Difference between revisions of "SIAM Student Chapter Seminar"

From UW-Math Wiki
Jump to navigation Jump to search
Line 73: Line 73:
 
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 :).
 
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, Shawn Mittal ===
=== 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.
 
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,Brandon Boggess ===
 
+
I will be talking about software development and the transition from academic research to enterprise engineering.
  
 
== Past Semesters ==
 
== Past Semesters ==

Revision as of 16:16, 18 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, Shawn Mittal

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,Brandon Boggess

I will be talking about software development and the transition from academic research to enterprise engineering.

Past Semesters