Nauman Fazal
Research Associate | AI & Computer Vision Expert | Deep Learning & Machine Learning Specialist | Full Stack Developer | Web Scraping and Automation Enthusiast
Nauman Fazal is a skilled full-stack developer with expertise in machine learning, computer vision, and web development. With proficiency in languages such as Python, TypeScript, and frameworks like React, Angular, and Node.js, they excel in creating scalable web applications and integrating advanced AI models. Nauman’s strong foundation in data engineering, deployment, and cloud services such as AWS enhances their capability to manage end-to-end application development. Currently, Nauman is working on innovative projects in deep learning and AI, combining cutting-edge tools like TensorFlow, PyTorch, and OpenCV to push the boundaries of generative AI, computer vision, and 3D reconstruction.
In their role, they have been intricately involved in the development and management of Early Warning Wildlife Preservation and Forest Fire Detection projects, demonstrating expertise in constructing the backend infrastructure, designing frontend dashboards, crafting APIs, and orchestrating application deployments, alongside ensuring the robust management of servers. A pivotal aspect of their contributions lies in the seamless integration of AI technologies into these systems, serving as the cornerstone of their functionality. Presently, their focus is directed towards enhancing the AI capabilities within the wildlife cam trap project, a venture poised to revolutionize ecosystem monitoring and conservation efforts backed by the World Wildlife Foundation.
They are working on refining the AI by fine-tuning existing models and exploring more efficient architectures to enhance accuracy and speed and trying to leverage pre-trained models and adapting them to the specific requirements of wildlife detection expedites development. Currently, they are exploring the integration of multimodal Large Language Models (LLMs) like CLIP and OWL etc. to detect wildlife using text prompts. This innovative approach leverages both textual and visual information to enhance the accuracy and efficiency of wildlife detection, promising new improvements for conservation efforts.
Education
- 2021 – 2025: Bachelors in Computer Science [Lahore University of Management Sciences]
Parts of this have been written using generative AI.
