Research Paper Sunday - Tackling Hard to Solve Issues in Technology Infrastructure
#research
#paper
#Sunday
#STEM
#seminar #case
#study #studies
#technology
#infrastructure
#quality
#AI
#artificial
#intelligence
#machine
#learning
#generative
#genAI
#gen-AI
#data
#center
#centre
#centers
#centres
#data-center
#data-centre
#data-centers
#data-centres
#networking
#interconnect
#interconnects
#high
#performance
#computing
#HPC
#high-performance
#supercomputer
#supercomputing
#hard
#to
#solve
#tackling
#in
Infrastructure (10 a.m.) and CAE Simulation (1 p.m.)
double header on the same day,
(Two events, two vTools links, same day)
Sunday, 26th of July 2026:
This Technology Infrastructure below
from 10:00 a.m. until 1:00 p.m. USA Eastern Daylight Time
followed by CAE Simulation
from 1:00 p.m. until 4:00 p.m. USA Eastern Daylight Time
Have any unsolved issues with technology infrastructure, the combination of systems (including computer hardware and software, as well as facilities where they are installed, and the land in which those facilities are located) and organizations that make technology work?
Fields in and outside of science and engineering are welcome, as everyone on Earth is affected by infrastructure.
This will be a long talk with summary of the topic followed by a few papers case studies then a long Q&A section.
Please note: this meeting will be recorded so that it can be posted for the general public later.
Ask your questions or give your comments from multiple topics in infrastructure, including of course data centers for artificial intelligence companies, the trade of rare-earth minerals that are used in computer hardware, and any other topics that appear in these case studies.
Date and Time
Location
Hosts
Registration
-
Add Event to Calendar
Loading virtual attendance info...
- Starts
29 June 2026 12:00 AM UTC
- Ends
25 July 2026 05:00 PM UTC
- No Admission Charge
Speakers
Biography:
Sharan Kalwani is a co-founder, trainer, trainer of trainers, and professor in the areas including high-performance computing, computer-aided simulation, artificial intelligence and machine learning, Big Data, infrastructure quality (including data centers for artificial intelligence), networking and interconnects.
He has provided his expertise in high-performance computing in such organizations including Intel, General Motors, Fermilab (the particle-physics accelerator facility in Metro Chicago that has made equipment used in CERN's Large Hardron Collider), as well as multiple universities around the world.
This is of course in addition to his role as Chair of the IEEE Southeastern Michigan Section, metropolitan Detroit, Michigan, United States of America.
LinkedIn: https://www.linkedin.com/in/sharankalwani/
Email:
