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Dr. Aarij Mahmood Hussaan

Professor- HOD

PhD (Artificial Intelligence), University of Lyon, France

ACMA (Research – Knowledge and Decision Making, A.I), University of Lyon, France

MSC (Computer Science), National University of Computer and Emerging Sciences

About

  1. Qualified and accomplished software engineer with years of technical proficiency in managing databases, deep learning, system designing & development, data storage, machine learning & project management; possesses skills to enhance data solutions by gathering, cleaning and analyzing data with technical acumen in predicting trends & identifying patterns
  2. Detail-oriented and talented professional with ability to design test plans and procedures, document software defects by utilizing tracking system, and implement corrective measures. Adept at identifying, recording, and statistically analyzing problems with program functions, while ensuring compliance with data security policies
  3. Dynamic and active team player with skills to collaborate with engineers and team members and play role to achieve objectives. Possesses excellent written and verbal communication skills and analytical, problem-solving, and decision-making abilities; holds strong business sense to recommend better business strategies and help organizations in dealing with business challenges.

Area of Expertise

  • Software Engineering
  • Algorithms
  • Machine Learning
  • Deep Learning
  • System Designing
  • Project Management
  • Data Organization/Interpretation
  • Data Visualization & Communication
  • Computational Theory
  • Enterprise System Development
  • Statistical Analysis
  • Blockchain Management
  • Artificial Intelligence
  • Problem-Solving &
  • Technical Reporting Skills
  • Communication &

Publications & Research Work

Dr. Muhammad Shahnawaz Adil

Dr. Muhammad Shahnawaz Adil is an Associate Professor of Leadership and Strategic Management at Iqra University, Karachi. He holds more than 17 years of full-time university teaching, research, mentorship, and graduate thesis supervision experience. Additionally, he has been serving as the Cluster Head (Management) since January 2020 at the Main Campus. He is currently a member of the advisory and review boards of 18 national and international scholarly journals. 

He has presented various research ideas at international conferences abroad and has published over 25 research papers in national and international journals with 700+ Google citations. He has also authored a monograph on Leadership and Strategy published in Germany. He is an HEC-approved PhD supervisor and five Ph.D. candidates are going to complete their doctoral thesis under his sole supervision. In addition to supervising several industrial projects, 32 MPhil and hundreds of MBA students have successfully passed their research thesis in the Management discipline under his sole supervision. His research interests include the dark side of leadership, workplace mistreatment, multilevel modeling, and creative performance in higher education. He completed a ten-day comprehensive Training of Trainers conducted by Sindh HEC in May 2023.

Dr. Shahnawaz earned his Ph.D. degree in Management from an AACSB and AMBA-accredited business school of Malaysia in 2021. Earlier, he received his MPhil from Iqra University, a ‘triple-crown’ (AACSB, AMBA, and EQUIS-accredited) MBA from Newcastle University (UK), Postgraduate Diploma from Stratford College London (UK), and B.Sc. (Honours) with Distinction from London Metropolitan University, UK. He has secured seven consecutive distinctions in his academic career and has clinched First Class First Position at Sindh Board of Technical Education. He has been associated with Iqra University as a permanent faculty member in the Department of Business Administration since August 2008. His main hobbies include horse-riding, playing scrabble, cooking, bird-farming, and long driving.

  • Consistency verification of learner profiles in adaptive serious games was presented at ECTEL 2016 in Lyon, France by A. M. Hussaan and Karim Sehaba.
  • A conceptual model to incorporate serious games mechanics in intelligent tutoring systems was discussed at ECGBL 2015 by Hina Mukhtar and A. M. Hussaan.
  • The GOALS (Generator of Adaptive Learning Scenarios) project was presented at ICT Asia 2015 in Los Baños, Laguna, Philippines by SEARCA.
  • An improved intrusion detection approach using synthetic minority over-sampling technique and deep belief network was proposed by SH Adil, SSA Ali, K Raza, and AM Hussaan at SOMET 265.
  • Learn and evolve the domain model in intelligent tutoring systems was the topic of discussion at CSEDU 2014.
  • Hybridization of multiple intelligent schemes to solve the economic lot scheduling problem using the basic period approach was presented by SH Adil, SSA Ali, A Hussaan, and K Raza in the Life Sci J.
  • The GOALS platform for the generation of adaptive pedagogical scenarios was featured in the International Journal of Learning Technologies in October 2013.
  • An adaptive serious game for the rehabilitation of persons with cognitive disabilities was presented at the 2013 IEEE 13th International Conference on Advanced Learning Technologies.
  • K. Sehaba and A.M. Hussaan developed an adaptive serious game for the re-education of cognitive disorders, which was published in AMSE Journals.
  • The Generator of Adaptive Learning Scenarios (GALS) was designed and evaluated in the CLES project by A.M. Hussaan and K. Sehaba at the 7th European Conference on Technology Enhanced Learning (EC-TEL 2012).
  • Jeux sérieux adaptatifs pour la rééducation des troubles cognitifs was a paper presented by K. Sehaba and A.M. Hussaan at Handicap 2012.
  • The papers presented at ECTEL 2016 and ECGBL 2015 focused on incorporating serious games mechanics into adaptive learning systems.
  • The GOALS project aimed to generate adaptive learning scenarios and was presented at ICT Asia 2015.
  • The improved intrusion detection approach proposed by SH Adil, SSA Ali, K Raza, and AM Hussaan utilized synthetic minority over-sampling technique and deep belief network.