The Evolution of the Statistician
2009: “I’m a statistician… it’s the sexiest job of the next decade 😏”
2011: “Actually I’m a Big Data expert”
2014: “Please, I’m a Data Scientist now”
2024: “Bro I’m an AI expert”
#DataScience#AI#Statistics
🎉 I’m incredibly proud to share the first publication with my first supervised PhD student at MSU!
Our R package RNAmf is now on CRAN! 🚀
#MultiFidelity#MSU#Research https://t.co/RPWeQdrAmB
Our team hosted an engaging event: “Rolling the Dice: Unveiling Normal Distributions”🎲✨ at @MSUSciFest. It was an absolute blast! #STEM#MSUScienceFestival#Statistics
https://t.co/1GodGRMk8Y
Thrilled to share our recent work on multi-fidelity simulations published in JUQ, in which we discussed when it is more effective to use single-fidelity or multi-fidelity simulations. #UncertaintyQuantification#UQ#multifidelity#DigitalTwins#DoE https://t.co/bv3Ml19vjt
📚 Excited to share our latest paper: "A Review on Computer Model Calibration" published in @WIREs_Reviews. In the Industry 4.0 era, calibration is 🔑. Explore the significance of aligning computer models with real-world data. #Industry40#calibration
https://t.co/xaKikqPJg6
Nicole E. Pashley, Rutgers Univ
Zhengling Qi, George Washington Univ
Arkaprava Roy, Univ of Florida
Chih-Li Sung, Michigan State Univ
Lu Tang, Univ of Pittsburgh
Ting Ye, Univ of Washington
Xiufan Yu, Univ of Notre Dame
@ChihLiSung@yetingshep
3/
Assistant Professor @BerkleyW6 teamed up with Assistant Professor @ChihLiSung to find a new statistical framework that can accurately estimate the parameters in biological models. This model can be adapted to fit other messy data sets in plant research. https://t.co/aAxrW0jwh5