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Welcome!

Dr.Chandra. R. MurthyI am a Professor in the department of Electrical Communication Engineering at the Indian Institute of Science, Bangalore, India. My research interests are primarily in the areas of digital signal processing, information theory, estimation theory, and their applications in the optimization of wireless communication systems.

News

  • [21 Jul. 2021]: Lekshmi Ramesh's paper in ISIT 2021 won the IEEE Jack Keil Wolf ISIT Student Paper Award! The paper is: Lekshmi Ramesh, Chandra R. Murthy, Himanshu Tyagi, Multiple Support Recovery Using Very Few Measurements Per Sample, IEEE International Symposium on Information Theory, Melbourne, Australia, July 2021. Click here for the full paper. Video.
  • [25 Jun. 2021]: Yashvanth's proposal titled Intelligent Reflecting Surface Assisted Opportunistic Multi-user Communication won the Qualcomm Innovation Fellowship 2021! Congratulations Yashvanth!
  • [12 Jun. 2021]: A complete set of video lectures and class notes for the Compressed Sensing and Sparse Signal Processing course I offered in the Jan. 2021 term is available here.
  • [31 May 2021]: A complete set of video lectures and class notes for the Matrix Theory course I offered in Fall 2020 is available on the NPTEL website and locally here.
  • [30 Apr. 2021]: Video recording of a talk titled modulo compressed sensing at the ECE Shannon Day is available on YouTube; slides.
  • [12 Feb. 2021]: A video recording of my talk titled “Irregular Repetition Slotted Aloha for Massive Machine-type Communications” at the ECE Webinar Series: here and here.

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Interesting Quotes

“I started with the purely tentative hypothesis that the person who signed the will was not Jeffrey Blackmore. I assumed this; and I may as that I did not believe it at the time, but merely adopted it as a proposition that was worth testing. I accordingly tested it, 'Yes?' Or 'No?' With each new fact; but as each new fact said 'Yes,' and no fact said definitely 'No,' it's probability increased rapidly by a sort of geometrical progression. The probabilities multiplied into one another. It is a perfectly sound method, for one knows that if a hypothesis is true, it will lead one, sooner or later, to a crucial fact by which its truth can be demonstrated.” R. Austin Freeman, "The Mystery of 31 New Inn".


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