Research
My main research spans information and communication theories, communication for networked control systems, convex optimization and state estimation.
Information measures
In this research, we study various functional and
topological properties of information measures, such as, directed information, causally condition directed information and its variants. In information
theory, directed information or its variants are primarily used to characterize the capacity of channels with feedback, some lossy compression
problems and in network information theory. However, the last decade such information measures are widely used to characterize the fundamental
performance limitations of delay constrained dynamical systems, like for instance, single closedloop control systems. This is because by definition,
such measures encapsulate the dynamics in such systems where the components are modeled by (stochastic or deterministic) processes. The utility
of directed information is not exhaustive to the previous research directions. Instead, it can be used in an anthology of problems like gambling,
portfolio theory, or in biology as an alternative to Granger's measure of causality.
Source coding and rate distortion theory
In this research direction, we study generalizations of classical source coding and Shannon's rate distortion
theory. We ask questions like, for instance, how source coding and rate distortion theory can be applied
to delayconstrained dynamical systems, or what are the performance limitations of block sequential source coding when the receiver decodes the message noncausally?
Selected Publications 
Book Chapters:
Journal papers:
[7] 
P. A. Stavrou, T. Tanaka and S. Tatikonda, "The timeinvariant multidimensional Gaussian sequential rate distortion problem revisited,"
IEEE Transactions on Automatic Control, Vol. 65, Issue 5, pp. 22452249, May 2020.
Full Text 
[6] 
P. A. Stavrou, T. Charalambous, and C. D. Charalambous, "Optimal estimation via nonanticipative rate distortion function and applications to
timevarying GaussMarkov processes,"
SIAM Journal on Control and Optimization, Vol. 56, Issue 5, pp. 37313765, 2018.
Full Text 
[5] 
P. A. Stavrou, J. Østergaard, and C. D. Charalambous, "Zerodelay rate distortion via filtering for vectorvalued Gaussian sources,"
IEEE Journal of Selected Topics in Signal Processing , Vol. 12, Issue 5, pp. 841856, October 2018.
Full Text 
[4] 
P. A. Stavrou, T. Charalambous and C. D. Charalambous, "Finitetime nonanticipative rate distortion function for timevarying scalarvalued GaussMarkov sources,"
IEEE Control Systems Letters, Vol. 2, Issue 1, pp. 175180, January 2018.
Full Text 
Conference papers:
[24] 
H. Ghourchian, P. A. Stavrou, T. Oechtering, M. Skoglund, Block source coding with sequential encoding, in proceedings of
IEEE Information Theory Workshop (ITW), 2019.

[22] 
P. A. Stavrou, T. Charalambous, C. D. Charalambous, S. Loyka and M. Skoglund, Asymptotic reversewaterfilling solution of
nonanticipative rate distortion function for vectorvalued GaussMarkov sources, in proceedings of
IEEE 57th Conference on Decision and Control (CDC), 2018.
Full Text

[20] 
P. A. Stavrou, J. Østergaard, and M. Skoglund, "On zerodelay source coding of LTI GaussMarkov
systems with covariance matrix distortion constraints," in proceedings of European Control Conference (ECC), 2018.
Full Text

[19] 
P. A. Stavrou and J. Østergaard, "Fixedrate zerodelay source coding for stationary vectorvalued GaussMarkov sources," in proceedings of Data Compression Conference (DCC), 2018.
Full Text

[18] 
P. A. Stavrou, J. Østergaard, C. D. Charalambous, and M. Derpich, "An upper bound to zerodelay rate distortion via Kalman filtering for Vector Gaussian
sources," in proceedings of IEEE Information Theory Workshop (ITW), 2017.
Full Text 
[16] 
P. A. Stavrou and J. Østergaard, "A lower bound on causal and zerodelay rate distortion for scalar Gaussian autoregressive sources," in proceedings of
International Symposium on Information Theory and Signal Processing in Benelux (SITB), 2017.
Full Text 
[12] 
P. A. Stavrou, C. K. Kourtellaris, and C. D. Charalambous, "Applications of information nonanticipative rate distortion function," in
proceedings of IEEE International Symposium on Information Theory (ISIT), 2014.
Full Text 

Joint sourcechannel coding
In this research direction, we study linear and nonlinear sourcechannel coding schemes to achieve optimal or nearoptimal
performance within a delay constrained pointtopoint system or a delay constrained network.?
Selected Publications 
Book Chapters:
[4] 
C. D. Charalambous, C. K. Kourtellaris, and P. A. Stavrou, "On Shannon's duality of a source
and a channel and nonanticipative communication and communication for control,"
Coordination Control of Distributed Systems (Edt. by Jan Van Schuppen and Tiziano Villa) in ser. Lecture Notes in Control and Information Sciences, Vol. 456, pp. 291305, November 2014.
Full Text 
[1] 
C. K. Kourtellaris, C. D. Charalambous, and P. A. Stavrou, "Nonanticipative duality of sources
and channels with memory and feedback,"
Coordination Control of Distributed Systems (Edt. by Jan Van Schuppen and Tiziano Villa) in ser. Lecture Notes in Control and Information Sciences, Vol. 456, pp. 325335, November 2014.
Full Text 
Journals:
[9] 
P. A. Stavrou, and M. Skoglund, "LQG control and linear policies for noisy communication links with synchronized side information at the decoder,"
Automatica, Vol. 123, January 2021 (to appear).
Full Text 
Conference papers:

Feedback capacity of channels with memory
In this research direction, we are interested in computing the (ergodic) channel capacity of (finite alphabet) noisy channels with memory and/or
feedback. Ergodic feedback capacity is one of the fundamental characterizations in communication theory because it
gives theoretical limitations on the least upper bound of allowable rate conveyed through a communication channel. However,
characterizing the ergodic channel capacity of a communication system that is often expressed as an intractable optimization problem is not an easy
task, let alone finding analytical expressions to such characterizations. In information theory,
ergodic channel capacity is computed in closed form expressions for simple memoryless channels (defined
either on finite or continuous alphabet spaces) For these simple channel models it is wellknown that the presence of noiseless
feedback often makes the coding much simpler but it cannot outperform the ergodic channel capacity without noiseless feedback. Unfortunately,
this is not the case for channels with memory and, thus, to arrive to similar conclusions as those deduced for the class of memoryless
channels, one has to characterize and then find analytical or computable expressions for specific classes of channels with memory.
Communication and Coding for Networked Control Systems
In this research direction, we are interested in identifying fundamental performance limitations and practical
coding schemes for single closed loop control systems, extensions to problems with side information and to multiloop closed loop systems which are the
epitomy of a networked control system. To do it, we use tools from estimation theory, identification and optimization.
Selected Publications 
Book Chapters:
Journals:
[9] 
P. A. Stavrou, and M. Skoglund, "LQG control and linear policies for noisy communication links with synchronized side information at the decoder,"
Automatica , Vol. 123, January 2021 (to appear).
Full Text 
[7] 
P. A. Stavrou, T. Tanaka and S. Tatikonda, "The timeinvariant multidimensional Gaussian sequential rate distortion problem revisited,"
IEEE Transactions on Automatic Control, Vol. 65, Issue 5, pp. 22452249, May 2020..
Full Text 
[6] 
P. A. Stavrou, T. Charalambous, and C. D. Charalambous, "Optimal estimation via nonanticipative rate distortion function and applications to
timevarying GaussMarkov processes,"
SIAM Journal on Control and Optimization, Vol. 56, Issue 5, pp. 37313765, 2018.
Full Text 
[5] 
P. A. Stavrou, J. Østergaard, and C. D. Charalambous, "Zerodelay rate distortion via filtering for vectorvalued Gaussian sources,"
IEEE Journal of Selected Topics in Signal Processing, Vol. 12, Issue 5, pp. 841856, October 2018.
Full Text 
[1] 
C. D. Charalambous, P. A. Stavrou, and N. U. Ahmed, "Nonanticipative rate distortion function and relations to filtering theory,"
IEEE Transactions on Automatic Control, Vol. 59, Issue 4, pp. 937952, April 2014.
Full Text 
Conference papers:
[22] 
P. A. Stavrou, T. Charalambous, C. D. Charalambous, S. Loyka and M. Skoglund, Asymptotic reversewaterfilling solution of
nonanticipative rate distortion function for vectorvalued GaussMarkov sources, in proceedings of
IEEE 57th Conference on Decision and Control (CDC), 2018.
Full Text

[21] 
C. D. Charalambous, P. A. Stavrou, C. K. Kourtellaris and I. Tzortzis, "Directed Information subject to a fidelity:
applications to conditionally Gaussian processes," in proceedings of European Control Conference (ECC), 2018.
Full Text

[17] 
M. Barforooshan, J. Østergaard, and P. A. Stavrou, "Achievable performance of zerodelay variablerate coding in rate constrained networked control systems with channel delay," in proceedings of
IEEE Conference on Decision and Control (CDC), 2017.
Full Text 
[15] 
P. A. Stavrou, T. Charalambous, and C. D. Charalambous, "Filtering with fidelity for timevarying GaussMarkov processes," in proceedings of
IEEE 55th Conference on Decision and Control (CDC), 2016.
Full Text 
[11] 
C. D. Charalambous and P. A. Stavrou, "Optimization of directed information and relations to filtering theory,"
in proceedings of 13th European Control Conference (ECC), 2014.
Full Text 
[9] 
C. D. Charalambous and P. A. Stavrou, "On the relation of nonanticipative rate distortion function and filtering theory,"
in proceedings of 12th Biannual European Control Conference (ECC), 2013.
Full Text 

Coordination and Cooperation in Network Topologies
In this research direction, we are interested in coordination and cooperation of nodes (or agents) of an abstract network
topology. We ask fundamental questions such as, how an agent can coordinate its actions with another agent when they communicate, or, what type of coordination
can be established if the communication between two agents is partially lost? There are two types of coordination thus far using information theoretic tools,
empirical and strong coordination. Our research is mainly focused in empirical coordination that can be established using modified techniques from
source coding theory. In addition, we are also interested in understanding strong coordination because this type of coordination seems more
appealing as it takes into account common information between agents which is a fundamental concept to further understand
the cooperation between nodes in multiagent systems.
Selected Publications 
Conference papers:
[27] 
M. Mylonakis, P. A. Stavrou, and M. Skoglund, Remote empirical coordination, in proceedings of
International Symposium on Information Theory and Applications (ISITA), 2020.
Full Text

[25] 
M. Mylonakis, P. A. Stavrou, and M. Skoglund, Empirical coordination with multiple descriptions, in proceedings of
57th Annual Allerton Conference on Communication, Control, and Computing, 2019.
Full Text

[23] 
M. Mylonakis, P. A. Stavrou, and M. Skoglund, Empirical coordination subject to a fidelity criterion, in proceedings of
IEEE Information Theory Workshop (ITW), 2019.
Full Text


Information Theoretic Privacy/Secrecy for Networks
Information theoretic secrecy comprises of a cryptosystem that needs to
be studied using information theoretic tools. This encrypted system cannot be broken even if the eavesdropper/adversary
has unlimited computing power and is considered cryptoanalytically unbreakable if the adversary does not have enough
information to break the encryption. The precursor of the concept of information theoretic secure communication was
Claude Shannon with his seminal paper back in 1949. After that work many notable researchers tried to understand
information theoretic secrecy from different perspectives using different information measures and coding schemes.