Upcoming Seminars

Show:
Title: Building Energy - Modeling, Optimization and Optimal Control
Seminar: Numerical Analysis and Scientific Computing
Speaker: Raya Horesh of IBM Research AI, TJ Watson Research Center
Contact: Lars Ruthotto, lruthotto@emory.edu
Date: 2018-01-19 at 2:00PM
Venue: W301
Download Flyer
Abstract:
Buildings consume about 40\% of the total energy in most countries, contributing to a significant amount of greenhouse gas (GHG) emissions and global warming. Therefore, reducing energy consumption in buildings, making buildings more energy efficient and operating buildings in more energy efficient manner are important tasks. Analytics can play an important role in identifying energy saving opportunities in buildings by modeling and analyzing how energy is consumed in buildings and optimizing energy consuming operations of buildings. In this talk I will cover areas ranging from physics based (ODE/PDE models) and data driven modeling to inverse problem for parameter estimation and model predictive control (MPC) framework that optimally determines control profiles of HVAC system given dynamic demand response signal, on-site energy storage system and energy generation system while satisfying thermal comfort of building occupants within the physical limitation of HVAC and other equipment.
Title: New methods in EEG/MEG source analysis
Seminar: Numerical Analysis and Scientific Computing
Speaker: Johannes Vorwerk of Scientific Computing and Imaging (SCI) Institute, University of Utah
Contact: Lars Ruthotto, lruthotto@emory.edu
Date: 2018-01-26 at 2:00PM
Venue: W301
Download Flyer
Abstract:
Electro- and magnetoencephalography (EEG and MEG) have become important tools for non-invasive functional neuroimaging due to their unique time resolution. In many applications of EEG/MEG, the goal is to reconstruct the sources inside the brain volume that evoke the measured signal, which leads to a related ill-posed inverse problem (EEG/MEG inverse problem). To solve this inverse problem accurately, it is necessary to precisely simulate the electric/magnetic field caused by a point-like source inside the brain volume: the so-called forward problem of EEG/MEG. When aiming to take the individual head shape and conductivity distribution of the subjects head into account, the EEG/MEG forward problem has to be solved numerically, e.g., using finite element methods (FEM). In this talk, we present examples showing how the use of novel mathematical methods can increase the accuracy of and help to better understand the uncertainties inherent to EEG/MEG forward solutions. We further analyze the influence of these uncertainties on EEG/MEG inverse solutions.
Title: TBA
Colloquium: N/A
Speaker: Sherry Li of Lawrence Berkeley National Lab
Contact: Lar Ruthotto, lruthotto@emory.edu
Date: 2018-04-05 at 4:00PM
Venue: W201
Download Flyer
Abstract:
TBA