PhD Data Science Program

College of Engineering, College of Science, School of Statistics

University of the Philippines, Diliman

Quezon City 1101 Philippines

About

Any scientific field is defined by the object of study and creates a systematic organization of knowledge about that object, as well as developing means to expand that knowledge. The natural object of study for data science is therefore data, especially digital data and including but not limited to unstructured data and big data. Data science is the study of the nature of data as carriers of information. It therefore includes the study of the data itself in its various forms and methods and tools involved in handling and analyzing data throughout its lifecycle from collection, information representation, processing and purification, analysis, presentation including visualization, storage and archiving, access, and many others even up to data retrieval and publication.

Program Goals

The PhD in Data Science at the University of the Philippines aims to produce PhD graduates equipped with a good scientific mindset, with adequate technical skills, and a professional perspective of expanding the science of data, with data as carriers of information. Distinct from an MS degree holder, the PhD (Data Science) degree holder is expected to exceed the skills of those with a master’s degree in science (research). The PhD graduate will therefore have a better integrative view of the field of data science beyond mastery of a specific chosen subfield. It is therefore typical of a PhD graduate to be able to defend the significance of a given research problem and the implications of a possible solution to other fields beyond its own. Results of a scientific study may also be found by a PhD to have entanglement with philosophy and our understanding of the true nature of things in a more holistic view.

Program Learning Outcomes

At the end of the program, graduates are expected to:

  1. Analyze the nature of data throughout its life cycle including the mechanism behind data generation and storage (domain knowledge base);

  2. Apply multi-disciplinary theories and methods with their underlying philosophies for data analysis resulting from various phenomena and processes (data science application to domain);

  3. Generate new data science theories, data models, architecture, and/or algorithms that can adapt to the evolving nature of data throughout its life cycle including generation, information representation, storage, and/or extraction (generation of new knowledge);

  4. Apply data science solutions to real-world problems in collaboration with and/or among academic, industrial and public governmental institutions (collaboration in the application of data science); and

  5. Practice ethical and lawful guidelines and policies related to the application of data science processes, methods and techniques, especially in the Philippine context (ethical practice).

Program Tracks

There are three program tracks available. See this page for more details.

This program is a cooperation between three implementing units are the College of Engineering, College of Science, and the School of Statistics. It is designed to naturally expand and tap the expertise from other units in the University of the Philippines in the future.

To Apply

Your intended or current domain area is important in choosing which implementing unit you will apply. Those with the intention of moving towards the engineering and systems aspect are recommended to the College of Engineering while those in the statistics and analytics to the School of Statistics and those who focus on the general sciences to the College of Science. Ultimately, the choice of mentors and your dedication will be critical in the entire learning process and for you to eventually obtain the PhD degree in Data Science.

Contact your possible mentor to help you apply in the program. The initial list of possible mentors are found in the Faculty page.

You may also proceed to the Application section for details.

Program Structure

A PhD (Data Science) candidate must show proof of acquiring the following qualifications before being given the degree.

  • Mastery of fundamental and applied scientific methods in studying and understanding data as information carriers. It is therefore expected of the PhD applicant without a master's degree to pass a qualifying exam that tests her/his basic and applied technical data science skills developed through the core courses where appropriate. For those who has master's degree, the qualifying exam may usually be waived.

  • Scientific appraisal of the scientific field (Data Science) that a PhD student is immersed in. After some period of training with a mentor, she/he must be able to demonstrate a satisfactory ability to discuss the latest development in the field covering open problems and exciting research directions open for investigation. This includes the ability to identify good research problems in a given scientific field. The PhD student must therefore pass a candidacy examination in which evaluation is done by competent PhD holders in the field of Data Science and other related fields of expertise directly connected to the general research direction being sought.

  • Adequate level of expertise in generating a sound proposal to solve a given problem. A PhD holder must also be able to provide possible solutions or hypothesis/es to solve a problem identified. Furthermore, a means to evaluate the same solution may also be proposed. Thus, the PhD Candidate must successfully defend a topic proposal approved by a committee/panel; such a topic proposal may be chosen by the Graduate Committee integrated with the candidacy examination.

  • Satisfactory defense of novel results surrounding a Data Science problem inclusive of its implication to the field. A degree in PhD is awarded conditional upon the completion of a successful PhD dissertation defense to a panel of experts chosen by the Graduate Committee. In a presentation and in the dissertation manuscript, the PhD candidate must be able to also identify the significance of solving a research problem within the scientific community and the opportunity to expand its scientific horizon or open new research directions. The dissertation may also include a novel application of data science to solving data science related real-world problems.

Facilities used

The program is supported by the use of the University computing resource UP Data Commons in Diliman Campus. Various other satellite resources are also available in each implementing units for classes and conferences.