Hafiz Shakeel Ahmad Awan

BIO

My research interests lie at the intersection of advanced image processing, computer vision, and artificial intelligence (AI), where I explore and advance new techniques in these fields. I have a strong interest in leveraging AI/deep learning to tackle challenges such as image manipulation, restoration, colorization, segmentation, inpainting, super-resolution, low-light image enhancement, deblurring, denoising, dehazing, detection, tracking, and underwater image processing.

Additionally, I am actively exploring generative AI, transformer networks, and multimodal systems, with a focus on integrating vision and language models. My interests also include deep feature manipulation, representation learning, and few-shot learning, aiming to ensure that models can generalize effectively, even with limited data.

I am also involved in video processing, 3D vision, depth perception, and image fusion, exploring these areas to integrate multimodal data for improved performance. My research interest also extends into medical imaging, applying supervised and unsupervised deep learning models to enhance image understanding and automate diagnostic tasks. I am equally invested in exploring explainable and ethical AI to ensure transparency in high-impact applications like healthcare.

I am continually refining my expertise in state-of-the-art deep learning architectures, including CNNs, GANs, diffusion models, and Transformers, and applying these models to both vision and NLP-related problems. I maintain a GitHub repository with simplified AI model implementations, to make them accessible for practical use and collaboration.

I am seeking research fellowship opportunities and am eager to collaborate with professionals passionate about AI in computer vision. Let’s connect and explore how we can advance this exciting field together.