Research Review 2023

Thank you for joining us for the 2023 Carnegie Mellon University Software Engineering Institute (CMU SEI) Research Review! The event consisted of our technical experts talking about their projects and answering your questions. Watch a video of the event below.

Cultivating Curiosity

This year’s theme, Cultivating Curiosity, highlights the spirit of inquiry driving our researchers to ask questions, evaluate existing practices, and seek creative approaches to addressing the most pressing software, cybersecurity, and AI challenges.

If you have any questions about this event or our research, please reach out to us at info@sei.cmu.edu.

Leveraging Adversarial Machine Learning Techniques to Perform Query-Access Fairness Evaluations

Principal Investigator

Anusha Sinha

The DoD would greatly benefit from automation and artificial intelligence (AI). However, recent studies have uncovered severe biases, likely removing qualified candidates from consideration.

Moving Explainable Artificial Intelligence (XAI) from Research to Practice: Defining and Validating an XAI Process Framework

Principal Investigator

Violet Turri

A lack of transparency about artificial intelligence (AI) decision-making processes can make it challenging for end users to determine whether AI system suggestions are right or wrong. Research into explainable AI (XAI) aims to address a lack of system transparency.

Portend: Drift Planning in ML Systems

Principal Investigator

Dr. Jeffery Hansen

While machine learning models (ML) can be very powerful, they are known to be brittle when presented with data outside their training distribution.

Formal Arguments for Large-Scale Assurance (FALSA)

Principal Investigator

Dr. Gabriel Moreno & Mark Klein

Re-assurance of evolving large-scale systems can bottleneck deployment of new capability the U.S. Department of Defense (DoD) needs for new missions and environments.

Detection of Malicious Code Using Static Taint Analysis

Principal Investigator

Dr. Will Klieber

Detecting malicious code is a challenge, particularly when it’s implanted in otherwise legitimate software. If undetected, malware injected into legitimate software can result in costly compromises of computer systems.

Building an SOC Knowledge Base

Principal Investigator

Dr. Justin Novak

Security operations centers (SOCs) are a critical tool for ensuring cybersecurity and information security across the U.S. Department of Defense (DoD) enterprise. Deployment requires a time-consuming and expensive process necessitating an expert or expert team.

Applied Automated Repair of Static Analysis Alerts

Principal Investigator

David Svoboda

Static analysis (SA) tools analyze source code for security defects and alert users to issues requiring repair. While invaluable, SA tools tend to produce many alerts (many of which are false positives), making it difficult to separate signal from noise and repair critical security defects.

Software Architecture for Systems that Use Quantum Computers

Principal Investigator

Daniel Justice

In recent years, with the increasingly larger leaps in technology, it has become a point of discussion on whether software architecture and engineering has the toolset to properly harness the benefits of advanced artificial intelligence (AI).

Co-Design for Edge AI: Application-Specific System on Chip

Principal Investigator

Dr. John Wohlbier

Hardware inefficiencies pose major limitations to U.S. Department of Defense (DoD) applications; current processors simply cannot keep up with the large and complex machine learning (ML) workloads needed to perform their missions.