iSchool Undergrad Events Calendar

View Full Calendar

The iSchool offers a number of events related to career and professional development, technology and information talks, research seminars, field trips, alumni panels, socials, and more. We also promote relevant opportunities on and around campus.

We encourage students to also visit additional calendars and websites:

HandShake Events, Research Park, NCSA, Technology Entrepreneur Center (TEC),

The Career Center, Office of Undergraduate Research, Leadership Center, Siebel Center for Design,

Office of Technology Management, Center for Innovation in Teaching & Learning,

Applied Technologies for Learning in the Arts & Sciences.

National & International Scholar's Programs, Student Wellness

iSchool Calendars: Study Abroad Hours, iSchool Events,

BSIS ICT Sessions, Express Advising

Colloquium on Digital Transformation Science: Toward Analytics-Based Clinical and Policy Decision Support to Respond to the COVID-19 Pandemic

Event Type: Lecture
Sponsor: C3.ai Digital Transformation Institute
Virtual
Date: Aug 13, 2020 3:00 pm
Speaker: Dimitris Bertsimas, Associate Dean of Business Analytics & Boeing Professor of Operations Research, MIT Sloan School of Management
Registration: Registration
Views: 12; The COVID-19 pandemic creates unprecedented challenges for healthcare providers and policymakers. How to triage patients when healthcare resources are limited? Whom to test? And how to design social distancing policies to contain the disease and its socioeconomic impact? Dimitris Bertsimas and Alexandre Jacquillat of MIT Sloan School of Management believe that analytics can provide an answer and have collected comprehensive data from hundreds of clinical studies, case counts, and hospital collaborations at www.covidanalytics.io. This colloquium will present their epidemiological model of the disease’s dynamics, a machine-learning model of mortality risk, and a resource allocation model. Specifically, it will address: How can we predict admissions in intensive care units using machine learning? How does COVID-19 impact different demographic and socioeconomic populations? How does mobility impact the disease’s spread, and how to optimize social distancing policies? And how to augment COVID-19 tests with data-driven warnings that identify high-risk subjects? Bertsimas will present a new machine learning model for predicting being COVID-positive and mortality using data from over 40 hospitals around the world, along with high-performance computing (using the C3 AI suite), and advanced machine learning and artificial intelligence. He will summarize his research group’s end-to-end ML/AI methods, spanning epidemiological modeling (to model the disease’s spread), machine learning (to predict ICU admissions and test results), causal inference (to investigate disparities across populations), and optimal control (to support social distancing guidelines), as well as a new optimization model for allocating vaccines to minimize deaths.

link for robots only