Imperial College London

Dr Khalid Baig Mirza

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Visiting Researcher
 
 
 
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Contact

 

k.mirza Website

 
 
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Location

 

Bessemer - B422Electrical EngineeringSouth Kensington Campus

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Summary

 

Summary

Khalid is a research assistant at the Centre for Bio-Inspired Technology, Institute of Biomedical Engineering. He completed his MSc in Analogue and Digital IC Design from Dept. of Electrical and Electronic Engineering, Imperial College London and started working as an Electronics Engineer for Ingenia Technology, in a product design team to implement a novel authentication technology called Laser Surface Authentication (LSA).

After 2.5 years at Ingenia, he returned to work and pursue a PhD at the Institute of Biomedical Engineering, Imperial College London. Currently, he is working under the ERC funded I2MOVE Synergy project, led by Prof Chris Toumazou and Prof Stephen Bloom, to develop an intelligent, implantable vagus nerve stimulator for obesity treatment. Previously he was also employed in a project funded by EPSRC aimed at real time sensing of neuro-chemical signals.

Further details about the I2MOVE project can be found here : http://www.imperial.ac.uk/a-z-research/i2move/

His research interests lies in developing intelligent,closed loop, implantable or point-of-care platforms which can be used to deliver personalised therapy for obesity and related metabolic conditions.

Publications

Journals

Wildner K, Mirza KB, De La Franier B, et al., 2020, Iridium oxide based potassium sensitive microprobe with anti-fouling properties, Ieee Sensors Journal, Vol:20, ISSN:1530-437X, Pages:12610-12619

Cheng R, Mirza KB, Nikolic K, 2020, Neuromorphic robotic platform with visual input, processor and actuator, based on spiking neural networks, Applied System Innovation, Vol:3, ISSN:2571-5577, Pages:1-16

Mirza KB, Golden C, Nikolic K, et al., 2019, Closed-loop implantable therapeutic neuromodulation systems based on neurochemical monitoring, Frontiers in Neuroscience, Vol:13, ISSN:1662-4548

Conference

Roever P, Mirza KB, Nikolic K, et al., 2020, Convolutional neural network for classification of nerve activity based on action potential induced neurochemical signatures, IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, Pages:1-5, ISSN:0271-4302

Mirza KB, Kulasekeram N, Liu Y, et al., 2019, System on chip for closed loop neuromodulation based on dual mode biosignals, 2019 IEEE International Symposium on Circuits and Systems (ISCAS), Institute of Electrical and Electronics Engineers (IEEE), ISSN:2158-1525

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