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 researcher working in the Sensing and Energy Research Group at MSR, Redmond. 

I specialize in computer engineering. My research interests lie at the crossroads of signal processing, machine learning, and low-power sensing systems. I am particularly interested in making portable devices more efficient both in terms of energy and performance. The following are my current research interests:

    • Energy-efficient computation platforms for portable devices
    • Hardware systems for machine learning and compressive sensing
    • Robust algorithms and architectures for VLSI signal-processing systems
    • 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

 

In general, I am interested in designing and building hardware devices. The following is a list of some of my current projects:

    • Active Multimedia Front-ends for Data Processing in Context-aware SoC Applications
    • Reconfigurable Computing Platforms for Real-time Audio/Video Processing
    • Energy-efficient Architectures for Multi-device Sensing
    • Data-driven Platforms for Personal and Commercial Vehicular Navigation

Selected Publications

 
  • M. Shoaib, N. K. Jha, and N. Verma, “Signal Processing with Direct Computations on Compressively-sensed Data", IEEE Transactions on VLSI Systems (TVLSI), to appear.
  • 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, to appear.
  • M. Shoaib, N. K. Jha, and N. Verma, “Algorithm-driven hardware-specialized architecture for low-energy biomedical sensor platforms,” IEEE Transactions on VLSI Systems (TVLSI), 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 professional member of the IEEE and the 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
  • IEEE Computer Society
  • IEEE Signal Processing Society
  • ACM SIGBED

Service

 

The following is my past/current participation:

  • Reviewer: TVLSI, DAC, TBME, and TBCAS
  • Organizing Committee: IPSN 2014