Fall 2019
Math4751/6751: MATHEMATICAL STATISTICS I
Probability, random variables and their distributions, mathematical expectation, moment generating functions, sampling distributions.
Prerequisites: Math 2215
Fall 2019
Math3030: MATH MODELS FOR COMPUTER SCIENCE
Elements of mathematical modeling including: multivariate functions, probability, distributions of random variables, sampling, statistical inference, operators, vector analysis; elements of linear algebra.
Prerequisites: Math 2212 and Math 2420 or CSc 2510
Spring 2019
Math3030: MATH MODELS FOR COMPUTER SCIENCE
Elements of mathematical modeling including: multivariate functions, probability, distributions of random variables, sampling, statistical inference, operators, vector analysis; elements of linear algebra.
Prerequisites: Math 2212 and Math 2420 or CSc 2510
Fall 2017
CS563 Digital Image Processing (graduate)
This course introduces the fundamental algorithms, concepts, and applications of image analysis with special focus on familiarizing students with contemporary techniques and applications in biomedical image analysis. Theoretical and practical knowledge concerning image analysis algorithms will be developed through short lectures, paper discussions, and a team project exercise. A variety of imaging modalities will be covered including bright field microscopy imaging, fluorescent microscopy imaging, and time-lapse microscopy imaging. Following this course, students will understand the process of image formation, how information is extracted from images, and the role of this information in biomedical applications from diagnostics to molecular cell biology.
Prerequisites: Signal Processing, machine learning, PDE, or permission of the instructor.
Spring 2016
CS 598R: Research Rotation Project (graduate)
Computer Science and Informatics PhD students are required to complete two rotation projects prior to their qualifying exams and dissertation research. Projects often involve interdisciplinary work, and can be co-supervised by a Math/CS faculty and an external faculty member or researcher (e.g., Schools of Medicine and Public Health, the CDC). Students are required to submit a project proposal and a final report.
Prerequisites: Image analysis, signal processing, machine learning, or permission of the instructor.
Fall 2015
CS584: Digital Image Prcocessing (graduate)
This course introduces the fundamental algorithms, concepts, and applications of image analysis with special focus on familiarizing students with contemporary techniques and applications in biomedical image analysis. Theoretical and practical knowledge concerning image analysis algorithms will be developed through short lectures, paper discussions, and a team project exercise. A variety of imaging modalities will be covered including microscopy and radiology. Following this course, students will understand the process of image formation, how information is extracted from images, and the role of this information in biomedical applications from diagnostics to molecular cell biology.
Prerequisites: Signal Processing, machine learning, PDE, or permission of the instructor.
Spring 2015
CS 597R: Directed Study (graduate)
Prerequisites:Image analysis, signal processing, machine learning, or permission of the instructor.
Spring 2015
CS 598R: Research Rotation Project (graduate)
Computer Science and Informatics PhD students are required to complete two rotation projects prior to their qualifying exams and dissertation research. Projects often involve interdisciplinary work, and can be co-supervised by a Math/CS faculty and an external faculty member or researcher (e.g., Schools of Medicine and Public Health, the CDC). Students are required to submit a project proposal and a final report.
Prerequisites: Image analysis, signal processing, machine learning, or permission of the instructor.
Fall 2013
CS584: Biomedical Image Analysis (graduate)
This course introduces the fundamental algorithms, concepts, and applications of image analysis with special focus on familiarizing students with contemporary techniques and applications in biomedical image analysis. Theoretical and practical knowledge concerning image analysis algorithms will be developed through short lectures, paper discussions, and a team project exercise. A variety of imaging modalities will be covered including microscopy and radiology. Following this course, students will understand the process of image formation, how information is extracted from images, and the role of this information in biomedical applications from diagnostics to molecular cell biology.
Prerequisites: Signal Processing, machine learning, or permission of the instructor.
Spring 2013
CS598R: Research Rotation Project (graduate)
Computer Science and Informatics PhD students are required to complete two rotation projects prior to their qualifying exams and dissertation research. Projects often involve interdisciplinary work, and can be co-supervised by a Math/CS faculty and an external faculty member or researcher (e.g., Schools of Medicine and Public Health, the CDC). Students are required to submit a project proposal and a final report.
Prerequisites: permission of the instructor.