Siddharth Srinivasan Iyer

Email  /  Github  

I am a first year graduate student in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. I got my undergraduate degree at the University of California, Berkeley.

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Research

I am interested in acquisition and reconstruction problems in Magnetic Resonance Imaging (MRI). I am currently advised by Professor Kawin Setsompop. In Berkeley, I worked under the guidance of Professor Michael Lustig.

Towards a Parameter Free ESPIRiT: Soft Weighting for Robust Coil Sensitivity Estimation.
Siddharth Srinivasan Iyer, Frank Ong and Michael Lustig.
In Proceedings of the International Society for Magnetic Resonance in Medicine, 2016.

Abstract. ESPIRiT is a robust, auto-calibrating approach to parallel MR image reconstruction that estimates the subspace of sensitivity maps using an eigenvalue-based method. While it is robust to a range of parameter choices, having parameters that result in a tight subspace yields the best performance. We propose an automatic, parameter free method that appropriately weights the subspace using a shrinkage operator derived from Stein's Unbiased Risk Estimate. We demonstrate the efficacy of our technique by showing superior map estimation without user intervention in simulation and in-vivo data compared to the current default method of subspace estimation.

Summa Cum Laude awarded.

Links:   Abstract  /  Talk   

T2 Shuffling - Dynamic MRI Dimensionality Reduction
Siddharth Srinivasan Iyer, Jon Tamir and Michael Lustig.

Abstract. MRI is a safe and powerful tool that can be used to image both anatomy and function. Acquiring 3D MRI over time has several clinical applications:

  • Reduce image blur from conventional 3D acquisition.
  • Visualize signal behavior over time.
  • Quantify tissue parameters in anatomy.
  • We aim to find a robust and low-dimensional representation of the dynamic images.

Link:  Poster   


Teaching

EE16B: Designing Information Devices and Systems II, Spring 2017
University of California, Berkeley

  • Co-head content TA with Brian Kilberg.
  • Some videos notes (as a YouTube playlist) made by me and fellow TA Saavan Patel: here.


EE16B: Designing Information Devices and Systems II, Fall 2016
University of California, Berkeley

  • Discussion and content TA.
  • Some videos notes (as a YouTube playlist) made by me and fellow TA Saavan Patel: here.
  • Draft supplemental linear algebra notes I've written: here.
  • Teaching evaluations: here.


EE16B: Designing Information Devices and Systems II, Spring 2016
University of California, Berkeley

  • Discussion and content TA.
  • Teaching evaluations: here.



Website template borrowed and modified from Jon Barron.