NCSI: Growing Artificial Tissues using Artificial Intelligence-based Controls

Status	Completed
Mentor Name	Roman Voronov
Mentor's XSEDE Affiliation	Campus Champion
Mentor Has Been in XSEDE Community	4-5 years
Project Title	Growing Artificial Tissues using Artificial Intelligence-based Controls
Summary	In this project we are developing a technology for controlling cell behavior in living cultures based on real time images acquired from high resolution microscopy. During the first year of the project we have published the automated platform and also developed parallelized stabilization codes for the very large microscopy images. The next phase of the project is to develop a parallelized controls algorithm for directing the cell behavior in real time based on the high speed large memory microscopy observations.
Job Description	-Process images obtained from Lattice Light Sheet microscopy using HPC resources -Develop and Train a Recurrent Neural Network (RNN) algorithm on the microscopy images of cell behavior, for implementation in a distributed network of Model Predictive Controller (MPC) -Implement the MPC network to direct artificial tissue growth experiments in real time
Computational Resources	The project will use Texas Advanced Computing Center resources via a New Jersey Institute of Technology Campus Champion allocation as follows: -Long term tape storage for large data from Lattice Light Sheet Microscopy -Image processing of the 3D Lattice Light Sheet Microscopy data, and Visualization using Visit and Paraview packages -Training of the Recurrent Neural Network (RNN) on experimental microscopy and chemical assaying data for implementation in the Model Predictive Controller (MPC).
Contribution to Community
Position Type	Learner
Training Plan	1) The student(s) will attend the NJIT High-Performance Numerical Computing Summer Workshop and also receive HPC training from the PI 2) The student(s) will receive personal training from the PI in the areas of Image Processing, Machine Learning and Controls Theory 3) The student(s) will further improve by interacting with an active research group of 2 PhDs and 3 MS students, all of whom are active in image processing, controls and HPC. 4) The student(s) will continue to help the PI with developing computational educational materials as a part of the Campus Champion and Computer Aids for Chemical Engineering Education (CACHE) initiatives (the PI is an active member of the CACHE community, see http://cache50th.org/?page=youngfaculty )
Student Prerequisites/Conditions/Qualifications	Must be an undergraduate student at NJIT with experience in Matlab and Lattice Light Sheet Microscopy. Additionally, interest in the following is highly desired: - Image Processing - Machine learning - Controls Theory -Supercomputing
Duration	Summer
Start Date	06/15/2020
End Date	08/31/2020