Khizar Anjum is a systems-focused AI researcher and engineer finishing a PhD in Computer Engineering at Rutgers, with eight years of experience building ultra-low-power neural networks, resource-constrained deep learning for drones/FPGAs, and resilient underwater joint source-channel coding. He invented the Folded Neural Network and CvPU to run continuous physiological signal processing at microwatt budgets, co-created the first real-world underwater acoustic dataset (ACommSet), and holds two international patents plus a publication in IEEE JSAC. Khizar has a track record of translating research into deployable systems—real-time 16 FPS video at 2.3 kbps underwater, 40x FPGA speedups for UAV fault detection, and ML models trained on NERSC’s Perlmutter—backed by $1.135M in NSF funding and 16 peer-reviewed publications. Now based in New York and working on deepfake video detection at Pindrop, he’s seeking applied ML/AI, embedded AI, or MLOps roles where tight hardware-software tradeoffs matter.
8 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Electrical and Electronics Engineering, Gold Medalist, Bachelor of Science - BS, Electrical and Electronics Engineering, Gold Medalist at Lahore University of Management Sciences
Doctor of Philosophy - PhD, Computer Engineering, Doctor of Philosophy - PhD, Computer Engineering at Rutgers University
Yet Another Repository for controlling Bebop/Bebop2 over Wifi and USB-Ethernet
Contributions:2 PRs, 4 pushes, 1 branch in 4 months
openflowusbntpcontrollingyet-another
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Khizar Anjum - AI Research Engineer at Rutgers University