Alireza Bagheri

Hi there! Welcome to my homepage.

I have successfully completed my Ph.D. degree in Electrical Engineering at New Jersey Institute of Technology (NJIT), Newark, NJ. I have been fortunate to work under the guidance of Professor Osvaldo Simeone and Professor Bipin Rajendran. I have been a member of the Elisha Yegal Bar-Ness Center for Wireless Information Processing (CWiP).

News!

Here is my PhD dissertation.
@April 2019, I have successfully passed my PhD dissertation defense!
@March 2019, I have attended the 7th Neuro-Inspired Computational Elements (NICE 2019) workshop series at IBM in Albany, NY, including tutorial platfroms for Loihi (Intel) and SpiNNaker (University of Manchester).
@March 2019, I have attended the 4th Fruit Fly brain Hackathon (FFBH 2019) workshop at Columbia University, NY.
@Januery 2019, I have attended the iJOBS SciPhD Workshop: Leadership and Business Skills for Scientists at Rutgers University, NJ.
@Januery 2019, I have attended the iJOBS Workshop: Computing Skills for Genomic Research at Rutgers University, NJ.
@June 2018, I have attended the MPI workshop at Claremont Graduate University, CA.
@May 2018, I have attended the NASIT workshop at the campus of Texas A&M University, TX.
@April 2018, My paper has been accepted for publication in the IEEE SPAWC.
@January 2018, My paper has been accepted for publication in the IEEE ICASSP.
@September 2017, I attended in Intel Nervana AI Academy Deep Learning Technical Seminar at NJIT, NJ.
@June 2017, I took participate in a 5-day Mathematical Problems in Industry (MPI) workshop at NJIT, NJ.
@April 2017, My co-authored journal paper was published in the IEEE TVT!
@February 2017, My co-authored journal paper was published in the IEEE TSIPN!
@January 2016, I attended the Apache Hadoop in one day workshop presented by Dr Douglas Eadline at NJIT, NJ.

Research Interesets

  • Machine learning: My current research interests focus on developing biology-inspired learning methods for probabilistic neural networks. My overall research goal is the establishment of a theoretical framework to enable the design of flexible spike-domain learning algorithms that are tailored to the solution of supervised and unsupervised cognitive tasks.
  • Wireless communications: My past research experience has been in the areas of design and performance analysis of wireless networks and wireless communication systems including:
    • Mobile Cloud Computing
    • Cognitive radio networks
    • Cooperative communications
    • Cellular networks
    • Experiments on embedded system platforms
  • Optimization theory

Education

Karaj Islamic Azad University (KIAU)

2005 - 2009

Bachelor of Science in Electrical Engineering
GPA: 16.76 / 20
Class rank: 6 / 128

Semnan University

2010 - 2013

Master of Science in Electrical Engineering
GPA: 17.62 / 20
Class rank: 1 / 9

New Jersey Institute of Technology (NJIT)

2015 - 2019

Doctor of Philosophy in Electrical Engineering
GPA: 3.83 / 4

Publications

Google Scholar Profile

Journal papers

  1. A Comprehensive Framework for Spectrum Sensing in Non-Linear and Generalized Fading Conditions

    P.C. Sofotasios, A. Bagheri, T.A. Tsiftsis, S. Freear, A. Shahzadi and M. Valkama
    IEEE Transactions on Vehicular Technology, vol. 66, issue 10, pp 8615-8631, Octobor 2017.

  2. Joint Uplink/Downlink Optimization for Backhaul-Limited Mobile Cloud Computing with User Scheduling

    A. AL-Shuwaili, O. Simeone, A. Bagheri and G. Scutari
    IEEE Transactions on Signal and Information Processing over Networks, vol. 3, issue 4, pp 787-802, December 2017.

  3. Another look at performance analysis of energy detector with multichannel reception in Nakagami-m fading channels

    A. Bagheri and A. Shahzadi
    Wireless personal communications, vol. 79, issue 1, pp 527-544, November 2014.

Conference papers

  1. Adversarial Training for Probabilistic Spiking Neural Networks

    A. Bagheri, O. Simeone, and B. Rajendran
    Accepted for publication in the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2018.

  2. Training Probabilistic Spiking Neural Networks with First-to-spike Decoding

    A. Bagheri, O. Simeone, and B. Rajendran
    Accepted for publication in the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018.

  3. Energy detection based spectrum sensing over enriched multipath fading channels

    A. Bagheri, P.C. Sofotasios, T.A. Tsiftsis, K. Ho-Van, M.I. Loupis, S. Freear and M. Valkama
    IEEE Wireless Communications and Networking Conference (WCNC), Doha, Qatar, 3-6 April 2016.

  4. Joint uplink/downlink and offloading optimization for mobile cloud computing with limited backhaul

    A.N. Al-Shuwaili, A. Bagheri and O. Simeone
    IEEE Conference on Information Science and Systems (CISS), Princeton, NJ, USA, 16-18 March 2016.

  5. Area under ROC curve of energy detection over generalized fading channels

    A. Bagheri, P.C. Sofotasios, T.A. Tsiftsis, A. Shahzadi, S. Freear and M. Valkama
    IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Hong Kong, China, 30 August-2 September 2015.

  6. Spectrum sensing in generalized multipath fading conditions using square-law combining

    A. Bagheri, P.C. Sofotasios, T.A. Tsiftsis, A. Shahzadi and M. Valkama
    IEEE International Conference on Communications (ICC), London, UK, 8-12 June 2015.

  7. AUC study of energy detection based spectrum sensing over η-μ and α-μ fading channels

    A. Bagheri, P.C. Sofotasios, T.A. Tsiftsis, A. Shahzadi and M. Valkama
    IEEE International Conference on Communications (ICC), London, UK, 8-12 June 2015.

  8. An analytical model for primary user emulation attacks in IEEE 802.22 networks

    S. Tabatabaee, A. Bagheri, A. Shahini and A. Shahzadi
    IEEE International Conference on Connected Vehicles and Expo (ICCVE), Las Vegas, NV, USA, 2-6 December 2013.

  9. A unified approach to performance analysis of energy detection with diversity receivers over Nakagami-m fading channels

    A. Shahini, A. Bagheri and A. Shahzadi
    IEEE International Conference on Connected Vehicles and Expo (ICCVE), Las Vegas, NV, USA, 2-6 December 2013.

  10. Analytical and learning-based spectrum sensing over channels with both fading and shadowing

    A. Bagheri, A. Shahini and A. Shahzadi
    IEEE International Conference on Connected Vehicles and Expo (ICCVE), Las Vegas, NV, USA, 2-6 December 2013.

  11. Cooperative Spectrum Sensing over κ- μ Fading Channel

    A. Bagheri and A. Shahzadi
    IEEE International Conference on Broadband, Wireless Computing, Communication and Applications (BWCCA), Victoria, BC, Canada, 12-14 November 2012.

Contact

Office Address: The Elisha Yegal Bar-Ness Center for Wireless Information Processing(CWiP) lab,
ECE department, New Jersey Institute of Technology (NJIT), University Heights, 07102 Newark, NJ, USA.
E-mail address: ab745 at njit dot edu