Imperial College London

Syed M Danish Rizvi

Faculty of EngineeringDyson School of Design Engineering

Research Postgraduate



d.rizvi21 Website




Dyson BuildingSouth Kensington Campus





I am a Ph.D. candidate at  Dyson School of Design Engineering, where I am a member of Systems and Algorithms Laboratory (SysAL). I am working under the supervision of Dr David Boyle and Dr Hamed Haddadi. I completed my Masters degree in Avionics Engineering at Air University, Islamabad Campus and Bachelors degree in Aeronautical Engineering at National University of Sciences and Technology, Pakistan. 

My research interests include applications of Machine Learning in IoT, Radar Signal Processing, and Autonomous Controls.



SM Danish Rizvi, Shahzore Ahmed, Khurram Jadoon, Azhar Hasan. "A deep learning approach for fixed and rotary-wing target detection and classification in radars". Submitted to IEEE Aerospace and Electronic Systems Magazine. (Under review)


Khan, Sharzil Haris, Zeeshan Abbas, and SM Danish Rizvi. "Classification of diabetic retinopathy images based on customised CNN architecture." In 2019 Amity International Conference on Artificial Intelligence (AICAI), pp. 244-248. IEEE, 2019.

Abbas, Zeeshan, Mobeen-ur Rehman, Shahzaib Najam, and SM Danish Rizvi. "An efficient gray-level co-occurrence matrix (GLCM) based approach towards classification of skin lesion." In 2019 Amity International Conference on Artificial Intelligence (AICAI), pp. 317-320. IEEE, 2019.


Mobeen, Sharzil Haris , SM Danish Rizvi, Zeeshan Abbas, and Adil Zafar. "Classification of skin lesion by interference of segmentation and convolotion neural network." In 2018 2nd International Conference on Engineering Innovation (ICEI), pp. 81-85. IEEE, 2018.