Summary
I am working as an Assistant Professor in the Department of Computer Software Engineering at NUST, I apply my PhD in Neuroinformatics to teach and research topics related to computational neuroscience, neuroimaging, and machine learning. I have several years of experience as a scientific researcher and consultant in this field, working on projects that aim to develop biomarkers for mental health and learning styles using EEG and fMRI data. My core competencies include analyzing and processing neuroimaging modalities such as EEG and fMRI, applying deep learning frameworks such as PyTorch and Tensorflow to extract features and patterns from complex data, and using statistical methods to evaluate and validate the results. I also have proficient programming skills in Python, Matlab, and C/C++. I am passionate about advancing the understanding and application of neuroinformatics to improve human cognition, health, and well-being.
Academic Background
PhD
(Biomedical Engineering) Universiti Teknologi Petronas
October 07, 2016 - June 03, 2021
Honours and Awards
Publications
Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environments.
January 07, 2025
Scientific Reports - Volume 15, Article Number: 1114
Deep Learning-Based Assessment Model for Real-Time Identification of Visual Learners Using Raw EEG
January 19, 2024
IEEE Transactions on Neural Systems and Rehabilitation Engineering - Volume 32, Pages 378-390
Hemispheric asymmetries in electroencephalogram oscillations for long-term memory retrieval in healthy individuals
December 04, 2020
Brain Sciences - Volume 10, Issue 12, Article Number 937
Classification of visual and non-visual learners using electroencephalographic alpha and gamma activities
May 07, 2019
Frontiers in Behavioral Neuroscience - Volume 13, Article Number 86
Conferences
EEG emotion classification using deep neural network
October 10, 2024 - October 13, 2024
Veronika Vengerová, Soyiba Jawed, Sophia Bano, Aamir Saeed Malik,
17th International Conference on Machine Vision (ICMV 2024)
Diagnosing ADHD with 1D-CNN: Efficient Analysis of fMRI Data
October 10, 2024 - October 13, 2024
Qurat Ul Ain, Soyiba Jawed,
17th International Conference on Machine Vision (ICMV 2024)
A Cross-domain Vision Transformer Based Framework for Baggage Threat Classification
March 14, 2024 - March 16, 2024
Ammara Nasim, zawar Khan, Taimur Hassan, Soyiba Jawed, Muhammad Usman Akram, Jahan Zeb,
International Conference on Computer and Automation Engineering (ICCAE)
Effective eeg feature selection for interpretable mdd (major depressive disorder) classification
July 12, 2023 - July 14, 2023
Vojtech Mrazek, Soyiba Jawed, Muhammad Arif, Aamir Saeed Malik,
GECCO 2023 - Proceedings of the 2023 Genetic and Evolutionary Computation Conference
Deep learning-based diagnosis of Alcohol use disorder (AUD) using EEG
September 02, 2022 - September 06, 2022
Soyiba Jawed, Aamir Saeed Malik, Rusdi Bin Abd Rashid, Mohamad Naufal Mohamad Saad,
IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
EEG Visual and Non- Visual Learner Classification Using LSTM Recurrent Neural Networks
December 03, 2018 - December 06, 2018
Soyiba Jawed, Hafeez Ullah Amin, Aamir Saeed Malik, Ibrahina Faye,
2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES)
Differentiating between Visual and Non-Visual Learners Using EEG Power Spectrum Entropy
August 13, 2018 - August 14, 2018
Soyiba Jawed, Hafeez Ullah Amin, Aamir Saeed Malik, Ibrahina Faye,
International Conference on Intelligent and Advanced System, ICIAS 2018
Performance and cost evaluation of IEEE 802.11g and 802.3i protocols for network connectivity at a university campus using OPNET simulation
April 10, 2013 - April 12, 2013
Arslan Musaddiq, Umair Sajid Hashmi, Soyiba Jawed,
UKSim 15th International Conference on Computer Modelling and Simulation, UKSim 2013
Researcher
Brno University of Technology
March 01, 2022 - October 17, 2023