01 - Intro - January 10, 2020 


What is this class for?

  • For you to get a better idea of the research that’s going on in and outside of CCI

Who is this class for?

  • Primary → CAIS PhD students
  • Open to everyone including
  • Faculty, MS/Undergrad students, staff, and general public

Let’s go over some “boring stuff”

Who am I?

  • Professor in Computer Science & Associate Dean for Research
  • Research in Computer Vision and its applications
  • Husband and father of five children

What do I want to accomplish?

  1. You get something valuable out of it.  
  1. i.e. not a time-waster
  1. You get to learn more about what others are doing
  1. You start talking and collaborating with other Ph.D. students.  
  1. More faculty and students come and get same benefit
  1. We start building more collaborative research community

So, could you help make this happen?

1 - Are talks lined up yet?  Yes, mostly.

2 - How different would the talk sessions be?

More conversational

With a focus on A.I.

3 - Test out Slido

  • Go to www.slido.com on any device
  • There will be a box asking to enter the event code. This event code will be projected onto the big screen
  • How audience asks questions: They tap the "Ask" button and type their question into the prompt then press Send
  • How audience upvotes questions: They tap/click the thumbs up button to the right of a question

Could you help to make the seminar better?  Now and later?  Using Slido

Q1 - How does this semester’s line up and format look?

Q2 - What can I (Min) do to make this better?

Q3 - What can you all do to make this better?

Next Talk - Next Friday at 12:30 pm

1/17 - “Square Peg, Round Hole, and a Hammer: Improperly Predicting Human Behavior” - Andrew Vlasic, Ph.D. (Data Scientist at BofA)

We will go through the logical restrictions of classical probability theory in its applications on predicting human behavior and describe a logical system that is not as restrictive but complete and stable enough to be applied to more accurately predict behavior.