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About Me



My name is Yupei Lin. I am a senior student at University of Wisconsin-Madison, I major in computer science and minor in Mathematics.

I am interested in Computational biology and Bioinformatics, particularly in interdiciplinary studies of computer science, mathematics, statistics to solve biology based problems. My current research interests are to work on developing computational and statistical models to annotate the human genome and explore genetic architecture of complex human diseases. I'm currently developing a statistical framework to identify variance-associated genetic loci by quantile regresison and hopefully interpret GxG and GxE interactions.
CV

My advisor is Professor Qiongshi Lu.

Publications

Fine-tuning Polygenic Risk Scores with GWAS Summary Statistics

Zhao Z, Yi Y, Wu Y, Zhong X, Lin Yupei , Hohman T.J., Fletcher J., Lu Q. Manuscript submitted for publication. Oct 2019. View

Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder

Huang K, Wu Y, Shin J, Zheng Y, Siahpirani A, Lin Yupei, Ni Z, Chen J, You J, Keles S, Wang D, Roy S, Lu Q. Manuscript submitted for publication. Nov 2019. View

A cross-trait genetic risk prediction framework leveraging UK Biobankdata

Manuscript in preparation.

Research Projects

Image Style Transfer

Realize both artistic style transfer and realism style transfer by implementing Neural Style Algorithm and Deep Style Transfer with CPU based on Tensorflow.

Its main goal of this project to reimplement Deep Photo Style Transfer (Luan et al., 2017), which can faithfully transfer the input image into the style of reference image while preserve the content of the original input image with a deep-learning method. And we want to create a GUI online so everyone can access to it easily to transfer style of their images.

View Project

Sentimental Analysis For Yelp Review

This project wins second place on Kaggle competition to predict Yelp categorical data based on Yelp open reviews by applying Term-Frequency Inverse Data Frequency to top 4000 features to construct a regression-prediction

Post-disaster recovery using optimization

In this project, we use the following model to address first two purposes: model Debris Clearance Scheduling Model (DCSM) which schedules the road restoration to maximize total weighted earliness under a set of scenarios. Once we gain the total earliness for each district under those scenarios, we solve equipment allocation resources by using Equipment Allocation Model (EAM). We have a modified version of EAM to compare performance of different districts and finally and Resource Distribution model to give out resources on the restored path.

Experience and Job

Dancas Dance Crew

Board Member for propaganda

Video editing for promotion video for Dancas Showcase, Spring Festival Dancas performance

Chinese Undergraduate Student Association

Team member

Attend organizing events from writing proposal to fulfill the actual event.
Post information on public media like Wechat and Facebook for Chinese Undergraduate students

DoIT Help Desk

Phone Agent

Assist customers with their technological problems such as canvas, office365, online learning software.
Provide excellent customer service to users both on and off-campus via phone, email, and chat.

UW-Madison Women In Computing

Team member and Mentee

Receive scholarship to attend 2018 Grace Hopper Celebration
Attend weekly talk by faculty member, attend one-to-one mentor program.

Madison International Trade Association

Student Intern

Assisting the communications committee and social media communication including LinkedIn.

Skills