Michael D. Konrad
Software Engineering Institute
Dr. Michael D. Konrad is a principal researcher at the Software Engineering Institute (SEI) of Carnegie Mellon University. He applies causal discovery and inference, and more broadly, artificial intelligence/machine learning, to systems engineering and software engineering problems. From 1999-2013, Konrad was the model team lead for the CMMI for Development; and a contributor to the original CMM for Software and to ISO/IEC 15504 (1988-1998). Konrad also worked at ISSI, SAIC, and Honeywell (1979-1987). He has a PhD in Mathematics from Ohio University, 1978.
A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes
• Technical Report
By Ipek Ozkaya , Anita Carleton , Matthew J. Butkovic , Sebastián Echeverría , Robert Edman , John Haller , Erin Harper , Michael D. Konrad , Natalie Schieber , Carol J. Smith , Shawn Wray
AI Robustness (AIR) Tool
• Software
Measuring AI Accuracy with the AI Robustness (AIR) Tool
• Blog Post
By Michael D. Konrad , Nicholas Testa , Linda Parker Gates , Crisanne Nolan , David James Shepard , Julie B. Cohen , Andrew O. Mellinger , Suzanne Miller , Melissa Ludwick
A Preliminary Report on a Model for Maturing AI Adoption: From Hype to Achieving Repeatable, Predictable Outcomes
• Technical Report
By Ipek Ozkaya , Anita Carleton , Matthew J. Butkovic , Sebastián Echeverría , Robert Edman , John Haller , Erin Harper , Michael D. Konrad , Natalie Schieber , Carol J. Smith , Shawn Wray
Poster - Causal Models for Software Cost Prediction and Control
• Poster
By Michael D. Konrad , Bill Nichols , Robert W. Stoddard , David Zubrow
Causal Models for Software Cost Prediction & Control
• Poster
By Michael D. Konrad , Robert W. Stoddard , Bill Nichols , David Zubrow
Measuring AI Accuracy with the AI Robustness (AIR) Tool
• Blog Post
By Michael D. Konrad , Nicholas Testa , Linda Parker Gates , Crisanne Nolan , David James Shepard , Julie B. Cohen , Andrew O. Mellinger , Suzanne Miller , Melissa Ludwick
How Can Causal Learning Help to Control Costs?
• Blog Post
Addressing Open Architecture in Software Cost Estimation
• Blog Post
By Michael J. Gagliardi , Michael D. Konrad , Douglas Schmidt (William & Mary)
Data-Driven Software Assurance
• Blog Post
Eliciting and Analyzing Unstated Requirements
• Blog Post
Why Does Software Cost So Much?
• Podcast
Data Driven Software Assurance
• Podcast
Can You Rely on Your AI? Applying the AIR Tool to Improve Classifier Performance
• Webcast
By Linda Parker Gates , Crisanne Nolan , Michael D. Konrad , Suzanne Miller , Nicholas Testa , David James Shepard
Causal Models for Software Cost Prediction & Control (video)
• Video
By Michael D. Konrad , Bill Nichols , Robert W. Stoddard , David Zubrow