Mohammed Shoaib

RESEARCHER

 

99/2613, Microsoft Research
One Microsoft Way,
Redmond, WA 98052

 

Phone: (425) 421-7114
Fax: (425) 936-7329

Email: myfirstname DOT mylastname AT microsoft DOT com

Background

 

I am a member of the of the Sensing and Energy Research Group at MSR, Redmond. 

I specialize in computer engineering. My work touches upon various aspects of signal processing, machine learning, and low-power sensing systems. I am particularly inclined towards making portable devices more efficient both in terms of energy and performance. Broadly, the following are my current research interests:

    • Energy-efficient computational platforms for portable devices
    • VLSI systems for sparse signal processing and compressive sensing
    • Robust algorithms and architectures for machine learning
    • Acceleration of networking and multimedia applications

My Ph.D. thesis was on the design of energy-efficient sensing systems with direct computations on compressively-sensed data. In the past, I have received the B.Tech. and M.Tech. dual degree in electrical engineering with a specialization in microelectronics and VLSI design from the Indian Institute of Technology (IIT), Madras in 2008. I have also received the M.A. and Ph.D. degrees in Electrical Engineering from Princeton University in 2010 and 2013, respectively.

Projects

 

I enjoy designing and building (hardware and software) systems, circuits, and devices. The following is a list of my current projects:

    • Sparsity-driven active sensing front-ends for context-aware SoC applications
    • Algorithms and VLSI architectures for (energy and performance) efficient machine-learning through cascaded data processing
    • Alternate inference algorithms that provide insight through multi-device sensing
    • Tools that exploit hardware variability  and heterogeneity for efficient cloud-server design

Selected Publications

 
  • M. Shoaib, K-H. Lee, N. K. Jha, and N. Verma, "0.6-107 µW energy-scalable processor for directly analyzing compressively-sensed EEG", IEEE Transactions on Circuits and Systems (TCAS) - 1, Apr. 2014.
  • M. Shoaib, N. K. Jha, and N. Verma, “Signal Processing with Direct Computations on Compressively-sensed Data", IEEE Transactions on VLSI (TVLSI) Systems, Feb. 2014
  • M. Shoaib, N. K. Jha, and N. Verma, “Algorithm-driven hardware-specialized architecture for low-energy biomedical sensor platforms,” IEEE Transactions on VLSI (TVLSI) Systems, Oct. 2013.
  • M. Shoaib, N. K. Jha, and N. Verma, “A compressed-domain processor for seizure detection to simultaneously reduce computation and communication energy,” IEEE Custom Integrated Circuits Conference (CICC), Sep. 2012.
  • M. Shoaib, G. Marsh, H. Garudadri, and S. Majumdar, “A closed-loop system for artifact mitigation in ambulatory electrocardiogram monitoring,” IEEE Design Automation and Test in Europe (DATE) Conference, Mar. 2012.
  • M. Shoaib, N. K. Jha, and N. Verma, “Enabling advanced inference on sensor nodes through direct use of compressively-sensed signals,” IEEE Design Automation and Test in Europe (DATE) Conference, Mar. 2012.
  • M. Shoaib, N. K. Jha, and N Verma, “Sub-threshold computational circuits for high-order data-driven analysis of physiological signals,” Sub-threshold Microelectronics Conference, Sept. 2011.

Communities

 

I am a member of the IEEE and ACM. While I am interested in working across multiple disciplines, my interests are particularly aligned with the following research communities:

  • IEEE Circuits and Systems Society, Computer Society, Signal-processing Society
  • ACM SIGMOBILE, SIGBED

Service

 

The following is my past/current participation:

  • Reviewer: TCAS-II, TVLSI, DAC, TBME, and TBCAS
  • Member of organizing/program committee: CPS Week 2015, IPSN 2014