Mehnaz Tabassum is a computer science graduate with a strong passion for artificial intelligence, computational ventures, and medical image analysis. Currently, she conducts cutting-edge research in brain tumor analysis at the Computational Neurosurgery Lab. Her work focuses on developing deep learning models to enhance tumor diagnosis and treatment. With expertise in image processing, computer vision, and pattern recognition, Mehnaz has supervised several thesis projects and published her research in reputable conferences and journals. She holds a Master's degree in Computer Science & Engineering and a Bachelor's degree in the same field. Mehnaz's dedication to leveraging deep learning technology to improve healthcare outcomes drives her research in health informatics and computational neurosurgery. Equipped with programming skills in Python, Java, C, C++, and MATLAB, and proficiency in deep learning frameworks like TensorFlow and Keras, Mehnaz tackles complex challenges in her research. Her knowledge of neural networks and convolutional neural networks allows her to design optimized models for brain tumor analysis. Mehnaz's commitment to advancing the field and improving patient care is evident in her research contributions. With her extensive technical skills and deep understanding of deep learning, she remains at the forefront of utilizing this technology in health informatics.