Junaid Ahmed Shaikh

I am a results-driven AI Engineer and Data Scientist with a strong foundation in machine learning, deep learning, and computer vision, complemented by extensive experience in image processing, big data analytics, and AI model deployment. With a background in physics and artificial intelligence, I specialize in developing and implementing AI-driven solutions to solve complex problems across various domains, including computer vision and natural language processing (NLP)

My expertise includes designing and optimizing deep learning models for image analysis, predictive analytics, and automation. I have successfully developed and deployed CNN-based classification models, U-Net architectures for segmentation, autoencoder-based feature extraction, and RNN/LSTM-based time-series prediction models. My experience extends to big data processing, cloud computing, and AI model deployment using Docker, Kubernetes, and cloud platforms such as Azure and IBM Cloud.

I hold an MS in Artificial Intelligence (2024) from NED University of Engineering and Technology, where I specialized in computer vision, machine learning, and deep learning frameworks. I have completed several industry-recognized certifications, including:

• IBM AI Engineering Professional Certificate
• IBM Data Science Professional Certificate
• DeepLearning.AI TensorFlow Developer Certificate
• DeepLearning.AI AI in Medicine Certificate

My technical skill set includes Python, MATLAB, TensorFlow, PyTorch, OpenCV, Scikit-learn, and expertise in data processing tools such as Pandas and NumPy. I am experienced in deploying AI models, and optimizing machine learning workflows to enhance efficiency and scalability.

I am passionate about leveraging AI and data science to drive innovation, optimize business processes, and develop intelligent systems. With strong problem-solving skills, analytical thinking, and a research-oriented mindset, I am eager to contribute to cutting-edge AI projects in industries such as technology, finance, healthcare, and manufacturing.

I am an experienced AI Engineer and Imaging Physicist with a strong background in machine learning, deep learning, and medical image processing. Over the past six years, I have worked extensively in AI-driven image analysis, PET/CT imaging, and algorithm development, combining my expertise in artificial intelligence, physics, and computational techniques to solve complex challenges.

Key Areas of Expertise:

• AI & Machine Learning: Developed and implemented CNN-based classification models, U-Net architectures for segmentation, autoencoders for feature extraction, and RNN/LSTM-based predictive analytics.
• Medical Imaging & Computational Analysis: Extensive experience in PET/CT imaging quality assessment, image reconstruction, and quantitative analysis using deep learning techniques.
• Big Data & Cloud Computing: Skilled in AI model deployment, cloud-based computing (Azure, IBM Cloud), and big data frameworks (Apache Kafka, Hadoop, Apache Airflow).
• Algorithm Development & Optimization: Designed and optimized deep learning pipelines for image analysis, anomaly detection, and real-time processing.
• Research & Collaboration: Conducted research on GAN-based image translation for PET data correction, working closely with cross-functional teams in AI, physics, and medical imaging.
• Technical Leadership: Led projects involving AI integration in imaging workflows, AI-based disease classification, and predictive analytics, ensuring practical deployment and impact.

With a strong foundation in Python, TensorFlow, PyTorch, OpenCV, and data science tools, I am passionate about leveraging AI to drive innovation and solve real-world challenges across industries.

I hold an MS in Artificial Intelligence (2024) from NED University of Engineering and Technology, where I specialized in machine learning, deep learning, and computer vision. My coursework covered mathematical foundations for AI, pattern recognition, big data processing, and deep learning applications. My thesis, Development of Generative AI (GAN)-Based Image Translation Methods for PET Data Correction, focused on enhancing medical imaging accuracy using AI-based models.

Additionally, I have an MSc in Physics (Specialized in Electronics) from the University of Karachi, where I secured 2nd position in my class. This foundation in physics, electronics, and computational modeling has provided me with a strong analytical and problem-solving mindset, which I apply in my work with AI and machine learning.