Optimizing AlexNet for Cyclone Intensity Prediction

I’m seeking a deep learning expert to refine the AlexNet architecture for a cyclone intensity prediction project. The primary objective is to reduce the prediction time of the model. Given that the specific modifications to make were not enumerated, the professional I am looking to partner with should be proficient and experienced in various aspects of deep learning and possesses the adeptness in understanding the optimal configurations that would yield faster prediction times. The dataset available for this project is composed of satellite images. Thus, a good comprehension of image processing, convolutional neural networks, and cyclone intensity prediction models would be essential. A summary of the key requirements include:

- Improve prediction time on AlexNet architecture
- Utilize provided dataset of satellite images
- Expertise in deep learning, image processing, and convolutional neural networks.
- Strong grasp on cyclone intensity prediction models is a plus.