Syeda Tehreem Haider

• Machine Learning & Deep Learning for Signal Processing and Computer Vision
• AI for Medical Diagnostics (signal and image analysis)
• Digital Security: Audio Deepfake Detection & Face Recognition Systems
• Anomaly Detection & Pattern Recognition
• Remote Sensing Image Analysis for Security & Environmental Monitoring

• ORCID: https://orcid.org/0009-0005-7553-2188
• Google Scholar: https://scholar.google.com/citations?user=28GN_2IAAAAJ&hl=en
• Linkedin: https://www.linkedin.com/in/syeda-tehreem-haider-98418a25b/

Electronics Engineering graduate with research interests in machine learning and deep learning for signal processing and computer vision. My work focuses on AI applications in medical diagnostics, digital security, and remote sensing. I aim to contribute to cutting-edge research in AI-driven signal and image analysis through a master’s program.

Final Year Project – IntelliGuard: AI-Powered Detection of Forgeries in Audio Data (Python, MATLAB)

• Designed machine and deep learning pipeline using CNN-based Mel-spectrogram (audios to image conversion) analysis to detect spoofed audios.
• Fused cepstral (extracted from audios) and CNN features, applied MRMR for feature selection, and classified with KNN.
• Achieved 98.6% accuracy and 0.01% Equal Error Rate (EER).

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Heartbeat to Music Conversion Using Signal Processing (MATLAB)

• Recorded heartbeats via modified stethoscope-microphone system.
• Applied filtering, Fourier analysis, and frequency mapping to generate musical notes.

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AI-Based Face Recognition for Secure Authentication (Python, TensorFlow/Keras)

• Developed CNN-based facial recognition with data augmentation for robust performance.
• Achieved high accuracy under varying lighting and facial expressions for secure access control.

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Color Space Comparison for Remote Sensing Image Classification (Python, OpenCV)

• Extracted color, texture, and edge features from RGB and HSV images.
• Evaluated classification accuracy to identify optimal feature representation.

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Leaf Recognition System (MATLAB)

• Utilized MATLAB based GUI for leaf segmentation and extracted features from segmented images.
• Classified species using MATLAB ML toolbox with high accuracy under challenging conditions.

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FPGA-Based Heart Rate Monitoring System (Verilog, MATLAB, Xilinx Vivado)

• Processed ECG signals from AD8232 sensor for binary conversion and thresholding.
• Implemented 16-bit classification on Artix-7 FPGA with real-time display on LEDs/7-segment.

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Embedded Speech Recognition System on Zynq FPGA (Verilog, Quartus, Modelsim)

• Implemented speech recognition pipeline (MFCC, FFT) on ZedBoard Zynq FPGA.
• Recognized commands (“ON”, “OFF”) to trigger FPGA-based actions in real time.

"Recognition of Leukocytes using a Combination of Deep Features and Ensemble Classifier", IEEE Xplore, Presented at 19th IEEE ICET

"https://ieeexplore.ieee.org/abstract/document/10935053"

• Developed leukocyte classification system using ResNet18 transfer learning on Raabin-WBC dataset.
• Applied preprocessing and oversampling to address class imbalance, and extracted deep features from pooling layer of ResNet18.
• Achieved 99.5% accuracy with Ensemble Bagged Trees classifier using 5-fold cross validation

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"Pattern Analysis Framework for Detection of Cardiac Disorders using VCG Signal Analysis", IEEE Xplore, Presented at IEEE 5th ICACS

"https://ieeexplore.ieee.org/abstract/document/10473256"

• Developed pattern recognition framework for detecting BBB, CMP, and DYS from VCG signals.
• Applied Empirical Mode Decomposition (EMD) for preprocessing and extracted time, spectral, and cepstral features.
• Used Back Elimination for feature selection, achieving 97.9% accuracy with KNN (Fine) and 10-fold cross-validation.

International Conferences (Presented)

1. IEEE 19th ICET 2024 — Leukocyte recognition using deep learning features + ensemble classifier for medical image analysis.

2. IEEE 5th ICACS 2024 — Cardiac disorder detection via VCG signal analysis for medical diagnostics.

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Workshops & Seminars (Attended)
3. Predictive Maintenance for Industry 4.0, 2024 — UET Taxila.
4. Speech Deepfakes Detection, 2023 — UET Taxila.
5. Technical Paper Writing Skills, 2023 — UET Taxila.
6. Introduction to LaTeX, 2023 — UET Taxila.

• Neural Network 101: Image Recognition using Machine Learning – Simplilearn (Completed: 08/2024)
• Introduction to Large Language Models – Google Cloud x Simplilearn (Completed: 07/2024)
• What is Generative AI? – LinkedIn Learning (Completed: 06/2024)
• FPGA Computing Systems: Partial Dynamic Reconfiguration – Politecnico Milano 1863 x Coursera (Completed: 04/2024)
• Introduction to Computer Vision – Great Learning (Completed: 04/2024)
• Business Intelligence and Data Analytics: Generate Insights – Macquarie University x Coursera (Completed: 02/2024)

• Pakistan Engineering Council (PEC)
• IEEE Council on Electronic Design Automation
• IAENG (International Association of Engineers)
• IEEE Biometrics Council
• IEEE Sensors Council
• IEEE Systems Council
• Systems Engineering Society of Australia (SESA)

• [ 2023 ] Prime Minister's Youth Laptop Scheme - Awarding institution: Higher Education Commission

Awarded with a laptop under the PM's Youth Laptop Scheme for academic excellence.  

• [ 2023 ] Best Volunteer Award - Awarding institution: IEEE Consumer Electronics Society (CES), UET Taxila

Recognized with the Best Volunteer Award for exceptional  contributions and dedication to volunteering.

• Joint Secretary, IEEE Consumer Technology Society (CTSoc), UET Taxila, 08/01/23 - 05/31/24 (Event coordination and management, inter-society collaboration)
• Director Documentation, IEEE Consumer Electronics Society (CES), UET Taxila, 08/01/22 - 07/31/23 (Documentation management, communication and team coordination)

• English, Fluent
• Urdu, Native

• Dr. Syed Zohaib Hassan Naqvi (BSc Final Year Project Supervisor and Lecturer)

Lecturer, Electronics Engineering Department, UET Taxila, Pakistan

Email: zohaib.naqvi@uettaxila.edu.pk

Phone: (+92) 51 9047724

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• Dr. Muhammad Faraz (BSc Final Year Project External Supervisor and Lecturer)

Lecturer, Electronics Engineering Department, UET Taxila, Pakistan

Email: muhammad.faraz@uettaxila.edu.pk

Phone: (+92) 51 9047723