Professor of Computing & Software Systems at the University of Washington Bothell and Principal Investigator of the Intelligent Networks Laboratory.

Research focuses on the intersection of complex networks, high-performance simulation, data and software provenance, and computational neuroscience.

• High-Performance Graph Simulation: Construction of parallel simulation architectures capable of modeling tens of thousands of vertices and millions of edges across CPUs and GPUs.
• Computational Neuroscience: Investigation of developmental dynamics in cortical cultures, spatiotemporal burst propagation, avalanche statistics, and spike-timing-dependent plasticity (STDP).
• Critical Infrastructure & Telecommunications: Modeling and simulation of Emergency Services Communications Systems (ESCS / Next-Generation 911) for cybersecurity and resiliency assessment.
• Scientific Workflow & Provenance Management: Development of PROV-DM based systems to track relationships between models, code versions, execution parameters, and simulation datasets.

Project	Description	Stack	Links
Graphitti	High-performance graph-based systems simulator supporting internal vertex/edge states, dynamic topology changes, and message passing on CPUs and GPUs.	C++CUDACMake	Repo
WorkBench	Scientific workflow management platform centering on PROV-DM provenance visualization (ProVis) for reproducible simulations.	JavaMavenSwing	Repo
GraphSystemsAnalysis	Analytical pipelines for spatiotemporal point processes, avalanche identification, and network-wide bursting characterization.	PythonMATLABC++	Repo
BrainGrid	Parallel neural simulation engine for large-scale multi-cluster CPU/GPU simulation of cortical networks (predecessor to Graphitti).	C++CUDAMPI	Repo
UML-Diagram-Generator	Source-to-diagram utility generating Graphviz DOT UML class structures directly from C++ header and source files.	PythonGraphviz	Repo
Signal Computing	Open-source textbook and computational curriculum: Signal Computing: Digital Signals in the Software Domain.	LaTeXDSPOpen Textbook	Book

Languages: C++, C, CUDA, Python, Java, MATLAB, SQL
High-Performance: OpenMP, MPI, POSIX Threads, GPU Computing (NVIDIA CUDA)
Systems & Tools: CMake, Make, Git, Linux/UNIX HPC Environments, Graphviz, PROV-DM
Research Domains: Computational Neuroscience, Complex Network Science,
Emergency Services Communications (ESCS/NG911),
Digital Signal Processing, Scientific Data Provenance

• Spatiotemporal Bursting in Simulated Cultures of Cortical Neurons (2026)
  M. Stiber, N. Gonzales, J.Y.H. Lee. BioSystems, 105868, doi:10.1016/j.biosystems.2026.105868.
• Graph Neural Network Interpretation of Bursting in Biological Neuronal Networks (2026)
  H. Dhanasekaran, M. Stiber. 35th International Conference on Artificial Neural Networks (ICANN), Padua, Italy.
• Effects of Spike Timing Dependent Plasticity on Structure and Behavior of Simulated Neural Networks (2025)
  V. Arndorfer, M. Stiber. 14th International Conference on Complex Networks and their Applications, Binghamton, NY.
• Graph-Based Simulation of Emergency Services Communications Systems (2022)
  J. Martinez Jordan, V. Salvatore, B. Endicott-Popovsky, V. Gandhi, C. O'Keefe, M.S. Sotebeer, M. Stiber. Annual Modeling and Simulation Conference (ANNSIM).
• Software and Data Provenance as a Basis for eScience Workflow (2021)
  J. Conquest, M. Stiber. 17th IEEE International Conference on eScience.
• Statistics of Inverse Interspike Intervals: The Instantaneous Firing Rate Revisited (2018)
  L. Kostal, P. Lansky, M. Stiber. Chaos, 28(10), 106305.
• BrainGrid + Workbench: High-Performance/High-Quality Neural Simulation (2017)
  M. Stiber, F. Kawasaki, D. Davis, H.U. Asuncion, J.Y.H. Chu, D. Boyer. International Joint Conference on Neural Networks (IJCNN).
• Bringing High Performance Neural Simulation to the Desktop with BrainGrid (2016)
  M. Stiber, F. Kawasaki, M. Strange, A. Watson. International Workshop on Neuronal Coding.
• A Simple Model of Cortical Culture Growth: Burst Property Dependence on Network Composition and Activity (2014)
  F. Kawasaki, M. Stiber. Biological Cybernetics, 108(4), 423–443.

Full publication list available via Google Scholar, ORCID, and the INL Publications Archive.

• Professor, Computing & Software Systems, University of Washington Bothell (1997–present; Founding Faculty)
• Chair, Computing & Software Systems Division, UW Bothell (2023–2025)
• Director of Cybersecurity Initiatives, UW Bothell (2022–2023)
• Associate Dean, School of STEM, University of Washington Bothell (2013–2019)
• Fulbright Scholar, Institute of Physiology, Czech Academy of Sciences
• Assistant Professor, Hong Kong University of Science & Technology (HKUST)
• Research Assistant Professor, University of California, Berkeley
• Ph.D. in Computer Science, University of California, Los Angeles (UCLA), 1992
• M.S. in Computer Science, University of California, Los Angeles (UCLA), 1990
• B.S. in Computer Science & Electrical Engineering, Washington University in St. Louis

• Institutional Webpage: faculty.washington.edu/stiber
• Laboratory Webpage: depts.washington.edu/biocomp
• Organization GitHub: github.com/UWB-Biocomputing
• Google Scholar: Michael Stiber
• ORCID: 0000-0002-1061-7667
• LinkedIn: linkedin.com/in/stiber

_{This work has been partially generated with use of a language model (AI), and the author has read through and tested the resulting content to ensure it accurately reflects the original intent. All errors are the responsibility of the author.}