Asim Mazin, Ph.D.

Asim Mazin, Ph.D.

Asim M. Mazin, Ph.D.

Summary

Engineering doctoral graduate possesses a strong technical background, excellent verbal and written communication skills

Education

  • Ph.D., Electrical Engineering, University of South Florida, Tampa, FL, May 2019
  • M.Sc., Electrical Engineering, Southern Illinois University, Carbondale, IL, May 2013
  • B.Sc., Electrical Engineering, College of Industrial Technology, Misurata, Libya, May 2007

Experience

Qualcomm Technologies, Inc. , San Diego, CA
5G SW Applications Engineer, Sep 2020 - Present
H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL
Applied Post-Doctoral Fellow, Aug 2019 - Sep 2020
  • Development of differential diagnostics for cancer by machine learning on multiparameter Magnetic Resonance Imaging (mpMRI) and digitized multiplexed immunohistochemistry (MIHC) images.
    • Processed 43GB of MHIC image data
    • Applied SOM-LVQ on the processed data of three panels (Each has six tissue microarrays (TMA)) for ~407 patients to predict whether the patient is long term survival or short term survival
    • Using a self-organized map (SOM) to reduce the dimensionality and create activation map form multiparameter MRI of 34 patients
    • Classify the tumors type from the activation maps using Learning Vector Quantization (LVQ) with an accuracy of 70%
University of South Florida, Tampa, FL
Graduate Assistant/Researcher, iWINLAB, May 2016 - May 2019
  • Machine Learning in 5G Wireless Networks (Initial Access)
    • Addressed the initial access in 5G Millimeter wave bands cellular systems using Recurrent Neural Network (GUR)
    • Learn and predict the user’s distribution from call detail records (CDRs) of Milano city dataset
    • Achieving a high accuracy in prediction the sweeping hopping pattern to send the synchronization signals
  • Anticipatory/proactive mobility management in 5G Coordinated Multipoint (CoMP)
    • Supportive technology for cell-less networks.
    • Achieve High data rates independent of the user location by Enabling Dynamic CoMP
    • Proactively knowing the BSs that will be joining/ leaving the CoMP set as the user moves across the network
  • Physical layer security for 5G/IoT systems
    • A novel method is proposed to exchange a secret key between two legitimate users using physical layer security methods
    • Achieved high secure communication when the main and eavesdropping channels are uncorrelated
  • Multiple access for IoT networks
    • Design M2M medium access protocol Slotted Aloha- NOMA (SAN).
    • Low complexity and substantial throughput gain of 5.5 dB relative to slotted Aloha.
  • Ultra-Low latency in 5G Network
    • A Bayesian game cell selection / user association approach was proposed to achieve the ultra-low latency (1ms) in 5G Networks
    • Attains the 5G low end-to-end latency target (1ms) with a probability exceeding 80%.
Teaching Assistant, Electrical Enginiring Department, Aug 2016 - May 2019
  • Delivering lectures in Digital Communication & Wireless Networks and architecture courses
  • Preparing exams, grading assignments and exams, and setting up distance learning technology in the classroom
Academic Tutor, INTO USF Tutoring Center, Aug 2014 - Dec 2018
  • Tutor Electrical Engineering courses in wireless & signal processing area.
  • Lead a policy and procedure committee to revise the vision and mission statements of INTO touring center and mentor new tutors.
College of Industrial Technology
Teaching Assistant, Jul 2007 - Feb 2010
  • Preparing tutorials and providing helping sessions in the following undergraduate courses:
    • Physics
    • Mathematics
    • Electrical and electronic circuits
    • Digital communication systems
    • Signals and systems

Selected Achievements

  • Published 9 articles to IEEE conferences
  • College of Engineering Research Day Poster Award, 2016
  • Tutor Excellent award 2015 and 2017

Publications

  1. A. Mazin, et al, “Identification of Sarcomatoid De-Differentiation in Renal Cell Carcinoma by Machine Learning on Multiparametric MRI,” Oral presentation at the scientific sessions of the ISMRM 28th Annual Meeting & Exhibition.
  2. A. Mazin, M. Elkourdi and R. D. Gitlin, “SAN- Slotted Aloha-NOMA a MAC Protocol for M2M Communications,” Information Theory and Applications (ITA 2019): San Diego, February 11-15, 2019.
  3. M. Elkourdi, A. Mazin and R. D. Gitlin, “Performance Analysis for Virtual-Cell Based CoMP 5G Networks Using Deep Recurrent Neural Nets,” the 18th annual Wireless Telecommunications Symposium (WTS 2019), New York City, NY, USA, April 9-12, 2019.
  4. A. Mazin, M. Elkourdi and R. D. Gitlin, “Comparative Performance Analysis of Beam Sweeping Using a Deep Neural Net and Random Starting Point in mmWave 5G New Radio,” (UEMCON) 2018, New York City, NY, USA, November 8-9, 2018.
  5. M. Elkourdi, A. Mazin and R. D. Gitlin, “Optimization of 5G Virtual Cell Based Coordinated Multipoint Networks Using Deep Machine Learning,” International Journal of Wireless & Mobile Networks (IJWMN) Vol. 10, No. 4, August 2018.
  6. A. Mazin, M. Elkourdi and R. D. Gitlin, “Accelerating Beam Sweeping in mmWave Standalone 5G New Radios using Recurrent Neural Networks,” (VTC2018-Fall), Chicago, IL, USA
  7. A. Mazin, M. Elkourdi and R. D. Gitlin, “Comparison of Slotted Aloha-NOMA and CSMA/CA for M2M Communications in IoT Networks,” (VTC2018-Fall), Chicago, IL, USA
  8. M. Elkourdi, A. Mazin and R. D. Gitlin, “Slotted Aloha-NOMA with MIMO Beamforming for Massive M2M Communication in IoT Networks,” (VTC2018-Fall), Chicago, IL, USA
  9. M. Elkourdi, A. Mazin, Eren Balevi and R. D. Gitlin, “Enabling Slotted Aloha-NOMA for Massive M2M Communication in IoT Networks,” IEEE 19th Wireless and Microwave Technology Conference (WAMICON), April 2018
  10. M. Elkourdi, A. Mazin and R. D. Gitlin “Towards Low Latency in 5G HetNets: A Bayesian Cell Selection / User Association Approach,” IEEE 5G World Forum (5GWF’18) July 9-11, 2018 in Santa Clara, CA, USA
  11. A. Mazin, K. Davaslioglu, and R. D. Gitlin, “Secure Key Management Using Physical Layer Security for 5G Networking,” IEEE 18th Wireless and Microwave Technology Conference (WAMICON), April 2017
  12. A. Mazin and Crosby, Garth V. “Reducing the Peak to Average Power Ratio of MIMO-OFDM Systems.” International Journal of Computer Networks & Communications (IJCNC) Vol.5, No.3, May 2013

Patents

  1. US Patent No. US 10,587,999 B2, Enabling slotted Aloha-NOMA for massive machine-to-machine (M2M) communication in internet of thing (IoT) networks, March 10, 2020.
  2. US Patent No. US 10,327,123 B1, System and Method for Machine-to-Machine Communication in an Internet-of-Things Network, June 18, 2019.

Certificates

  • SQL for Data Science,
  • Sequence Models
  • Improving Deep Neural Networks: Hyper-parameter tuning, Regularization and Optimization
  • Structuring Machine Learning Projects
  • Convolutional Neural Network
  • Neural Networks and Deep Learning
  • Certified Tutor II: CRLA’s International Tutor Training Program Certification