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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.


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

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.

Network Alignment Demo

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  • 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

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.

SmartNet Demo

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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.

Info Dynamics Demo

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  • 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%).


David Huber

Samuel Johnson

Kyungnam (Ken) Kim

Soheil Kolouri

Kangyu Ni

Nigel Stepp

Ryan Uhlenbrock

Alex Waagen

Jiejun Xu


Journals (15)

Authors Title Publication Year
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
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
Deepak Khosla, Yang Chen, Kyungnam Kim A Neuromorphic System for Video Object Recognition Frontiers in Computational Neuroscience 2014
Kang-Yu Ni and Tsai-Ching Lu Information Dynamic Spectrum Characterizes System Instability toward Critical Transitions EPJ Data Science, 3:28 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
Jiejun Xu, Vignesh Jagadeesh, B. S. Manjunath Multi-Label Learning With Fused Multimodal Bi-Relational Graph IEEE Transactions on Multimedia 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
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

Conferences (50)

Members Topic Conference Year
Kolouri, S., Rostami, M., Owechko, Y., Kim, K. Joint Dictionaries for Zero-Shot Learning AAAI 2018
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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

Patents (38)

Authors Title Patent # Date
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
Sofia Apreleva, Tsai-Ching Lu System and Method for Predicting Significant Events Using Progress Curve Model US9613309 04/04/2017
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
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 11/02/2016
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
Rashmi Sundareswara, Narayan Srinivasa System for three-dimensional object recognition and foreground extraction US9220070 12/29/2015
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
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
David Allen, Tsai-Ching Lu, Eric Tressler and Hankyu Moon System and Method for Insider Threat Detection US9043905 05/26/2015
Ryan Compton, Hankyu Moon, Tsai-Ching Lu Catastrophe Prediction via Estimated Network Autocorrelation US9020875 04/28/2015
Michael Daily, Michael Howard, Yang Chen, David Payton and Rashmi Sundareswara Recall System Using Spiking Neuron Networks US9020870 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 and 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
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 WO20140309031A1 05/13/2014
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



Past Events

February 9th, 2018

GTA³ 2018: Workshop on Graph Techniques for Adversarial Activity Analytics

Current Openings for CCNI

|Post Doc Research Staff, Social Systems
|Post Doc Research Staff, System Health Intelligence
|Summer Intern in Graph Computing
|Summer Intern in Social Computing Intelligence
|Summer Intern in Causal Discovery and Inference
|Summer Intern in Adversarial Machine Learning
|Summer Intern in Algorithmic Game Theory and Mechanism Design


Email: tlu[at]

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