About


 Junyuan KeORCID iD icon

Doctoral Student

Computer Information Systems

Simon Business School, The University of Rochester

junyuan.ke AT simon.rochester.edu, j.ke AT utexas.edu


Bio

I am a doctoral student in Information Systems at The Simon School of Business of The University of Rochester. My research interest intersects Data Mining and Causal Inference with an emphasis on studying the impact of emerging technologies and innovation on digital platforms.


Education

Before moving to Rochester, I was briefly a PhD student at The University of Texas at Austin under the guidance of Wen Wen.

In 2018, I graduated from Emory University with a B.S. in Computer Science and a B.A. in Economics & Mathematics. I was advised by Joyce Ho and Vilma Todri.


Publications


Background and Miscellaneous

When I’m not in the office, I am try to be an avid boxer. I also used to play video game competitively in collegiate tournaments. You can also find me on Twitter and LinkedIn


What I’m Up To

You know what is kind of funny but swept under the rug a lot? Bob LaLonde is his 1986 AER influential evaluation of the NSW program which was an RCT where he dropped the experimental controls and replaced with nonexperimental controls from CPS and PSID, both representative 1/n

4/10 - Cut & paste your surroundings to Photoshop

Code: https://github.com/cyrildiagne/ar-cutpaste

Book: @HOLOmagazine
Garment: SS17 by @thekarentopacio
Type: Sainte Colombe by @MinetYoann @ProductionType
Technical Insights: ↓

#ML #AR #AI #AIUX #Adobe #Photoshop

I have a working paper out that I think is interesting! It's about instrumental variables and what you get out of thinking about heterogeneity in the effect of the instrument. A lot, it turns out! (thread) https://business.fullerton.edu/department/economics/assets/CSUF_WP_6-19.pdf?_=0.4520744169447609

PyPI downloads for TensorFlow (and its closest competitor, added for scale). Notice how it starts jumping after the release of TF 2.0 late last year (the short gap afterwards is the holiday break)

Up and to the right 📈

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