User: Lil112
edit| — Wikipedian — | |
 Li Liping at TCL 2015 Product Release Conference | |
| Name | Li Liping |
|---|---|
| Languages | Chinese, English |
| Education and employment | |
| Employer | TCL Corporation |
| Education | MS in Information Science(in progress) University of Pittsburgh MS in Applied Psychology (2012) Sun Yat-sen University |
| Contact info | |
| https://www.facebook.com/liping.li.37017 | |
| https://www.linkedin.com/in/liping-li-5b465991/ | |
My name is Li Liping and I am a graduate student at University of Pittsburgh School of Computing and information. I was born in Yongxing County, Chenzhou City, Hunan Province, China. I earned a BS degree from Sun Yat-sen University Department of Psychology in 2010 followed by a MS degree in 2012. I entered Pitt's MSIS program in 2016, studying data analysis skills and technology understanding.
I have over three years of user experience research and design professional experience at Smart TV manufacturer TCL corporate. I'm interested in data-driven experience-centered product/service design, striving to improve product design based on user feedback data.
I have a solid background on user research area. As the experience quality leader of TCL Iqiyi TV, I organized a 10-day national home test participated by 300+ users as well as comprehensive usability tests and researches on TV sets, TV remotes, content service and in-store experience. This product was honored with 2013 Innovative Award of Asian Electronic Forum.
In my previous product manager job, I worked for “TCL Wei Dian Shi”. This service involves VOD control on TV by Phone, serving 1 million Smart TV users. It is based on WeChat platform, the hottest social App in China (600m users). It builds an instant control on a TCL TV by using WeChat to scan the QR code on a TV. This service was recognized as WeChat IOT INNO Case Top 5 in 2014.
Recently, I worked on colorsenserecommendation service.(github repository for detailed introduction) Inspired by the way that professional designers study palettes, I want to present people a service recommending them Kuler highly-rated palette based on their pictures. Colorsense can extract colors of user-upload pictures, compare them with palette dataset, rate them with similarity of palettes, and show similar palettes recommendation.