This symposium highlights developments in AI, machine learning, data analytics and robotics that will enable multiple application areas. These innovations will have broad impact - but they will revolutionize manufacturing, advanced materials, biomaterials, and drug design and development - the focus areas for this conference. Submit an abstract describing your contributions to this exciting field and plan to join us in Washington DC in June.
Back to Top ↑2023 Symposium Sessions |
| 9:00 | AI Innovations I |
| 1:30 | AI Innovations II |
| 4:00 | AI Innovations - Posters |
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2023 Symposium Program |
| Monday June 19 |
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| 9:00 | AI Innovations I | Chesapeake A |
| Session chair: Amarda Shehu, George Mason University, US |
| 9:00 | Detection of Organic Cofactors Binding Sites via Deep Learning
B. Jacobson, University of New Mexico, US |
| 9:25 | Predicting Antimalarial Activity of Compounds using SMILES strings and Machine Learning: A Study on the Relationship between Chemical Structure and Molecular Properties in the fight against Malaria
C. Ekenna, University at Albany, US |
| 9:50 | Generative design for small molecule drugs
A. Roy, Norachem, US |
| 10:10 | Break
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| 10:20 | Creating the Extended Reality of the Future with Artificial Intelligence and Computational Design
L-F. Yu, George Mason University, US |
| 10:45 | Industrial Internet of Things (IIOT) Physics-Based Dimensionality Reduction
N. Loychik, Los Alamos National Laboratory, US |
| 11:05 | Why You Need to Start Preparing for the American Data Privacy and Protection Act (ADPPA): Understanding its Impact on Enterprises
M. O'Malley, SenecaGlobal, US |
| 11:25 | Automated Detection and Classification of Vehicle Dashboard Warning Lights for Improved Understanding of Vehicle Condition
W. Giegerich, T.S. Porter, K. Shuttleworth, L. Forte III, Ph.J. Schneider, K.W. Oh, University at Buffalo, US |
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| 1:30 | AI Innovations II | Chesapeake A |
| Session chair: Craig Yu, George Mason University, US |
| 1:30 | Automated Classification of Electric Vehicle Models and Drivetrains by Means of Magnetic Field Characterization via Machine Learning
W. Giegerich, Dennis Federoshin, Philip Gentz, Livio Forte III, Ph.J. Schneider, K.W. Oh, University at Buffalo, US |
| 1:50 | Neural Networks and the Problem of Style in Art Attribution
V. Sundaram, A. Coyle, Southern Methodist University, US |
| 2:10 | Utilizing AI & Wearable Technology to Optimize Physical Performance in Military Personnel
H. Bundele, ibLaunch Company, US |
| 2:30 | Break
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| 2:40 | Artificial Intelligence for Visual Battlefield Awareness
M. Karnes, Ubihere, US |
| 3:00 | Investigating Intersection Safety with 3D Object Detection and Digital Twin Technology from Video Data
D. Patel, A. Nayeem, R. Alfaris, M. Jalayer, Rowan University, US |
| 3:20 | Predictive Human Motion Using Physics-Based Avatars for Unreal Engine 4
T. Klopfenstein, R. Bhatt, K. Malek, University of Iowa Technology Institute, US |
| 3:40 | Graph Anomaly Dection
R. Karn, V. Sundaram, SMU Dallas, US |
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| 4:00 | AI Innovations - Posters | Expo Hall AB |
| AI and THz Based Advanced Hardware Security and Reliability Testing for VLSI
N. Akter, J. Suarez, M. Shur, N. Pala, Rensselaer Polytechnic Institute, US |
| Machine learning pipeline of novel peptide and protein generation with refined selection for production in vivo
S.N. Dean , J.A.E. Alvarez, P.M. Legler, A.P. Malanoski, US Naval Research Laboratory, US |
| Adversarial probabilistic AI
T. Ekin, Texas State University, US |
| Real-Time Intelligent Surveillance using Ethical Anomoly Detection
S. Reid, C. Neff, Chimeras, US |
| Innovation in Contracting and Focus on SBIR Phase IIIs
A. Donahoo, A. Rouse, GSA, US |
| Detection of Distracted Driving using Deep Learning Algorithm
A.S. Hasan, D. Patel, M. Jalayer, Rowan University, US |
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