About

Dr. Hussain has a dual-doctorate in Information and Communications Engineering from The Hong Kong Polytechnic University (awarded in 2021) and another from Xi'an Jiaotong University (awarded in 2022 and under a Joint PhD Programme); an MSc. degree from the University of Leicester, UK (2011); and a bachelor's degree in electrical engineering (First-class Honours) from Bahria University, Pakistan (2010). He has over five years - around 1 year post-doctoral and 4.5 years pre-doctoral - of academic experience teaching undergraduate and graduate-level courses in telecommunications, Electronics, and Computer Science.

His general research interests include Applications of Artificial Intelligence and Big Data Analytics in Wireless Communication Systems (6G/5G Mobile Networks), Mobile Edge and Fog Computing, and Cyber-Physical Systems Security.

In particular, he does the following/has an interest in the following topics:

- Analysis of user traffic data collected from cellular networks.

- AI-based attack detection in cellular networks, from the cyber-physical systems (CPS) security perspective.

- AI-based network optimization using data (self-healing, traffic prediction, resource reallocation).

- Intelligent detection of faults and anomalies in mobile networks.

Educational
background

Ph.D. in Information & Communications Engineering

The Hong Kong Polytechnic University, Hong Kong SAR
September 2019 to August 2021

M.Sc. in Information & Communications Engineering

University of Leicester, United Kingdom
2010 to 2011

Bachelor of Electrical Engineering (Telecommunication Specialization)

Bahria University
Fall 2006 to Spring 2010

Peer-Reviewed Journal Papers

J4. B. Hussain, Q. Du, B. Sun and Z. Han, "Deep Learning-Based DDoS-Attack Detection for Cyber–Physical System Over 5G Network," in IEEE Transactions on Industrial Informatics, vol. 17, no. 2, pp. 860-870, Feb. 2021, doi: 10.1109/TII.2020.2974520.

J3. B. Hussain, Q. Du, A. Imran and M. A. Imran, "Artificial Intelligence-Powered Mobile Edge Computing-Based Anomaly Detection in Cellular Networks," in IEEE Transactions on Industrial Informatics, vol. 16, no. 8, pp. 4986-4996, Aug. 2020, doi: 10.1109/TII.2019.2953201. Link

J2. B. Hussain, Q. Du, S. Zhang, A. Imran and M. A. Imran, "Mobile Edge Computing-Based Data-Driven Deep Learning Framework for Anomaly Detection," in IEEE Access, vol. 7, pp. 137656-137667, 2019, doi: 10.1109/ACCESS.2019.2942485.

J1. B. Hussain, Q. Du and P. Ren, "Semi-supervised learning based big data-driven anomaly detection in mobile wireless networks," in China Communications, vol. 15, no. 4, pp. 41-57, April 2018, doi: 10.1109/CC.2018.8357700.

Ph.D. in Information & Communications Engineering

Xi'an Jiaotong University, P. R. China
September 2017 to June 2022

Peer-Reviewed Conference Papers

C2. B. Hussain, Q. Du and P. Ren, "Deep Learning-Based Big Data-Assisted Anomaly Detection in Cellular Networks," 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates, 2018, pp. 1-6, doi: 10.1109/GLOCOM.2018.8647366.

C1. B. Hussain, Q. Du and P. Ren, "Big data-driven anomaly detection in cellular networks," 2017 IEEE/CIC International Conference on Communications in China (ICCC), Qingdao, China, 2017, pp. 1-6, doi: 10.1109/ICCChina.2017.8330468.

“A good teacher is like a candle – it consumes itself to light the way for others."

- Mustafa Kemal Atatürke.

“It is the supreme art of the teacher to awaken joy in creative expression and knowledge."

- Albert Einstein.

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