Dr. Farah Shahid

Dr. Farah Shahid

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
MScInformation Technology Punjab University, Lahore 2010
Lecturer Lahore leads university 2016
1Shahid, 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)
2Shahid, F., Zameer, A., & Muneeb, M, “A Novel Genetic LSTM Model for Wind Power Forecast”, Energy, vol.223, February 2021, (IF=7.147)
3Shahid, 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)
4Shahid, 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)
5Shahid, 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)
6E. 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)

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