Doctor of Philosophy in Computer Science- Data Science and Machine Learning

Data Mining and Knowledge Discovery studies scalable and robust interest measures, algorithms and methods for mining interesting, useful and non-trivial patterns (e.g., anomalies, associations, classifiers, clusters) in big data for descriptive, prescriptive, predictive, planning, previously-unknown knowledge discovery tasks in diverse applications,
Machine Learning probes deep, supervised, unsupervised, self-supervised, semi-supervised, knowledge-guided and other generalizable training methods to leverage representative data samples for prediction, decision-making and other tasks (e.g., object recognition in images, spam detection in emails), where explicitly-programmed algorithms are infeasible or ineffective,
Database Management Systems studies data models (conceptual, logical, physical), query languages (e.g., SQL), query processing and optimization, storage and indexing, concurrency control, recovery from failure, privacy, scalability, and system structures to manage persistent, interrelated and shared databases for decision support, transaction processing, collaborative work, and scientific discovery,
Spatial Data Science explores space-time concepts, context, relationships, patterns, and algorithms to collect, model, integrate and analyze location-aware data (e.g., census, geo-imagery, maps) to understand and/or design location-based services (e.g., delivery, navigation, ride-sharing), systems (e.g., GPS, GIS), and methods (e.g., spatial statistics) when generics are inaccurate or inadequate,

A degree in any major with a substantial background in computer science is required, a computer science major is preferred.
A previous Master's degree is not required to apply to the Ph.D. program.
The preferred undergraduate GPA for admittance to the program is 3.45.
International applicants must submit score(s) from one of the following tests:
TOEFL
Internet Based - Total Score: 85
Internet Based - Writing Score: 23
Internet Based - Reading Score: 23
Paper Based - Total Score: 550
IELTS
Total Score: 6.5