CURRENT
PROJECTS
FALL 2025 - SPRING 2026
CURRENT
PROJECTS
FALL 2025 - SPRING 2026
MEET OUR
2025 - 2026
PROJECT PARTNERS
We are excited to offer these opportunities to our DMR students for Fall of 2025 and Spring of 2026. These projects will push the boundaries of applied data science, addressing topics like GPS anomaly detection, satellite reentry risk, infrastructure resilience, space domain awareness, and AI-based benchmarking.
MEET OUR
2025 - 2026
PROJECT PARTNERS
We are excited to offer these opportunities to our DMR students for Fall of 2025 and Spring of 2026. These projects will push the boundaries of applied data science, addressing topics like GPS anomaly detection, satellite reentry risk, infrastructure resilience, space domain awareness, and AI-based benchmarking.
American Systems: Detecting Cyber-Suspicious Behavior in Space
American Systems: Detecting Cyber-Suspicious Behavior in Space Have you ever wondered how we track and identify threats in space? In this project, you’ll dive into the world of Space Domain Awareness (SDA) and help design tools to identify Resident Space Objects (RSOs) that might be behaving suspiciously—like changing orbits or acting outside their stated mission. These could signal cyber-related anomalies, and you’ll be part of developing the tech to spot them.
You’ll work on a prototype user interface (UI) and risk-scoring system to help analysts detect and flag unusual satellite behavior. Using skills like Python, AI/ML, SQL, and data visualization, your work will contribute to automated assessments that improve situational awareness in orbit. This project is a great fit for students interested in cybersecurity, modeling & simulation, space tech, and real-world defense applications.
Must be a U.S. person due to national security requirements.
Mentor Time
Tues., 9:30-10:20 A.M. (MT)
Lab Time
Thurs., 9:30-11:20 A.M. (MT)
American Systems: Detecting Cyber-Suspicious Behavior in Space
American Systems: Detecting Cyber-Suspicious Behavior in Space Have you ever wondered how we track and identify threats in space? In this project, you’ll dive into the world of Space Domain Awareness (SDA) and help design tools to identify Resident Space Objects (RSOs) that might be behaving suspiciously—like changing orbits or acting outside their stated mission. These could signal cyber-related anomalies, and you’ll be part of developing the tech to spot them.
You’ll work on a prototype user interface (UI) and risk-scoring system to help analysts detect and flag unusual satellite behavior. Using skills like Python, AI/ML, SQL, and data visualization, your work will contribute to automated assessments that improve situational awareness in orbit. This project is a great fit for students interested in cybersecurity, modeling & simulation, space tech, and real-world defense applications.
Must be a U.S. person due to national security requirements.
Mentor Time
Tues., 9:30-10:20 A.M. (MT)
Lab Time
Thurs., 9:30-11:20 A.M. (MT)
L3 Harris: Satellite Cyberattack Detection Using Telemetry
L3Harris: Satellite Cyberattack Detection Using Telemetry Ever wondered how we protect satellites from cyber threats? In this project, you’ll join a team building a machine learning model that can detect cyberattacks using real satellite telemetry data. Using new datasets from the European Space Agency, you’ll simulate a “day-in-the-life” of a satellite and train AI models to detect and classify different types of cyber intrusions.
You’ll gain hands-on experience with tools like Python, Jupyter Notebooks, network packet analysis, threat modeling frameworks like SPARTA and MITRE ATT&CK, and more. Along the way, you’ll learn the fundamentals of cybersecurity in space systems, satellite operations, and data science.
This is an ideal project for students interested in space, cybersecurity, AI/ML, or defense innovation. No need to be an expert—just bring your curiosity and commitment to tackling real-world problems.
Must be a U.S. person due to national security requirements.
Mentor Time
Thurs., 1:30-2:20 P.M. (MT)
Lab Time
Tues. 1:30-3:20 P.M. (MT)
L3Harris: Satellite Cyberattack Detection Using Telemetry Ever wondered how we protect satellites from cyber threats? In this project, you’ll join a team building a machine learning model that can detect cyberattacks using real satellite telemetry data. Using new datasets from the European Space Agency, you’ll simulate a “day-in-the-life” of a satellite and train AI models to detect and classify different types of cyber intrusions.
You’ll gain hands-on experience with tools like Python, Jupyter Notebooks, network packet analysis, threat modeling frameworks like SPARTA and MITRE ATT&CK, and more. Along the way, you’ll learn the fundamentals of cybersecurity in space systems, satellite operations, and data science.
This is an ideal project for students interested in space, cybersecurity, AI/ML, or defense innovation. No need to be an expert—just bring your curiosity and commitment to tackling real-world problems.
Must be a U.S. person due to national security requirements.
L3 Harris: Satellite Cyberattack Detection Using Telemetry
Mentor Time
Thurs., 1:30-2:20 P.M. (MT)
Lab Time
Tues. 1:30-3:20 P.M. (MT)
NSIC: Project Shoelace: Detecting GPS Signal Disruptions
NSIC: Project Shoelace: Detecting GPS Signal Disruptions GPS signals are everywhere—from military operations to Uber rides—and disruptions can have serious, wide-ranging consequences. In this project, students will work alongside NSIC to improve machine learning algorithms that detect anomalies in the data supplied by the United States’ Global Positioning System (GPS), or more generally in readings from Global Navigation Satellite Systems (GNSS includes international peers of GPS). The student team will use large, complex, real-world, and publicly-accessible datasets. Students will refine and test models, explore global sensor networks, and help scale analytics that could eventually provide real-time warnings to GPS/GNSS users around the world. This is a chance to get hands-on with data science, AI, and national security while solving challenges that impact both defense and everyday life.
Must be a U.S. person due to national security requirements.
Mentor Time
Mon., 12:30-1:20 P.M. (MT)
Lab Time
Fri., 11:30-1:20 P.M. (MT)
NSIC: Project Shoelace: Detecting GPS Signal Disruptions
NSIC: Project Shoelace: Detecting GPS Signal Disruptions GPS signals are everywhere—from military operations to Uber rides—and disruptions can have serious, wide-ranging consequences. In this project, students will work alongside NSIC to improve machine learning algorithms that detect anomalies in the data supplied by the United States’ Global Positioning System (GPS), or more generally in readings from Global Navigation Satellite Systems (GNSS includes international peers of GPS). The student team will use large, complex, real-world, and publicly-accessible datasets. Students will refine and test models, explore global sensor networks, and help scale analytics that could eventually provide real-time warnings to GPS/GNSS users around the world. This is a chance to get hands-on with data science, AI, and national security while solving challenges that impact both defense and everyday life.
Must be a U.S. person due to national security requirements.
Mentor Time
Mon., 12:30-1:20 P.M. (MT)
Lab Time
Fri., 11:30-1:20 P.M. (MT)
SDA TAP Lab: Labeling & Storing Space Domain Data
SDA TAP Lab: Labeling & Storing Space Domain Data Are you curious about how the U.S. Space Force identifies and tracks unknown objects in orbit? Join the SDA TAP Lab project to help build the data infrastructure that powers space situational awareness. This project focuses on creating a standardized, web-based system to label and store data on uncorrelated tracks (UCTs)—objects in space that don’t match known satellites. You’ll help develop the tools that feed into a Common Task Framework, enabling future machine learning algorithms to detect, classify, and respond to space threats in real time. If you’re interested in working with real-world orbital data, developing structured datasets, and supporting national security missions, this is your chance to make a real impact.
Must be a U.S. person due to national security requirements.
Mentor Time
Thur, 1:30 - 2:20 P.M. (MT)
Lab Time
Tue, 1:30 - 3:20 P.M. (MT)
SDA TAP Lab: Labeling & Storing Space Domain Data
SDA TAP Lab: Labeling & Storing Space Domain Data Are you curious about how the U.S. Space Force identifies and tracks unknown objects in orbit? Join the SDA TAP Lab project to help build the data infrastructure that powers space situational awareness. This project focuses on creating a standardized, web-based system to label and store data on uncorrelated tracks (UCTs)—objects in space that don’t match known satellites. You’ll help develop the tools that feed into a Common Task Framework, enabling future machine learning algorithms to detect, classify, and respond to space threats in real time. If you’re interested in working with real-world orbital data, developing structured datasets, and supporting national security missions, this is your chance to make a real impact.
Must be a U.S. person due to national security requirements.
Mentor Time
Thur, 1:30 - 2:20 P.M. (MT)
Lab Time
Tue, 1:30 - 3:20 P.M. (MT)
Space ISAC: Informing Satellite & Debris Reentry Considerations: Gaps in Awareness & Coordination
Space ISAC: Informing Satellite & Debris Reentry Co Have you ever wondered what happens when satellites or space debris reenter Earth’s atmosphere? This project offers students a unique opportunity to explore that very question with one of the leading organizations in space cybersecurity and situational awareness—Space ISAC. As a DMR student, you’ll contribute to research focused on improving how the space community anticipates and coordinates around satellite and debris reentry events.
You’ll examine current gaps in awareness, communication, and coordination across space agencies and private entities, and propose data-driven solutions that could enhance global collaboration and response efforts. The insights developed through this project could influence future strategies for safer and more informed space operations.
This is a great project for students interested in space policy, cybersecurity, systems thinking, and data analysis with real-world impact.
Must be a U.S. person due to national security requirements.
Mentor Time
Thur, 2:30 - 3:20 P.M. (MT)
Lab Time
Tue, 1:30 - 3:20 P.M. (MT)
Space ISAC: Informing Satellite & Debris Reentry Considerations: Gaps in Awareness & Coordination
Space ISAC: Informing Satellite & Debris Reentry Co Have you ever wondered what happens when satellites or space debris reenter Earth’s atmosphere? This project offers students a unique opportunity to explore that very question with one of the leading organizations in space cybersecurity and situational awareness—Space ISAC. As a DMR student, you’ll contribute to research focused on improving how the space community anticipates and coordinates around satellite and debris reentry events.
You’ll examine current gaps in awareness, communication, and coordination across space agencies and private entities, and propose data-driven solutions that could enhance global collaboration and response efforts. The insights developed through this project could influence future strategies for safer and more informed space operations.
This is a great project for students interested in space policy, cybersecurity, systems thinking, and data analysis with real-world impact.
Must be a U.S. person due to national security requirements.
Mentor Time
Thur, 2:30 - 3:20 P.M. (MT)
Lab Time
Tue, 1:30 - 3:20 P.M. (MT)
SpOC: Building Better AI with Space Data – SpOC UCT Benchmarking
SpOC: Building Better AI with Space Data – SpOC UCT Benchmarking In this project, you’ll work directly with Space Operations Command (SpOC) and the SDA TAP Lab to help shape the future of space data science. Your team will design tools to build benchmark datasets—essential for training and testing machine learning models used in Space Domain Awareness (SDA). These tools will support the processing of Uncorrelated Tracks (UCTs), which are unknown or untracked objects in space.
Using open-source data and working with subject matter experts, you’ll automate the labeling, cleaning, and organizing of real space data (like satellite maneuvers and launch events). Then, you’ll help define how algorithm performance should be measured—so results can be fairly compared across developers using a Common Task Framework.
This is an exciting opportunity for students interested in artificial intelligence, space operations, or software development to be part of building the next generation of tools for national security and space traffic management.
Must be a U.S. person due to national security requirements.
Mentor Time
Thur, 1:30 - 2:20 P.M. (MT)
Lab Time
Tue, 1:30 - 3:20 P.M. (MT)
SpOC: Building Better AI with Space Data – SpOC UCT Benchmarking
SpOC: Building Better AI with Space Data – SpOC UCT Benchmarking In this project, you’ll work directly with Space Operations Command (SpOC) and the SDA TAP Lab to help shape the future of space data science. Your team will design tools to build benchmark datasets—essential for training and testing machine learning models used in Space Domain Awareness (SDA). These tools will support the processing of Uncorrelated Tracks (UCTs), which are unknown or untracked objects in space.
Using open-source data and working with subject matter experts, you’ll automate the labeling, cleaning, and organizing of real space data (like satellite maneuvers and launch events). Then, you’ll help define how algorithm performance should be measured—so results can be fairly compared across developers using a Common Task Framework.
This is an exciting opportunity for students interested in artificial intelligence, space operations, or software development to be part of building the next generation of tools for national security and space traffic management.
Must be a U.S. person due to national security requirements.
Mentor Time
Thur, 1:30 - 2:20 P.M. (MT)
Lab Time
Tue, 1:30 - 3:20 P.M. (MT)
SPACECOM: Predicting Infrastructure Degradation and Failure
United States Space Command J4 (SPACECOM J4): Predicting Infrastructure Degradation and Failure.
Mentor Time
Tues. 10:30-11:20 A.M. (MT)
Lab Time
Thurs. 9:30-11:20 A.M. (MT)
United States Space Command J4 (SPACECOM J4): Predicting Infrastructure Degradation and Failure.
SPACECOM: Predicting Infrastructure Degradation and Failure
Mentor Time
Tues. 10:30-11:20 A.M. (MT)
Lab Time
Thurs. 9:30-11:20 A.M. (MT)