In this project, the student is expected to develop a MATLAB Graphical User Interface software toolkit that processes GPS data and outputs the position estimates on a Google Map (or similar) Throughout this process, the student will learn the basics of GPS positioning and converting the GPS raw measurements to position estimates, and utilize that in writing a user friendly interface and displays the results on a map. The student will also be exposed to processing Inertial Measurement Unit (IMU) data, and the theory behind it, which will be used to provide a robust localization output. The student is expected to run through the whole process from collecting the data to running the software and producing the mapped results.

Mentor: Dr. Samer Khanafseh

Institution: Illinois Institute of Technology

Necessary Skills: MATLAB, Basics of Basics of Linear Algebra (vector/matrix operations) 

Machine-learning based network intrusion detection systems (ML-NIDS) are increasingly popular in the fight against network attacks. In particular, promising detection results have been demonstrated in conjunction with Software-Defined Networks (SDN), in which the logically centralized control plane provides access to data from across the network. Hence, this project aims at building a novel intrusion detection and prevention system (IDPS) to thwart common SDN security issues (e.g., Denial of Service, Link Layer Discovery Protocol exploitation, etc.).

Mentor: Dr. Mohamed Rahouti

Institution: Fordham University

Necessary Skills: 

• basics of computer networking
• some knowledge in programming (e.g., Pyhton, C, or Java)
• basics of machine learning

In this project, the student(s) will work on the development of an open source software toolkit for modeling optical wireless communication (OWC) systems. This includes the development of basic signal processing blocks for modulation/demodulation schemes and the optical channel model. The students will work remotely with students at UMass Boston who will validate the toolkit with existing OWC hardware. The toolkit will be made openly available to the research community in order to assist researchers who are new to the field and/or interested in working on higher layer OWC research problems.

Mentor: Dr. Michael Rahaim

Institution: University of Massachusetts, Boston

Necessary Skills: 

• Basic programming experience (C++ and Python and/or Matlb/Simulink)
• Some knowledge of Linux and/or signal processing is preferred
• Prior use of source code management (e.g., Git) is also preferable

According to its website, GDELT “monitors the world's broadcast, print, and web news from nearly every corner of every country in over 100 languages and identifies the people, locations, organizations, themes, sources, emotions, counts, quotes, images and events driving our global society every second of every day.” Community resilience is defined as “a process linking a set of networked adaptive capacities to a positive trajectory of functioning and adaptation in constituent populations after a disturbance” (Norris et al, 2008). This process of adaptation by communities in response to stress has been modeled by Norris as a set of four networked resources or capacities – “Economic Development, Social Capital, Information and Communication, and Community Competence.” Kulig, Edge, Townshend, Lightfoot and Reimer (2013) also present a model of community resilience with the following three key factors: interactions as a collective unit, expressions of a sense of community and community action. Factors from both models can be developed and promoted in the context of library services to communities.

Mentor: Dr. Kimberly Black

Institution: Chicago State University

Necessary Skills: 

• Experience with or understanding of inferential statistics
• Experience with R using the RStudio environment (or possibly some other statistical analysis package) OR using GDELT Knowledge Graph
• Experience extracting large datasets from publicly available sources such as Google Big Query

Come up with a model to predict the ability of Artificial intelligence to replace a certain Profession. The expected model will take as input the types of tasks performed in a given profession. The model will produce as output the ability of Artificial intelligence to replace that profession, where it could be fully replaceable by AI, not replaceable, or partially replaceable with a possible percentage.

Mentor: Dr. Sufyan Almajali

Institution: Vertex International

Necessary Skills: 

• computer science/engineering or related background
• AI general understanding

IoT applications are becoming common nowadays with over 30 billion IoT devices in the market in 2020, and the number is expected to reach 70 billion devices by 2025. IoT Applications over edge computing architectures (ECAs) are gaining attention as edge computing provides IoT applications with the new abilities such as applications with minimum delay in communication, processing, and storage options near the end user of IoT devices. Nevertheless, providing the right ECA for a given IoT application is a challenging task. This research projects attempts to build a framework that represents all the elements involved in ECA design according to IoT application requirements.

Mentor: Dr. Sufyan Almajali

Institution: Vertex International

Necessary Skills: 

• computer science/engineering or related background
• AI general understanding

The purpose of this project is to expose students to the different aspects of smart homes security. Students will be introduced to the different components of smart homes networks and the vulnerabilities when it comes to network security. Students will work with TERT faculty on identifying the key vulnerabilities and what is takes to secure smart homes. This project involves Internet and library research as well as implementing proof-of-concept experiments. .

Mentor: Dr. Moussa Ayyash

Email: mayyash@csu.edu

Institution: Chicago State University

Necessary Skills: 

• Access to internet

Data science is a growing research field. Student researcher will identify a data science field from a multitude of areas (environment, healthcare, sports, computing, etc.) Student will formulate a research question in his/her data science area.

Mentor: Dr. Moussa Ayyash

Institution: Chicago State University

Necessary Skills: 

• Access to internet

Cognitive radio (CR) is an important field in wireless communications. CR offers an intelligent solution for spectrum scarcity. Student researcher will work on a study to compare the different tools available to investigate and do research in CR. Students will be introduced to the key concepts related to wireless technologies, characteristics of wireless signaling, CR, etc.

Mentor: Dr. Moussa Ayyash

Institution: Chicago State University

Necessary Skills: 

• Access to internet

This project’s primary research goal is to identify critical privacy and security threats of machine learning (ML) deployments in future wireless networks through analyzing data from multiple sources that are related to ML privacy and security issues and to relate them to privacy and security threats in the context of future wireless networks and associated applications.

Mentor: Dr. Hany Elgala

Institution: University at Albany- State University of New York (SUNY)

Necessary Skills: 

• Wireless communications and networks, cybersecurity
• Pyhton

Machine learning and artificial intelligence is having a large impact on systems in Army Applications. As the corporate R&D laboratory for the Army, this project will focus on using open ARL datasets to train state of the art machine learning algorithms for future predictions. The datasets may include sensing & IOT, ballistic applications for Soldier protection, advanced materials & manufacturing, power & energy, autonomy & maneuver, or UAS propulsion. This project will start with common low-level ML algorithms like linear regression and/or logistic regression as a baseline, and then explore different algorithms, architectures, and hyperparameters to improve the performance on validation and test sets.

Mentor: Dr. Mark Tschopp

Institution: Army Research Laboratory

Necessary Skills: Knowledge of advanced math (linear algebra, linear regression) and some computer programming is desirable. MATLAB or Python is a plus.

Within artificial intelligence (AI) is the continued challenge to create intelligent systems that reason in similar ways that individuals reason as they make decisions and perform actions. An important area of AI falls under artificial reasoning. Though artificial reasoning we can generate computational models that enable intelligent systems to reason across various data types. There are two main aspects to explore applying mathematical and AI/ML techniques included in the research (1) using various methods for formulating equations that model the expressions and associated data, (2) using various methods to uncover trends and patterns for forecasting or making predictions dynamically as data is available, (3) create computational models for integrating reasoning which includes looking toward other mathematical techniques including setting a series of linear and non-linear equations for solving for the associated value. The possible solutions can be various ML methods, hybrid reward function methods, optimization methods, tensor algebra methods or others. This project involves both of these aspects utilizing heterogeneous data and human-in-the-loop experimentation.

Mentor: Dr. Adrienne Raglin

Institution: Army Research Laboratory