OCTOBER 18-20, 2021
WASHINGTON, DC

AI TechConnect
 

AI/Machine learning for Characterization

Nanoscale Materials Characterization

Call for Abstract - due September 13 »

Symposium Co-Chairs

Dalia YablonDalia Yablon
Technical Program Chair
TechConnect World Innovation Conference

Key Speakers

Stefan JaegerDetecting Malaria Parasites with Machine Learning
Stefan Jaeger
Staff Scientist, U.S. National Library of Medicine / NIH

James HorwathAutomated Analysis of Transmission Electron Microscopy Images for Characterization of Dynamic Material Systems
James Horwath
Graduate Student, University of Pennsylvania

 
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2021 Symposium Sessions

Monday October 18

10:30AI for Characterization & Manufacturing
1:30Machine Learning for Microscopy

Tuesday October 19

1:30Advances in Image Analysis

Wednesday October 20

8:30AI Track Keynote
1:30User Facilities for Industrial Participation

2021 Symposium Program

Monday October 18

10:30AI for Characterization & ManufacturingBaltimore 1
Session chair: Greg Haugstad, University of Minnesota & Grace Gu, University of California, Berkeley
Materials Informatics for Simultaneous Design of Alloy Chemistry and AM Process
S. Broderick, University of Buffalo, US
Manufacturing Informatics: Embracing Machine Learning for Smart Manufacturing
Y. Liu, Cardiff University, UK
Machine Learning for In-Water Inspection of Submarine Hull Coatings
M. An, J. Cipolla, A. Shakalis, B. Hiriyur, R. Tolimieri, Prometheus Inc., US
Gamma-Ray Raster Imaging with Robotic Data Collection
W. Wells, T. Aucott, M. Siddiqi, Savannah River National Laboratory, US
A New Method for Atmospheric Correction of Satellite Data
D. Groeneveld, Advanced Remote Sensing, Inc., US
Real-Time Porosity Prediction for Metal Additive Manufacturing using Convolutional Neural Networks
W. Young, S. Ho, S. Al Jufout, M. Mozumdar, M. Buchholz, W. Zhang, K. Dajani, California State University, Long Beach, US
1:30Machine Learning for MicroscopyBaltimore 1
Session chair: Greg Haugstad, University of Minnesota
Automated Analysis of Transmission Electron Microscopy Images for Characterization of Dynamic Material Systems
J.P. Horwath, D.J. Groom, P.J. Ferreira, E.A. Stach, University of Pennsylvania, US
Rapid DNA Origami Nanostructure Detection and Classification Using the YOLOv5 Deep Convolutional Neural Network
M. Chiriboga, C.M. Green, D.A. Hastman, D. Mathur, Q. Wei, I.L. Medintz, S.A. Díaz, R. Veneziano, United States Naval Research Laboratory, US
Machine learning for microstructures classification in functional materials
A.K. Choudhary, A. Jansche, Grubesa Tvrtko, T. Bernthaler, G. Schneider, Aalen University, DE
Machine learning based detection and deep learning based image inpainting of preparation artefacts in micrographs
A. Jansche, A.K. Choudhary, T. Bernthaler, G. Schneider, Aalen University, DE

Tuesday October 19

1:30Advances in Image AnalysisAnnapolis 3
Session chair: Alex Norman, Modern Meadow & Greg Haugstad, University of Minnesota
Advanced Analytical Approaches for Research and Development of Plant-Based Food Ingredients
M. Crowe, Ingredion, US
X-ray computed tomography for materials characterization: Transformation by machine learning
A. Takase, Rigaku Corporation, US
Development of innovative X-ray scattering and scanning probe microscopy software for materials imaging
G. Yu, University of Minnesota, US
Microwave Sensing of Water-Cut in Production Fluids
J. Oliverio Alvarez, Aramco Services Company: Aramco Research Center -- Houston, US
Conversion of Natural Gas to Value-Added Carbon Materials Using Microwave Plasma Technology
R.R. Kumal, A. Gharpure, A. Mantri, K. Zeller, V. Viswanathan, G. Skoptsov, R. Vander Wal, Penn State University, US
Probing the time-temperature relationship of mechanical properties in polymer composites
B. Pittenger, S. Osechinskiy, J. Thornton, S. Loire, T. Mueller, Bruker Nano, US
Nanoscale Scanning Probe Metrology for a Non-Flat World: How to measure sub-nanometer roughness on complex geometries and large samples
D. Griffin, E. Nelson, C. Newcomb, Nanosurf, US
Intermodulation AFM with machine learning
D. Forchheimer, Intermodulation Products AB, SE
Physical interpretations of multimodal AFM contrast on soft materials
G. Haugstad, University of Minnesota, US

Wednesday October 20

8:30AI Track KeynoteWoodrow Wilson D
Session chair: Richard Ross, 3M Company & Peter Koenig, Procter & Gamble
Detecting Malaria Parasites with Machine Learning
S. Jaeger, U.S. National Library of Medicine / NIH, US
AI-enabled additive manufacturing platform for extreme environments
G. Gu, University of California, Berkeley, US
From atoms to emergent mechanisms with information bottleneck and diffusion probabilistic models
P. Tiwary, University of Maryland, US
1:30User Facilities for Industrial ParticipationAzalea 1
Session chair: Greg Haugstad, University of Minnesota
Industrial Access to the Penn State Materials Characterization Lab
J. Shallenberger, Penn State University, US
NIST, Neutrons, and Next Gen Product Development
R. Jones, National Institute of Standards and Technology, US
Analytical Resources for Industry in an Academic Institution
J. Shu, Cornell Center for Materials Research, US
Neutron Imaging and Far-Field Interferometry
K. Weigandt, National Institute of Standards and Technology, US
TBA
W. Wilson, Harvard University, US

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