Theory and algorithms for machine learning research; in-depth focus on advanced machine learning topics such as clustering, learning from data streams, and climate informatics.
1. Analyze machine learning algorithms.
2. Design machine learning algorithms.
3. Read and understand recent academic literature in machine learning and related fields.
4. Give an oral presentation about his/her own research, and about the research of others.
5. An ability to apply knowledge of mathematics, science and engineering
6. an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability.
7. An ability to identify, formulate, and solve engineering problems
8. An ability to communicate effectively, both orally and in writing.
9. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context.
10. A recognition of the need for, and an ability to engage in life-long learning
11. A knowledge of contemporary issues.
12. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.