Kevin Lin

Assistant prof: UW Biostat, on single-cell, regulatory network, fate commitment. | Postdoc: UPenn, Stat. PhD: CMU, Stat | Cooking and Zumba enthusiast (He/him)

[Kevin Lin @linnyKos]

Had a great time presenting and chairing at #JSM2023, thanks to @AmstatNews! Additionally, many thanks to @MengjieChen6, @jsb_ucla, @xzlab_org, @RoederKat, and Zhijin Wu for a fantastic session of single-cell ideas.

(Kudos to @DurenZhana for the picture!)

[Kevin Lin @linnyKos]

Hug thank you to @ICSA_Statistics for a great conference! Hugely appreciative of Gongjun Xu's and Jian Kang's effort (and the other wonderful faculty and students of @UMichStatistics and
@umichsph Biostatistics) for a wonderful time in Ann Arbor!

[Kevin Lin @linnyKos]

Finished my post-doc, onto Seattle for the next phase! Absolutely loved my time here

[Kevin Lin @linnyKos]

@raziehnabi Congrats!! 🎉🎉🎉

[Kevin Lin @linnyKos]

My article got printed in this month's @signmagazine! :) Many thanks to @CMU_Stats for helping me along the way! https://t.co/Eg2Zc2UM4X

[Carnegie Mellon Statistics & Data Science @CMU_StatDS]

@CMU_Stats CLEANED UP!!!!!!
#22500dollarsricher #headedtoNYC

[Kevin Lin @linnyKos]

It's happening!! \o/ https://t.co/yufc6Xjr9g #starcraft #MachineLearning #deeplearning #bots

[Kevin Lin @linnyKos]

Great to see the support for open source! https://t.co/theuLzUACQ

[Kirk Borne @KirkDBorne]

Artificial Intelligence 101 - What Gov Needs To Know: https://t.co/hMTSYUpCQ2 #AI #MachineLearning featuring @AngelaZutavern @BoozAllen https://t.co/vdANhqKbiM

[Kevin Lin @linnyKos]

Important discussion of how to interpret linear regression under misspecification! #statistics https://t.co/P7w34JUgfs A must-read

[Kevin Lin @linnyKos]

Very interested in this recent idea of adding noise prior to selection events #statistics https://t.co/GliaJBeTpf

[Kevin Lin @linnyKos]

Been reviewing some of the basics of regular languages, might give me inspirations for my research! https://t.co/hJRMSyjqXC

[Kevin Lin @linnyKos]

There's a lot of algorithms in this library that I never heard of! I'm definitely learning a lot reading through it #ML https://t.co/XWMgU7Rgxd

[Banana Data News @BananaData]

This guy implemented 1 #algorithm a day for 100 days - and wrote one article on each https://t.co/tkr60ml5Rw kudos to @athena_maker! #ML

[Kevin Lin @linnyKos]

Fascinating! I've never thought about a benchmark to classify algorithms before, and now I'm can't stop think about it! #ML #statistics https://t.co/Io7T1R4Com

[Randy Olson @randal_olson]

Our preprint on a comprehensive benchmark of #sklearn is out. Some interesting findings! #MachineLearning #dataviz

https://t.co/GGxpykECc1

[Kevin Lin @linnyKos]

Simple proof of the CLT using a telescoping argument #statistics https://t.co/21KIvKpXfz

[Kevin Lin @linnyKos]

Revisiting a great graphical model estimator that can be solved with a linear program #statistics https://t.co/YekrfeQPPn

[Kevin Lin @linnyKos]

Been looking into sensitivity analysis of linear programs (#optimization) as a link to #statistics! https://t.co/GUarED5X5Q

[Kevin Lin @linnyKos]

Revisiting "KL-projections" to interpret parameter estimates under misspecified models #statistics https://t.co/Wmwb6wMX9k

[Kevin Lin @linnyKos]

Excellent roadmap for proving misspecified error rates for linear estimators! #statistics https://t.co/H5X80PSSMa

[Kevin Lin @linnyKos]

This is such a joy to watch, and inspires me to think of new ways to visualize statistical estimates in higher dimensions! https://t.co/D6kdvRCJj3

[Grant Sanderson @3blue1brown]

New video is out! "A trick to visualizing higher dimensions" https://t.co/75bz1opRgr

[Kevin Lin @linnyKos]

Have my poster to support @TeamLiquid #LETSGOLIQUID #TI7 #TLDOTA @LiquidKuroKy @LiquidMATUMBA @LiquidMinD_ctrL @Liquid_Miracle @LiquidGh_