Saeid Haghighatshoar

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Postdoctoral Researcher

Communications and Information Theory Group (CommIT)

Technical University Berlin (TU Berlin)

My CV and Research Statement


Einsteinufer 25, 10587 Berlin, HFT 604.

Tel: +49(0)30 314-28461


Fax: +49(0)30 314-28320


TU Berlin Website:

About me

I received my B.Sc. in Electrical Engineering in Electronics (2004-2007) and my M.Sc. in Communication Systems (2007-2009) both from Sharif University of Technology Tehran-Iran.

I received my Ph.D. in Computer and Communication Science from École Polytechnique Fédérale de Lausanne (EPFL) in September 2014. My Advisor was Prof. Bixio Rimoldi. The title of my dissertation is ‘‘Compressed sensing of memoryless sources: a deterministic Hadamard construction’’.

Since January 2015, I am a post-doctoral researcher in the Communications and Information Theory Group (CommIT) in Technische Universität Berlin (TU Berlin) working with Prof. Giuseppe Caire.


I am mainly working at the intersection of information and communication theory, wireless communication and wireless signal processing, compressed sensing, optimization theory and convex analysis. I am interested in developing efficient and low-complexity algorithms to deal with high-dimensional data that arises signal processing application in wireless communication.

A summary of my research interest is as follows:

  • Information theory and wireless communication

  • Compressed sensing and its applications

  • Optimization theory especially convex optimization

  • High-dimensional statistics

Past Research

During my Ph.D. I mainly worked on designing deterministic and structured matrices that yield high-speed acquisition and recovery algorithms for compressed sensing. The title of my thesis was ‘‘Compressed sensing of memoryless sources: a deterministic Hadamard construction’’. An unofficial PDF version of my thesis is available here. A list of topics that I studied includes:

  • designing deterministic partial Hadamard matrices (matrices obtained by selecting a subset of rows of Hadamard matrices) for compressed sensing of sparse signal

  • designing Walsh-Hadamard sketches for sparse signals

  • designing partial Hadamard matrices for integer-valued sources

  • study of multi-terminal compressed sensing for distributed signals.

Current Research

My current research focuses on designing efficient and low-complexity algorithms for signal processing (e.g., signal acquisition, subspace estimation, and user clustering, etc.) in massive MIMO systems. Massive MIMO is a special case of MIMO where a base-station is equipped with very large number of antennas.

There are many interesting mathematical problems that arise because of the stochastic nature of the channel and high-dimensional structure of the signal because of using many number of antennas. This relates my research to other research areas such as:

  • high-dimensional statistics

  • optimal experiment design

  • compressed sensing

  • optimization theory

  • convex analysis.