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Expert Witness Code 6790
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Professional Summary: This Ph.D. designs and models conventional and biologically inspired computational systems. He understands various structural and functional aspects of the brain to implement hardware/software computational models that address the von Neumann bottleneck, and develops architectural tools to address the semantic gap between neural algorithms and contemporary neuromorphic architectures. He has a deep knowledge of traditional neural networks particularly in the space of continuous monitoring and analysis of digital and analog sensor data. |
Expertise:
§ Embedded Hardware – Verilog HDL design, efficient neural systems design, pre/post synthesis validation, FPGA prototyping
§ Embedded Software – Embedded software (C/C++) for complex sensor data analysis in smartphones/wearables, sensor drivers, power and memory footprint optimizations
§ Neuromorphic Systems – Brain inspired hardware/software system design and neural networks
§ Smart Devices – Sensor fusion, “Always-on” sensing,Android application, Android/Chrome kernel hacking
§ Grants/Proposal Writing – NSF Small Business,Innovation, and Research (SBIR) Phase I & II
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Additional Information:
- Ph.D., Electrical and Computer Engineering (University of Wisconsin)
- M.S., Electrical and Computer Engineering (University of Wisconsin)
- B.S., Computer Engineering (Lahore University of Management Sciences, Pakistan)
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