Mr. Zeeshan Aslam
Category: Faculty
Published on: June 17, 2021
Personal Information
Name Zeeshan Aslam
Email zaslam.buic@bahria.edu.pk
Phone 9260002 ext 1341
Research Area Data Science, Machine learning, Smart Grids, Energy management
Number of Publications Conferences = 3, Journals = 2
Affiliation
Designation Lecturer
Department Computer Science
University Bahria University Islamabad Campus
Qualification
Degree Passing Year Majors University
Master of Science in Software Engineering 2020 Software Engineering COMSATS University Islamabad, Pakistan
Bachelors of Science in Software Engineering 2018 Software Engineering University of Sargodha
Teaching Experience
Designation From To Organization
Lecturer Feb 2021 Date Bahria University Islamabad
Industrial Experience
Designation From To Organization
Research Associate July 2019 Feb 2020 COMSATS University Islamabad, Pakistan
Publications

Journals:

Sr. #
1. Aslam Z., Javaid N., Ahmad A., et. al., “A Combined Deep Learning and Ensemble Learning Methodology to Avoid Electricity Theft in Smart Grids”, Energies, 13, p.5599, 2020. Doi:10.3390/en13215599. (IF=2.702)
2. Aslam Z., Ahmed F., et. al., “An Attention Guided Semi-supervised Learning Mechanism to Detect Electricity Frauds in the Distribution Systems”, IEEE Access, vol. 8, pp. 221767-221782, 2020. DOI: 10.1109/ACCESS.2020.3042636. (IF=3.745)

Conferences:

Sr. #
1. Z. Aslam, et. al., “An Enhanced Convolutional Neural Network model based on weather parameters for short-term electricity supply and demand”, accepted in 34-th International Conference on Advanced Information Networking and Applications (AINA-2020), Caserta, Italy, pp. 22-35.
2. A. Naeem, Z. Aslam, et. al., “Analyzing quality of software requirements; a comparison study on nlp tools,” in 2019 25th International Conference on Automation and Computing (ICAC), 2019, pp. 1-6
3. Shehzad, F., Asif, M., Aslam, Z., Anwar, S., Rashid, H., Ilyasd, M., & Javaid, N. “Comparative Study of Data Driven Approaches towards Efficient Electricity Theft Detection in Micro Grids”, 2021.

Book Chapters:

Sr. #
1. Z. Aslam, et. al., “An Enhanced Convolutional Neural Network model based on weather parameters for short-term electricity supply and demand”, accepted in 34-th International Conference on Advanced Information Networking and Applications (AINA-2020), Caserta, Italy, pp. 22-35.