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Mohammed Shoaib

RESEARCHER

 

99/2613, Microsoft Research
1 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 Sensing and Energy Research Group at MSR, Redmond.

I build efficient computing systems for the internet-of-things (IoT). In particular, I am interested in developing networked sensing platforms and specialized hardware processors for portable devices. My work applies various techniques of deep/shallow machine learning, signal processing and VLSI design to this problem domain.

As part of my doctorate thesis, I developed energy-efficient sensing systems that are able to compute directly on compressed data. I received the Ph.D. and M.A. degrees in Electrical Engineering from Princeton University in 2013 and 2010, respectively. I 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.

Projects

 

I enjoy working at the level of both software (C++, C#, Python, Matlab) and hardware (accelerator architectures, RTL design) implementations. At Microsoft, I primarily work on developing energy-efficient devices and IP for machine-learning with IoT data.

The following are my active projects:

- Wearable activity tracking using low-power and high-precision body area networks
- Context aware SoC applications with real-time object recognition and detection on streaming media
- Cloud infrastructure design methodologies that exploit heterogeneity and variability in server hardware

Recent Publications

    • X. Zhan, M. Shoaib and S. Reda, “Creating Soft Heterogeneity in Clusters Through Firmware Re-configuration”, Int. Symp. Cluster, Cloud and Grid Computing (CCGrid) May 2016

    • M. Gottscho, S. Govindan, B. Sharma, M. Shoaib and P. Gupta, “X-Mem: A Cross-Platform and Extensible Memory Characterization Tool for the Cloud”, Int. Symp. Performance Analysis of Systems and Software (ISPASS) Apr. 2016

    • S. Desai, M. Shoaib and A. Raychowdhury, "An ultra-low power, always-on camera front-end for posture detection in body worn cameras using Restricted Boltzmann Machines" IEEE Transactions on Multi-Scale Computing Systems, 2016

    • M. Shoaib, S. Venkataramani, X-S Hua, J. Liu, and J. Li, "Exploiting on-device image classification for energy efficiency in ambient-aware systems", Book chapter in Springer Mobile and Cloud Visual Media Computing Jan. 2016

    • V. Beharavan, S. Li, N. E. Glover, D. Chen, M. Shoaib, G. C. Temes and P. Y. Chiang, "A compressed-sensing sensor-on-chip incorporating statistics collection to improve reconstruction performance", IEEE Custom Integrated Circuits Conf. (CICC) Sep. 2015

    • S. Desai, M. Shoaib, and A. Raychowdhury, "An ultra-low power always-on camera front-end for posture detection in body-worn cameras using RBMs", IEEE Symposium on Low Power Electronic Design (ISLPED), Aug. 2015
    • V. Behravan, N. E. Glover, R. Farry, P. Y. Chiang, and M. Shoaib, "Rate-adaptive compressed-sensing and sparsity variance of biomedical signals", IEEE Body Sensor Networks (BSN) Conf. Jun. 2015
    • S. Venkataramani, J. Liu, A. Raghunathan, and M. Shoaib, "Scalable-effort classifiers for energy-efficient machine learning", IEEE Design Automation Conference (DAC) Jun. 2015
    • S. Venkataramani, V. Bahl, X. Hua, J. Liu, J. Li, M. Phillipose, B. Priyantha, and M. Shoaib, "SAPPHIRE: An always-on context-aware computer vision system for portable devices", IEEE Conf. Design Automation and Test in Europe (DATE) Mar. 2015
    • M. Shoaib, N. K. Jha, and N. Verma, “Signal processing with direct computations on compressively-sensed Data", IEEE Transactions on VLSI (TVLSI) Systems, Jan. 2015
    • M. Shoaib, J. Liu, and M. Phillipose, "Energy scaling in multi-tiered sensing systems through compressive sensing", IEEE Custom Integrated Circuits Conference (CICC), Sep. 2014 (best paper award nomination)
    • 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, “Algorithm-driven hardware-specialized architecture for low-energy biomedical sensor platforms,” IEEE Transactions on VLSI (TVLSI) Systems, Oct. 2013
    • M. Shoaib, G. Marsh, H. Garudadri, and S. Majumder, “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, "A compressed-domain processor for seizure detection to simultaneously reduce computation and communication energy", IEEE Custom Integrated Circuits Conference (CICC), Sep. 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

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 groups:

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

Service

 

I have served as a committee member and reviewer of the following events and journals:

  • IEEE Transactions on Circuits and Systems (TCAS), VLSI Systems (TVLS), Biomedical Engineering (TBME), and Biomedical Circuits and Systems (TBCAS).
  • Design Automation Conference (DAC) 2014
  • International Conference on Information Processing in Sensor Networks (IPSN) 2014
  • Cyber-physical Systems (CPS) Week 2015
  • Embedded Systems (ES) Week 2015: IoT Systems Track