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Jaebong Son
1-720-360-5057
855 W. Dillon Rd. Louisville F203
Boulder, Colorado, 80027
[email protected]
[email protected]
SUMMARY
My challenge is to solve business problems that companies face in the Big Data era, with my
expertise in computational linguistics, graph theory, business intelligence (BI), database design &
implementation, and machine learning techniques.
EDUCATION
UNIVERSITY OF COLROADO, Leeds School of Business, Boulder, CO.
Research Associate in Leeds School of Business, Aug. 2013 ~ Present
UNIVERSITY OF ARIZONA, Eller College of Management, Tucson, AZ.
Management Information Systems with minoring in Computational Linguistics, Completed 2nd
year Ph.D. course, July 2012
UNIVERSITY OF ARIZONA, Eller College of Management, Tucson, AZ.
Master of Science in Management Information Systems (Technical track), May 2010
KOREA UNIVERSITY, Seoul, Korea
Master of Science in Management Information Systems, Feb. 2006
KONKUK UNIVERSITY, Seoul, Korea
Bachelor of Arts in Business Administration and Management Information Systems, Feb. 2003,
ANALYTICS
SKILL SET
Natural Language Processing (NLP)
 Conducted topic analysis (topic modeling) based on LDA (Latent Dirichlet Allocation) to
find out “What have been going on?” phenomena by modeling news articles, blog posts, and
forum threads
 Analyzed sentiments of movie reviews written in English and Korean based on SVM
(Support Vector Machine) algorithm
 Built a NER(Named Entity Recognition) component to identify Person, Location, and
Organization based on Stanford NLP parser
 Implemented a English statistical POS (Part-Of-Speech) parser based on Hidden Markov
chain Model (HMM) and Viterbi algorithm
 Used probabilistic language models to extract key phrases from unstructured text data
Graph Theory and Implementation
 Built a recommendation system based on graph theory and centrality measures such as Eigenvector,
Betweenness, Closeness centrality, and etc.
 Implemented graph-based clustering known as community detection to find sub-graphs which have
characteristics in common identified by relation with other nodes in graph
 Combined topic modeling with graph-based community detection to group similar set of topics
which is called topic groups
Business Intelligence (BI)
 Diverse experiences in Microsoft SQL Server with Analysis Service (SSAS) and Integration
Service (SSIS)
 Highly skilled in implementing SQL Server objects such as tables, indexes, stored procedures,
triggers, and functions
 Executed several content (unstructured data) analysis by leveraging Transact-SQL, text mining
components of SSIS, and clustering algorithm of SSAS
 Implemented an automated web recommender system by inter-connecting SQL Server relational
database engine (T-SQL), SSAS (Data Mining Expressions), and SSIS (Workflow)
 Familiar with dimensional modeling, relational modeling, star schema / snowflake schema, fact and
dimensional tables
 Experienced in implementing machine learning algorithms such as K-means clustering and HITS
(Hyperlink-Induced Topic Search) by Transact-SQL
Programming language: Java, Python, and ASP.NET
 Highly skilled and specialized in processing texts using regular expressions
 Designed and implemented several Java-based crawling systems using SQL Server as
repository
 Experienced in implementing machine learning algorithms such as Bayesian networks,
Markov chain model, neural network, genetic algorithm, and so on.
EXPERIENCE
07/2013~02/2014
IBM GBS, Seoul, Korea
Freelancer, Managing Consultant, Advanced Analytics, Business Analytics and Optimization
(BAO)
 Participating in risk modeling using user-generated content (text) in social media
09/2012-07/2013
IBM GBS, Seoul, Korea
Managing Consultant, Advanced Analytics, Business Analytics and Optimization (BAO)
 Project leader (04/2013) of Samsung Electronics Big Data Platform project (POC)
- Successfully achieved all tasks given by Samsung MSC Unit and delivered all results
- Designed and implemented a buddy recommender system
- Executed topic identification, extraction, and clustering based on movie synopsis
- Produced a 2-mode network to identify topic-movie relation
 Project leader (09.2012~03.2013) of the LG U+ Big Data Platform project
- Delivered a series of successful analyses of customers’ purchase & viewing behavior of HDTV
content, browsing behavior of the Internet, and recommender system for HDTV content
- Designed and implemented a recommendation module for HDTV contents for smartphone
customers by leveraging structured and unstructured data
- Designed integrated data model from diverse data sources
- Implemented Social Network Analytics module for recommender system
01/2010-07/2012
Artificial Intelligence Laboratory, Tucson, AZ
Research associate
 Project leader (10/2010~07/2012) of nanotechnology research funded by National Science
Foundation (NSF award #0926270)
 Executed content analysis on nanotechnology patents to extract technology topics
 Carried out social network analysis to figure out inventors’ and assignees’ collaboration
networks in nanotechnology and semiconductor industry
 Conducted competitor analysis on the semiconductor industry considering Taiwan
Semiconductor Manufacturing Company (TSMC), Samsung Electronics, IBM, and Micron
Inc. using patents issued with the USPTO (United States Patent and Trademark Office)
(Reference: http://ai.arizona.edu/mis510/other/TSMC%20Patent%20Analysis.ppt)
 Designed and developed a large-scale data collection system to gather forum postings from
politically unstable countries such as Afghanistan, Somalia, Lebanon, Yemen, and so on for
research purposes (70 forums from 14 countries)
01/2006-12/2006
SPSS, Seoul, Korea
Data Modeler, Data Mining Consultant, Consulting Division
 Executed two BI projects at Korea Exchange Bank (KEB) and Korean Transportation
Safety Authority (KOTSA)
 Developed data mining and statistics components for BI systems based on Microsoft SQL
Server, SPSS statistics package, and Clementine data mining software
 Analyzed business requirements to gather information for system design and analysis
 Participated in creating logical and physical data models to meet user and business
requirements
 Developed SSIS packages to extract, transform, and load the customer data from the OLTP
databases for data mining tasks
 Participated in writing a book about data handling using SPSS statistics package
 Lectured data handling using SPSS statistics package at SPSS Education Center
05/1997-07/1999
THE THIRD QUARTERMASTER CORPS OF KOREA, Kyongki, Korea
Sergeant, IMO (Information Management Office) assistant
 Installed, upgraded, managed Microsoft SQL server 7
 Developed and managed SQL objects such as tables, procedures and functions, and indexes.
RESEARCH
EXPERIENCE
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Jaebong Son et al., (2013). Global nanotechnology development from 1991 to 2012:
patents, scientific publications, and effect of NSF funding. Journal of Nanotechnology
Research (JNR).
Jaebong Son et al., (2013). Nanotechnology Public Funding and Impact Analysis: A
Tale of Two Decades (1991-2010), IEEE Nanotechnology Magazine, vol.7, issue 1, pp.914
Woo, J., Son, J., and Chen, H., (2011). An SIR model for violent topic diffusion in social
media. 2011 IEEE International Conference on Intelligence and Security Informatics,
Beijing, China, pp.15-19.
Son, J. and Suh, Y. (2006). Using Degree of Match (DOM) to Improve Prediction
Quality in Collaborative Filtering System. Information Systems Review (ISR). vol.8,
issue 2, pp.139-154.
INVITED
SPEAKER

CERTIFICATTION
AND OTHERS
Certification
 Risk Analyst, Entry Level, CNSS No.4016, 2009
 Microsoft Data Base Administrator (MCDBA), 2003
 Oracle Certified Professional (OCP), 2001

Competitive Landscape Analysis through Patent Analytics, ETRI (Electronics and
Telecommunications Research Institute), May, 2012
Intellectual Property and Text Analytics: A Case of Patent Analytics, ETRI (Electronics
and Telecommunications Research Institute), Dec, 2011
Additional Professional Education
 Advanced Statistical Analysis at SPSS Education Center (2 Courses), 2004
 Microsoft MCDBA 2000 Course (4 Courses), 2001
Other Projects
 Participated in designing and developing data warehouse system at TUSD (Tucson Unified
School District), 2010
 Conducted cancer data analysis to identify the relationship of cancer, treatment, and cost
using Microsoft SQL Server, WEKA, and Clementine, 2005
 Executed query optimization for performance tuning of SQL Server 2000 at Epson Korea,
2004