Join industry partners and applied research leadership accelerating the development and deployment of artificial intelligence into products and society.
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Monday June 13 | ||
8:30 | TechConnect World Innovation Conference - Plenary Keynotes | |
10:00 | Coffee Break | |
12:00 | Lunch Break | |
1:30 | AI for Materials & Manufacturing | |
4:00 | SBIR/STTR Agency Meet-and-Greet at SBIR Pavilion, Expo Hall | |
4:00 | TechConnect Innovation Showcase Reception (4:00 - 6:00) | |
Tuesday June 14 | ||
9:00 | AI for Bio & Medical Applications | |
12:00 | Lunch Break | |
1:30 | Machine Learning for Characterization | |
2:45 | AI, Data, Cyber, and Software Innovation Spotlights: USINDOPACOM | |
4:00 | TechConnect Expo & Networking Reception (4:00 - 6:00) - Poster Session | |
4:00 | AI Innovations - Posters | |
Wednesday June 15 | ||
9:00 | AI Innovations | |
Program | ||
Monday June 13 | ||
8:30 | TechConnect World Innovation Conference - Plenary Keynotes | Maryland A |
Session chair: Matthew Laudon, TechConnect Division ATI | ||
8:30 | 2022 Science & Technology Acceleration Opportunities M. Laudon, TechConnect Division, ATI, US | |
8:35 | TechConnect Technical & Business Program Highlights J. Rocha, D. Yablon, J. Williams, TechConnect Division, ATI, US | |
8:40 | What if a country other than the United States dominates the nanomaterial market? L. Mertz, Cerion Nanomaterials, US | |
9:00 | Materials Informatics at 3M: The Intersection of Simulation, Machine Learning, Data Management, and Experimentation C. Lipscomb, 3M Company, US | |
9:25 | Advancements in Novel Neural Interfaces A. Emondi, PionTier LLC, US | |
9:45 | National Nanotechnology Initiative - 2022 Opportunities & Insights L. Friedersdorf, National Nanotech Coordination Office, US | |
10:00 | Coffee Break | Lobby |
12:00 | Lunch Break | On own |
1:30 | AI for Materials & Manufacturing | Chesapeake B |
Session chair: Jan-Willem Handgraaf, Siemens Digital Industries Software, NE | ||
1:30 | The Machine Learning Route to Accelerated Discovery and Inverse Design of Materials Systems J. Hachmann, University of Buffalo, US | |
1:55 | Efficient Navigation of Additive Manufacturing Process Space via Data-Driven and Bayesian Inference Methods P. Balachandran, University of Virginia, US | |
2:20 | Machine learning driven materials discovery, manufacturing process optimization, and intelligent applications W. Shou, University of Arkansas, US | |
2:55 | A product-oriented synchronization and effective information extraction of continuous streaming data for relationship mining in a hot rolling process H. Miao, A. Wang, T-S Chang, J. Shi, Arizona State University, US | |
3:15 | Agile AI-ML Enabled Robotic Manufacturing of 3D Multi-Ply Composites​ A. Kravitz, Advanced Robotics for Manufacturing (ARM) Institute, US | |
4:00 | SBIR/STTR Agency Meet-and-Greet at SBIR Pavilion, Expo Hall | Expo Hall DE |
U.S. Department of Defense (DOD), US | ||
U.S. Department of Energy (DOE), US | ||
U.S. Army, US | ||
U.S. Navy, US | ||
U.S. Air Force, US | ||
National Institutes of Health (NIH), US | ||
NASA, US | ||
NOAA, US | ||
National Science Foundation (NSF), US | ||
Department of Homeland Security (DHS), US | ||
Missile Defense Agency (MDA), US | ||
DARPA, US | ||
Defense Health Agency (DHA), US | ||
U.S. Department of Education, US | ||
Environmental Protection Agency (EPA), US | ||
U.S. Department of Agriculture (USDA), US | ||
4:00 | TechConnect Innovation Showcase Reception (4:00 - 6:00) | Expo Hall DE |
Tuesday June 14 | ||
9:00 | AI for Bio & Medical Applications | Chesapeake 11 |
Session chair: Karl Leswig, Schrodinger, US | ||
9:00 | DeepChem: Towards Open Source Foundations for Modern Drug Discovery B. Ramsundar, Deep Forest Sciences, US | |
9:25 | Active Optimization of Computational Properties to Drive Synthesis K. Leswing, Schrodinger, US | |
9:50 | Small Molecule Generation with Property Control via Disentangled Representation Learning A. Shehu, George Mason University, US | |
10:15 | Real-time Multi-Modality Clinical Decision Support Platform: An Overview of Incorporating Deep Learning within Multi-Modality Fusion Framework in HealthCare A. Kia, P. Timsina, Mount Sinai Health System, US | |
10:35 | App using AI for Recording Vital Signs from heartbeat V. Chaganti, Vipura Technology LLC, US | |
10:55 | Automatic Aortic Aneurysm Screening using Deep-Learning Models Y. Li, H. Nguyen, Rowan University, US | |
11:15 | Athlete Engineering BaseLine Ecosystem: innovative technologies to enhance human performance T. Luczak, R. Burch, P. Nelsen, C. Freeman, H. Chander, J. Ball, J.A. Jones, J. Barlow, D. Saucier, M. Duclos, S. Grice, M. Taquino, Mississippi State University, US | |
12:00 | Lunch Break | On own |
1:30 | Machine Learning for Characterization | Chesapeake 10 |
Session chair: Alex Norman, Modern Meadow, US | ||
1:30 | Machine Learning for Automated Experiments in Charged Particle Beam Tools A. Belianinov, Sandia National Laboratories, US | |
1:55 | Machine learning for recognition and classification of AFM images I. Sokolov, Tufts University, US | |
2:20 | Deep learning to predict structure property relationships with AFM D. Yablon, I. Chakraborty, SurfaceChar LLC, Cognite, US | |
2:40 | Automated Classification of Defected Images by Means of Machine Learning for Improved Analysis of Vehicle Undercarriages W.V. Giegerich, A. Stone, L. Forte III, P.J. Schneider, K.W. Oh, University at Buffalo, US | |
2:45 | AI, Data, Cyber, and Software Innovation Spotlights: USINDOPACOM | National Harbor 10 |
Session chair: Jennifer Rocha, TechConnect Division ATI | ||
2:45 | USINDOPACOM Innovation Spotlight R. Roley, USINDOPACOM, US | |
3:00 | ABScan C. Serino, AlphaBravo, US | |
3:07 | Digital Twins D. Beecham, Beast Code, LLC, US | |
3:14 | Amazon Web Services for Cybersecurity (NIST 800-171, DFARS 7012, and CMMC) J. Joseph, Atomus, US | |
3:21 | A Wearable Computing Cluster and Platform for Multi-agent Cyberphysical Systems J. McClure, Virginia Polytechnic Institute and State University, US | |
3:28 | Decision science Integrated Collaboration Environment (DICE) S. Griffin, Disaster Tech, US | |
3:35 | Ostendo’s Wearable Displays to Support DoD Training, Operations, and Rapid Sustainment B. Noble, Ostendo Technologies, US | |
3:42 | Edge based vision sensor for traffic study M. Farhadi, ARGOS Vision, US | |
3:49 | Emerging Technology Identification S. Hughes, CHN Analytics, US | |
3:56 | Family Resilience and Community Platform J. Risner, Family Proud, Inc, US | |
4:03 | Huna - Automated Information Retrieval M. Mossman, Pueo Business Solutions LLC, US | |
4:10 | OmniTap: Universal Capture and Translation of ICS Communication K. Mecham, Idaho National Laboratory, US | |
Review Panelist J. Rocha, TechConnect Division, ATI, US | ||
Reivew Panelist J. Fanelli, U.S. Navy, US | ||
Review Panelist R. Roley, USINDOPACOM, US | ||
4:00 | TechConnect Expo & Networking Reception (4:00 - 6:00) - Poster Session | Expo Hall DE |
4:00 | AI Innovations - Posters | Expo Hall DE |
A Novel Method for Anomaly Detection Using Scan Statistics J. Woody, T.L Wu, Z. Zhao, Mississippi State University, US | ||
AROSV - An ROS based Self-Driving Vehicle Controller using Unsupervised Machine Learning Methods B. Abegaz, Loyola University Chicago, US | ||
Industry-level Reactive Neural Network Potentials M. Sipka, A. Erlebach, C.J. Heard, P. Nachtigall, L. Grajciar, EigenSpace s.r.o., US | ||
Wednesday June 15 | ||
9:00 | AI Innovations | Chesapeake 11 |
Session chair: Chris Menzel, Fujifilm Dimatix, Inc., US | ||
9:00 | Work From Home/ Work Remote for Infrastructure Consumers C.T. Reynolds, Technical Systems Integrators, US | |
9:20 | Flexible AI for real-world environments T. Achler, Optimizing Mind, US | |
9:40 | Predictive Modeling of Industrial Control Cyber Attacks P. Trainor, Nozomi Networks, US | |
10:00 | A Framework for Proactive Safety Evaluation of Intersection Using Surrogate Safety Measures and Non-Compliance Behavior D. Patel, M. Jalayer, N. Carla Bouaynaya, Rowan University, US | |
10:20 | ABSCA - A Boost Converter Switching Controller using Machine Learning Algorithms B. Abegaz, Loyola University Chicago, US | |
10:40 | CORSI - AI/ML Verification & Validation S. Vasan, S. Chelian, Quantum Ventura Inc., US | |
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