Paul Bogdan

I am currently a Post-Doctoral Fellow in the Department of Electrical and Computer Engineering of Carnegie Mellon University. Throughout the period of my doctoral studies under the supervision of Professor Radu Marculescu at Carnegie Mellon University, I have conducted research within the Center for Silicon System Implementation on the topic of modeling, analysis and optimization of dynamic processes taking place on networked architectures. My research interests lie at the intersection of computer engineering, computer science, applied mathematics, and statistical physics. In my future research, I intend to focus on studying the behavior and performance of large-scale distributed algorithms in random environments over dynamic networked architectures. Relevant applications are in the area of design and optimization methodologies for on-chip and off-chip networked architectures consisting of a large number of nodes; modeling, analysis, and optimization of complex biological micro-robotic systems with applications in medicine; design methodologies for emerging nanotechnologies; computational biology, mathematical models, algorithms and design methodologies for regenerative medicine; analytical models for abnormal prediction with applications in cyber-physical systems, social dynamics and financial markets; design, optimization and control of Smart Grids.

News

Research interests

  1. Communication-centric Design Methodologies and CAD Algorithms for Multiprocessor Systems
  2. Fault-Tolerant Communication for Multi-Processor Systems-on-Chip at Nanoscale
  3. Cyber Physical Systems: Theoretical Foundations for CPS Design and Dynamic Optimization
  4. Mathematical Models and Design Methodologies for Stem Cell Based Regenerative Medicine
  5. Modeling, Analysis and Optimization of Biological Propelled Micro-Robotic Swarms
  6. Large Scale Dynamic Networked Systems: Optimal Control Under Uncertainty
  7. Control of Fractal Dynamics: Nonlinear System Theory and Stochastic Optimization
  8. Statistical Physics Implications on Machine Learning Algorithms