OCTOBER 18-20, 2021

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2021 Symposium Sessions

Monday October 18

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

Tuesday October 19

1:30AI for Biomedical Applications

Wednesday October 20

8:30AI Track Keynote
10:30AI for Advanced Materials Discovery & Design
4:00AI Innovations - Posters

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

1:30AI for Biomedical ApplicationsBaltimore 4
Session chair: Armada Shehu, George Mason University & Sarah Tao, Sanofi
1:30Machine Learning for Automated Hepatic Fat Quantification, pp. 105-108
H. Sagreiya, A. Akhbardeh, I. Durot, D.L. Rubin, University of Pennsylvania, US
1:55Point-of-care serodiagnostic test using a multiplexed paper-based immunoassay and machine learning
Z.S. Ballard, H-A Joung, A. Goncharov, J. Liang, K. Nugroho, J. Wu, D.K. Tseng, H. Teshome, L. Zhang, E.J. Horn, P.M. Arnaboldi, R.J. Dattwyler, O.B. Garner, D. Di Carlo, University of California, Los Angeles, US
2:15Kidney Cancer Staging using Deep Learning Neural Network: Comparing Models Trained on Whole Kidney with Cancer and Only the Cancer, pp. 161-164
N. Hadjiyski, Ann Arbor Pioneer High School, US
2:35Robust and Trustworthy AI for Brain Tumor Surveillance
G. Rasool, Rowan University, US
2:55Preventing Elderly Falling Through Machine Learning, pp. 111-113
P. Hardigan, Nova Southeastern University, 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
10:30AI for Advanced Materials Discovery & DesignAnnapolis 2
Session chair: Richard Ross, 3M Company & Peter Koenig, Procter & Gamble
10:30The combination of data-driven and physics-based modeling with application in protein formulations
J.G.E.M. Fraaije, P. Petris, Siemens Culgi, NL
10:55Next Generation PCIe Network Fabric for Simulators and Performance Computing
C.T. Reynolds, Technical Systems Integrators, US
11:15AI-accelerated materials innovation: From Optoelectronics to Fluorescent Biomarkers
C. Kreisbeck, Kebotix, US
11:35Machine Learning for the Exploration of Nanomaterial Synthesis Parameter Spaces
R. Sappington, B. Cornick, Epic Advanced Materials, US
11:55A Self-Driving Laboratory for Accelerated Materials Discovery
C.P. Berlinguette, J.E. Hein, A. Aspuru-Guzik, B.P. MacLeod, F.G.L. Parlane, University of British Columbia, CA
4:00AI Innovations - PostersExpo Hall AB
Using Robotics to Assemble Graphene Supercapacitor, pp. 122-125
C. Wu, J. Kim, D. Magluyan, D. Kawamoto-Kindred, Y.H. Zhou, N. Cao, H. Zhao, Z. Kuang, T. Kidd, S. Wu, S. Dobbs, Z. Yu, California State Polytechnic University, Pomona, US
An eHR Using AI Technology as a Clinical Decision Support Tool
J. Penn, Guidance Foundation Inc,, US
Benefits of a Decentralized AI, pp. 130-133
M. Bergstrom, Internet of Everything Corporation, US
Automatic deep-learning classification models for breast lesions
S. Hasan, A. Hasan, Princeton Day School, US
Zero Bandwidth, Zero Storage, Full Evidentiary Data
M. Script, In2Capital.com, US
Benefits of a Decentralized AI
M. Bergstrom, Internet of Everything Corp, US
Simulation in Minutes, not Hours
A. Grosvenor, MSBAI, US

Topics & Application Areas

  • AI for Advanced Manufacturing
  • AI for Biomaterials and Drug Design
  • AI for Advanced Materials Design
  • AI Innovations
  • Machine learning for Characterization

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2021 Sponsors & Partners


SBIR/STTR Agency Partners