Mark Blackburn

Senior Research Scientist

Building: Altorfer

Room: 319

Phone: (201) 216-8025

Fax: (201) 216-5541

Email: mblackbu@stevens.edu

Website

Research

Dr. Blackburn is primarily responsible for research focused on methods and automated tools for reasoning about computer-based systems. His research combines tools, formal methods, modeling, simulation, visualization and computation in support of design, architecting, and testing. Current interests include use of semantic technologies and ontologies to enable AI for cross-domain model integration of complex and cyber physical systems, and research in use of Bayesian networks for prediction, estimation and decision-making. Dr. Blackburn has been the Principal Investigator (PI) on 12 Systems Engineering Research Center research tasks, with two currently ongoing: one sponsored by NAVAIR and another by the US Army ARDEC/CCDC investigating the most advanced and holistic approaches to model-centric engineering and digital engineering. He was co-PI on Architecting Digital Twins for Model-Centric Engineering: A Combined Semantic Modeling and Machine Learning Approach, as well as a task for Quantitative Risk. He has also been the PI on research tasks for the National Science Foundation, Federal Aviation Administration, and National Institute of Standards and Technology. Prior to joining Stevens, Dr. Blackburn was a Fellow at the Systems and Software Consortium where he conducted applied research and received over $10 million dollars from industry primarily focused on formal method-based modeling, analysis, simulation, and test generation tools and methods.

Selected Publications
Conference Proceeding
  1. Chell, B.; Hoffenson, S.; Kruse, B.; Blackburn, M. (2020). Mission-Level Optimization: A New Approach to Complex Systems Design for Highly Stochastic Life Cycle Use Case Scenarios. Proceedings of the ASME International Design Engineering Technical Conferences.
  2. Chell, B.; Hoffenson, S.; Blackburn, M. (2019). Comparing Multifidelity Model Management Strategies for Multidisciplinary Design Optimization. ASME International Design Engineering Technical Conferences.
  3. Chell, B.; Hoffenson, S.; Blackburn, M. (2019). A comparison of multidisciplinary design optimization architectures with an aircraft case study. AIAA Scitech 2019 Forum.
Journal Article
  1. Chell, B.; Hoffenson, S.; Philippe, C. J.; Blackburn, M. (2021). Comparing Filtering Multifidelity Optimization Strategies with a Simulation-Based Multidisciplinary Aircraft Model. Journal of Mechanical Design, Transactions of the ASME (8 ed., vol. 143).
  2. Kruse, B.; Blackburn, M. (2019). Collaborating with OpenMBEE as an Authoritative Source of Truth Environment. Procedia Computer Science (C ed., vol. 153, pp. 277-284).
    https://www.sciencedirect.com/science/article/pii/S1877050919307392?via%3Dihub.
  3. Bone, M.; Blackburn, M.; Kruse, B.; Dzielski, J.; Hagedorn, T.; Grosse, I. (2018). Toward an Interoperability and Integration Framework to Enable Digital Thread. Systems (4 ed., vol. 6).
    https://www.mdpi.com/journal/systems/special_issues/MBSE.
Magazine/Trade Publication
  1. Dzielski, J.; Blackburn, M. (2018). Implementing a Decision Framework in SysML Integrating MDAO Tools. INSIGHT Practitioners Magazine. INCOSE.
    https://onlinelibrary.wiley.com/doi/abs/10.1002/inst.12221.
Modeling & Simulation Special Edition
    Report
    1. Blackburn, M.; Peak, R. S.; Cimtalay, S.; Baker, A.; Ballard, M.; Rhodes, D. H.; Bone, M.; Dzielski, J.; Giffin III, R.; Kruse, B.; Smith, B.; Austin, M.; Coelho, M. (2019). Transforming Systems Engineering through Model-Centric Engineering (SERC-2019-TR-005 ed.). SERC.
      https://apps.dtic.mil/dtic/tr/fulltext/u2/1073187.pdf.
    2. Blackburn, M.; Verma, D.; Dillon-Merrill, R.; Blake, R.; Bone, M.; Chell, B.; Dove, R.; Dzielski, J.; Grogan, P.; Hoffenson, S.; Hole, E.; Jones, R.; Kruse, B.; Pochiraju, K.; Snyder, C.; Cloutier, R.; Grosse, I.; Hagedorn, T. (2018). Transforming Systems Engineering through Model-Centric Engineering (SERC-2017-TR-111 ed.). SERC.