OCTOBER 18-20, 2021

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

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

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

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

10:30Machine Learning for MicroscopyBaltimore 1
Session chair: Greg Haugstad, University of Minnesota
10:30Automated 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
10:55Rapid DNA Origami Nanostructure Detection and Classification Using the YOLOv5 Deep Convolutional Neural Network, pp. 134-137
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
11:15Using machine learning to probe classification and correlation AFM images
I. Chakraborty, Stress Engineering Services, Inc, US
11:35Machine learning for microstructures classification in functional materials, pp. 114-117
A.K. Choudhary, A. Jansche, Grubesa Tvrtko, T. Bernthaler, G. Schneider, Aalen University, DE
11:55Machine learning based detection and deep learning based image inpainting of preparation artefacts in micrographs, pp. 118-121
A. Jansche, A.K. Choudhary, T. Bernthaler, G. Schneider, Aalen University, DE
1:30AI for Characterization & ManufacturingBaltimore 1
Session chair: Greg Haugstad, University of Minnesota & Grace Gu, University of California, Berkeley
1:30Materials Informatics for Simultaneous Design of Alloy Chemistry and AM Process
S. Broderick, University of Buffalo, US
1:55Machine Learning for In-Water Inspection of Submarine Hull Coatings
M. An, J. Cipolla, A. Shakalis, B. Hiriyur, R. Tolimieri, Prometheus Inc., US
2:15Gamma-Ray Raster Imaging with Robotic Data Collection, pp. 109-110
W. Wells, T. Aucott, M. Siddiqi, Savannah River National Laboratory, US
2:35A New Method for Atmospheric Correction of Satellite Data
D. Groeneveld, Advanced Remote Sensing, Inc., US
2:55Real-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
3:15Forecasting and Decision Impact Analysis from Ripple Effects of Behaviors
B. Frutchey, BigBear.ai, US
3:35Leveraging Machine Learning to Predict Public Transportation Arrival Times
P. Reshetova, W. Ruzicka, EastBanc Technologies, US

Tuesday October 19

1:30Advances in Image AnalysisAnnapolis 3
Session chair: Alex Norman, Modern Meadow & Greg Haugstad, University of Minnesota
1:30Advanced Analytical Approaches for Research and Development of Plant-Based Food Ingredients
M. Crowe, Ingredion, US
1:55X-ray computed tomography for materials characterization: Transformation by machine learning
A. Takase, Rigaku Corporation, US
2:20Development of innovative X-ray scattering and scanning probe microscopy software for materials imaging
G. Yu, University of Minnesota, US
2:45Microwave Sensing of Water-Cut in Production Fluids
J. Oliverio Alvarez, Aramco Services Company: Aramco Research Center -- Houston, US
3:05Probing the time-temperature relationship of mechanical properties in polymer composites
B. Pittenger, S. Osechinskiy, J. Thornton, S. Loire, T. Mueller, Bruker Nano, US
3:30Nanoscale 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
3:55Intermodulation AFM with machine learning
D. Forchheimer, Intermodulation Products AB, SE
4:20Physical 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
8:30Closed-loop autonomous combinatorial experimentation for streamlined materials discovery
I. Takeuchi, University of Maryland, US
9:00From atoms to emergent mechanisms with information bottleneck and diffusion probabilistic models
P. Tiwary, University of Maryland, US
9:30Deep Learning for Linking Chemical and Biological Space in Small Molecules and Macromolecules
A. Shehu, George Mason University, US
1:30User Facilities for Industrial ParticipationAzalea 1
Session chair: Greg Haugstad, University of Minnesota
1:30Industrial Access to the Penn State Materials Characterization Lab
J. Shallenberger, Penn State University, US
1:55NIST, Neutrons, and Next Gen Product Development
R. Jones, National Institute of Standards and Technology, US
2:20Analytical Resources for Industry in an Academic Institution
J. Shu, Cornell Center for Materials Research, US
2:45Neutron Imaging and Far-Field Interferometry
K. Weigandt, National Institute of Standards and Technology, US
3:10Harvard Center for NanoScale Systems: An Epicenter for Interdisciplinary Quantum and Nano Science Research and Technologie
W. Wilson, Harvard University, US

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