Anwaar Khalid has completed his B.Tech in Computer Sciences from NIT Srinagar and M. Tech in Computer Sciences from the University of Roorkee. He is a skilled and dedicated professional in the field of Artificial Intelligence and Machine Learning known for his technical acumen, problem-solving capabilities and innovative approach to complex challenges. With a strong academic foundation and a keen interest in research-driven engineering, he has continuously been contributing to the advancement of efficient AI solutions, particularly in neural network optimization and deep learning applications.Over the years, Anwaar has gained valuable experience working across multiple domains involving model adaptation, compression, and quantization for high-performance computing and embedded systems. His professional journey reflects a balance between theoretical understanding and practical execution, having worked on diverse projects that required developing and refining ML frameworks, improving inference speeds and enhancing system efficiency for real-world applications. Anwaar possesses in-depth expertise in machine learning algorithms, deep neural networks, and optimization techniques. He is proficient in PyTorch, TensorFlow, and Ivy, with hands-on experience in Tensor Decomposition, model pruning, and quantization strategies. His technical proficiency is complemented by a strong understanding of backend-agnostic ML architectures and cross-platform AI deployment methodologies. A passionate learner and innovator, Anwaar has been actively involved in the design and development of intelligent systems aimed at improving the accessibility and scalability of AI models. His research-oriented mindset has led him to explore novel compression algorithms and model transformation pipelines, contributing to the broader goal of optimizing performance without compromising accuracy. He has also shared knowledge through publications, collaborations and open-source contributions.Anwaar is known for his disciplined work ethic, analytical thinking and ability to adapt to evolving  technologies. His certifications in Generative Adversarial Networks, Convolutional Neural Networks and Neural Network Optimization reflect his commitment to continuous learning. With a strong focus on innovation and excellence, he remains dedicated to advancing AI technologies that promote efficiency, sustainability, and real-world impact.