Dr. Bekit brings a strong academic foundation and extensive technical expertise to the fields of artificial intelligence and machine learning (AI/ML). With years of experience leading research and development (R&D) for the U.S. Department of Defense (DoD), his work spans AI/ML, signal processing, algorithm design, data fusion, and object tracking — all with a focus on advancing Decision Dominance capabilities.

A creative problem solver and innovative researcher, Dr. Bekit develops cutting-edge technologies and concepts to address some of the nation’s most complex and evolving technical challenges. He also shares his expertise as a lecturer on advanced topics including Deep Learning, Generative AI, Language Models, and Probability and Stochastic Processes.

Dr. Bekit is a proud member of the Johns Hopkins University (JHU) Data Science and Artificial Intelligence (DSAI) Institute.

Education History

  • B.S., Electrical Engineering, University of Maryland at College Park
  • M.S., Electrical Engineering, University of Maryland Baltimore County
  • MBA, Business Administration, Johns Hopkins University
  • M.S., Electrical Engineering, Johns Hopkins University
  • Ph.D., Electrical Engineering, University of Maryland Baltimore County

Publications

A. Bekit, B. Lampe, and C.-I Chang, “Unsupervised Hyperspectral Unmixing Using Compressive Sensing”, The International Society for Optics and Photonics, April 2016.

A. Bekit, B. Lampe, and C.-I Chang, “Unsupervised Hyperspectral Unmixing Using Compressive Sensing”, International Conference on Earth Observations and Societal Impacts, July 2018.

A. Bekit, B. Lampe, and C.-I Chang, Chao-Cheng Wu, “N-FINDER for Finding Endmembers in Compressively Sensed Band Domain” IEEE Transaction on Geoscience and Remote Sensing, October 2019.

A. Bekit, B. Lampe, C. J. Della Porta, C.-I Chang, and B. Xue, “Unsupervised Automatic Target Generation Process via Compressive Sensing”, SPIE, March 2019.

C. J. Della Porta, A. Bekit, B. Lampe, C.-I Chang, “A compressed sensing approach to hyperspectral classification”, May 2019.

C. J. Della Porta, A. Bekit, B. Lampe, and C.-I Chang, “A universal sensing model for compressed hyperspectral image analysis” SPIE, March 2019.

B. Lampe, A. Bekit and C.-I Chang, “Unsupervised Band Selection Using Sparsity and Incoherence”, The International Society for Optics and Photonics, April 2016.

B. Lampe, A. Bekit and C.-I Chang, “A New property of Compressive Sensing for Hyperspectral Data Processing”, International Conference on Earth Observations and Societal Impacts, July 2018.

C. J. Della Porta, A. Bekit, B. Lampe, and C.-I Chang, “Hyperspectral Image Classification Via Compressive Sensing”, IEEE Transaction on Geoscience and Remote Sensing, October 2019.

B. Lampe, A. Bekit, C. J. Della Porta, C.-I Chang, “Restricted Entropy and Spectrum Properties for Compressive Sensing in Hyperspectral Imaging”, IEEE Transaction on Geoscience and Remote Sensing, 2019

Honors and Awards

  • DoD Achievement Award (2022)
  • Leadership Excellence Award (2022)
  • DoD Outstanding Team Achievement Award (2020)
  • DoD Innovation in the Workplace Award (2019)

Professional Organizations

Association for the Advancement of Artificial Intelligence (AAAI)
Neural Information Processing Systems (NIPS) Foundation
Institute of Electrical and Electronics Engineers (IEEE)

Courses

Next Offered
Spring 2026
Waitlist Only
Course Format
Online - Asynchronous
Primary Program
Electrical and Computer Engineering
Location
Online