Difference between revisions of "SIAM Student Chapter Seminar"

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| Feb 7, 3:30-4 PM
 
| Feb 7, 3:30-4 PM
 
| Virtual [https://meet.google.com/gfs-yjbq-dmv/ (link)]
 
| Virtual [https://meet.google.com/gfs-yjbq-dmv/ (link)]
| Keith Rush (Senior Software Engineer at Google)
+
| Keith Rush (Senior Software Engineer at [https://www.google.com/ Google])
 
|''[[#Feb 7, Keith Rush |Industry talk]]''
 
|''[[#Feb 7, Keith Rush |Industry talk]]''
 
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|-
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| Feb 14, 3:30-4 PM
 
| Feb 14, 3:30-4 PM
 
| Virtual [https://uwmadison.zoom.us/j/91217562664?pwd=SGZOS3JGaFVGa250NXhDZlkrbWU3dz09/ (link)] Passcode: 400453
 
| Virtual [https://uwmadison.zoom.us/j/91217562664?pwd=SGZOS3JGaFVGa250NXhDZlkrbWU3dz09/ (link)] Passcode: 400453
| [https://www.linkedin.com/in/shawnmittal/ Shawn Mittal] (Senior Deliver Data Scientist at Microsoft)  
+
| [https://www.linkedin.com/in/shawnmittal/ Shawn Mittal] (Senior Deliver Data Scientist at [https://www.microsoft.com/en-us/?ql=5/ Microsoft])  
|''[[#Feb 14, Shawn Mittal |Industry talk]]''
+
|''[[#Feb 14, Shawn Mittal |Who, What, Why of Data Science in Industry]]''
 
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=== Feb 14 ===
 
=== Feb 14 ===
 +
A short snapshot of what the data science industry looks like followed by some lessons learned on what makes an effective data scientist.
  
 
=== Feb 21 ===
 
=== Feb 21 ===

Revision as of 12:17, 8 February 2022



Spring 2022

date and time location speaker title
Feb 7, 3:30-4 PM Virtual (link) Keith Rush (Senior Software Engineer at Google) Industry talk
Feb 14, 3:30-4 PM Virtual (link) Passcode: 400453 Shawn Mittal (Senior Deliver Data Scientist at Microsoft) Who, What, Why of Data Science in Industry
Feb 21, 3:30-4 PM 9th floor lounge Brandon Boggess (Epic) Industry talk
Feb 28, 3:30-4 PM 9th floor lounge Shi Chen (UW-Madison) TBA
Mar 7, 3:30-4 PM Virtual (link) Passcode: 400453 Tom Edwards Industry talk
Mar 21, 3:30-4 PM 9th floor lounge Aidan Howells (UW-Madison) TBA
Apr 4, 3:30-4 PM 9th floor lounge Eza Enkhtaivan (UW-Madison) TBA


Abstracts

Feb 7, Keith Rush

I'll talk about the kind of work I do today, the way I got here, and any insight I can give for someone hoping to pursue a similar path. I'll also discuss some of the things I've learned, and some of the advantages and disadvantages a mathematician has in the machine learning and computer science world. We'll be sure to have a freewheeling discussion and a good time :).


Feb 14

A short snapshot of what the data science industry looks like followed by some lessons learned on what makes an effective data scientist.

Feb 21

Past Semesters