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Recent Grants


Title: "Education and Workforce Training for Artificial Intelligence in Criminal Activity Recognition: Computing and Criminology Perspectives"

This project discusses the two-fold nature of the research, focusing on understanding how criminals might exploit AI for criminal activities and utilizing AI to detect and combat criminal behavior. It emphasizes the urgency of offering advanced education and workforce development in the field of homeland security to address emerging threats, especially in the realm of cybercrimes facilitated by AI. The project aims to provide state-of-the-art training to deal with existing criminal activities and to recognize and counter AI-driven cybercrimes. To address these challenges, the project outlines the development of educational modules and certificate programs that cover topics such as analytics for criminal investigations, computer vision for identifying illegal activities, natural language processing in crime investigations, and the integration of criminology perspectives with AI investigations. The objective is to equip students, practitioners, and law enforcement personnel with the knowledge and skills required to comprehend and confront AI-enabled criminal activities. By leveraging technologies like GIS crime mapping and computer vision, law enforcement can predict crime patterns and trends more effectively, ultimately enhancing public safety.

Funding Agency: U.S. Department of Homeland Security (DHS)
$99,500; 11/2023-10/2024; Dr. Ahmed Imteaj (SoC).

Title: "Artificial Intelligence for Greener Livestock: Educational and Research"

The goals of this two-years project are to applying artificial intelligence technologies in the field of animal science to estimate the methane emission on a large livestock production farm. Therefore, this project will conduct a number of experiments in lab and field to develop a low cost and a highly efficient system that will be able to monitor and measure methane emission on a larger scale throughout developing computer vision and deep learning techniques. The results of this project will be used for promoting greener livestock and disseminated in a straightforward way to livestock workers through conducting workshop and accessible website.

Funding Agency: U.S. Department of Agriculture (National Institute of Food and Agriculture).
$149,960; 06/2022-5/2024; Dr. Khaled Ahmed (PI, SoC), Dr. Amer Abu Ghazaleh (co-PI, SoAS)

Title: "RAPID: A Testbed for Experimenting with Industrial IoT and Cybersecurity Integration in Small Manufacturing"

The goals of this project are to study ways to enhance resilience and sustainability for small and medium-sized manufacturers in Southern Illinois. This grant will create a testbed at SIU called the Resilient, Adaptive Production leveraging IoT Disruptions (RAPID) Testbed. It will examine industrial IoT, a new concept in fully connected, transparent, automated and intelligent factory setup aimed at improving manufacturing processes and efficiency. The project would allow small and mid-size manufacturers in Southern Illinois to utilize a “sandbox” when exploring the integration of smart manufacturing in their own companies.  Ultimately, the testbed will be a resource for supporting the security and resilience of small and medium manufacturers, especially in the Southern Illinois region while enabling them to be agile in adapting to changes as they transition to smart manufacturing.

Funding Agency: Illinois Manufacturing Excellence Center, National Institute of Standards and Technology (NIST)
$99,102; 06/2022-11/2022; Dr. Kanchan Mandal (PI, MAME), Dr. Sajedul Talukder (co-PI, SoC), Dr. Koushik Sinha (co-PI, SoC).

Title: "A Framework to Defend Against Sockpuppet Connection Requests in Social Networks"

This project will build a digital framework rooted in cognitive psychology, UX research, and machine learning methods to defend against sockpuppet connection requests in online social networks. In a first research thrust, the researchers will develop survey instruments and user studies to investigate pending connection decisions, motivations, and behaviors in OSNs. The findings from this research thrust will be utilized to develop the next thrust, where the researchers will implement a "spam connection" folder through a pending connection decision classifier. Finally, the researchers will develop a novel Online Social Network Pending Connection Processing Interface. This will be designed as a layer on top of existing social networks that can be used to administer and assess educational and interface interventions around sockpuppets in the context of real social networks, while allowing the research team to address ethical and legal considerations of working with sockpuppet connections and people's private data. Together, this work will both enhance the understanding of just-in-time motivations and behaviors related to social network risks and help sociologists gain deeper insights from underexplored social and spatial dimensions provided by social networks to test relevant theories.

Funding Agency: National Science Foundation (NSF)
$157,888; 2022-2024; Dr. Sajedul Talukder (PI, SoC).

Title: "SAFHIRE: A Model for Bridging Digital Inequality in the Southern Economic Development Region of Illinois"

The goals of this one-year project are to develop a Sustainable, Affordable, High-Impact and Reliable Ecosystem (SAFHIRE) model to dramatically improve broadband access/adoption in Jackson County and establish a pathway to replicate this model across the nineteen-county southern Illinois region. SAFHIRE was one of just four Broadband Regional Engagement for Adoption and Digital Equity (READY) planning grants from the Illinois Department of Commerce & Economic Opportunity (IDCEO) to develop models for expansion of high-speed broadband Internet access across the State of Illinois.

Funding Agency: Illinois Department of Commerce & Economic Opportunity (IDCEO)
$50,000; 2021-2022; Dr. Liu (co-PI) and (PI) Dr. Koushik Sinha, in collaboration with the SIU Research Park.

Title: "Surveying SARS-CoV-2 Genomes and Public Data in Near Real-Time for Pandemic Response in Chicago"

The goal of the project will be to create a ‘one-stop-shop’ data and analytics infrastructure for storing, integrating, analyzing, and visualizing multiple types of epidemiological data. This project is designed to significantly improve our understanding of the COVID-19 pandemic in Chicago and immediately boost our ability to make and evaluate public health policies. Mapping the diversity of mutations that the virus acquires will provide critical insight into better vaccine development and our tools can be used to evaluate the success of future vaccines as they are deployed. Dr. Sinha's role in the project will be to create a custom visualization and data-analytics platform called COVID-19 Data Map (CoVD-Map).

Funding Agency: Walter Foundation
$499,533; 2020-2021; (co-PI) Dr. Koushik Sinha, Keith Gagnon (co-PI) and Matthew Trunnell (PI).

Title: "Virus Contact Map (VCM): A Privacy-Preserving Platform for Modeling and Predicting the Spread and Impact of COVID-19"

The COVID-19 pandemic is catalyzing the innovation of our privacy-preserving, data-driven Virus Contact Map (VCM) public-health surveillance platform to provide government and health officials, researchers, and the general public a powerful tool to fight COVID-19 and future infectious diseases. Through its unique architecture and features, VCM will be designed to provide situational awareness and arrest the spread of infectious diseases such as COVID-19 through contact tracing. Using practical deployment and early prototypes for COVID-19 scenarios as well as with synthetic datasets generated from actual data samples, this project’s goal is to develop VCM in consonance with CDC’s vision on future of public-health surveillance.

Funding Agency: SIU Foundation
$14,157; 2020-2021; (PI) Dr. Koushik Sinha.

Title: "Enhancing High-resolution Terrain Data Model for Improving the Delineation of Multi-scale Hydrological Connectivity"

The project is to establish a novel geospatial and hydrological modeling approach for improving the delineation of hydrologic connectivity using deep learning. This research will improve the characterization of hydrologic features and their connectivity at multiple scales by designing a geospatial artificial intelligence-hydrological modeling framework.

Funding Agency: National Science Foundation (NSF)
$170,718; 2020-2022; Dr. Ruopu Li, Dr. Banafsheh Rekabdar, Dr. Guangxing Wang.

Title: "Establishing Cybersecurity Digital Forensics Laboratory at SIUC"

We used the bulk of the funds ($8046.05) to purchase the workstations referred in the proposal. These workstations are in our computer laboratory and are intended to be used in support of computer security courses that use the unique workstation capabilities. Given the pandemic and the covis-19 virus concerns, the current workstation access is strictly limited. When we return to an environment that is safer and fully consistent with university guidelines, we will increase access to these workstations.

Funding Agency: SIU Foundation
$9,798; 2020-2022; (PI) Dr. Henry Hexmoor.

Title: "Structures and Catalytic Mechanisms of Cas13b and Potentially Related Cas9"

CRISPR-based technologies have revolutionized biochemical and biomedical research. In the past few years, many CRISPR systems have been discovered and characterized. These CRISPR systems greatly expand the CRISPR toolkit. Cas13b is the most recently identified CRISPR system. The usefulness of the Cas13b system as a gene editing tool has been demonstrated in human cells. Cas13b system can be exploited to achieve not only RNA knockdown, but also highly specific and efficient RNA editing. The RNA editing ability of the Cas13b- based technology has been used for the correction of human disease relevant mutations. Despite the rapid progresses of Cas13b research, little is known about the structures and catalytic mechanisms of this important family of CRISPR enzymes. The overall goal of this proposed study is to fill this knowledge gap. A cross-disciplinary research approach is employed in the study. Methods from the fields of bioinformatics, biochemistry, structural biology, and molecular & cellular biology are used to characterize the Cas13b CRISPR systems. Results from the study will reveal the molecular basis of the enzymatic reactions catalyzed by Cas13b enzymes. The gained knowledge will benefit further development of Cas13b CRISPR tools for basic research, diagnostic, and medical applications.

Funding Agency: National Institutes of Health (NIH)
$442,300; 2018-2021; (Investigators) Dr. Zhihua Du, Dr. Xiaolan Huang.

Title: "Big Data Analytic for Healthcare"

The objective of this research work is to study a wide range of possibilities to develop and/or adopt methodologies for healthcare-related big data analysis that meets current and future needs of Envision Health. We will adopt a four step approach to reach this objective including concept study and statement, road map proposal, methodology, and test-bed deployment. The outcomes of this work will be used to establish a long term collaboration between Southern Illinois University and Envision Health to develop and implement a comprehensive big data analytics center that would be supported financially by Envision Health to provide cutting age contribution to big data analytics in healthcare and more specifically in Envision Health.

Funding Agency: Envision Health
$109,000; 2015-2017; (PI) Dr. Shahram Rahimi.

Title: "Privacy-Preserving Data Collection and Access for IEEE 802.11s-Based Smart Grid Applications"

The modernized Smart Grid (SG) is expected to enable several new applications such as dynamic pricing, demand response and fraud detection; however, collection of such fine-grained data raises privacy issues. This project aims to design and implement several novel mechanisms for securing data collection and communication in SG Advanced Metering Infrastructure applications while preserving user privacy when the data are to be accessed. The underlying communication infrastructure, namely Neighborhood Area Networks, is to be built with wireless mesh networks using the IEEE 802.11s, an IEEE 802.11 amendment for mesh networking. The project investigates user privacy preservation mechanisms using partially and fully homomorphic encryption during data collection in the Neighborhood Area Networks. For the collected data at the data repository, attribute-based access control mechanisms are studied. As part of these access control mechanisms, novel scalable key establishment and group key management schemes are investigated. A testbed consisting of IEEE 802.11 Linux routers is part of the project to assess the overhead of privacy mechanisms under quality of service constraints. 

Funding Agency: National Science Foundation (NSF)
$298,112; 2013-2016; (PI) Dr. Kemal Akkaya.

Title: "Pattern Learning in a Minimax Framework"

The research objective of this award is to establish necessary theory and methods for reliable pattern learning that explicitly account for uncertainty. It will extract useful patterns, provide more reliable predictions, and significantly enhance various applications for discovering knowledge in large-scale data. Deliverables include new theoretical derivations and computational methods, research reports and publications, and education of undergraduate and graduate students. This project is funded by National Science Foundation.

Funding Agency: National Science Foundation (NSF)
$254,661; 2012-2015; (PI) Dr. Qiang Cheng.

Title: "A Bayesian Approach for Modeling and Simulation of Non-Stationary Ground Motions"

The research objective of this award is to develop a probabilistic ground motion model that takes into account the time-varying characteristics of earthquake ground motions to better describe their damage potential. This research will result in new methodologies to identify the most relevant seismological features affecting the severity of ground motions, to describe the manner in which seismic energy is distributed in the joint time-frequency domain and to quantify the prediction uncertainty in a unified and structured manner. The research approach is to use a combination of signal processing, feature selection, and machine learning tools that will be customized for ground motions. Deliverables include new methodologies and software tools for analysis and simulation of ground motions, research reports and publications, and education of undergraduate and graduate students. This project is funded by National Science Foundation.

Funding Agency: National Science Foundation (NSF)
$269,027; 2011-2014; (PI) Dr. Jale Tezcan, (Co-PI) Dr. Qiang Cheng.

Title: "Federating Disjoint Wireless Sensor Networks"

In this project, federating segments of a structurally damaged WSN or linking multiple standalone WSNs with the least resources and overhead is investigated. While segments are formed as a result of large scale damage involving many sensors, multiple standalone WSNs can be operated by different agencies for various purposes. The objectives of this project are to develop novel solutions for various aspects and contexts of federation problems for WSNs, to create a prototype for validation and to share the results with application designers.
The technical approaches pursued for rapid federation of disjoint WSNs consider the availability of resources such as mobile sensors, mobile and static gateways and their count. Both optimal and heuristic solutions for repositioning of mobile sensors and placement of mobile gateways are studied to establish connectivity as well as achieving some desired performance (i.e., QoS). Finally, the results are validated via a real test-bed consisting of sensors and mobile robots. This project is funded by National Science Foundation.

Funding Agency: National Science Foundation (NSF)
$191,878; 2010-2013; Dr. Kemal Akkaya.

Title: "Intelligent Database Agents for Geospatial Knowledge Integration and Management: Phase I"

The objective of the proposed research is to develop autonomous updating methodologies to provide for the collection and integration of geospatial data from multiple sources, including web-based repositories, into a single database system for subsequent access and retrieval. Autonomous updating subsumes several research issues that must be resolved for a successful system implementation. Among these are integration of heterogeneous geospatial data types, resolution of multiple representations (conflation) and data validation. In summary, there are currently no available capabilities for automatically and intelligently: (1) determining available network-based digital geospatial data resources, (2) integrating the various geospatial data formats into a single database schema, (3) validating data quality, and (4) conflating multiple representations. To address these deficiencies, we propose the use of intelligent mobile agents as the primary mechanism for data identification and collection, integration (including conflation) and quality monitoring. This project is funded by G. I. Tech.

Funding Agency: G. I. Tech
$37,800; 2010; Dr. Shahram Rahimi.

Title: "Towards a Scalable and Adaptive Application Support Platform for Large-Scale Distributed E-Sciences in High-Performance Network Environments"

This proposal develops a generic distributed computing platform to support large-scale collaborative scientific applications in high-performance networks. On this platform, scientists can conveniently launch and control distributed computing tasks with workflows as complex as directed acyclic graphs or as simple as linear pipelines in heterogeneous environments with guaranteed end-to-end performance. This project is funded by the U.S. Department of Energy.

Funding Agency: U.S. Department of Energy (DOE)
$389,398; 2009-2012; Dr. Mengxia Zhu.

Title: "II-NEW: Southern Illinois HPC Infrastructure (SIHPCI)"

This project involves the building of a high-performance computing (HPC) infrastructure at Southern Illinois University Carbondale (SIHPSI-Southern Illinois HPC Infrastructure), a facility first-of-its-kind not only within the campus but in the greater Southern Illinois region also. High-performance computing refers to the use of supercomputers and/or computer clusters to accelerate the solution of fundamental problems in science, engineering and business that have broad economic and scientific impact. SIHPCI will initially consist of a 110 nodes Linux cluster with Intel Xeon dual CPU quad-core 2.3 GHz processors, 6 GB RAM, and 90 TB data storage facility. Dr. Cheng will conduct research for utilizing massive data and high computing power to enable precise and personalized medicine. This project is funded by NSF Division of Computer and Network Systems.

Funding Agency: National Science Foundation (NSF)
$360,779; 2009; PI: Shaikh S. Ahmed (ECE), Co-PI: Tonny Oyana (Geography), Mesfin Tsige (Physics), Qiang Cheng (Computer Science), Mark Byrd (Physics).

Title: "Agent-based Man on the Loop Extensions"

This project is actually a technical and implementation extension to previous “Distributed Computational Monitoring and Steering System” project. This work involves connecting the current remote steering system to the experimental 10Gbps extensions to DOE UltraSceince Net (USN). A system demonstration is planned at Supercomputing 2007 conference site to show the cutting-edge technologies. This project is funded by Oak Ridge National Laboratory, a world-leading research institute under the U.S. Department of Energy.

Funding Agency: U.S. Department of Energy (DOE)
$15,000; 2007-2008; Dr. Mengxia Zhu.

Title: "Agent-based methods for Intelligence, Surveillance, and Reconnaissance "

The goal of this project is to develop a novel framework for human control of a robot community; it will produce "natural" human-machine techniques and protocols. Human control of a robot community will advance the net-centric warfare paradigm sought in the U.S. Department of Defense.   This project is funded by an Air Force Research Laboratory subcontract from Sierra Nevada Corporation. 

Funding Agency: Nevada Corporation
$35,000; 2006-2007; Dr. Henry Hexmoor.

Title: "Distributed Computational Monitoring and Steering Systems"

This project propose an efficient distributed computational monitoring and steering system, which optimizes the utilizations of distributed resources for maximal frame rate and minimal total delay. This system couples areas including numerical modeling, high performance computing, advanced visualization, high-speed communications, and virtual environments. This project is funded by Oak Ridge National Laboratory, a world-leading research institute under the U.S. Department of Energy

Funding Agency: U.S. Department of Energy (DOE)
$50,362; 2006-2007; Dr. Mengxia Zhu.

Title: "Enhancing Software Development through Communication, Collaboration and Team Building with TabletPCs"

Modern software engineering recognizes the value of communications and other social aspects of software development. Traditional computer science curricula have emphasized only the technical aspects of software development leaving students on their own to discover responsible team and collaboration skills.  This project, supported by an HP Technology for Teaching Grant, explores how new technology (wireless Tablet PCs) can be used to enhance software development education by supporting learning experiences which address skills in communication, collaboration and team building. 

Funding Agency: HP Technology
$69,000; 2006-2007; Dr. Michael Wainer.

Title: "Clinical Decision Support System for Early Prediction of Obesity in Children"

The goal of this project is to design and implement an intelligent system that aids in the prediction and early detection of childhood obesity in the school system, with the hope of implementing a meaningful, cost efficient intervention mechanism.

Funding Agency: Southern Illinois Healthcare
$33,800; 2006; Dr. Shahram Rahimi.

Title: "Terahertz Optical A/D Converter"

The goal of this project is to investigate an optical architecture based on a delta-sigma modulator with a potential to approach the terahertz A/D conversion rate. Fast and reliable A/D converters are needed for sampling of high-speed RF signals.

Funding Agency: U.S. Navy, Office of Naval Research
$500,000; 2006-2009; Dr. Mohammad Sayeh.

Title: "Practical Quantum Error Prevention Protocols Involving Quantum Systems With More Than Two Orthogonal States"

The goal of the proposed project is to develop a model of computation based on higher-dimensional quantum systems, i.e., those with more than two states, and also develop associated quantum error prevention protocols which combine the known methods of error protection. The main goal is to overcome the obstacles presented by noisy experiments in order to help develop a prototypical quantum computing device. The impact on science and society could be far-reaching since a quantum computer could solve several important problems more efficiently. In addition to problems in Computer Science, they could simulate quantum mechanical systems far more efficiently than the computers being used today. Such problems are found in Engineering, Chemistry, Biology and Physics. This could lead to better materials, nano-scale devices, pharmaceuticals and better ways in which to extract energy from nuclei.

Funding Agency: National Science Foundation (NSF), NSF Career
$400,000; 2006-2011; Dr. Mark Byrd.

Title:"Distributed Interpretation in a Communication Limited Environment"

The aim of this project is using a MAS testbed to develop empirical data that links the performance of various DPS strategies to different classes of sensor network problems. The goal is to identify useful classes of sensor network problems and build a library of DPS strategies that are appropriate for each. Much of the theoretical work has been based on the use of Decentralized Markov Decision Processes (DEC-MDPs) for modeling MAS problems and producing minimum communication coordination strategies. This work is currently being funded by its second grant from the National Science Foundation. 

Funding Agency: National Science Foundation (NSF)
$300,000; 2005-2008; Dr. Norman Carver.