Wikipedia

Yehia Massoud

Yehia Massoud has had significant progressive academic leadership and has been involved in forging and building effective partnerships with numerous academic and industrial institutions, and international organizations, and governmental funding agencies.

Yehia Massoud
NationalityAmerican
EducationMIT (PhD)
Alma materMassachusetts Institute of Technology
AwardsIEEE Fellow
Scientific career
FieldsHigher Education, Computer Science, Electrical and Computer Engineering, Systems Engineering,
InstitutionsStevens Institute of Technology, Stanford University, MIT, WPI, Rice University
Websitehttps://yehiamassoud.com/

Education

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He received his Ph.D. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology.[1]

Career

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He was a Group Leader in the Advanced Technology Group at Synopsys Inc. in Mountain View, CA from 1999 to 2003, where he was awarded the Synopsys Special Recognition Engineering Award. He later joined Rice University in 2003 and became one of the fastest Rice faculty to be granted tenure in the department of Electrical Engineering and the Department of Computer Science in 2007. He was the ECE Department Head at WPI from 2012 to 2017.[2] He strongly advocated for dynamic curricula that combine foundational competencies and knowledge breadth, along with a vibrant innovation mindset. During his five-year term as the department head, the department saw an unprecedented growth in research expenditures, research output, industrial partnerships, undergraduate and graduate student enrollments, unrestricted funds and gifts, and the visibility and recognition of the department, along with a 26-position improvement in the department rankings by U.S. News & World Report.

Awards

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He was selected as one of the ten MIT Alumni featured by the EECS department at MIT in 2012.[3] He was a recipient of the Rising Star of Texas Medal in 2007, the National Science Foundation CAREER Award in 2005,[4] the DAC fellowship and the Synopsys Special Recognition Engineering Award. He has been selected to the IEEE CAS Awards Nomination Committee, the IEEE Mac Valkenburg Award Selection Committee,[5] the IEEE Nanotechnology Council, the IEEE Rebooting Computing Steering Committee, the IEEE ISCAS Steering Committee, and the IEEE/ACM GLSVLSI Steering Committee, as well as an official nominee for the Japan Prize.[6]

Research

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He is a Fellow of the IEEE and was named a Distinguished Lecturer by the IEEE Circuits and Systems Society.[7] He has served as the Editor of the Mixed-Signal Letters - the Americas, as an Associate Editor of the IEEE Transactions on Very Large Scale Integration Systems,[8] and the IEEE Transactions on Circuits and Systems I,[9] as well as a Guest Editor of a special issue of the IEEE TCAS-I. He also served as the 2016 IEEE MWCAS Technical Program Co-chair,[10] as well as the 2009 General Program Co-chair and the 2007 Technical Program Co-chair of the ACM Great Lakes Symposium on VLSI.[11] He received several Best Paper Award Nominations and two Best Paper Awards at the 2007 IEEE International Symposium on Quality Electronic Design and the 2011 IEEE International Conference on Nanotechnology. He has been a PI or a Co-PI on more than $28 Million of funded research from the NSF, DOD, SRC, and the industry.

Massoud has published more than 300 papers in leading peer-reviewed journals and conference publications. Hit research include machine learning, autonomous vehicles, healthcare systems, smart cities, intelligent transportation systems, and smart and embedded systems. Massoud's research group at Rice University [7][8][9] was responsible for developing the world's first realization of compressive sensing systems for signals.[12][13][14][15] This DARPA-funded project provided an unprecedented one order of magnitude savings in power consumption and significant reductions in size and cost and has enabled the implementation of self-powered sensors for smart cities and ultra-low power biomedical implantable devices.[16][17][18]

References

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  1. ^ Massoud, Yehia Mahmoud (1999). Simulation algorithms for inductive effects (Thesis). Massachusetts Institute of Technology. hdl:1721.1/80593.
  2. ^ "Worcester Polytechnic Institute", Wikipedia, 2019-05-14, retrieved 2019-06-14
  3. ^ "Yehia Massoud, MIT PhD '99 | MIT EECS". eecswebdev.mit.edu. Retrieved 2019-06-14.
  4. ^ "Awards support developing careers of young engineers". news.rice.edu. Retrieved 2019-06-14.
  5. ^ "Mac E. Van Valkenburg Award | IEEE Education Society". ieee-edusociety.org. Retrieved 2019-06-14.
  6. ^ "ジャパンプライズ（Japan Prize/日本国際賞）". www.japanprize.jp. Retrieved 2019-06-14.
  7. ^ "Past DLP Lectures | IEEE CAS". ieee-cas.org. Retrieved 2019-06-14.
  8. ^ "IEEE Transactions on Very Large Scale Integration Systems". IEEE. Retrieved 2019-06-14.
  9. ^ "IEEE Transactions on Circuits and Systems I". tcas1.polito.it. Retrieved 2019-06-14.
  10. ^ "Technical Program Committee – 2016 IEEE 59th International Midwest Symposium on Circuits and Systems". Retrieved 2019-06-14.
  11. ^ "GLSVLSI 2019 Washington, D.C., USA". glsvlsi.org. Retrieved 2019-06-14.
  12. ^ US 8687689, Baraniuk, Richard; Baron, Dror Z. & Duarte, Marco F. et al., "Method and apparatus for on-line compressed sensing", published 2014-04-01, assigned to William Marsh Rice University 
  13. ^ Laska, J. N.; Kirolos, S.; Duarte, M. F.; Ragheb, T. S.; Baraniuk, R. G.; Massoud, Y. (May 2007). "Theory and Implementation of an Analog-to-Information Converter using Random Demodulation". 2007 IEEE International Symposium on Circuits and Systems. pp. 1959–1962. doi:10.1109/ISCAS.2007.378360. ISBN 978-1-4244-0920-4. S2CID 17401815.
  14. ^ Kirolos, S.; Laska, J.; Wakin, M.; Duarte, M.; Baron, D.; Ragheb, T.; Massoud, Y.; Baraniuk, R. (October 2006). "Analog-to-Information Conversion via Random Demodulation". 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software. pp. 71–74. CiteSeerX 10.1.1.131.9104. doi:10.1109/DCAS.2006.321036. ISBN 1-4244-0669-2. S2CID 8418279.
  15. ^ Laska, J.; Kirolos, S.; Massoud, Y.; Baraniuk, R.; Gilbert, A.; Iwen, M.; Strauss, M. (October 2006). "Random Sampling for Analog-to-Information Conversion of Wideband Signals". 2006 IEEE Dallas/CAS Workshop on Design, Applications, Integration and Software. pp. 119–122. CiteSeerX 10.1.1.154.4821. doi:10.1109/DCAS.2006.321048. ISBN 1-4244-0669-2. S2CID 12879662.
  16. ^ Wilhelm, K.; Massoud, Y. (May 2012). "Compressive sensing based classification of intramuscular electromyographic signals". 2012 IEEE International Symposium on Circuits and Systems. pp. 273–276. doi:10.1109/ISCAS.2012.6271873. ISBN 978-1-4673-0219-7. S2CID 28872741.
  17. ^ Smaili, S.; Massoud, Y. (June 2014). "Multi-channel random demodulation for hardware efficient compressive sensing". 2014 IEEE 12th International New Circuits and Systems Conference (NEWCAS). pp. 177–180. doi:10.1109/NEWCAS.2014.6934012. ISBN 978-1-4799-4885-7. S2CID 10816437.
  18. ^ Smaili, S.; Massoud, Y. (June 2014). "Accurate and efficient modeling of random demodulation based compressive sensing systems with a general filter". 2014 IEEE International Symposium on Circuits and Systems (ISCAS). pp. 2519–2522. doi:10.1109/ISCAS.2014.6865685. ISBN 978-1-4799-3432-4. S2CID 21902968.
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