Dr. Mohammad Ali Humayun

Assistant Professor

Phd in System Engineering from University Brunei Darussalam, Brunei Darussalam

  • ali.humayun@newitu2.itu.edu.pk

RESEARCH INTERESTS

speech processing, natural language processing, and deep learning

Biography

Mr. Ali Humayun has completed his Ph.D in System Engineering from the Universiti Brunei Darussalam, where his research focus was on deep learning for speaker and author profiling. He has previously worked with global telecom giants such as Nokia, Huawei, ZTE, as an IP Networks Expert. He obtained Masters degree in Telecommunication Engineering from the University of Engineering and Technology Peshawar and Bachelors degree of Electronics Engineering from Ghulam Ishaq Khan Institute of Engineering.

  1. Mohammad Ali Humayun, Hayati Yassin, and Pg Emeroylariffion Abas. "Native language identification for Indian-speakers by an ensemble of phoneme-specific, and text-independent convolutions". Speech Communication 139 (2022): 92–101.
  2. Mohammad Ali Humayun, Hayati Yassin, and Pg Emeroylariffion Abas. "Spatial position constraint for unsupervised learning of speech representations". PeerJ Computer Science 7 (2021): e650.
  3. Mohammad Ali Humayun, Ibrahim A Hameed, Syed Muslim Shah, Sohaib Hassan Khan, Irfan Zafar, Saad Bin Ahmed, and Junaid Shuja. "Regularized Urdu Speech Recognition with Semi-Supervised Deep Learning".Applied Sciences 9, no.9 (2019): 1956.
  4. Junaid Shuja, Mohammad Ali Humayun, Waleed Alasmary, Hassan Sinky, Eisa Alanazi, and Muhammad Khurram Khan. "Resource efficient geo-textual hierarchical clustering framework for social iot applications".IEEE Sensors Journal 21, no.22 (2021): 25114–25122.
  5. Junaid Shuja, Mohammad Ali Humayun, and Muhammad Habib Ur Rehman. "Innovating Educational Policies with Machine Learning in the Covid-19 Pandemic." . In 2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop (pp. 1–7).2021.
  6. Sohaib Hasan Khan, Syed Muslim Shah, Irfan Zafar, Junaid Shuja, and Mohammad Ali Humayun. "Performance Comparison of Modified Non-Linear FxLMS Algorithm for Impulsive Noise Based on ANCs." . In 2019 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) (pp. 1–6).2019.

Pakistan Engineering Council