Dr. Hammad Majeed

Faculty Member

Dr. Hammad Majeed

Professor

HEC Approved PhD Supervisor
(+9251 111 128 128) 672
hammad.majeed@nu.edu.pk

Education

P.hD (Computer Science), University of Limerick, Ireland, 2007

BS (Software Engineering), National University of Science & Technology, Islamabad, 1999

Summary

Dr. Hammad Majeed is  teaching at National University of Computer and Emerging Sciences as an Associate  professor. He has research interests in the areas of Artificial Intelligence, Computational Intelligence, Machine Learning, Data Mining & Knowledge Discovery, Evolutionary Gaming, Machine Vision & Robotics. He is actively invovled in research in these areas.

Publications

Journal Papers

  1. Ha?z Tayyeb Javed, Mirza Omer Beg, Hasan Mujtaba, Hammad Majeed, Muhammad Asim, Fairness in Real Time Energy Pricing for Smart Grid using Unsupervised Learning In The Computer Journal, 2018
  2. Kiran Fatima, Hammad Majeed, A New Texture and Shape Based Technique for Improving Meningioma Classi?cation Microscopy Research Technique, Volume 77, Issue 11 Pages 862873, Wiley, 2014.
  3. Muhammad Tariq, Hammad Majeed, Mirza Beg, Farrukh Aslam, Accurate detection of sitting posture activities in a secure IoT based assisted living environment Future Generation Computer Systems, 2018
  4. K Fatima, H Majeed, A Two Phase Hybrid Classi?er based on Structure Similarities and Textural Features for Accurate Meningioma Classi?cation. International journal of advanced computer science and applications, Vol. 8, No 4, 2017
  5. Ha?z Tayyeb Javed, Mirza Omer Beg, Hasan Mujtaba, Hammad Majeed, Muhammad Asim, Fairness in Real-Time Energy Pricing for Smart Grid Using Unsupervised Learning The Computer Journal, 2019
  6. A Darwaish, H Majeed, MQ Ali, A Rafay, Dynamic Programming Inspired Genetic Programming to Solve Regression Problems, International journal of advanced computer science and applications, Vol. 8, No 4, 2017
  7. Hammad Majeed, Samina Naz, Deja Vu: a hyper heuristic framework with Record and Recall (2R) modules Cluster Computing, 2019
  8. Hammad Majeed, Samina Naz, Deja Vu - A Hyper Heuristic Framework with Record and Recall (2R) Modules Cluster computing-the journal of networks software tools and applications, pages 1-15, 2017.
  9. Muhammad Quamber Ali, Hammad Majeed, Di?cult ?rst strategy GP: an inexpensive sampling technique to improve the performance of genetic programming Evolutionary Intelligence, 2020
  10. Akif, R., Hammad Majeed, Issues and Challenges In Scrum Implementation. In International Journal of Scienti?c & Engineering Research, Vol. 3, Issue 8, 2014.

Conference Papers

  1. Majeed, H. and Ryan, C. On the constructiveness of context-aware crossover. In Thierens, D., Beyer, H.-G., Bongard, J., Branke, J., Clark, J. A., Cli?, D., Congdon, C. B., Deb, K., GECCO ’07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, volume 2, pages 1659–1666, London. ACM Press.
  2. Majeed, H., Ryan, C., and Azad, R. M. A. Evaluating GP schema in context. In Beyer, H.-G., O’Reilly, U.-M., Arnold, D. V., Banzhaf, W., Blum, C., Bonabeau, E. W., Cantu-Paz, E., Dasgupta, D., Deb, GECCO 2005: Proceedings of the 2005 conference on Genetic and evolutionary computation, volume 2, pages 1773– 1774, Washington DC, USA. ACM Press.
  3. Hammad Majeed, Conor Ryan, A New Approach to Calculate the Best Context of a Tree and its Application in De?ning a Constructive, Context Aware Crossover for GP, In fbit ,pp.765-768, 2007 Frontiers in the Convergence of Bioscience and Information Technologies, 2007.
  4. Majeed, H. A new approach to evaluate GP schema in context. In Rothlauf, F., Blowers, M., Branke, J., Cagnoni, S., Garibay, I. I., Garibay, O., Grahl, J., Hornby, G., de Jong, E. D., Kovacs, T., Genetic and Evolutionary Computation Conference (GECCO2005) workshop program, pages 378–381, Washington, D.C., USA. ACM Press.
  5. Malik, F and Majeed, H., E?ect of Development Strategies and Project Types on O?shore Software Development using Agile Paradigm-A Study. Published in Agile 2010, conference, to be held on August 9-13, Orlando, Florida, US.
  6. Majeed, H. and Ryan, C. Using context-aware crossover to improve the performance of GP. In Keijzer, M., Cattolico, M., Arnold, D., Babovic, V., Blum, C., Bosman, P., Butz, M. V., Coello Coello, C., GECCO 2006: Proceedings of the 8th annual conference on Genetic and evolutionary computation, volume 1, pages 847–854, Seattle, Washington, USA. ACM Press.
  7. Naz, Samina, Majeed, H. and Irshad, H, Image Segmentation using Fuzzy Clustering: A Survey. Published in IEEE ICET 2010.
  8. Majeed, H. and Ryan, C, Context-aware mutation: a modular, context aware mutation operator for genetic programming.
  9. Ryan, C., Majeed, H., and Azad, A. A competitive building block hypothesis. In Deb, K., Poli, R., Banzhaf, W., Beyer, H.-G., Burke, E., Darwen, P., Dasgupta, D., Floreano, D., Foster, J., Harman, M., Genetic and Evolutionary Computation – GECCO-2004, Part II, volume 3103 of Lecture Notes in Computer Science, pages 654–665, Seattle, WA, USA. Springer-Verlag.

Books & Chapters

  1. Majeed, H. and Ryan, C. A re-examination of a real world blood ?ow modelling problem using context-aware crossover. In Riolo, R. L., Soule, T., and Worzel, B., editors, Genetic Programming Theory and Practice IV, volume 5 of Genetic and Evolutionary Computation, chapter 14, pages –. 2006, Springer, Ann Arbor.
  2. Hammad Majeed, Feroza Erum, Exploiting Semantics to Improve Classi?cation of Text Corpus. In Managing and Processing Big Data in Cloud Computing, chapter 2, pages 23-36. 2016, IGI Global.