AFRAH NAEEM
| PERSONAL INFORMATION | |||
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| afrah.buic@bahria.edu.pk | |||
| Phone Ext. | nill | ||
| Research Areas / Expertise | Data Science (Data Analytics), Machine Learning, Deep Learning for Smart grids and Health Care Applications, Energy Management systems | ||
| QUALIFICATION | |||
| Degree | Passing Year | Majors | University |
| MS | 2020 | Software Engineering | University Comsats University Islamabad, Pakistan |
| TEACHING EXPERIENCE | |||
| Designation | From | To | Organization |
| Lecturer | 10-Feb-2023 | Present | Bahria University Islamabad, Pakistan |
| Lecturer | 01-Feb-2021 | 08-Feb-2023 | Capital University Islamabad (CUST), Pakistan |
| Lecturer | 05-Oct-2020 | 31-Jan-2021 | Comsats University Islamabad, Pakistan |
| Research Associate | 01-Mar-2019 | 01-Sep-2020 | Comsats University Islamabad, Pakistan |
Publications
Conferences
- Analyzing quality of software requirements; a comparison study on NLP tools. | 25th International Conference on Automation and Computing (ICAC)
- Short-term load forecasting using EEMD-DAE with enhanced CNN in smart grid. | Workshops of the International Conference on Advanced Information Networking and Applications, Cham: Springer International Publishing
- Electricity Load and Price Forecasting Using Machine Learning Algorithms in Smart Grid: A Survey | Workshops of the international conference on advanced information networking and applications, Cham: Springer International Publishing
- Short Term Electricity Price Forecasting Through Convolutional Neural Network (CNN) | Workshops of the International Conference on Advanced Information Networking and Applications, Cham: Springer International Publishing
- Electricity price and load forecasting using data analytics in smart grid: A survey. | International Conference on Emerging Internetworking, Data & Web Technologies. Cham: Springer International Publishing
- Classification and regression based methods for short term load and price forecasting: A survey. | International Conference on Emerging Internetworking, Data & Web Technologies, Cham: Springer International Publishing