for Unsupervised Feature Learning and Multiple Organ Detection in a

Pilot Study Using 4D Patient Data, to appear in IEEE Transactions on Pattern Analysis

and Machine Intelligence (TPAMI).

Hoo-Chang Shin, Hybrid Clustering and Logistic Regression for Multi-Modal Brain Tu-

Conference

Proceedings mor Segmentation, In Proceedings of the Workshops and Challenges of Medical Image

Computing and Computer Assisted Intervention (MICCAI), 2012.

Hoo-Chang Shin, Matthew Orton, David Collins, Simon Doran, Martin Leach, Au-

toencoder in Time-Series Analysis for Unsupervised Tissues Characterisation in a Large

Unlabelled Medical Image Dataset, In Proceedings of the 10th IEEE International Con-

ference on Machine Learning and Applications (ICMLA), pages 259-264, 2011.

Christopher Claus, Hoo Chang Shin and Walter Stechele, Tunnel Entrance Recognition

for Video-based Driver Assistance Systems, In Proceedings of the 13th International

Conference on Systems, Signals and Image Processing (IWSSIP), pages 419-422, 2006.

(Links to the publications can be found on my personal webpage)

Honours

{ Full Stipend for the 4 year PhD - The Institute of Cancer Research, UK

{ Advisory Professor’s Stipend - Sogang University, Korea

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Languages

English, German, Korean

Fluent

Japanese

Basic

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