
Overview of Computational Methods and Machine Learning: Panel Discussion
14 Jun 2019   Contributor(s):: Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin
The individual Panel Talks which accompanies this discussion can be found here.Why do we need experiments?Are your methods “descriptive” or “predictive”?Do you work with any other theory/simulation groups?On the 5 year timescale: is machinelearning hype or a real...

Overview of Computational Methods and Machine Learning: Panel Talks
14 Jun 2019   Contributor(s):: Brett Matthew Savoie, Pradeep Kumar Gurunathan, Peilin Liao, Xiulin Ruan, Guang Lin
The Panel Discussion which follows these individual presentations can be found here.Individucal Presentations:Theory and Machine Learning in the Chemical Sciences, Brett Matthew Savoie;Divide and Conquer with QM/MM Methods, Pradeep Kumar Gurunathan;Computational Chemistry/Materials, Peilin...

SMART Films Tutorials
05 Jun 2019   Contributor(s):: Ali Shakouri (organizer)

Big Data in Reliability and Security: Some Basics
30 May 2019   Contributor(s):: Saurabh Bagchi

Big Data in Reliability and Security: Applications
30 May 2019   Contributor(s):: Saurabh Bagchi

HumanInterpretable Concept Learning via Information Lattices
23 May 2019   Contributor(s):: Lav R. Varshney
The basic idea is an iterative discovery algorithm that has a studentteacher architecture and that operates on a generalization of Shannon’s information lattice, which itself encodes a hierarchy of abstractions and is algorithmically constructed from grouptheoretic foundations.

Bryan Arciniega
Bryan Arciniega is a third year undergraduate at California State Polytechnic University, Pomona who is studying computer engineering and finance. He currently works as an IT technician for Cal...
https://nanohub.org/members/230182

Nanomanufacturing with 2D Materials Informed by Machine Learning
22 Apr 2019   Contributor(s):: Joel Ager

Suprit Chaudhari
I am a final year undergraduate student of Engineering Physics at the Indian Institute of Technology (IIT), Guwahati. I am interested in Nanotechnology and machine learning.
https://nanohub.org/members/224852

Literature transcriptomics review and data of Nanoparticle Induced Cellular Outcomes
07 Mar 2019   Contributor(s):: Irini Furxhi
Data from in vitro differential gene expression analysis studies were gathered from peerreviewed scientific literature. The studies gathered had a considerably variety of different human cell models including both primary cells and immortalized cell lines which exhibit varying...

Machine Learning for Materials Science: Part 1
09 Feb 2019   Contributor(s):: Juan Carlos Verduzco Gastelum, Alejandro Strachan, Saaketh Desai
Machine learning and data science tools applied to materials science

3 min Research Talk: Deep Machine Learning for Machine Performance & Damage Prediction
04 Feb 2019   Contributor(s):: Elijah Reber
In this talk, we look at how effective a deep neural network is at predicting the failure or energy output of a wind turbine. A data set was obtained that contained sensor data from 17 wind turbines over 13 months, measuring numerous variables, such as spindle speed and blade position and whether...

Networked Dynamical Systems for Function and Learning: Paradigms for DataDriven Control and Learning in Neurosensory Systems
16 Jan 2019   Contributor(s):: J. Nathan Kutz
Our objective is to use emerging datadriven methods to extract the underlying engineering principles of cognitive capability, namely those that allow complex networks to learn and enact control and functionality in the robust manner observed in neurosensory systems. Mathematically, the...

DataDriven Discovery of Governing Equations of Physical Systems
16 Jan 2019   Contributor(s):: J. Nathan Kutz
We introduce a number of datadriven strategies for discovering nonlinear multiscale dynamical systems and their embeddings from data. We consider two canonical cases: (i) systems for which we have full measurements of the governing variables, and (ii) systems for which we have incomplete...

Creating Inflections: DARPA’s Electronics Resurgence Initiative
09 Jan 2019   Contributor(s):: William Chappell

ECE 695E: An Introduction to Data Analysis, Design of Experiment, and Machine Learning
07 Jan 2019   Contributor(s):: Muhammad A. Alam
This course will provide the conceptual foundation so that a student can use modern statistical concepts and tools to analyze data generated by experiments or numerical simulation.

TensorFlow Tutorials
03 Dec 2018   Contributor(s):: Juan Carlos Verduzco Gastelum, Saaketh Desai, Alejandro Strachan
Readytorun Jupyter notebooks for machine learning using Tensorflow and Keras

Desmond Brennan
Providing dissertation help at University of Florida
https://nanohub.org/members/214385

Juan Carlos Verduzco Gastelum
Materials Engineering PhD Graduate Student at Purdue University.Research in "Solidstate energy storage devices rational materials design".Background in Mechanical and Electrical Engineering.
https://nanohub.org/members/207041

Deep Machine Learning for Machine Performance and Damage Prediction
08 Aug 2018   Contributor(s):: Elijah Reber, Nickolas D Winovich, Guang Lin
Deep learning has provided opportunities for advancement in many fields. One such opportunity is being able to accurately predict real world events. Ensuring proper motor function and being able to predict energy output is a valuable asset for owners of wind turbines. In this paper, we look at...