As the Director of the Distributed Multimedia Information Systems Laboratory at SCIS,
Dr. Chen has worked with undergraduate and graduate students on the design, implementation, and maintenance of challenging, far-reaching, and community-centered projects.
Florida Public Hurricane Loss Model
Dr. Chen is the Co-PI and leader of the Computer Science Component of the Florida Public Hurricane Loss Model (FPHLM), a large-scale hurricane catastrophe model developed by a multi-disciplinary team of experts
in the fields of meteorology, wind and structural engineering, computer science, GIS, statistics, finance, and actuarial science. It is the first public hurricane loss model in the world.
The realization of this innovative project involves the close collaboration of multiple academic and scientific institutions, of which Florida International University is the leading institution.
The state of Florida ranks number one in total insured property value exposed to hurricane wind. Out of Florida's $3.6 trillion in insured properties, about $2 trillion are residential,
and all are exposed to hurricane risk. This reality gave birth to this project. Funded by the Florida Office of Insurance Regulation (FL OIR), the FPHLM was born out of the need of accurately
assessing hurricane wind risk and predicting insured losses for the Floridians' residential properties.
Since the release of its first version in March of 2006 (see press release), the model has been used over 3,450 times by the state and over 260 times by firms in the insurance industry.
As an open project, which undergoes a strict certification process every two years, the FPHLM provides the state regulators a reliable benchmark in the
homeowner insurance market and allows them to better formulate the state's homeowner insurance rate-making policy. The FPHLM's impact on the community is unquestionable,
as its predictions directly influence the home insurance rates payed by Floridians every month.
The model consists of three major components: wind hazard (meteorology), vulnerability (engineering), and insured loss cost (actuarial). It has over a dozen sub-components.
The computer platform is designed to accommodate future hookups of additional sub-components or enhancements.
The FPHLM estimates loss costs and probable maximum loss levels from hurricane events for personal lines and commercial lines of residential property.
The losses are estimated for building, appurtenant structures, contents, and additional living expenses.
In essence, the FPHLM is a complex collection of computer programs that simulate and predict how, where and when hurricanes form, their wind speeds, intensity and sizes, their tracks,
how they are affected by the terrain after landfall, how the winds interact with different types of structures, how much damage they can cause to house roofs, windows, doors, and interiors,
how much it will cost to rebuild the damaged parts, and how much of the loss will be paid by insurers.
Florida also ranks number one in coastal property exposed to storm surge. In the face of this reality, in 2013 the state funded FIU to enhance the FPHLM by
adding both a storm surge component and an inland flooding component.
The proposed new model will assess storm surge and hurricane-related rain flood risk and estimate both the insured and uninsured losses that they may cause.
The enhancement project will take three years with $4.5 million funding from the State.
Miami-Dade County is particularly susceptible to storm surges caused by hurricanes. To help Miami-Dade county residents understand the dangers of storm surge, hydrological and software development experts at FIU's
International Hurricane Research Center (IHRC) and College of Engineering and Computing (CEC) teamed up with
Miami-Dade County to create a Storm Surge Simulator, a web-based application that allows users to visualize the potential storm surge effects on their home or business.
Dr. Chen led the development team of Computer Science students to combine cutting-edge web technologies with storm surge modeling output in order to help the Miami-Dade community.
The result of the paper A Progressive Morphological Filter for Removing Non-Ground Measurements from Airborne LIDAR Data, authored by Dr. Chen and his colleagues
K. Zhang, D. Whitman, M.-L. Shyu, J. Yan, and C. Zhang, and published in IEEE Transactions on Geoscience and Remote Sensing, vol. 41, issue 4, pp. 872-882, April 2003,
was used by the official Miami-Dade County Storm Surge Simulator project. This paper has been cited 1182 times by Google Scholar.
The Storm Surge Simulator is available to the public at no charge. Click here to visit the Storm Surge Simulator.
3D Hurricane Storm Surge Animation and Visualization
Dr. Chen's work on 3D Hurricane Storm Surge animation has been used by NOAA's National Weather Service (NWS) Tampa Bay Area Office.
Demo videos of the project were showcased by the Tampa NWS at the following public outreach events:
Press conference at the Hillsborough County Emergency Operations Center (EOC) on May 14, 2010.
Hurricane Kickoff Meeting for Critical Employees of the Transportation Security Administration (TSA) at the Tampa International Airport.
Meteorologist in Charge of the NWS Tampa Office, Brian LaMarre's presentation at the Florida Governor's Hurricane Conference.
Briefing to Tampa Mayor on May 17, 2010 by Brian LaMarre.
Tampa Hurricane Exercise for Senior Leadership on June 1, 2010 by Daniel Noah (Warning Coordination Meteorologist, Tampa NWS).
University of Tampa Emergency Preparedness meeting on June 2, 2010 by Daniel Noah
For his work on the project, Dr. Chen has received several appreciation e-mails from NOAA's NWS Tampa Bay Area Weather Forecast Office and the Storm Surge Group at NOAA:
On behalf of the NWS Tampa Bay Area Weather Forecast Office - a huge thank you! The video will be an excellent complement to our active outreach
program in support of hurricane preparedness focused on storm surge impacts. The video will enable our audiences to see first hand some of the related
impacts we have been educating them on for years.
The visual nature of [the video] describing surge resonated with the audience.
Thanks so much for your ongoing support and willingness to work with us toward the development of a new outreach tool.
K. Zhang, S.-C. Chen, P. Singh, K. Saleem, and N. Zhao, A 3D Visualization System for Hurricane Storm Surge Flooding, IEEE Computer Graphics and Applications, vol. 26, issue 1, pp. 18-25, Jan.-Feb. 2006.
Keqi Zhang, Jianhua Yan, and Shu-Ching Chen, Automatic Construction of Building Footprints from Airborne LIDAR Data, IEEE Transactions on Geoscience and Remote Sensing, vol. 44, issue 9, pp. 2523-2533, September 2006. (This paper has been cited 308 times by Google Scholar.)
Jianhua Yan, Keqi Zhang, Chengcui Zhang, Shu-Ching Chen and Giri Narasimhan, Automatic Construction of 3D Building Model From Airborne LIDAR Data Through 2D Snake Algorithm, IEEE Transactions on Geoscience and Remote Sensing, Volume 53, Issue 1, pp. 3-14, January 2015.
Maria E. Presa Reyes and Shu-Ching Chen, A 3D Virtual Environment for Storm Surge Flooding Animation, The Third IEEE International Conference on Multimedia Big Data (IEEE BigMM 2017), Laguna Hills, California, USA, pp. 244-245, April 19-21, 2017. (Demo paper)
For a demo of the project, play the videos below.
3D Hurricane Storm Surge Animation and Visualization Key Biscayne Demo
3D Hurricane Storm Surge Animation and Visualization Miami Beach Demo
3D Hurricane Storm Surge Animation and Visualization Tampa Demo
3D Hurricane Storm Surge Animation and Visualization Miami Beach Demo (2018)
Multimedia-Aided Disaster Information Integration System
Thanks to the availability of mobile devices, emergency responders, supporting agencies and even private citizens can capture imagery of disaster events as they unfold.
Once the crisis is contained, however, it's a daunting task for emergency managers to collect, organize and integrate disaster event data from multiple sources into incidence command systems
where situation reports, incidence action plans, etc. are being held. Therefore, Dr. Chen's group has developed a semi-autonomous system, the Multimedia-Aided Disaster Information Integration System
(MADIS), that uses advanced data integration and visual analysis techniques to associate temporal, spatial and other textual features of a disaster event situation report with event images
and related text annotations.
The system is developed on Apple's mobile operating system (iOS) and runs on iPad tablets, and it is evaluated by domain experts from the local emergency management
department. By interacting with the Miami-Dade Emergency Management (MDEM) personnel through evaluation and exercise activities, the system is constantly being updated by improving user
interface experience and back-end support techniques. Feedback from our collaborative partners at MDEM and the potential users suggests that our system will be very useful for emergency
managers to gain insight of the situation at the actual disaster scene and to respond swiftly. It is also encouraged to further develop the system into an operational pilot and promote the
commercialization of the system for benefiting the whole Emergency Management community.
The system, developed as part of the project A Data Mining Framework for Enhancing Emergency Response Situation Reports with Multi-Agency, Multi-Partner, Multimedia Data, received
funding from the Visual Analytics for Command, Control, and Interoperability Environments (VACCINE), the Department of
Homeland Security's (DHS) Center of Excellence in Visual and Data Analytics, which was established in July of 2009.
For a demo of the project, play the video below.
Multimedia-Aided Disaster Information Integration System Demo
Business Continuity Information Network
Dr. Chen's Business Continuity Information Network (BCIN) project is the first web-based Public-Private Partnership tool that helps the County Business Recovery Program communicate,
share information, and collaborate on disaster events with the private sector.
By tracking the status of critical services over multiple counties, the BCIN helps businesses to better assess the impact of a disaster on the community and find resources
to recover faster after a disaster. Additionally, it provides a gathering place for businesses to report on the available resources (products/services) they can provide,
and helps county partners collect damage report data from county and company sources in order to understand the amount of damage in the business community immediately after a disaster event.
The role of the BCIN in the success of businesses is invaluable. Studies show that about 40% of the companies that closed for three
or more days as a result of a hurricane failed within 36 months. If the BCIN helped 5% of the companies in South Florida to speed up their hurricane recovery by one week,
it would prevent $220 million of non-property economic losses that would result from that week's closure.
Many businesses have already joined the Network. Some of the participating businesses are listed below:
Florida International University
American Airlines
Aon Corporation
AT&T
Bank of America
Baptist Health South Florida
Becker & Poliakoff
Carnival Cruise Lines
Caterpillar
ClearChannel Communications
Crowley
Exeter Architectural Products
Florida Public Health Institute
Florida Power and Light
Greyhound Lines
IBM
Home Depot
Hurricane Protection Industries
Insurance Information Institute
City Bank
Beckman Coulter
Greater Miami Convention & Visitor Bureau
U.S. Century Bank
Miami River Marine Group
Greater Miami Chamber of Commerce
Macy's Florida
Miami Christian School
Miami Dade College
Miami International Airport
Office Depot
Publix Supermarkets
Ryder Systems
T-Mobile
Target Stores
Terremark
Trane
United States Postal Service
UPS
URS Corporation
Visa
Wal-Mart
Wachovia Bank
WFOR-CBS-4
Winn-Dixie
ABN AMRO
American National Bank
BAC Florida Bank
Banco Popular
Bank First
Bank United
City National Bank of Florida
Commerce Bank, N.A.
Executive National Bank
Fidelity Federal Bank & Trust
Intercredit Bank, N.A.
International Bank of Miami, N.A.
Mellon
Mesirow Financial
Northern Trust, N.A.
Ocean Bank
Regent Bank
Sun American Bank
Third Federal Savings
Tropical Financial Credit Union
Total Bank
Transatlantic Bank
Union Credit Bank
Since its release, the BCIN has been actively used in many community activities, some of which are listed below:
Hurricane exercise by using BCIN
2008
Joint county exercises in March and May with partners
Activated in Miami-Dade for Fay, Gustav, and Ike
2009
Miami-Dade EM Business Recovery Desk
Florida Statewide Hurricane Suitor Training Exercise
UASI Operation Cassandra
Miami-Dade EM Business Recovery Program Training
2010
Private-Public Partnership in Palm Beach County
Statewide Hurricane Exercise
Expanded company exercise
Focus on mobile platform
2011
Florida Statewide Hurricane Griffin Exercise, Palm Beach County Emergency Management BCIN training and Exercise for the Business & Industry Desk Operations
South Florida Disaster Management Symposium -- Miami-Dade, Browad, Palm Beach and Monroe County Organized by The South Florida Business Resiliency Consortium (SFBRC), SFBRC support BCIN as its information tool.
2013-2014
Steve Detwiler was hired as the new business recovery manager at Miami Dade Emergency Management after almost two years of the position being vacant.
The Business Recovery Program meet in 2013 to discuss activities leading into the 2014 hurricane season.
A table top exercise which will involve BCIN is being planned either to coincide with the 2014 Hurricane Exercise or as an independent activity.
BCIN training will occur with MDEM at the end of March 2014.
Dr. Chen has received multiple recognitions as his role has been critical for the success of the BCIN.
The development and implementation of the Business Continuity Information Network (BCIN) has provided the [Miami-Dade County's Business Recovery] program with a key tool necessary
to carry out many of its critical functions including real-time data collection and gathering. BCIN is quickly becoming a nationally recognized information sharing tool
for use by public-private collaborative programs ... FIU's contribution to the success of Miami-Dade County's Business Recovery Program is truly immeasurable.
(Read recognition letter).
Part of a recognized Public-Private Partnership model by the FEMA Private Sector Office is available here.
New U.S.-Japan collaborations bring Big Data approaches to disaster response - NSF Press release 15-029 is available here. United States Senator Bill
Nelson's recognition letter to project PI, Dr. Tao Li, is available here. Dr. Chen is the Co-PI of this project.
Click here to visit the Business Continuity Information Network's public service.
Coordinated Damage Assessment Application
Dr. Chen's work on the Coordinated Damage Assessment Application (CDAA) is a reinterpretation of Miami-Dade County's SnapShot Damage Assessment Application.
The CDAA has been made available to the residents of Miami-Dade County, and has assisted in providing accurate situational awareness regarding the impact of a disaster as well as has helped emergency responders plan
an appropriate response and recovery.
The CDAA is composed of two components: a public page and a private administration web application, both of which were powered by an application called Snapshot, which was officially used by the Miami-Dade
Department of Emergency Management (DEM).
The CDAA is implemented with shared codebase to eliminate as much platform-specific code as possible, modularized code for organized and easily visualized application structure,
and lightweight frameworks to abstract several developmental processes. It provides support for assessing either online or offline via PCs, laptops, tablets, and smartphones, and provides
an aggregated view of the impact of the disaster.
The goals of this application are to leverage on the community's altruism, provide the community a role and leave them situationally aware, streamline impact assessments, rapidly gather disaster impact information,
and efficiently plan for a response and recovery.
From the community's point of view, the CDAA's main roles are to simplify the assessment process for the affected properties and to provide feasible channels for having assessments.
On the other hand, the CDAA is implemented for government officials to quickly update the assessment process and to support the ability to easily view and utilize aggregated impact results.
Affinity Hybrid Tree
In the paper Affinity Hybrid Tree: An Indexing Technique for Content-Based Image Retrieval in Multimedia Databases
published in Proceedings of the IEEE International Symposium on Multimedia (ISM2006), pp. 47-54, December 11-13, 2006, San Diego, CA, USA, Dr. Chen and his PhD student
Kasturi Chatterjee proposed the Affinity Hybrid Tree (AH-Tree), a novel indexing and access method to organize large image data sets efficiently and to support popular image access
mechanisms like Content-Based Image Retrieval (CBIR) by embedding the high-level semantic image-relationship in the access mechanism as it is.
The AH-Tree combines SpaceBased and Distance-Based indexing techniques to form a
hybrid structure that is efficient in terms of computational overhead and fairly accurate in producing query results close to human perception.
The proposed index structure solves the existing problems of introducing high-level image relationships in a retrieval mechanism without going through the pain of translating
the content-similarity measurement into feature-level equivalence and yet maintaining an efficient structure to organize the large sets of images.
The paper won the Best Paper Award.
Novel Anomaly Detection Scheme Based on Principal Component Classifier
In the paper A Novel Anomaly Detection Scheme Based on Principal Component Classifier, published in Proceedings of the IEEE Foundations and New Directions of Data Mining Workshop,
in conjunction with the Third IEEE International Conference on Data Mining (ICDM'03), pp. 172-179, November 19-22, 2003, Melbourne, Florida, USA., Dr. Chen and his colleagues Dr. Mei-Ling Shyu, Dr. Kanoksri Sarinnapakorn, and Dr. LiWu Chang,
proposed a novel scheme that uses robust principal component classifier in instrusion detection problems where the training data may be unsupervised.
Assuming that anomalies can be treated as outliers, they constructed an intrusion predictive model from the major and minor principal components of the normal instances. A measure of the difference of an anomaly from the
normal instance is the distance in the principal component space. In the paper, they showed that the distance based on the major components that account for 50% of the total variation and
the minor components whose eigenvalues are less than 0.20 work well.
They also showed that experiments with KDD Cup 1999 data demonstrated that the proposed method achieves 98.94% in recall and 97.89% in precision with the false alarm rate 0.92%, and outperforms the nearest neighbor method,
density-based local outliers (LOF) approach, and the outlier detection algorithm based on Canberra metric.
The paper has been cited 773 times by Google Scholar.
Use of a Subspace-Based Multimedia Data Mining Framework in Video Semantic Event/Concept Detection
In the paper Video Semantic Event/Concept Detection Using a Subspace-Based Multimedia Data Mining Framework, published in IEEE
Transactions on Multimedia, Special Issue on Multimedia Data Mining, Volume 10, Number 2, pp. 252-259, February 2008, Dr. Chen, together with his colleagues and students, proposed a subspace-based
multimedia data mining framework for video analysis, specifically video event/concept detection, by addressing two basic issues: semantic gap and rare event/concept detection.
The proposed framework achieves full automation via multimodal content analysis and intelligent integration of distance-based and rule-based data mining techniques. The content analysis process
facilitates the comprenhensive video analysis by extracting low-level and middle-level features from audio/visual channels. The integrated data mining techniques effectively address these two
basic issues by alleviating the class imbalance issue along the process, and by reconstructing and refining the feature dimension automatically.
The promising experimental peformance on goal/corner event detection and sports/commercials/building concepts extraction from soccer videos and TRECVID news collections demonstrates the effectiveness
of the proposed framework.
Additionally, the framework's unique domain-free characteristic indicates the great potential of extending it to a wide range of different application domains.
TRECVID Ad-hoc Video Search Competition
TRECVID is one of the most famous international video retrieval competitions, conducted by the National Institute of Standards and Technology (NIST), and has held a total of 15 competitions taking place annually since the year 2003. The Ad-hoc Video Search (AVS) task requests the participants to build a video retrieval system within a one-month period, capable of searching for thirty types of videos in a large-scale database. Each type of the videos is described by a query, such as "Find shots of a projection screen" and "Find shots of a truck standing still while a person is walking beside or in front of it."
In the proposed framework, the most recent advances in video processing and deep learning are utilized to understand the contents of the videos. The results outperformed those of several recognized research groups. The development of this system can potentially promote the search engine's capability to understand general descriptions of the video's content without relying on user-created text metadata.
The proposed work won the third place in TRECVID 2018 (AVS task). The FIU News article detailing this achivement can be found here.
Awards
Excellence in Fundamental Research Award, School of
Computing and Information Sciences, Florida
International University, 2017.
Director's Special Recognition Award, School of Computing and Information Sciences, Florida International University, 2016.
AAAS Fellow (2016).
Best paper Award, The 17th IEEE International Conference on Information Reuse and Integration (IRI 2016), Pittsburgh, PA, USA, July 28-30, 2016.
IEEE Fellow (2016) (through IEEE Computer Society, "For contributions to multimedia data and disaster information management")
Eminent Scholar Chaired Professor in Computer Science, School of Computing and Information Sciences, Florida International University, 2014-2017.
Excellence in Service Award, School of Computing and Information Sciences, Florida International University, 2014.
SIRI Outstanding Service Award, Society for Information Reuse and Integration, 2014.
Excellent in Research Award, School of Computing and Information Sciences, Florida International University, 2012.
2012 FIU Top Scholar Award.
2011 ACM Distinguished Scientist Award.
2011 FIU President's Council World Ahead Faculty Award, Finalist.
IEEE International Conference on Multimedia and Expo (ICME) 2011 Quality Reviewer.
2011 FIU Top Scholar Award.
2011 Kauffman Professor Award.
IBM Scalable Data Analytics Innovation Award, 2010.
Excellence in Mentorship Award, School of Computing and Information Sciences, Florida International University, 2010.
Outstanding Leadership Award, The 4th International Conference on Multimedia and Ubiquitous Engineering (MUE 2010), 2010.
SIRI Fellow, Society for Information Reuse and Integration in 2009 (Contributions to Multimedia Theory and the Development of Multimedia Applications and Outstanding Service to SIRI).
Best Paper Award, IEEE International Symposium on Multimedia (ISM2006), December 11-13, 2006, San Diego, CA, USA.
Most Active SMC Technical Committee Award, IEEE Systems, Man, and Cybernetics Society, October 2006.
The Inaugural Florida International University Excellence in Graduate Mentorship Award, 2006.
Excellence in Mentorship Award, School of Computing and Information Sciences, Florida International University, 2006.
Outstanding Contribution Award, IEEE Systems, Man, and Cybernetics Society, August 2005.
2004 Florida International University Outstanding Faculty Research Award.
Outstanding Faculty Service Award, School of Computer Science, Florida International University, 2004.
Outstanding Faculty Research Award, School of Computer Science, Florida International University, 2002.
Students
Achievements
Fausto Fleites
FIU Worlds Ahead Graduate, Summer 2014.
Outstanding Ph.D. Graduate Award, College of Engineering and Computing, FIU, 2014.
Greater Miami Chamber of Commerce's 2010 Technology Leaders Award in the category "Top Technology Student."
GAANN (Graduate Assistance in Areas of National Need) Fellowship, U.S. Department of Education.
The Outstanding Graduate Award for Undergraduate Study, FIU, 2009.
Diana Machado
Summa Cum Laude Graduate, FIU, 2014.
Outstanding Undergraduate Student Award, College of Engineering and Computing, FIU, 2014.
Raul Garcia
Magna Cum Laude Graduate, FIU, 2014.
Outstanding Undergraduate Student Award, School of Computing and Information Sciences, FIU, 2013.
Hsin-Yu Ha
People's Choice award, EPA P3 event (P3: People, Prosperity, and the Planet Student Design Competition for Sustainability), US Science and Engineering Festival (USA SEF).
Chengcui Zhang
The Best Graduate Student Research Award, School of Computer Science, FIU, 2002.
Presidential Fellowship, School of Computing and Information Sciences, FIU, 2000-2003.
Min Chen
Outstanding PhD Graduate, College of Engineering and Computing, FIU, 2007.
Deans Award, College of Engineering and Computing, FIU, 2007.
Presidential Fellowship, School of Computing and Information Sciences, FIU, 2004-2006.
The Outstanding Graduate GPA Award within the Field of Information and Technology, School of Computer Science, FIU, 2003.
The Best Graduate Student Research Award, School of Computer Science, FIU, 2004.
The Dissertation Year Fellowship, FIU, 2007.
Outstanding Academic Performance Award, School of Computing and Information Sciences, FIU, 2006.
Na Zhao
Presidential Fellowship, School of Computing and Information Sciences, FIU, 2007.
The Dissertation Year Fellowship, FIU, 2007.
Kasturi Chatterjee
Best Paper Award, IEEE International Symposium on Multimedia (ISM2006), December 11-13, 2006, San Diego, CA, USA.
Strategic Initiative Teaching Award, College of Engineering and Computing, FIU, 2007.
Excellence Award, School of Computing & Information Sciences, FIU, 2007-2008.
2008 Global CyberBridges Fellowship Award, NSF.
PIRE IBM Fellowship, 2008.
First Place in Poster Presentation, 6th LA Grid Summit, October 30-31, 2008.
The Dissertation Year Fellowship, FIU, 2009.
Li Zheng
The Best Graduate Student Research Award, School of Computing and Information Sciences, FIU, 2011.
Jairo Pava
Greater Miami Chamber of Commerce's 2011 Technology Leaders Award in the category "Top Technology Student".
FIU Honors College Summa Cum Laude Award - a prestigious annual award given to a graduating student who embodies the ideals of the Honors College.
CRA Outstanding Undergraduate Researcher Awards 2011 - Honorable Mention in the Computing Research.
2010 Outstanding Undergraduate Student Award, School of Computing and Information Sciences, FIU.
2011 SEAGEP Undergraduate Research Award, FIU.
FIU Worlds Ahead Graduate, Fall 2011.
Jesse Domack
Greater Miami Chamber of Commerce's 2013 Technology Leaders Award in the category "Top Technology Student".
CRA Outstanding Undergraduate Researcher Awards 2013 - Honorable Mention in the Computing Research.
Finalist, Greater Miami Chamber of Commerce's 2012 Technology Leaders Award in the category "Top Technology Student."
Distributed Biohazard Surveillance System and Apparatus for Adaptive Aerosol Collection and Synchronized Particulate Sampling, Stuart H. Rubin and Shu-Ching Chen, US Patent No. 7,082,369, Issue Date: July 25, 2006.