Project Info

*DEVELOPING ROBUST BRAIN IMAGING GENOMICS DATA MINING FRAMEWORK FOR IMPROVED COGNITIVE HEALTH

Hua Wang
huawang@mines.edu
The research objective of this project is to address the computational challenges in an innovative big data application on neuroinformatics. This project will study the problem of integrating multi-level data with the emerging key computational techniques: large-scale non-convex sparse learning models with linear convergence algorithms and linear computational cost multi-task multi-dimensional data integration algorithms.

More Information:

Grand Challenge: Engineer better medicines
The below website describes the project with details and it has listed more than 10 related publications by the research team led by the proposing faculty for this MURF project: http://minds.mines.edu/project/med_image/

Primary Contacts:

Dr. Hua Wang, CS Department, huawang@mines.edu

Student Preparation

Qualifications

The applicant student is expected to have already taken CSCI 261 and 262. It would be beneficial if the student has already taken CSCI 358, 404, 470.

TIME COMMITMENT (HRS/WK)

6 hours per week

SKILLS/TECHNIQUES GAINED

1. The students will learn the skills to perform data processing and management. 2. The students will be involved my research team to perform research on machine learning and data mining. 3. The students will be involved into scientific paper writing for the results from this project. 4. The students will have chance to work together with my collaborators in medical schools. 5. The students will gain the fundamental knowledge on medical image computing, as well as how to use machine learning, as well as computational algorithms, to deal with problems in medical image computing. In a word, after the training in this project by successfully completing the assigned research tasks, the student is expected to be ready for pursing a graduate degree in the area of machine learning, data mining, or artificial intelligence, or a broader area of computer science.

MENTORING PLAN

1. One orientation meeting is planned at the beginning of the project, in which the undergraduate students will be introduced to the research team. The project and research culture of the faculty’s research team will be introduced to the undergraduate students in the meeting. 2. Technical seminars within the research team are planned, once per week. In every meeting, the undergraduate students will present a research paper relevant to the project and lead discussions on it with the faculty and the graduate students in the research team. 3. Professional development sessions within the research team are planned, once per week. In every meeting, the faculty or the graduate students in the research team will examine the progress of the project and the recent research results, exchange the ideas with the undergraduate students, and help them develop research skills, including algorithm development, experimental design, scientific results evaluation, paper writing, and so on. 4. A poster session will be conducted at the end of the project in which the results of this project will be presented to the research teams of the faculty, the Computer Science Department, and the collaborators of the faculty.

PREFERRED STUDENT STATUS

Sophomore
Junior
Senior
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