CPS Network Simulation with Variable Fidelity
Primary Investigator: Himanshu Neema
Project Description
Cyber-Physical systems are engineering systems where the functionality emerges from networked interactions among the physical and computational components. Thus for simulation based evaluation of CPS, communication network simulation is a central piece that must almost always be integrated with rest of the heterogeneous simulations. In such large-scale CPS simulation based studies, the actual mechanism by which certain network effects such as cyber-attacks, or packet delays and drops, becomes less important as compared to the overall impact of such effects. For that to be simulated along with large CPS simulations, it becomes highly expensive to simulate communication networks at packet levels through all the OSI layers. At the same time, for certain effects to be simulated that is exactly is necessary. In order to balance the increased efficiency of higher-level network simulation with high-fidelity of packet-level simulation, we propose to create an architecture that allows the simulators to dynamically vary the fidelity level of the network simulation during run-time. The key research challenges that we want to address in this project are: (1) to develop, using an open-source simulation tool, a network simulation architecture that enables varying the network model's fidelity levels during run-time, (2) to maintain consistency of network data during such transitions, and (3) generate use-cases to demonstrate both the feasibility and applicability of this approach.
Desired Qualifications
C++ Programming; Computer Networking
Cyber-Physical Systems Virtual Organization
Primary Investigator: Janos Sztipanovits
Project Description
The Cyber-Physical Systems Virtual Organization (CPS-VO) is a portal used by thousands of researchers across the country to collaborate on topics involving the intersection between computing and the physical world. Our goal is to bring together academia, government, and industry, and some ways to do that include integrating research tools and models within our website and making this content citable. Students will be involved in helping to upgrade code modules from Drupal 6 to Drupal 8 as part of our on-going effort to modernize and update this platform. Students may also be involved in helping to integrate existing tools into the website.
Desired Qualifications
For those involved in code upgrades, a background in Computer Science/Software Development with strong experience in PHP and Drupal is necessary. Those involved in integrating tools should be comfortable working in a Linux command line environment, installing/debugging complex applications and dependencies, and working with Docker, VNC, nginx, and related technology.
Cybersecurity AI, and Autonomous Systems Research
Primary Investigator: Jules White
Project Description
This project will involve students in one or more topics related to cybersecurity, AI, or autonomous systems. Students will work to understand cybersecurity issues in domains, ranging from software engineering to manufacturing. Work with AI and autonomous systems may also be performed as needed.
Desired Qualifications
Determination of acceptance for an internship will be assessed on a case-by-case basis for all interested students.
Data Science for Micro-Mobility
Primary Investigator: Dan Work
Project Description
Increasingly, urban environments are experiencing numerous revolutions in transportation, which includes shared bikes and scooters. In this project we will work with a variety of research questions concerning these shared personal transportation devices, referred to broadly as “micromobility”. These modes of transportation have the potential to service short trips around dense areas of cities, but are subject to numerous management challenges for operators and city governments. Nashville is one such city dealing with the benefits and challenges of micromobility. Vanderbilt has served in multiple ways, already, as a testing ground for new micromobility strategies and data analysis. Areas of study for this project include micromobility infrastructure planning (e.g., bike lanes, designated parking), urban development, transportation demand management, and sustainability.
Desired Qualifications
Data science, programming in Python or ability to learn quickly, possible familiarity with GIS software, possible experience with web servers or databases
Innovative Illustrations of Climate Change in the Classroom
Primary Investigator: Akos Ledeczi
Project Description
The goal of the research project is to develop innovative projects that simultaneously raise awareness about climate change and teach computer science in high schools. NetsBlox is an educational visual programming environment specifically designed to introduce advanced computing concepts to novices. For a 3-min introduction to NetsBlox, watch this video. The project aims to 1) identify interesting online data sources and services that can be used to quantify climate change, 2) extend NetsBlox to be able to access these, and 3) devise corresponding innovative projects that novice programmers can create in NetsBlox. For example, a simple example project shows carbon dioxide concentrations as a function of temperature variations for the past 800,000 years from ice core measurements from Antarctica and the past 100 years from other data sources.
Desired Qualifications
Software development experience, JavaScript
Neural Network and Machine Learning Verification
Primary Investigator: Taylor Johnson
Project Description
In this project, students will help develop benchmarking processes for recent machine learning and neural network verification algorithms and tools, such as our nnv tool (https://github.com/verivital/nnv). These approaches allow, for example, to detect or prove the absence of perturbations that can cause various computer vision and machine perception tasks to misbehave, known colloquially as adversarial perturbations, but the source of which could be due to environmental uncertainty, noise, attackers, etc. Anticipated contributions include developing scripts for performing benchmarking of our methods and other research groups' recent approaches, to primarily be evaluated on convolutional neural networks (CNNs) on standard data sets, such as MNIST, CIFAR, and ImageNet.
Desired Qualifications
Students at all levels (freshman through senior) are welcome and will be able to help refine our prototype systems and approach. Programming experience in Matlab, Java, and Python would all be desirable, as would prior experience with machine learning frameworks, such as Keras, TensorFlow, etc. All code will be version controlled using Git/Mercurial, which experience with is desired, but not required.
Tools for Assured Autonomy
Primary Investigators: Gabor Karsai, Abhishek Dubey
Project Description
Autonomous vehicles (cars, drones, underwater vehicles, etc.) have started using software components that are built using machine learning techniques. This is due to the fact that these vehicles must operate in highly uncertain environments and the we cannot design a correct algorithm for all situations. Instead, we collect data from a real or simulated environment and train a general purpose system - typically a neural net - to perform a certain function using machine learning techniques. But the challenge is that the training data cannot cover all possible cases, yet we need to know that the system works safely and has acceptable performance.
Our project is doing fundamental research and building tools for supporting the engineering of such system. The tools are for modeling the system (e.g. an underwater vehicle), executing the training and testing of the learning-based components, and building formal arguments (called assurance cases) to show that the system is safe.
Desired Qualifications
CS/CmpE/EE background with familiarity with concepts and techniques of signals and systems, computer architecture, software design, and embedded systems. Knowledge of the Python/C/C++ languages is a plus, as well as experience with ROS (the Robot Operating System).
Traffic Control with Connected and Autonomous Vehicles
Primary Investigator: Dan Work
Project Description
This project will look at using Connected and Autonomous Vehicles (CAVS) to beneficially control the flow of traffic. Traffic is known to exhibit complicated, nonlinear behavior that often results in so-called phantom traffic jams in which traffic jams can appear seemingly from thin air. These jams are known to cause decreases in fuel efficiency, increases in commute time, and decreases in driver safety. An emerging technology for attempting to mitigate this phenomenon is the use of CAVs, which employ novel control methods specifically designed for stopping phantom jams.
Students will work on developing algorithms to implement on real instrumented vehicles, as well as developing techniques for modeling their effect on traffic.
Desired Qualifications
Background in data science, proficiency in programming with python/matlab, background in simulation or transportation modeling
Creation and Evaluation of CPS System Model Library
Primary Investigator: Theodore Bapty
Project Description
Cyber-Physical systems, combinations of physical and computer components, are challenging to design and evaluate. To manage complexity, these systems are often composed from high-level components and subsystems, rather than building them form elemental parts. Prior work at ISIS has produced tools (OpenMETA) that allow modeling these systems and automatically composing models for various types of engineering analysis. Upcoming research will attempt to use AI to automatically create systems from libraries of components and subsystems to achieve required performance. For these tools to work for a particular domain, libraries of components and subsystems must be created, along with the transforms (Test Benches) to map the models to the relevant engineering tools. This internship will work to create component libraries for small, unmanned underwater vehicles (UUV) and engineering tools to evaluate their hydrodynamic properties (Computational Fluid Dynamics and dynamic simulations). Students may also create example system and execute system analysis campaigns.
Desired Qualifications
Background in mechanical engineering is advantageous, familiarity with CFD tools, CAD tools. Programming in C++/C# and/or Python.