1. Network Science, National Academies Press, 2006
Robert Nowak
ECE Dept., UW-Madison
Research Interests: statistical signal processing, machine learning, imaging and network science, and applications in communications, bio/medical imaging, and in silico genomics. 
Network Science, National Academies Press, 2006
The study of complex networked systems.
Key Challenges : “Characterization of the dynamics and information flow in networked systems, modeling, analysis, and acquisition of experimental data for extremely large networks.”
I would like to thank Josiane Zerubia for inviting me to speak today and to visit INRIA again. It is a great pleasure to continue my collaborations with her outstanding research group.
My take: In many large-scale problems we have limited prior knowledge, but a wealth of data.  How much can we learn from data? Adaptivity to unknown system behavior is key.

2. Challenge 1: Inferring Networks from Experimental Data
Network Tomography: Infer network behavior and structure from indirect and incomplete data
Challenges:
ill-posed problem
errors and noise
calibration
MAP Kinase Regulation Network
Internet routing behavior/structure
I would like to thank Josiane Zerubia for inviting me to speak today and to visit INRIA again. It is a great pleasure to continue my collaborations with her outstanding research group.

3. Challenge 2: Detecting Weak Non-Local Signals
Network Detection:
Xi = data at each node
Test:
H0 : Xi ~ N(0,1) for all i
vs.
H1 : Xi ~ N(m,1), m > 0,
at handful of nodes
Challenge:
m > 0 may be so small, that individual testing at each node is unreliable (e.g., biohazard or Internet virus detection)
plug-in schemes (e.g., the GLRT) are suboptimal in high dimensional settings
Data fusion (aggregation) can enhance detection capabilities, but typically requires strong prior knowledge
I would like to thank Josiane Zerubia for inviting me to speak today and to visit INRIA again. It is a great pleasure to continue my collaborations with her outstanding research group.
Detection must be adaptive to unknown network behavior and/or structure