AI Expert for Healthcare Personal Assistant
2022 - 2023RunKicker Pte Ltd- Developed deep learning pipelines for BMI detection on complex data.
- Designed deep learning algorithms to handle small data and make it robust, giving a distribution gathered from a small amount of data.
- Optimized existing models and reduced sizes of the models from 250 MB to just 50 MB.
Technologies: Artificial Intelligence (AI), Image Processing, Python, Signal Processing, Health, Computer Vision, C++, Models, PyTorch, TensorFlow, Mobile, AI Programming, Image Generation, APIs, AI Design, Data Pipelines, Data Visualization, Large Language Models (LLM)Machine Learning Developer | Models Build and Models Fine Tune
2022 - 2022Psi.Wave LLC- Designed and Implemented deep learning LLM pipelines on huge data sets.
- Optimized the existing training pipeline from both time and computation perspectives.
- Implemented custom attention heads for multiple LLMs.
Technologies: Python, Machine Learning, Deep Learning, Artificial Intelligence (AI), AI Programming, APIs, AI Design, Data Pipelines, Data Visualization, Large Language Models (LLM)Senior Data Scientist
2021 - 2022HamzaAi- Implemented a machine learning pipeline for vessel delay prediction at Khalifa Port in the UAE. Reduction in error rate from more than 24 hours to two hours. This resulted in better use of resources, including data mining and ML at Khalifa Port.
- Executed the machine learning pipeline for job category detection through text mining.
- Implemented the pipeline to detect Arabic content originality through text mining.
Technologies: Computer Vision, Natural Language Processing (NLP), PyTorch, TensorFlow, Deep Learning, Image Processing, Machine Learning, Python, Custom Models, Artificial Intelligence (AI), Neural Networks, Artificial Neural Networks (ANN), Generative Adversarial Networks (GANs), Facial Recognition, OpenCV, Computer Vision Algorithms, Azure Machine Learning, Pandas, Azure, Spark ML, Best Practices, Performance Optimization, Language Models, Text Generation, Fine-tuning, Inference, Stable Diffusion, Diffusion, AI Programming, Image Generation, APIs, Chatbots, AI Design, PostgreSQL, Data Pipelines, Data Visualization, Financial Forecasting, Large Language Models (LLM)Graduate Research Assistant
2021 - 2021Texas A&M University- Researched T-cell and Receptor sequence contact prediction on human protein sequences using deep learning. (NLP).
- Investigated cancer region detection in whole slide images (WSI) in collaboration with the University of Chicago.
- Achieved the challenge of each WSI taking GBs to be stored, so it's impossible to use direct deep learning methods like image classification and segmentation.
Technologies: Computer Vision, Natural Language Processing (NLP), PyTorch, Deep Learning, Image Processing, Machine Learning, Python, Custom Models, Artificial Intelligence (AI), Neural Networks, Artificial Neural Networks (ANN), Generative Adversarial Networks (GANs), Facial Recognition, OpenCV, Computer Vision Algorithms, Pandas, Best Practices, Language Models, Text Generation, Inference, AI Programming, Data Visualization, Large Language Models (LLM)Data Scientist
2020 - 2021HamzaAi- Implemented a deep learning pipeline for event and accident detection on self-driving car synthetic data.
- Executed an Arabic OCR detection pipeline based on EasyOCR adjustments.
- Worked on a handwriting recognition tool for Arabic schools.
Technologies: Computer Vision, Natural Language Processing (NLP), PyTorch, Deep Learning, Image Processing, Machine Learning, Python, Custom Models, Artificial Intelligence (AI), Neural Networks, Point Clouds, Artificial Neural Networks (ANN), Generative Adversarial Networks (GANs), OpenCV, Computer Vision Algorithms, Azure Machine Learning, Pandas, Azure, Spark ML, Best Practices, Performance Optimization, Language Models, Text Generation, Fine-tuning, Inference, AI Programming, AI Design, Data Pipelines, Data Visualization, Large Language Models (LLM)Data Scientist
2020 - 2021National University of Computer and Emerging Sciences- Researched breast cancer detection using whole slide images, computerized medical imaging, and graphics.
- Worked on a low-cost pathology project that received a $13.68 million grant for breast cancer detection.
- Worked on Amal. It wasn't just a project but served as an awareness campaign too. I was the lead to start a movement about low-cost pathology—breast cancer detection—in Pakistan using artificial intelligence.
Technologies: Computer Vision, Machine Learning, Deep Learning, PyTorch, Image Processing, Python, Custom Models, Artificial Intelligence (AI), Neural Networks, Point Clouds, Artificial Neural Networks (ANN), Generative Adversarial Networks (GANs), OpenCV, Computer Vision Algorithms, Pandas, Best Practices, Language Models, Inference, AI Programming, AI Design, Data VisualizationSoftware Engineer
2019 - 2020National University of Computer and Emerging Sciences- Developed a deep learning pipeline to detect breast cancer based on low-cost pathology by extracting whole slide images from a scanned microscopic mobile video.
- Designed a Python library and package to optimize training for whole slide images called OpTorch. Optimized the PyTorch training pipeline library for WSI. Published OpTorch research paper in a well-reputed conference.
- Built a deep learning pipeline to detect brain tumors based on CAT scan Images.
Technologies: Machine Learning, Deep Learning, PyTorch, TensorFlow, Computer Vision, Generative Adversarial Networks (GANs), OpenCV, Computer Vision Algorithms, Pandas, Language Models, Inference, AI Programming, AI Design, Data Visualization