Ai Research Intern
Led the development of a Skin Cancer Classification model using ResNet50, a deep convolutional neural network, to identify melanoma from dermoscopic images.Performed extensive image augmentation techniques (e.g., rotation, flipping, zooming) to prevent overfitting and improve the robustness of the model.Conducted error analysis on misclassified images, providing insights that helped in refining the model’s performance.Published a report detailing the approach and findings, which was later shared with academic and professional communities through AI research forums.Enhanced teamwork and cross-cultural collaboration through regular communication with supervisors and peers from diverse backgrounds, refining global project management skills.