Future Thinking Scenarios in the Intersection of Engineering, Computer Science, Data Science and AI

#AI #robotics #automation #cs #autonomous
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In this presentation we will 
  1. expose AI as an automation process inspired by but to a large extent without having the goal of creating a human intelligence clone. Most, if not all tools, created by humans for as long as human have existed have had a component of artificial intelligence.
  2. review up to date advances in the latest wave of AI that automates human information and communication processes (written language using LLMs like chatGPT, graphic language, music language and more).
  3. present possible scenarios in the job market, engineering education and practice, and other inspired by the current advances in Data Science and Technology
  4. give the audience an opportunity to gauge their understanding of current advances by engaging in an open discussion.


  Date and Time

  Location

  Hosts

  Registration



  • Date: 20 Oct 2023
  • Time: 07:00 PM to 09:00 PM
  • All times are (UTC-04:00) Eastern Time (US & Canada)
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  • Contact Event Hosts
  • ilya.grinberg@ieee.org

  • Co-sponsored by Buffalo Section


  Speakers

Joaquin of SUNY Buffalo State University

Biography:

First and foremost, I am fully committed to the development to the field of Data Science and Analytics across disciplines, and in the cross section between academia and industry.
I was trained in Combinatorial Mathematics at the University of California, San Diego in the research group lead by Jeffrey Remmel and Adriano Garsia. My lifelong passion has been connecting mathematics with other disciplines and other aspects of science, art, humanities and life in general. From the start, I chose to work at a 4-year public university (SUNY Buffalo State), which I believed would allow me to pursue the kind of career I had in mind. 
I started my academic career right when the internet was taking off. After realizing the power and influence that information within the digital revolution had, I acquired graduate level Computer Science training at the University at Buffalo and focused my attention to applied and computational mathematics. At Buffalo State I created in 2010 the Professional Applied and Computational Mathematics MS, a degree part of the Professional Science Master’s movement, with the support of a $750k grant from NSF. In 2018, I created a second Professional Science Master’s degree in Data Science and Analytics. I played a significant role at my institution by introducing the Professional Science Master’s concept. I was for 4 years part of the Executive Committee of the National Professional Science Master’s Association. My chosen path allowed me to work with Biologists, Physicists, Computer Scientists and many successful companies that use applied and computational mathematics. As the lead faculty and director of the Interdisciplinary Unit in Data Science and Analytics and the chair of the M.S. in Data Science and Analytics I have been able to create an active network of students, faculty and people from industry to work on the challenges of understanding data as the new source of raw material to do science and implement technology.
 

Email:

Address:1300 Elmwood Ave, , Buffalo, United States, 14222