Epilepsy affects over 50 million people globally. This paper presents an automated multi-class seizure classification model using EEG signals from the Temple University Hospital Seizure Corpus. The model combines multi-head self-attention mechanism with a deep convolutional neural network to classify seven subtypes of generalized and focal epileptic seizures, achieving 0.921 weighted accuracy and 0.902 weighted F1 score.
@article{gill2024epilepsy,title={Attention-based deep convolutional neural network for classification of generalized and focal epileptic seizures},author={Gill, Taimur Shahzad and Zaidi, Syed Sajjad Haider and Shirazi, Muhammad Ayaz},journal={Epilepsy \& Behavior},year={2024},doi={10.1016/j.yebeh.2024.109732},journal_cover={epilepsy-behavior-cover.jpg},dimensions={true},}
ICRAI
Time Series Forecasting of KSE-100 Index Using a Hybrid ESN-LSTM Model
Taimur Shahzad Gill and Syed Ibrahim Zahid
In 2024 International Conference on Robotics and Automation in Industry (ICRAI), 2024
This paper aims to improve the predictive accuracy of the Karachi Stock Exchange index (KSE-100) by comparing and combining advanced deep learning models. The research investigates the effectiveness of Echo State Networks (ESN), Long Short-Term Memory (LSTM) networks, and a hybrid ESN-LSTM model in capturing both short-term fluctuations and long-term trends.
@inproceedings{gill2024kse,title={Time Series Forecasting of KSE-100 Index Using a Hybrid ESN-LSTM Model},author={Gill, Taimur Shahzad and Zahid, Syed Ibrahim},booktitle={2024 International Conference on Robotics and Automation in Industry (ICRAI)},year={2024},doi={10.1109/ICRAI62391.2024.10894346},journal_cover={kse-lstm-cover.jpeg},}
2023
Eng. Proc.
Early Detection of Mesothelioma Using Machine Learning Algorithms
Taimur Shahzad Gill, Muhammad Ayaz Shirazi, and Syed Sajjad Haider Zaidi
Early detection of mesothelioma, a severe form of cancer commonly associated with asbestos exposure, is a significant challenge that greatly affects prognosis. This study addresses this issue using Machine Learning algorithms, including Gradient-Boosted Trees (GBT), Support Vector Machines (SVM), and Logistic Regression (LR), achieving 100% accuracy in detecting the disease.
@article{gill2023mesothelioma,title={Early Detection of Mesothelioma Using Machine Learning Algorithms},author={Gill, Taimur Shahzad and Shirazi, Muhammad Ayaz and Zaidi, Syed Sajjad Haider},journal={Engineering Proceedings},volume={46},number={1},pages={6},year={2023},doi={10.3390/engproc2023046006},journal_cover={engineering-proceedings-cover.jpg},dimensions={true}}
2021
ICET
IoT Based Smart Power Quality Monitoring and Electricity Theft Detection System
Taimur Shahzad Gill, Durr E Shehwar, Hira Memon, and 5 more authors
In 2021 16th International Conference on Emerging Technologies (ICET), 2021
Electricity theft is a worldwide issue, but it is most prevalent in developing countries like Pakistan. This system comprises a network of sensors to transmit real-time power consumption data to the microprocessor, which processes the data to detect power theft. The proposed method involves transmitting power consumption readings to ThingSpeak using IoT.
@inproceedings{gill2021iot,title={IoT Based Smart Power Quality Monitoring and Electricity Theft Detection System},author={Gill, Taimur Shahzad and Shehwar, Durr E and Memon, Hira and Khanam, Sobia and Ahmed, Ali and Shaukat, Urooj and Mateen, Abdul and Zaidi, Syed Sajjad Haider},booktitle={2021 16th International Conference on Emerging Technologies (ICET)},pages={1--6},year={2021},organization={IEEE},doi={10.1109/ICET54505.2021.9689908},journal_cover={iot-power-theft-cover.jpeg},dimensions={true}}
