Abubakar Siddique

Abubakar Siddique (Graduate Student Member, IEEE) received the B.Sc. degree in computer science from Quaid-i-Azam University, Islamabad, Pakistan, in 2003, and the M.Eng. degree in computer engineering from the University of Engineering and Technology, Taxila, Pakistan, in 2008. He is currently pursuing the Ph.D. degree with the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand. His undergraduate senior project was conducted in an internship with Ultimus Pakistan, Rawalpindi, Pakistan, where his work was deployed at the company’s Workflow product. He spent nine years at Elixir, Islamabad, Pakistan, a California-based software company. His last designation was a Principal Software Engineer where he led a team of software developers. He developed enterprise-level software for customers such as Xerox, IBM, and Finis. Mr. Siddique’s main research lies in lateralized systems based on artificially intelligent techniques, particularly evolutionary computation, to provide efficient solutions for challenging and complex problems in different domains, such as Boolean, computer vision, and navigation. Lateralization, inspired by the principles of biological intelligence, is an advanced form of transfer learning which utilizes feature detection, feature extraction, and feature construction. The decision-making process of a novel lateralized system is interpretable which is a step toward explainable/trustworthy AI. He is also interested in evolutionary deep learning, reinforcement, supervised, and unsupervised learning, image analysis, programming models, algorithms, runtime systems, and applications. Mr. Siddique was a recipient of the VUWSA Gold Award and the Student Of The Session Award during his Ph.D. and bachelor’s studies, respectively.