Center for Computational Network Intelligence (CCNI)
We develop innovative solutions for challenging problems in application areas ranging from vehicle health and machine intelligence to emerging inter-connected human-machine and social systems.
We create computational theories, models and techniques that can enable us to better understand, characterize, anticipate, predict, intervene and control evolving events, behaviors, and phenomena in complex systems. We focus on transitioning our innovative technologies to products and platform for our owners and the DoD, IC and DHS communities.
We strive for robust and reliable research findings that are reproducible, replicable, and generalizable. We are committed to open science paradigm and actively collaborate with researchers and practitioners from universities and industries.
Research
Advanced Vehicle Health
Advanced Vehicle Health
Develop hybrid data-driven & model-based prognostics that fuse multiplex data to detect, attribute and predict impending faults for sustainable vehicle operations and missions.
- HRL developed Next Generation Aircraft Prognostics technologies for Boeing platforms to exploit design engineering knowledge, filter/fuse weak signals, and overcome high-dimensionality in massive, heterogeneous operational data. These technologies use advanced machine learning algorithms to generate relevant and important features for early detection of impending faults, robust identification of root causes, and accurate prediction of component remaining useful life.
- HRL developed Adaptive Prognostics technologies for GM platforms to automatically adapt existing physics-based prognostics models with new information provided by field data. These technologies enables the rapid deployment of prognostics models to similar, but critically different systems (e.g., new versions of existing systems) with optimal adaptations of existing prognostics models to changes in the system (e.g., aging parts) for accurate first-time detections of potential failure patterns in different operating conditions
Computational Social Intelligence
Computational Social Intelligence
Develop anticipatory learning capability to understand and utilize hybrid social intelligence to forecast events, prevent surprise, and adapt to new norms with rigorous validations in scalable simulation and experimentation platforms.
HRL’s network alignment technology enables the identification and mapping of node, edge, and higher-order relations across two or more networks given limited, noisy initial correspondence. The video shows an example of aligning nodes from two networks via embedding and warping techniques.
- HRL’s Twitter geo-localization technology processes social networks (billions of edges and hundreds of millions of nodes) to accurately geo-locate more than 110 million users with a median error less than 7 km in ~80TB of Twitter data.
- HRL’s network alignment technology aligns more than 21 million Twitter users to their alternative accounts on different social media platforms (Tumblr, WordPress, Facebook, Blogger, and Instagram) with an estimate of 95% accuracy.
- HRL’s network inference technology leverages cognitive, sociological, behavioral principles with machine learning algorithms to harvest network-based and content-based features to classify group vs individual user accounts (98% accuracy), identify pro-ISIS accounts (90% precision and 99% specificity), and infer demographic attributes of social media user accounts (77% accuracy).
Intelligent Sensing
Intelligent Sensing
Develop active perceptual sensing and processing capabilities to contextualize, anticipate, and track rare and sudden changes in activity and behavior patterns for optimal, flexible, and timely information gain.
HRL’s SmarNet technology devises a self-organized intervention strategy to mitigate large-scale cascading failure by performing smart switching between alternate connections; Reduced the probability of large (>30 lines) failures (33% reduction for a cascade of 100 lines) on a random geometric graph of AC power grid with 4,096 nodes.
Collaborative Multi-Intelligence
Collaborative Multi-Intelligence
Fuse OSINT and other INT to anticipate the spread, cascade and contagion behaviors of a target system to develop controlling strategies and curate dynamic sensors with optimized coverage and precision.
- HRL’s multilayer information dynamics technology fused maritime activity data (AIS data, simulated ship-to-ship communications, port logs) and open source data (Twitter) and demonstrated the detection of “coordinated movements” and “silence before action” with hit rate (>98%) for noise level (<0.8) with small false alarms (<0.5%).
People
David Huber
Samuel Johnson
Soheil Kolouri
Kangyu Ni
Shane Roach
Nigel Stepp
Alex Waagen
Dana Warmsley
Jiejun Xu
Publications
Journals (20)
| Authors | Title | Publication | Year |
|---|---|---|---|
| Dawei Zhou, Lecheng Zheng, Jiejun Xu, & Jingrui He | Misc-GAN: A Multi-Scale Generative Model for Graphs | In Frontiers in Big Data, Vol 2 | 2019 |
| Kundu S., Kolouri S., Erickson K.I., Kramer A.F., McAuley E, Rohde G.K. | Discovery and visualization of structural biomarkers from MRI using transport-based morphometry | NeuroImage | 2018 |
| Patel, A.N., Howard, M.D., Roach, S.M., Jones, A.P., Bryant, N.B., Robinson, C.S.H., Clark, V.P., Pilly, P.K. | Mental State Assessment and Validation Using Personalized Physiological Biometrics | Frontiers in Human Neuroscience 12, 221 | 2018 |
| Kolouri S., Park S.R., Thorpe M., Slepcev D., Rohde G.K. | Optimal Mass Transport: Signal processing and machine-learning applications | IEEE Signal Processing Magazine | 2017 |
| Park, S.R., Kolouri, S., Kundu, S., Rohde, G.K. | The cumulative distribution transform and linear pattern classification | Applied and Computational Harmonic Analysis | 2017 |
| Thorpe, M., Park, S., Kolouri, S., Rohde, G.K., Slepčev, D. | A Transportation Lp Distance for Signal Analysis | Journal of Mathematical Imaging and Vision | 2017 |
| Uhlenbrock, R., Kim, K., Hoffmann, H., Dolne, J. | Rapid 3D registration using local subtree caching in iterative closest point (ICP) algorithm | Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2017 (Vol. 10410, p. 104100J) International Society for Optics and Photonics | 2017 |
| Alex Waagen, Raissa D’Souza, and Tsai-Ching Lu | Explosive Percolation on Directed Networks Due to Monotonic Flow of Activity | Phys. Rev. E 96, 012317 | 2017 |
| Kang-Yu, Shankar Rao, Yuri Owechko | Foveated Compressive Imaging for Low Power Vehicle Fingerprinting and Tracking in Aerial Imagerys | Inverse problems & Imaging, 11:1 | 2017 |
| Hankyu Moon and Tsai-Ching Lu | Network Catastrophe: Self-Organized Patterns Reveal both the Instability and the Structure of Complex Networks | Scientific Reports, 5:9450 | 2015 |
| Sam Johnson, Raissa M. D’Souza | Inequality and Network Formation Games | Internet Mathematics | 2015 |
| Kang-Yu Ni and Tsai-Ching Lu | Information Dynamic Spectrum Characterizes System Instability toward Critical Transitions | EPJ Data Science, 3:28 | 2014 |
| Waagen, A., & D’souza, R. M. | Given enough choice, simple local rules percolate discontinuously | The European Physical Journal B, 87(12), 304 | 2014 |
| Jiejun Xu, Vignesh Jagadeesh, B. S. Manjunath | Multi-Label Learning With Fused Multimodal Bi-Relational Graph | IEEE Transactions on Multimedia | 2014 |
| Ryan Compton, Craig Lee, Tsai-Ching Lu, Jiejun Xu, Lalindra De Silva, Michael Macy, Luis Artieda-Moncada | Using Publicly Visible Social Media to Build Detailed Forecasts of Civil Unrest | Security Informatics | 2014 |
| Deepak Khosla, Yang Chen, Kyungnam Kim | A Neuromorphic System for Video Object Recognition | Frontiers in Computational Neuroscience | 2014 |
| Jiejun Xu, Vignesh Jagadeesh, Zefeng Ni, Santhoshkumar Sunderrajan, B. S. Manjunath | Graph-Based Topic-Focused Retrieval in Distributed Camera Network | IEEE Transactions on Multimedia | 2013 |
| Vijayaraghavan, V. S., Noel, P. A., Waagen, A., & D'Souza, R. M. | Growth dominates choice in network percolation | Physical Review E, 88(3), 032141 | 2013 |
| Narayan Srinivasa, Rajan Bhattacharyya, Rashmi Sundareswara, Craig Lee, Stephen Grossberg | A Bio-Inspired Kinematic Controller for Obstacle Avoidance during reaching tasks with Redundant Robots | Neural networks: the official journal of the International Neural Network Society 08/2012; 35:54-69. DOI:10.1016/j.neunet.2012.07.010 | 2012 |
| Lu, U., Roach, S.M., Song, D., Berger, T.W. | Nonlinear dynamic modeling of neuron action potential threshold during synaptically driven broadband intracellular activity | IEEE Trans Biomed Eng 59, 706–716 | 2012 |
Conferences (63)
| Members | Topic | Conference | Year |
|---|---|---|---|
| Huber, D., Stepp, N., Jammalamadaka, A., Kim, T., Johnson, S., Warmsley, D. and Lu, T-C. | MATRICS: A System for Human-Machine Hybrid Forecasting of Geopolitical Events | IEEE BIG Data 2019, Los Angeles, CA | 2019 |
| Ni, K-Y, Waagen, A., Martin, C., Apreleva, S., Korchev, D., Liapis, D., Lu, T-C. | Extract Twitter Network Features for Enhanced Market Volatility Prediction | Statistical Physics for Financial & Economic Networks (SPEFEN@NetSci2019), NetSci 2019 Satellite, Burlington, Vermont | 2019 |
| Xu, J., Ni, K-Y., Kopylov, A., Roach, S., Lu, T-C. | On Modeling Adversarial Activities in Large Multi-Source Networks | NetCrime, NetSci2019 Satellite, Burlington, Vermont | 2019 |
| Martin, C. and Pilly, P. | Probabilistic Program Neurogenesis | ALIFE conference, Aug, UK | 2019 |
| Wu, J., He, J., and Xu, J. | DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification | SIGKDD Conference on Knowledge Discovery and Data Mining, Alaska, USA | 2019 |
| Rostami, M., Kolouri, S., Kim, K.,Eaton, E. | Multi-Agent Distributed Lifelong Learning | AAMAS | 2018 |
| Joel Douglas, Ben Zimmerman, Alexei Kopylov, Jiejun Xu, Daniel Sussman, Vince Lyzinski | Metrics for Evaluating Network Alignment | ACM WSDM workshop on Graph Techniques for Adversarial Activity Analytics (GTA3) | 2018 |
| Kolouri, S., Rostami, M., Owechko, Y., Kim, K. | Joint Dictionaries for Zero-Shot Learning | AAAI | 2018 |
| Martin, C., Lu, T-C., Slaughter, S. and Murphy, A. | Abnormal Derivative Frequency for Sensor and Wiring Prognostics | 2018 American Helicopter Society (AHS) Conference in Phoenix, AZ | 2018 |
| Jammalamadaka, A., Xu, J., and Lu, T-C. | Behavior Deviations in Social Media Caused by Emergency Events | 2018 Interactional Conference on Social Computing, Behavior-Cultural Modeling & Prediction, Washington DC (SBP-BRiMS 2018) | 2018 |
| Sundareswara, R., Betz, D. and Lu, T-C. | Interpretable Unsupervised Feature Extraction and Learning of Abnormal System State Transitions in Aircraft Sensor Data | Annual Conference of the Prognostics and Health Management Society 2018 (PHM 2018), Philadelphia, PA | 2018 |
| Rostami, M., Huber, D. and Lu, T-C. | A Crowdsourcing Triage Algorithm for Geopolitical Event Forecasting | 12th ACM Conference on Recommender Systems (RecSys-18), Vancouver | 2018 |
| Warmsley, D., Xu, J. and Lu, T-C. | From Gamergate to FIFA: Identifying Polarized Groups in Online Social Media | IEEE BIG Data 2018, Seattle, WA | 2018 |
| Zhang, S., Tong, H., Xu, J. and Maciejewski., R. | Graph Convolutional Networks: Algorithms, Applications and Open Challenges | IEEE International Conference on Computational Data & Social Networks (CSoNet) | 2018 |
| Stepp, N. and Jammalamadaka, A. | A Dynamical Systems Approach to Neuromorphic Computation of Conditional Probabilities | Proceedings of the International Conference on Neuromorphic Systems. ACM, Knoxville, TN | 2018 |
| Thomas, D., Warmsley D., Macy, M. | Automated hate speech detection and the problem of offensive language | Proceeding of Eleventh International AAAI Conference on Web and Social Media, Montreal, Canada, | 2017 |
| Daniel Xie, Jiejun Xu, Tsai-Ching Lu | What’s trending tomorrow, today: Using early adopters to discover popular posts on Tumblr | IEEE Big Data | 2017 |
| Khosla, D., Uhlenbrock, R., Chen, Y. | Automated scene understanding via fusion of image and object features | Technologies for Homeland Security (HST) IEEE International Symposium on (pp. 1-4) | 2017 |
| Kolouri, S., Martin, C.E., Hoffmann, H. | Explaining Distributed Neural Activations via Unsupervised Learning | CVPRW | 2017 |
| Rahimi, A.M., Kolouri, S., Bhattacharyya, R. | Automatic Tactical Adjustment in Real-Time: Modeling Adversary Formations with Radon-Cumulative Distribution Transform and Canonical Correlation Analysis | CVPRW | 2017 |
| Shay Deutsch, Soheil Kolouri, Kyungnam Kim, Yuri Owechko, Stefano Soatto | Zero Shot Learning via Multi-Scale Manifold Regularization | IEEE Conference on Computer Vision and Pattern Recognition (CVPR) | 2017 |
| Stephan Salas, Shane Roach, Matthew E. Phillips, Nigel Stepp, Jose Cruz-Albrecht, Vincent De Sapio, Tsai-Ching Lu | IEEE International Symposium on Technologies for Homeland Security, Waltham MA | Continuous Authentication of a Mobile Device using Neuromorphic and Early Warning Behavior-Based Authentication in Common Theft Scenarios | 2017 |
| Steven Munn, Kang-Yu Ni, Jiejun Xu | Learning Network Dynamics from Tumblr: A Search for Influential Users | Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS) | 2017 |
| Krishna Bathina, Aruna Jammalamadaka, Jiejun Xu, Tsai-Ching Lu | An Agent-based Model of Posting Behavior During Times of Societal Unrest | International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation | 2017 |
| Deepak Khosla, Jiejun Xu, Kyungnam Kim, Yang Chen | Online Location recognition for drift-free state estimation and efficient autonomous exploration | SPIE Unmanned Systems Technology | 2017 |
| David Huber, Kyungnam Kim, Deepak Khosla | Motion-Seeded Object-Based Attention for Dynamic Visual Imagery | SPIE Defense and Security | 2017 |
| Laura Cruz-Albrecht, Jiejun Xu, Kang-Yu Ni and Tsai-Ching Lu | Characterizing Regional and Behavioral Device Variations Across the Twitter Timeline: a Longitudinal Study | ACM Web Science Conference (WebSci), Troy, USA | 2017 |
| Jiejun Xu, Daniel Xie, Tsai-Ching Lu, John Cafeo | EDSV: Emerging Defect Surveillance for Vehicles | ACM Web Science Conference (WebSci), Troy, USA | 2017 |
| Jiejun Xu, Samuel Johnson, Kang-Yu Ni | Cross-Modal Event Summarization: A Network of Networks Approach | International Conference on Big Data (IEEE BigData), Washington D.C., USA | 2016 |
| Richards, M. G., McArdle, R., Feller, E., Lu, T. C., Ni, K., Uhlenbrock, R. M. | Integrating ISR Data with Open Source Indicators | AIAA SPACE 2016 (p. 5289) | 2016 |
| Samuel D. Johnson, Jemin George, and Raissa M. D’Souza | Strategic Seeding of Rival Opinions | GamesNet | 2016 |
| Daniel Xie, Jiejun Xu, Tsai-Ching Lu | Automated Classification of Extremist Twitter Accounts Using Content-Based and Network-Based Features | IEEE BigData, workshop on Application of BigData for Computational Social Science, Washington D.C., USA | 2016 |
| Rashmi Sundareswara, Tsai-Ching Lu, Yilu Zhang | Network-based Relevant Feature Identification and Early Detection of Impending Faults | Aerospace Conference, March 6-11, Big Sky, Montana | 2016 |
| Samuel D. Johnson, Jemin George, Raissa M. D'Souza | Strategic Seeding of Rival Opinions | International Conference on Game Theory for Networks (GamNet) | 2016 |
| Samuel D. Johnson, Kang-Yu Ni | A Pricing mechanism using social media data and web data to infer dynamic customer valuations | IEEE Big Data | 2015 |
| Kyungnam Kim, David J. Huber, Jiejun Xu, Deepak Khosla | Efficient Algorithms for Indoor MAV Flight using Vision and Sonar Sensors | 11th International Symposium on Visual Computing (ISVC), Las Vegas, Nevada, USA | 2015 |
| Jiejun Xu, Kyungnam Kim, Lei Zhang, Deepak Khosla | 3D Perception for Autonomous Robot Exploration | 11th International Symposium on Visual Computing (ISVC), Las Vegas, Nevada, USA | 2015 |
| Jiejun Xu, Tsai-Ching Lu | Toward Precise User-Topic Alignment in Online Social Media | IEEE International Conference on Big Data (IEEE BigData), Santa Clara, California | 2015 |
| Peter Li, Jiejun Xu, Tsai-Ching Lu | Leveraging Homophily to Infer Demographic Attributes | Workshop on Information in Networks, New York, USA | 2015 |
| Jiejun Xu, Tsai-Ching Lu | Inferring User Interests with a Heterogeneous Bi-relational Graph Model | Conference on Complex Systems (CCS), Arizona, USA | 2015 |
| Jiejun Xu, Tsai-Ching Lu | Seeing the Big Picture from Microblogs: Harnessing Social Signals for Visual Event Summarization | ACM Conference on Intelligent User Interfaces (IUI), Atlanta, USA | 2015 |
| Jiejun Xu, Tsai-Ching Lu | Inferring User Interests on Tumblr. In Social Computing | Behavioral Modeling and Prediction Conference (SBP), Washington DC, USA | 2015 |
| T. N. Mundhenk, Kyungnam Kim, Yuri Owechko | PanDAR: a wide-area, frame-rate, and full color lidar with foveated region using backfilling interpolation upsampling, Proc. SPIE 9406 | Intelligent Robots and Computer Vision XXXII: Algorithms and Techniques | 2015 |
| Chelian, S. E., Uhlenbrock, R. M., Herd, S., Bhattacharyya, R. | Application of a neural network model of prefrontal cortex to emulate human probability matching behavior | Biologically Inspired Cognitive Architectures, 10, 10-16 | 2014 |
| Ryan Compton, Craig Lee, Jiejun Xu, Luis Artieda-Moncada, Tsai-Ching Lu, Lalindra De Silva, Michael Macy | Using Publicly Visible Social Media to Build Detailed Forecasts of Civil Unrest | Springer Journal on Security Informatics | 2014 |
| Jiejun Xu, Kyungnam Kim, Zhiqi Zhang, Hai-Wen Chen, Yuri Owechko | 2D/3D Sensor Exploitation and Fusion for Enhanced Object Detection | IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Multi-Sensor Fusion for Outdoor Dynamic Scene Understanding, Columbus, USA | 2014 |
| T. N. Mundhenk, Kyungnam Kim, Y. Owechko | Real time fusion and backfilling of EO/LIDAR data | IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Multi-Sensor Fusion for Outdoor Dynamic Scene Understanding, Columbus, USA | 2014 |
| Jiejun Xu, Ryan Compton, Tsai-Ching Lu, David Allen | Rolling through tumblr: Characterizing Behavioral Patterns of the Microblogging Platform | ACM Web Science Conference (WebSci), Bloomington, USA | 2014 |
| Jiejun Xu, Ryan Compton, Tsai-Ching Lu, David Allen | Quantifying Cross-platform Engagement through Large-scale User Alignment | ACM Web Science Conference (WebSci), Bloomington, USA | 2014 |
| Ryan Compton, Matthew Keegan, Jiejun Xu | Inferring the Geographic Focus of Online Documents from Social Media Sharing Patterns | Computational Approaches to Social Modeling Workshop (ChASM), Bloomington, USA | 2014 |
| Jiejun Xu, Tsai-Ching Lu, Ryan Compton, David Allen | Civil Unrest Prediction: A Tumblr-Based Exploration | Social Computing, Behavioral Modeling and Prediction Conference (SBP), Washington DC, USA | 2014 |
| Rangachar Kasturi, Dmitry Goldgof, Rajmadhan Ekambaram, Gill Pratt, Eric Krotkov and Douglas D. Hackett, Yang Ran and Qinfen Zheng, Rajeev Sharma, Mark Anderson, Mark Peot, Mario Aguilar, Deepak Khosla, Yang Chen, Kyungnam Kim, Lior Elazary, Randolph C. Voorhies, Daniel F. Parks, Laurent Itti | Performance Evaluation of Neuromorphic-Vision Object Recognition | ICPR | 2014 |
| Kang-Yu Ni, Shankar Rao | SAR moving target imaging using sparse and low-rank decomposition | SPIE Defense and Security | 2014 |
| Santhoshkumar Sunderrajan, Jiejun Xu, B. S. Manjunath | Context-aware Graph Modeling for Object Search and Retrieval in a Wide Area Camera Network | International Conference on Distributed Smart Camers (ICDSC), Palm Springs, USA | 2013 |
| Rashmi Sundareswara, Mike Daily, Mike Howard, Howard Neely, Rajan Bhattacharyya, Craig Lee | Using a Distracted Driver’s Behavior to Inform The Timing of Alerts in a Semi-Autonomous | IEEE International Multi-Disciplinary Conference on Cognitive Methods in situation Awareness and Decision Support (CogSIMA 2013), San Diego, USA | 2013 |
| Deepak Khosla, Yang Chen, David J. Huber, Darrel J. Van Buer, Kyungnam Kim, Shinko Y. Cheng | Real-time low-power neuromorphic hardware for autonomous object recognition | SPIE Defense, Security, and Sensin | 2013 |
| Shankar Rao, Kang-Yu Ni, Yuri Owechko | Context and task-aware knowledge-enhanced compressive imaging | SPIE Optical Engineering+ Applications | 2013 |
| Matthew S. Keegan, Kang-Yu Ni, Shankar Rao | L1-methods for low-power surveillance | SPIE Optical Engineering+ Applications | 2013 |
| Mike Howard, Rashmi Sundareswara, Mike Daily, Rajan Bhattacharyya, Sam Kaplan, Nathan Mundhenk, Craig Lee, Howard Neely | Using Tactile Displays to Maintain Situational Awareness during Driving | IEEE International Multi-Disciplinary Conference on Cognitive Methods in situation Awareness and Decision Support (CogSIMA 2013), San Diego, USA | 2013 |
| Kyungnam Kim, Yang Chen, Alexander Honda, Changsoo Jeong, Shinko Cheng, Lei Zhang, Deepak Khosla | Bio-inspired Algorithms for Target Detection and Classification in Airborne Videos | Association for Unmanned Vehicle Systems International, North America | 2012 |
| Kang-Yu Ni, T.N. Mundhenk, Kyungnam Kim, Y. Owechko | Manifold-based fingerprinting for target identification | Camera Networks & Wide Area Scene Analysis, IEEE CVPR Workshop | 2012 |
| Jiejun Xu, Ziyu Guan, Vishwakarma Singh, B.S. Manjunath | Unified Hypergraph for Image Ranking in a Multimodal Context | IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan | 2012 |
| Zefeng Ni, Jiejun Xu, B.S. Manjunath | Object Browsing and Searching in a Camera Network using Graph Models | IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Workshop on Camera Networks & Wide Area Scence Analysis, Providence, USA | 2012 |
Patents (65)
| Authors | Title | Patent # | Date |
|---|---|---|---|
| Ni, K-Y., Lu, T-C. | Predicting System Trajectories toward Critical Transitions | US10460008 | 10/29/2019 |
| Lu, T-C., Sundareswara, R., Huber, H., Waagen, A. | System and Method for Aircraft Failure Prediction | US10457423 | 10/29/2019 |
| Keegan, M., Compton, R., Lu, T-C. | System and Method for Using Network Data to Improve Event Prediction | US10452729 | 10/22/2019 |
| Pilly, P., Howard, M., Hoffmann, H., Lu, T-C., Ni, K., Payton, D. | Method and Apparatus to Determine Optimal Brain Stimulation to Induce Desired Behavior | US10420937 | 09/24/2019 |
| El Defrawy, K., Maxon, I., Keegan, M., Lu, T-C. | Inferring Network Services and Their Dependencies from Header and Flow Data and the Switching Topology | US10425489 | 09/24/2019 |
| Chen Y., Xu J., Khosla D. | System and method for location recognition and learning utilizing convolutional neural networks for robotic exploration | US10373335 | 08/06/2019 |
| Lu, T-C., Stepp, N., Betz, F. | Systems and Methods for Aircraft Message Monitoring | US10325421 | 06/18/2019 |
| Jammalamadaka, A., Xu, J., Lu, T-C. | System and Method for Assessing Spatiotemporal Impact of Emergency Events based on Social Media Posting Behavior | US10326847 | 06/18/2019 |
| Ni, K. and Rao, S. | System and method for denoising synthetic aperture radar (SAR) images via sparse and low-rank (SLR) decomposition and using SAR images to image a complex scene | US10310074 | 06/04/2019 |
| Kong, X., Ni, K. | Real-time signal detection over very wide band in low SNR environments | US10306486 | 05/28/2019 |
| Xu, J., Lu, T-C., Compton, R., Allen, D. | Social Media Mining System for Early Detection of Civil Unrest Events | US10255352 | 04/09/2019 |
| Ni, K., Xu, J. | Tensor-based Framework for Analyzing High Velocity Large-scale Network Activities to Infer Latent Mesostructures and Important Nodes | US10218579 | 02/26/2019 |
| Ni, K., Benvenuto, J. | Feature Transformation of Neural Activity with Sparse and Low-rank (SLR) Decomposition | US10172532 | 01/08/2019 |
| Keegan, M., Ni, K., Lu, T-C. | Method for Determining Contagion Dynamics on a Multilayer Network | US10178120 | 01/08/2019 |
| Zhang, L., Kim, K., Khosla, D., Xu, J. | System and method for finding open space efficiently in three dimensions for mobile robot exploration | US10134135 | 11/20/2018 |
| Johnson, S., Lu, T-C. | Strategic Network Formation Involving Sources, Aggregations, and Consumers | US10129093 | 11/13/2018 |
| Zhang, L., Monterrozo, F., Kim, K., Xu, J., Chen Y., Khosla, D. | Generic frontal and side doorway detection with line tracking and vanishing point based verification | US10068336 | 09/04/2018 |
| Xu, J., Lu, T-C. | System and Method for Real World Event Summarization with Microblog Data | US10055486 | 08/21/2018 |
| Holland, G., Howard, M., Lu, T-C., El Defrawy, K., Keegan, M., Ni, K. | System and Method for Determining Reliability of Nodes in Mobile Wireless Network | US10003985 | 06/18/2018 |
| Holland, G., Howard, M., Ding, C., Lu, T-C. | System and Method to Detect Attacks on Mobile Wireless Networks based on Motif Analysis | US9979738 | 05/22/2018 |
| Cao, Y., Khosla, D., Chen, Y., Huber, D. | System and method for real-time collision detection | US9934437 | 04/03/2018 |
| Alexey Rudenko, Tsai-Ching Lu, Craig A. Lee, Franz David Betz | Systems and Methods for Monitoring Operative Sub-Systems of A Vehicle | US9916702B2 | 03/13/2018 |
| Ni, K., Lu, T-C. | Network of Networks Reconstruction Employing Compressed Sensing | US9904740 | 02/27/2018 |
| Medasani, S., Meltzer, J., Xu, J., Chen, Z., Sundareswara, R., Paton, D., Uhlenbrock, R., Barajas, L., Kim, K. | Method for object localization and pose estimation for an object of interest | US9875427 | 01/23/2018 |
| Tsai-Ching Lu, David Allen | Multi-scale Information Dynamics for Decision Making | US9792551 | 10/17/2017 |
| David Jurgens, Tsai-Ching Lu | System and Methods for Automated Community Discovery with Multiple Relational Types | US9749406 | 08/29/2017 |
| Pejman Mahboubi, Ryan Compton, Tsai-Ching Lu | System and Method for Farsi Language Temporal Tagger | US9740689 | 08/22/2017 |
| Kang-Yu Ni, Shankar Rao | Spatio-temporal signal monitoring | US9660693 | 05/23/2017 |
| David Jurgens, Tsai-Ching Lu, Veronika Stmadova | Systems for Discovering Important Elements that Drives an Online Discussion for a Topic Using Network Analysis | US9646057 | 05/09/2017 |
| David Jurgens, Tsai-Ching Lu, Veronika Stmadova | Method for Gauging Public Interest in A Topic Using Network Analysis of Online Discussions | US9639610 | 05/02/2017 |
| Jiejun Xu, Kyungnam Kim, Yuri Owechko | System for filtering, segmenting and recognizing objects in unconstrained environments | US9633483 | 04/25/2017 |
| Sofia Apreleva, Tsai-Ching Lu | System and Method for Predicting Significant Events Using Progress Curve Model | US9613309 | 04/04/2017 |
| Tsai-Ching Lu, Charles E. Martin, Alice A. Murphy, Stephen C. Slaughter, Christopher R. Wezdenko | Systems and Method for Detecting Vehicle System Fault | US9558601B2 | 01/31/2017 |
| Kang-Yu Ni, Shankar Rao, Yuri Owechko | Low power surveillance camera system for intruder detection | US9544550 | 01/10/2017 |
| Nikolay Laptev, Tsai-Ching Lu | A Scalable Bootstrap Method for Assessing the Quality of Machine Learning Algorithm over Massive Time Series | US9530104 | 12/27/2016 |
| David Allen, Tsai-Ching Lu | Mining Group Patterns in Dynamic Relational Data via Individual Event Monitoring | US9483729 | 11/01/2016 |
| David Jurgens and Tsai-Ching Lu | Automated Collaborative Behavior Analysis Using Temporal Motifs | US9465504 | 10/11/2016 |
| Mohin Ahmed, Shankar Rao, Willie W. Ng | Hardware based compressive sampling ADC architecture for non-uniform sampled signal recovery | US9450597 | 09/20/2016 |
| Hankyu Moon, Tsai-Ching Lu | System for Instability Detection and Structure Estimation of Complex Network Dynamics | US9368804 | 06/14/2016 |
| Y. Chen, S. Medasani, Q. Jiang, DL Allen, Tsai-Ching Lu | Video Content-Based Retrieval | US9361523B1 | 06/07/2016 |
| Rashmi N. Sundareswara, Tsai-Ching Lu, Franz David Betz | System and Method for Detecting Faults within Operative Sub-systems of a Vehicle | US9349226B2 | 05/24/2016 |
| Tsai-Ching Lu, David L. Allen, Hankyu Moon | System and Method of Computational Social Network Development Environment for Human Intelligence | US9317567 | 04/19/2016 |
| Jiejun Xu, Deepak Khosla, Kyungnam Kim | Fast Open Doorway Detection for Autonomous Robot Exploration | US9251417B1 | 02/02/2016 |
| Yuri Owechko, Kang-Yu Ni, Shankar Rao | Foveated compressive sensing system | US9230302 | 01/05/2016 |
| Tsai-Ching Lu, David D. Holland, David L. Allen, Aleksey Nogin, Michael D. Howard | System and Methods for Digital Artifact Genetic Modeling and Forensic Analysis | US9224067 | 12/29/2015 |
| Rashmi Sundareswara, Narayan Srinivasa | System for three-dimensional object recognition and foreground extraction | US9220070 | 12/22/2015 |
| Zhiqi Zhang, Kyungnam Kim, Jiejun Xu, Yuri Owechko, Hai-Wen Chen | Sensor Fusion using Detector Confidence Boosting | US9183459B1 | 11/10/2015 |
| David L. Allen, Tsai-Ching Lu, David J. Huber, Hankyu Moon | System and Method for Modeling and Analyzing Data via Hierarchical Random Graphs | US9147273 | 09/29/2015 |
| Swarup Medasani, Suhas Chelian, Shinko Cheng, Rashmi Sundareswara, Howard Neely | Method and System for Embedding Visual Intelligence | US9129158 | 09/08/2015 |
| Yilu Zhang, Xinyu Du, Mutasim Slaman, Tsai-Ching Lu, David L. Allen, Shengbing Jiang | Method and Apparatus for Isolating A Fault in A Controller Area Network | US9110951B2 | 08/18/2015 |
| David Allen, Tsai-Ching Lu, Eric Tressler and Hankyu Moon | System and Method for Insider Threat Detection | US9043905 | 05/26/2015 |
| Michael Daily, Michael Howard, Yang Chen, David Payton and Rashmi Sundareswara | Recall System Using Spiking Neuron Networks | US9020870 | 04/28/2015 |
| Ryan Compton, Hankyu Moon, Tsai-Ching Lu | Catastrophe Prediction via Estimated Network Autocorrelation | US9020875 | 04/28/2015 |
| Suhas Chelian, Rashmi Sundareswara, Heiko Hoffman | Robotic Visual Perception System | US9002098 | 04/07/2015 |
| Tsai-Ching Lu, Hankyu Moon, David L. Allen | Explosive Network Attack and Mitigation Strategies | US8997224 | 03/31/2015 |
| Kyungnam Kim, Shankar R. Rao, Yuri Owechko, Swarup Medasani, Michael Cao, Jiejun Xu | Three-Dimensional Object Detection and Multi-Agent Behavior Recognition using 3D Motion Data | US8948501B1 | 02/03/2015 |
| Yang Chen, David L. Allen, Qin Jiang, Yuri Owechko, Tsai-Ching Lu | A Hierarchical Video Search and Recognition System | US8874584 | 10/28/2014 |
| Rashmi Sundareswara, Narayan Srinivasa | System for Three Dimensional Object Recognition and Foreground Extraction | US8774504 | 07/08/2014 |
| Michael Daily, Michael Howard, Yang Chen, Rashmi Sundareswara, David Payton | System for Representing, Storing and Reconstructing an Input Signal | US8756183 | 06/17/2014 |
| Zhang Z., Kim K., Xu, J., Owechok, Y. and Chen H-W. | Sensor Fusion Using Detector Confidence Boosting | US9183459 | 05/06/2014 |
| Tsai-Ching Lu, Yilu Zhang, Alejandro Nijamkin, David L. Allen, Hankyu Moon, Mutasim A. Salman | System and Methods for Fault-Isolation and Fault-Mitigation based on Network Modeling | US8577663 | 11/05/2013 |
| Swarup Medasani, Yuri Owechko, Tsai-Ching Lu, Deepak Khosla, David Allen | Method and System for Directed Area Search Using Cognitive Swarm Vision and Cognitive Bayesian Reasoning | US8213709 | 07/03/2012 |
| Wojtek Przytula, Tsai-Ching Lu | Method for Developing Probabilistic Models | US7739213 | 06/15/2010 |
News
Press Releases
Media Coverage
02/21/2018 | Work the Crowd: How Ordinary People Can Predict the Future
01/30/2018 | DARPA adds network-analysis tools to its antiterrorism arsenal
Events
Past Events
December 15, 2021 | Virtual Conference
GTA³ 2021: The 5th workshop on Graph Techniques for Adversarial Activity Analytics
December 10, 2020 | Atlanta, GA
GTA³ 4.0: The 4th workshop on Graph Techniques for Adversarial Activity Analytics
December 9, 2019 | Westin Bonaventure - Los Angeles, CA
GTA³ 3.0: The 3rd workshop on Graph Techniques for Adversarial Activity Analytics
December 10, 2018 | The Westin - Seattle, WA
GTA³ 2.0: The 2nd workshop on Graph Techniques for Adversarial Activity Analytics
August 23-24, 2018 | HRL Laboratories - Malibu, CA
Workshop on Human Machine Systems
February 9th, 2018 | The Ritz-Carlton Hotel - Marina Del Rey, CA
GTA³ 2018: Workshop on Graph Techniques for Adversarial Activity Analytics
Current Openings for CCNI
Contact
Email: tlu[at]hrl.com
Dr. Tsai-Ching Lu
Senior Research Scientist,
Leader, Center for Computational Network Intelligence
Information and Systems Sciences Lab
HRL Laboratories, LLC
3011 Malibu Canyon Road
Malibu, CA 90265
USA
