Artificial Intelligence & Machine Learning

AI Applications

The traditional applications of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects. Owing to recent technological advances, AI now has a broad range of application, and is potentially applicable to any intellectual task. Examples of AI applications include autonomous vehicles (such as drones and self-driving cars), medical diagnosis, creating art (such as poetry), proving mathematical theorems, playing games, search engines (such as Google search), online assistants, image recognition in photographs, spam filtering, and prediction of judicial decisions.

AI Applications areas at Rice include biological and biomedical applications; robotics; problems related to geosciences, oil and gas; computer vision; engineering-wide applications; and applications in computational social science.

For example, Professor Pedram Hassanzadeh has an Microsoft AI grant focused on using deep learning approaches such as convolutional neural networks and recurrent neural networkers to identify and predict large-scale weather patterns that cause extreme events such as heat waves, cold spells, downpours, and floods. Professor Caleb Kemere develops machine learning tools to discover how the cognitive processes by a large numbers of neurons evolve across circadian timescales and over time with learning, and how these processes are implemented in neural circuits. The AI based tools he is developing allow for researchers in neuroscience/neuroengineering community to perform reliable, robust pre-processing and analysis of neural data.