Title:

Scalable and Reliable Design and Decision-Making: A Bayesian Perspective

Speaker:

Dr. Seyede Fatemeh Ghoreishi

Affiliation:

University of Maryland

When:

Wednesday, March 4, 2020 at 11:00:00 AM   Add to Calendar

Where:

MRDC Building, Room 4211

Host:

Dr. Bert Bras
bert.bras@me.gatech.edu

Abstract

Design problems are pervasive in scientific and industrial endeavors, scientists design experiments to gain insights into physical and social phenomena, engineers design machines to execute tasks more efficiently, and pharmaceutical researchers design new drugs to fight disease. All these design problems are fraught with choices, choices that are often complex and high-dimensional, with constraints and uncertainties that make them difficult for individuals to reason about. Despite several advances made in design and decision making in recent years, lack of reliability and lack of scalability have prevented their applications to a wide range of practical problems. This talk will focus on large-scale and reliable design and decision-making from the machine learning and Bayesian statistical perspective.

Biography

Seyede Fatemeh Ghoreishi is a postdoctoral research fellow at the Institute for Systems Research at the University of Maryland. She received her Ph.D. and M.Sc. degrees both in Mechanical Engineering from Texas A&M University in 2019 and 2016 respectively. She holds a minor in Applied Statistics from the department of Statistics at Texas A&M University. She also received a M.Sc. degree in Biomedical Engineering from Iran University of Science and Technology in 2014 and a B.Sc. degree in Mechanical Engineering from the University of Tehran in 2012. She was selected as Rising Stars in Computational and Data Sciences at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin in 2019.

Notes

Refreshments will be served.