Dr. Muhammad Farrukh Shahid, PhD

Assistant Professor

I am Dr. Muhammad Farrukh Shahid, completed PhD under the Joint Doctorate Program between Queen Mary University of London (QMUL) London UK and the University of Genoa (UNIGE) Genoa Italy in June 2021. I have been serving as an Assistant Professor in the Computer Science Department FAST-NUCES Karachi, Pakistan since 2021. I teach the courses of Artificial Intelligence to the undergraduate and Machine Learning to the masters and PhD students. My research focuses on the Machine and Deep Learning and Probabilistic models for developing Self-Aware Cognitive Radio Internet of Things networks.


Courses Taught


–  Artificial Intelligence

– Machine Learning for Data Science

– Statistical and Mathematical Methods for Data Science

– Programing Fundamentals




Joint PhD from Queen Mary University of London (QMUL) London UK and the University of Genoa (UNIGE) Genoa Italy




Virtual Apparel Try Room using Augmented Reality (Bachelor’s Final Year Project Supervision). This project won 2nd prize in the Hack Fest 22 organized by Google Developers Students Club (GDSC) in collaboration with bytecorp, Sastaticket.p and TPS at IBA Karachi City Campus on 18 to 20 March 2022. First Prize in the Project Competition held on Devday on May 11 2022 at Fast. This project is also selected in the National Incubation Centre Karachi.




• Automatic Jammer Signal Classification using Deep Learning in the Spectrum of AI-enabled CR-IoT Network, 7th International Congress on Information and Communication Technology ICICT’2022 held on 23-24 Feb 2022 in London UK.

• AI-Based Abnormality Detection at the PHY-Layer of Cognitive Radio by Learning Generative Models,” in IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 1, pp. 21-34, March 2020, doi: 10.1109/TCCN.2020.2970693

• Jammer detection in M- QAM-OFDM by learning a Dynamic Bayesian Model for the Cognitive Radio,” 27th European Signal Processing Conference (EUSIPCO 2019) Coruna, Spain, 2019.

• Learning a Switching Bayesian Model for Jammer Detection in the Cognitive-Radio-Based Internet of Things,” 2019 IEEE 5th World Forum on Internet of Things (WF-IoT), Limerick, Ireland, 2019, pp. 380-385.

• 1.2–3.8 GHz active quasi-circulator with >30 dB transmit-receive isolation, 2nd IEEE International Conference on Integrated Circuits and Microsystems (ICICM). 8-11 November 2017, China.