CMU SEI Research Review 2019
• Collection
Publisher
Software Engineering Institute
Collection Items
CMU SEI Research Review 2019 Project Descriptions and Posters
• Annual Review
By Software Engineering Institute
This brochure includes descriptive information about the SEI's fiscal year 2019 research portfolio
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Research Review 2019 Schedule
• Brochure
By Software Engineering Institute
This handout outlines the schedule for Research Review 2019, held on October 21 and 22, 2019.
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Automated Code Repair to Ensure Memory Safety (2019)
• Presentation
By William Klieber
This presentation describes an approach to automatically repair source doe to assure memory safety.
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Automated Code Repair to Ensure Memory Safety (video)
• Video
By William Klieber
Watch Dr. Will Klieber discuss research on automatically repairing memory safety violations so programs become provably memory-safe.
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Recovering Meaningful Variable Names in Decompiled Code (video)
• Video
By Professor Vasilescu
Watch CMU ISR assistant professor Dr. Bogdan Vasilescu discuss collaborative research with SEI in the reverse engineering of legacy systems using ML to identify variables.
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Rapid Construction of Accurate Automatic Alert Handling System (2019)
• Presentation
By Lori Flynn, Ebonie McNeil
This presentation describes development of a reference architecture and prototype for rapid, accurate, and adaptive alert classification and prioritization.
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Rapid Construction of Accurate Automatic Alert Handling System (video)
• Video
By Lori Flynn, Ebonie McNeil
Watch Dr. Lori Flynn and Ebonie McNeil discuss a prototype tool for automated static analysis alert classification that reduces cost and data barriers.
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Causal Models for Software Cost Prediction and Control (video)
• Video
By Michael D. Konrad, Bill Nichols, Robert W. Stoddard, David Zubrow
Researchers at CMU SEI collaborated with other researchers to apply causal learning to learn how to control costs in software development and sustainment.
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Causal Models for Software Cost Prediction and Control
• Presentation
By Michael D. Konrad, Robert W. Stoddard, Bill Nichols, David Zubrow
This presentation describes work toward establishing causation with observational data, which remains a vital need and a key technical challenge.
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Integrated Safety and Security Engineering for Mission-Critical Systems
• Presentation
By Sam Procter
This presentation describes research to develop software and processes that use a system's architecture to support developer intuition and improve safety and security.
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Graph Convolutional Neural Networks
• Presentation
By Oren Wright
This project used graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs).
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Graph Convolutional Neural Networks
• Video
By Oren Wright
Oren Wright discusses using graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs).
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Video Summarization and Search
• Presentation
By Rachel Brower-Sinning, Jeffrey Hansen
This project's goal is to assist video analysts by increasing the volume of data that can be analyzed and providing insights into patterns of life
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Field Stripping a Weapons System: Building a Trustworthy Computer
• Presentation
By Gabriel Somlo
This presentation describes research to demonstrate the practicality of a comprehensive approach to guaranteeing the trustworthiness of computer systems.
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Field Stripping a Weapons System: Building a Trustworthy Computer (video)
• Video
By Gabriel Somlo
Watch SEI principal investigator Dr. Gabriel Somlo discuss research to demonstrate the practicality of guaranteeing the trustworthiness of DoD fielded computer systems.
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KalKi: High-Assurance Software-Defined IoT Security
• Presentation
By Sebastián Echeverría
We are developing a solution for DoD's use of commodity IoT technologies that remains resilient and trustworthy, even in the presence of a powerful attacker.
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Kalki: High Assurance Software-Defined IoT Security (video)
• Video
By Sebastián Echeverría
Watch Sebastian Echeverria discuss research to enable secure integration of IoT devices into DoD systems, even if devices are not fully trusted or configurable.
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Using All Processor Cores While Being Confident about Timing
• Presentation
By Bjorn Andersson
This presentation describes research to address the use of all processor cores while retaining confidence about timing.
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Using All Processor Cores While Being Confident about Timing
• Video
By Bjorn Andersson
Watch Dr. Bjorn Andersson discuss research on solutions to avoid the common practice of disabling all processor cores except one in order to be confident about timing.
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Emotion Recognition from Voice in the Wild
• Presentation
By Oren Wright
This presentation describes progress in research to use advances in micro-articulometry to identify emotion from voice.
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Untangling the Knot: Recommending Component Refactorings
• Presentation
By James Ivers
This presentation describes work to improve the ability to evolve software efficiently.
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Untangling the Knot: Recommending Component Refactorings
• Video
By James Ivers
Watch principal investigator James Ivers discuss research on applying AI techniques to rapidly increase the pace of making structural changes to software code bases.
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A Series of Unlikely Events: Learning from Sequential Behavior for Activity-Based Intelligence and Modeling Human Expertise
• Presentation
By Eric Heim
This presentation describes work to use inverse reinforcement learning techniques to perform activity-based intelligence.
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A Series of Unlikely Events: Learning Patterns by Observing Sequential Behavior (video)
• Video
By Eric Heim
Watch SEI principal investigator Eric Heim discuss research to develop novel Inverse Reinforcement Learning (IRL) techniques.
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Spiral/AIML: Co-optimization for High-Performance, Data-Intensive Computing in Resource Constrained Environments
• Presentation
By Scott McMillan, Franz Franchetti (Carnegie Mellon University)
This presentation updates research that helps developers build high-performance AI/ML applications on advanced hardware architectures faster.
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Spiral/AIML: Resource-Constrained Co-Optimization for High-Performance, Data-Intensive Computing
• Video
By Scott McMillan, Franz Franchetti (Carnegie Mellon University)
Watch SEI Principal Investigator, Dr. Scott McMillan, and research collaborator, CMU ECE Professor Franz Franchetti, discuss a community research effort to develop tools to reduce the prohibitive cost of implementing …
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Rapid Certifiable Trust (video)
• Video
By Dionisio de Niz
Dr. Dionisio de Niz discusses verification techniques that reduce development and deployment time for cyber-physical systems, including unmanned vehicles.
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Rapid Certifiable Trust
• Presentation
By Dionisio de Niz
Rapid Certifiable Trust preserves cyber-physical system safety by verifying and protecting part of a system and enforcing constraints on unverified components.
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Panel: Supercharging the Software Factory: Deploying Capability at the Speed of Relevance
• Video
By Anita Carleton
Watch as Anita Carleton moderates a discussion on deploying mission capability at the speed of relevance to maintain DoD competitive advantage.
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Integrating Safety and Security Engineering for Mission-Critical Systems
• Video
By Sam Procter, Alex Boydston (U.S. Army ADD/JMR)
Sam Procter discusses ongoing research to make it easier to specify, design, and assure critical systems that are safer and more secure using model based engineering with AADL.
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Future Reach Conversation: Countering Adversarial Operations Made Possible by AI
• Video
By Allen D. Householder, Lujo Bauer (Carnegie Mellon University, Department of Electrical and Computer Engineering), Kathleen Carley (Carnegie Mellon School of Computer Science)
Watch as Dr. Matt Gaston, Director of SEI Emerging Technology Center, moderates discussion on countering adversarial operations made possible by AI
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Summarizing and Searching Video (2019)
• Video
By Edwin J. Morris, Rachel Brower-Sinning, Jeffrey Hansen
SEI and CMU researchers discuss ways to improve the training of machine learning algorithms necessary for detecting, tracking, and recognizing patterns of objects in video.
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Defining AI Engineering
• Video
By Matt Gaston
Dr. Matt Gaston and Professor Martial Hebert discuss the emerging field of AI Engineering.
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Emotion Recognition from Voice in the Wild (Video)
• Video
By Oren Wright
Watch SEI Principal Investigator, Oren Wright, and CMU Language Technologies Institute collaborator, Shahan Ali Memon, discuss machine emotional intelligence and introduce an innovative speech emotion recognition database, CMU-SER.
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Projecting How AI/ML Will Revolutionize Software Vulnerability Discovery
• Video
By Greg Shannon
Watch as Dr. Greg Shannon moderates discussion on projecting how AI/ML will revolutionize software vulnerability discovery, mitigation, and/or coordination.
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