About Me

I am a graduate student in Computer and Information Science at University of Pennsylvania.
I received B.S. in Computer Science and Engineering and B.A. in Economics at Seoul National University and attended University of California, Berkeley as an exchange student. My undergraduate research was advised by Professor U Kang.
My interest fields are Machine Learning, Deep Learning, Data Mining and Game Theory.
Here is my Resume.

Contact Information

Email: jvlee at seas.upenn.edu

Education

University of Pennsylvania, PA, United States of America (Aug 2018 – Expected: May 2020)
M.S.E. in Computer and Information Science

Seoul National University, Seoul, South Korea (Mar 2013 – Aug 2018)
B.S. in Computer Science and Engineering
B.A. in Economics

University of California, Berkeley, CA, United States of America (Jan 2016 - May 2016)
Exchange student

Work Experience

Intern, NAVER, Seongnam, South Korea (Jan 2018 – Mar 2018)
Developed and wrote paper on a click model that predicts user click behavior, given search query and corresponding search engine results page. Utilized Generative Adversarial Network to precisely replicate real user behavior, especially incorporating sequential GAN, conditional GAN, and reinforcement learning, using Python (TensorFlow).

Undergraduate Research Intern, Data Mining Lab, Seoul National University (Nov 2016 – Aug 2017)
Advisor: Professor U Kang
Researched on Deep Learning by writing papers on applying neural network on coupled matrix factorization (first author), and feature learning in signed directed networks (third author). Both were submitted, while SIDE: Feature Learning in Signed Directed Networks was accepted to WWW’18. Developed a time series data based stock price prediction project using deep learning. Modeled a neural network model that makes long term predictions (stock price after one to four quarters) on whether an individual stock price will rise, fall, or stay constant, which achieved up to 70.64% precision. Used Python (TensorFlow, NumPy, Pandas, SKLearn) for all implementations.

Undergraduate Intern, Software Platform Lab, Seoul National University (Jul 2016 – Aug 2016)
Advisor: Professor Byung-Gon Chun
Developed a deep learning framework of Dolphin, a machine learning platform built on top of Apache REEF. Used Java to build layers needed in neural networks and test benches.

Intern, Care Rights, Seoul, South Korea (Aug 2015 – Aug 2016)
Supervisor: Professor Sooyeon Han
Care Rights is a United Nations DPI/NGO(ECOSOC) nonprofit organization working for older person’s human rights. Contributed to legalizing “Act on Decisions on Life-Sustaining Treatment for Patients in Hospice and Palliative Care or at the End of Life” (Act No. 14013). Wrote and translated official documents in English, Korean and contributed to thesis writing.

Projects

Amazon Bin Image Challenge [Git Repository]
Using the extensive Amazon Bin Image Dataset, tackled two tasks: count (predict the number of items in the image) and classify (predict what item is contained in the image), with recreated established neural networks (VGGNet, AlexNet, etc.) and modified versions. Accomplished 68.57% accuracy on count task, and 41.43% accuracy on classify task. Used Python (TensorFlow) for the model and Amazon Web Services (AWS) for experiments. Gathered feedback from mentors to improve performance.

Time Series Data Based Stock Price Prediction
Developed a time series data based stock price prediction project using deep learning. Modeled a neural network model that makes long term predictions (stock price after one to four quarters) on whether an individual stock price will rise, fall, or stay constant, which achieved up to 70.64% precision. Used Python (TensorFlow, NumPy, Pandas, SKLearn) for implementation.

Generative Adversarial Network Click Model on Web Search (GANCM)
Developed a click model that predicts user click behavior, given a search query and the corresponding search engine results page. Utilized Generative Adversarial Network to precisely replicate real user behavior, especially incorporating sequential GAN, conditional GAN, and reinforcement learning, using Python (TensorFlow).

Agent Behavior in Personalized Recommendations
Modeled multi-agent system with consumer and marketer agents that maximize their utility. Consumers react to the given personalized recommendation from marketers, and marketers change their personalization level based on consumer feedback. Used NetLogo for the main model and additionally R for statistical experiments.

Papers

Ji-Eun Lee, Hyokyun Park, Jinhwan Kwon, “Generative Adversarial Network Click Model on Web Search” International Conference on Information and Knowledge Management (CIKM), 2018
(Submitted)

Ji-Eun Lee, Hyunsik Jeon, U Kang, “Neural Network Coupled Matrix Factorization” IEEE International Conference on Big Data (BigData), 2017
(Submitted) [Website]

Junghwan Kim, Haekyu Park, Ji-Eun Lee, U Kang, “SIDE: Feature Learning in Signed Directed Networks” The Web Conference (WWW), 2018
(Accepted) [Website]

Teaching

Student Directed Education: A study on recommendation system algorithms, their applications, and possible legal issues
Organized and led group sessions especially on introducing algorithms used in recommendation system: matrix factorization, deep learning.

Technical and English Skills

Python, Java (Advanced)/ MATLAB, NetLogo, Ocaml (Experienced) / C, C++, Stata, Scheme, R, SQL, HTML (Intermediate)
TensorFlow, AWS (Amazon Web Services), Apache REEF (Retainable evaluator execution framework), Caffe (deep learning framework developed by BVLC)

TOEFL iBT (Oct 2017) Total 114 (Reading 30 Listening 30 Speaking 28 Writing 26)
TOEFL iBT (Feb 2014) Total 114 (Reading 29 Listening 29 Speaking 28 Writing 28)

Courses

M.S.E. in Computer and Information Science, University of Pennsylvania
Machine Learning, Agent Modeling and Simulation

B.S. in Computer Science and Engineering, Seoul National University
Data Structures, Algorithms, Computer Programming, Discrete Mathematics, Introduction to Linear Algebra, Principles of Programming, Programming Language, Computer Architecture, Operating Systems, Logic Design, Electrical and Electronic Circuits, Hardware System and Design, Software Engineering, Creative Integrated Design 1, IT-Leadership Seminar, Computer Engineering Seminar, Student Directed Education

B.A. in Economics, Seoul National University
Microeconomics, Macroeconomics, Introductory Statistics for Economists, Mathematics for Economics, Seminar on Industrial Economy, Introduction to Market Economy, Economics of Contract 1, Economic History, Seminar on Financial Economy

University of California, Berkeley
Foundations of Data Science, Wage Theory and Policy, Economic Development, Topics in Economic Research

Scholarship

UC Berkeley Economic Semester Abroad Program (BESAP) Scholarship (Jan 2016)
(The First) Samsung Convergence Software Course (SCSC) Program Scholarship (Aug 2014)