Issac Lee

Anyone can learn anything.

Biography

Hello! I am Issac Lee who is a PhD candidate of Statistics & Actuarial Science at the University of Iowa. My beloved academic supervisor is N.D. Shyamalkumar .

I am generally interested in many machine learning techniques which can be applied in actuarial science field. More specifically, here are some lists of topics which graped my attention thesedays:

Interests

  • Pay-How-You-Drive insurance telematics data
  • Replacing nested monte carlo simulation in insurance product valuation process.
  • Making compression portfoilo of insurance products

Education

  • MS in Actuarial Science

    Sungkyunkwan University, 2014

  • BS in Statistics & Industrial Engineering

    Sungkyunkwan University, 2012

Working Experience

 
 
 
 
 

Statistical modeling consultant

neurophet

Aug 2020 – Present Remote
Helping datascienceteamtobuild and verifybrainscoringmodels using quantile regression. Working on a semi‑supervised learning problem for patients group segmentation using statistical learning algorithmssuch as randomforest, orderedlogisticregression,and k‑mean, etc.
 
 
 
 
 

Data science Intern

Transamerica

Jun 2020 – Aug 2020 Denver, CO
Canceled due to COVID 19.
 
 
 
 
 

Teaching Assistant

University of Iowa

Aug 2018 – Present Iowa City, IA
Leading four discussion sections (50 min) per a week. Answer questions and reinforce materials used in lecture. Explain the statistical methods by solving examples in the text book. Each class consists of 25 students.

Certifications

Exam P, FM, MFE, C, VEE

Credential ID:

  • P: 40456, FM: 22339, MFE: 63652, C: 35765

Publications

Data Augmentation Techniques for Telematics Analysis (In progress)

Combining information from the two independent sensors via Kalman filter, we suggests a longitudinal-lateral acceleration density …

I KNOW HOW YOU DRIVE! DRIVING STYLE PROFILE VIA SMARTPHONE (In progress)

Combining information from the two independent sensors via Kalman filter, we suggests a longitudinal-lateral acceleration density …

Asymptotic Normality for the Sample CTE Revisited

Insurance regulation relies on the conditional tail expectation(CTE) of a loss random variable for specifying required capital as well …

Analysis of Multiple Life Insurance using Copula and Common Shock

The Gaussian copula is applied to reflect the correlations among policy holders and then to diversify the common shock of the multiple …

Analysis of reserves in multiple life insurance using copula

We analyze the change of the reserves of standard multiple-life insurance contracts at various dependence levels.

Projects

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Web crawler for Society of Actuaries’ MORT

SOAmort R package is a web crawler for mortality rate table data site hosted by Society of Actuaries

Pricing barrier option with Brownian bridge MC simulation

Modeling the stock price using the geometric brownian motion. By using the Monte carlo simulation, the price of the barrier options are calculated.

Courses

RPYTHON:101 - Be bilingual! R to Python

Codes collection: R <==> Python NumPy, Panda

STAT:2010 - Statistical Methods and Computing (SAS version)

Methods of data description and analysis using SAS; descriptive statistics, graphical presentation, estimation, hypothesis testing, sample size, power; emphasis on learning statistical methods and concepts through hands-on experience with real data.

Recent Posts

GPS data visualization

Animate GPS data using ggmap and gganimate packages

Determine the threshold "p" in the logistic regression

Sometime we need to recap quickly to prepare some test. This is the good reading for recap about logistic regression.

GPS 3D visualization

threejs provides 3d plots which can be rotated by users

Academic theme google analytics registration

Blogdown google analytics register summary

Rotations in 2D space

Introduction to the concept of rotation in 2D space.