Dr. Farah Shahid
Assistant Professor
Farah.shahid@ucp.edu.pk
Dr. Farah Shahid is working as an Assistant Professor in the Faculty of Information Technology, University of Central Punjab. She has received her Doctoral degree in Computer Science from Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad. Her research focused on time series analysis and predictions (wind power & solar prediction) using deep learning models, Natural language processing. She has six month working experience at Ubiquitous Knowledge Processing (UKP) Lab, Technical University of Darmstadt, Germany. Her research work has been published in highly reputed journals (Applied Energy, Energy).
| PhD | Computer Science | Pakistan Institute of Engineering and Applied Sciences, Islamabad | 2021 |
| MS | Information Technology | Bahauddin Zakariya university, Multan | 2015 |
| MSc | Information Technology | Punjab University, Lahore | 2010 |
| Lecturer | Lahore leads university | 2016 |
| 1 | Shahid, F., Zameer, A., Mehmood, A., & Raja, M. A. Z. “A novel wavenets long short term memory paradigm for wind power prediction”, Applied Energy, vol.269, May 2020, (IF=9.746) |
| 2 | Shahid, F., Zameer, A., & Muneeb, M, “A Novel Genetic LSTM Model for Wind Power Forecast”, Energy, vol.223, February 2021, (IF=7.147) |
| 3 | Shahid, F., Zameer, A., & Muneeb, M., “Predictions for COVID-19 with deep learning models of LSTM, GRU and Bi-LSTM”, Chaos, Solitons & Fractals, vol.140, August 2020, (IF= 5.944) |
| 4 | Shahid, F., Khan, A., Zameer, A., Arshad, J., & Safdar, K, “Wind power prediction using a three stage genetic ensemble and auxiliary predictor”, Applied Soft Computing, vol.90, February 2020, (IF=6.725) |
| 5 | Shahid, F., Javeed, M., & Zameer, A., “Intelligent forecast engine for short term wind speed prediction based on stacked long short term memory, Neural Computing and Applications, vol.110, March 2021, (IF= : 5.606) |
| 6 | E. Mushtaq, Shahid, F., A. Zameer, A. Khan, and M. Hussain, “Malware detection using tree based ensemble classifiers”, Arabian Journal of Science and Engineering. (IF: 2.33) |