Computer Science
Associate Teaching Professor, D2K
Member, Ken Kennedy Institute
Average rating
3.5
12 temporary mock ratings
Difficulty
3.8
course-linked average
Courses
8
in seeded sections
His research interests include Medical Image Computing, Deep Learning, Computer Vision, Machine Learning, Data Mining, and Heuristic Optimization Algorithms. He has also been involved in curriculum design and has taught a diverse range of courses at different levels.
COMP 449
In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: DSCI 435, DSCI 535, COMP 549. Mutually Exclusive: Cannot register for COMP 449 if student has credit for COMP 549/COMP 559/DSCI 535. Repeatable for Credit.
COMP 549
In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: DSCI 535. Mutually Exclusive: Cannot register for COMP 549 if student has credit for COMP 449/DSCI 435. Repeatable for Credit.
DSCI 435
In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: DSCI 535, COMP 449, COMP 549. Mutually Exclusive: Cannot register for DSCI 435 if student has credit for COMP 549/DSCI 535. Repeatable for Credit.
DSCI 535
In this project-based course, student teams will complete semester-long data science research or analysis projects selected from a variety of disciplines and industries. Students will also learn best practices in data science. Cross-list: COMP 549. Mutually Exclusive: Cannot register for DSCI 535 if student has credit for COMP 449/DSCI 435. Repeatable for Credit.
ELEC 490
Theoretical and experimental investigations under staff direction. A research project plan should be prepared and approved by the faculty member advising the project. Information about ELEC 490 project plans is available on the ECE Web site on the Academics section under ECE forms. May be repeated for a total of 6 credit hours for undergraduates. Repeatable for Credit.
ELEC 590
Theoretical and experimental investigations under staff direction. Repeatable for Credit.
STAT 490
This course provides 1-3 credit hours of credit for STAT majors who wish to pursue a research project of mutual interest to the student and a faculty member in a selected area of statistical specialization. The student will conduct independent research under the faculty member’s direction. Repeatable for Credit.
STAT 590
Research course for graduate level research in probability and statistics. This course provides 1-15 hours of credit for students who wish to pursue a statistical research project of mutual interest to the student and a faculty member. The student will conduct independent research under the faculty member’s direction. Repeatable for Credit. Repeatable for Credit.
