Noorden Shrah

I am a passionate machine learning engineer with a strong computer science and mathematics background. I hold a master's in Computer Science from Mcmaster University and have worked in the field for the past 2 years. My expertise lies in developing and deploying machine learning models to solve complex real-world problems. I am skilled in various machine learning techniques, including deep learning, natural language processing, and computer vision

AI/ML Engineer Health and Rehab Research Inc. Toronto, Canada

Sep 2021-Dec 2022

Lung Cancer Prediction Health Application

• Developed and evaluated a predictive Artificial Neural Network (ANN) model to predict patient prognosis using demographic and medical history.
• Mentored and coached a team of six undergraduate students on machine learning software and meeting project goals.
• Led a research team in developing dashboards and analytics platforms for data management and analysis including the development and evaluation of visual analytics tools.
• Designed and implemented a multi-layer feedforward neural network architecture with backpropagation for training the lung cancer prediction model.
• Conducted extensive research and experimentation to optimize the model's performance.
• Preprocessed and cleaned a diverse dataset of patient records, handling missing values and normalizing features to ensure data quality and consistency.
• Chronic Lower Back Pain Prediction Application (CLBP)
• Developed a self-management tool (mobile application) to predict back pain in CLBP patients for a planned exercise.
• Analyzed the exercise data with machine learning to predict a patient’s expected pain. • Performed a comparative study to evaluate prediction performance.
• Built a Convolutional Neural Network (CNN) model using edge detection and face detection to process patient emotions to predict back pain.
• Collaborated with healthcare professionals to collect a diverse dataset of medical images and associated patient information.

AI Research Graduate

Jan 2021 – Dec 2022

McMaster University/W Booth School of Engineering Practice & Technology- Canada Image Processing of Steel Microstructures Using Machine Learning (ML) Based Algorithms

• Developed an AI-based algorithm to process SEM images of steel microstructure and identified the steel phase fractions.
• Designed and implemented CNN models for steel microstructure classification, and segmentation using TensorFlow and Keras.
• Optimized CNN architectures by experimenting with various hyperparameters and regularization techniques to achieve high accuracy on the steel micrographs.
• Implemented data preprocessing for steel micrographs such as augmentation, normalization, and feature extraction to enhance CNN model performance.

I graduated with a Master of Engineering in Systems & Technology with an emphasis on AI and developing cyber-physical systems from McMaster university in December of 2022. I completed a Master of Science in Electrical Engineering in July 2020 from the Budapest University of Technology and Economics (BME) in Hungary.