Selected Presentations

  • An Information Theoretic View of Cache-Aided Communication, Compression, and Computation Systems
    Keynote talk at GlobalSIP, Dec. 2015.

  • Constrained Intra-Cell and Inter-Cell Cooperation in Cellular Networks
    ETH Zurich, August 2015.

  • Coordination in State-Dependent Networks: The Two-User Case
    ISIT 2015.

  • Communication, Compression, and Coordination over Networks: Benefits of Cooperation and Side-Information
    Habilitation Exam; July 2015.

  • Broadcasting with Side-Information and Applications to Caching and Feedback Communication
    Huawei Algorithmic Research Lab; ETIS ENSEA-Université de Cergy-Pontoise; INSA Lyon; May--Sep. 2015.

  • How Rate-Limited Feedback Increases Capacity for Memoryless Broadcast Channels
    EPF Lausanne; Supelec; Feb. 2014.

  • Schemes and Achievable Rates for Broadcast Channels with Rate-Limited Feedback
    ETH Zurich, Aug. 2013.

  • Variations of Source Coding with Side-Information at the Decoder(s)
    Chalmers University of Technology Gothenburg, May 2013.

  • Max-Entropy Results under Markov Conditions and Applications to Capacity Problems
    Technion-The Israel Institute of Technology, June 2011.

  • Constrained Wyner-Ziv Source Coding
    Technical University Munich, Mar. 2011.

  • An Achievable Region for the Discrete Memoryless Broadcast Channel with Feedback
    ISIT 2010.

  • Gaussian Multiple-Access Channels with Cooperating Transmitters
    Stanford University; UC Berkeley; 2009

  • Receivers-Transmitters Side-Information Duality in Linear Interference Networks
    2009 ITA Workshop, Graduation Day; Qualcomm; 2009

  • Side-Information with a Grain of Salt
    Harvard University; Princeton University; Telecom Paris-Tech (ENST); 2009

  • Cooperation on the Multiple-Access Channel
    Chalmers University of Technology; ETH Zurich (PhD Defense); 2008

  • Wireless Networks with Imperfect Side-Information
    Ecole Superieure d'Electricite (Supelec); KTH Stockholm; Chalmers University of Technology; 2008

  • On Cognitive Interference Networks
    UC Berkeley, 2007

  • Noisy feedback is strictly better than no feedback
    Kailath Colloquium on Feedback Communications 2006, Stanford University