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The methodology includes 3D geometric modelling, machine learning and pattern recognitiion for data classification. The application will be devoted to rehabilitation analysis and correlations of physiological signals related to physical activities. The proposed methodology of fluorophores 3D mapping will utilize of the full information content of microscopy datasets.

Annotation: Biotechnological processes are very complex, nonlinear and time-variant systems, for which it is difficult to obtain appropriate models. The work is devoted to the study and possible applications of reinforcement learning methods, which are just able to learn in initially unfamiliar environments, in the field of biotechnology.

PhD thesis topics - Faculty of Chemical Engineering

Annotation: The quality of process control of biotechnological production processes used in the pharmacy and food industry is often constrained by the limited possibilities of on-line measurement of key process parameters e. One possible solution is the use of software sensors to continually estimate the values of key process indicators from on-line measurable process variables.

Modern approach can be represented by point processes with density, especially interacting particle systems. The work assumes i the study of advanced methods for image analysis, ii the study of interacting particle systems iii the proposal of specific algorithms for analysis of selected biomedical images, and iii comparison, implementation and verification in the hospital.

Annotation: The project includes analysis of multichannel EEG data and motion sensors signals.


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Research part of the project includes the study of Bayesian classification of selected features using computational intelligence methods. Resulting algorithms will be verified for the group of individuals related to the illness progression and they will be used for early diagnostics of movement disorders in the clinical environment. The comprehensive final examination fulfills the capstone requirement. The following courses can be used as substitutes:.

Required Courses

A third elective course taken from Mathematics, Statistics, Computer Science, or related disciplines with approval of the Graduate Advisor. Link to Course Descriptions: level undergraduate - level graduate. Full-time students must enroll for 12 units per quarter including research, academic and seminar units.

Once course requirements are completed, students can take additional classes as needed, although the 12 units per quarter are generally fulfilled with a research class and perhaps seminars, or additional electives, approved by one of the Graduate Advisors. Per UC regulations, students should not ordinarily enroll in more than 12 units of graduate level courses or more than 16 units of combined undergraduates and graduate level , , courses per quarter.

Standard Track: 32 units of core coursework and 12 units of electives are required for a total of 44 units. Emphasis in Data Science Track: 36 units of core coursework and 12 units of electives are required for a total of 48 units. Every M. Comprehensive Examination is a written examination.

Plan I: Thesis

The examination may include the use of statistical software and may be offered in a computer lab. If a student does not attempt the examination upon completion of those courses, and does not receive prior approval from the exam committee, it will be counted as not passing the comprehensive exam. Should a student not pass the comprehensive exam at this time, the student will be offered a second examination during the Spring quarter following the first exam.

2 Divide And Conquer

If a student does not attempt the second exam, it will be counted as a failure. Failure to pass the exam at the second attempt will be counted as a failure of the comprehensive exam. Failure to pass the comprehensive exam will result in a recommendation to the Dean of Graduate Studies for disqualification of the student from the graduate program. Students who entered the graduate program as Ph. Plan II M.

Applications of Statistics to Applied Algorithm Design

Candidates must file an advancement to M. Candidates must have taken at least half of the required coursework for their degree requirements 18 units. Since the M. Towards Data Science Follow. Sharing concepts, ideas, and codes. See responses Discover Medium. Make Medium yours.


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