Department of Computer Science
Dr. Mohammad Nadeem
|Qualification :||Ph. D|
|Designation :||Assistant Professor|
|Thrust Area :||Nature inspired optimization, Machine learning|
|Time Table :||Click to View|
|Download :||Click here to download study materials|
|Online :||Click here to View Video Lectures|
Dr. Mohammad Nadeem is currently working as Assistant Professor in the Department of Computer Science, AMU, Aligarh. He joined the department in June 2016. He received his Ph.D degree from IIT(ISM), Dhanbad, Jharkhand. Before that, he has also worked as Assistant System Engineer at Tata Consultancy Services (TCS). He completed his Masters and Graduation from AMU in 2011 and 2008 respectively. He was also awarded University Medal in Graduation. His research areas are Machine Learning and Soft Computing.
- Muhammad Azeem Akbar, Mohammad Shameem, Arif Ali Khan, Mohammad Nadeem, Ahmed Alsanad and Abdu Gumaei, A fuzzy analytical hierarchy process to prioritize the success factors of requirement change management in global software development, Wiley- Software: Evolution and Process, Accepted (2020).
- Mohammad Shameem, Rakesh Ranjan Kumar, Mohammad Nadeem and Arif Ali Khan, Taxonomy of Barriers and their Prioritization using Fuzzy Analytic Hierarchy Process for Scaling Agile Development in the Global Software Development, Elsevier- Applied Soft Computing, Accepted, 90, pp. 106-122 (2020).
- Mohammad Nadeem, Haider Banka and R. Venugopal, Intelligent Techniques Based Modelling Of Size Enlargement Process For Fine Materials: A Quick Survey, 16th International Mineral Processing Symposium (IMPS 2018), Antalya, Turkey – October 23-25, 2018.
- Mohammad Nadeem, Haider Banka and R. Venugopal, A neural network based approach for steady-state modelling and simulation of continuous balling process, Springer- Soft Computing, 22(3), pp. 873-887 (2018).
- Mohammad Nadeem, Haider Banka and R. Venugopal, Estimation of pellet size and strength of limestone and manganese concentrate using soft computing techniques, Elsevier- Applied Soft Computing, 59, pp. 500-511 (2017).
- Mohammad Nadeem, Haider Banka and R. Venugopal, SVM-Based Predictive Modelling of Wet Pelletization Using Experimental and GA-Based Synthetic Data, Springer-Arabian Journal for Science and Engineering, 41(3), pp. 1053-1065 (2016).
- Mohammad Nadeem, Haider Banka and R. Venugopal, A Comparison of multilayer perceptron (MLP) and support vector machine (SVM) in predicting green pellet characteristics of manganese concentrate, Proceedings of Fifth International Conference on Soft Computing for Problem Solving, pp. 311-320. Springer Singapore, 2016.
- Mohammad Nadeem, and R. Venugopal. Analysis of size-strength trade-off in green pelletization for manganese concentrate using multiobjective evolutionary algorithm (NSGA-II), 3rd International Conference on Recent Advances in Information Technology (RAIT), pp. 268-273. IEEE, 2016.