Program details
Introduction
NLP focuses on system development that allows computers to communicate with people using everyday language. Natural language generation systems convert information from the computer database into readable or audible human language and vice versa. Such systems also enable sophisticated tasks such as inter-language translation, semantic understanding, text summarization and holding a dialog. The key applications of NLP algorithms include interactive voice response applications, automated translators, digital personal assistants (e.g., Siri, Cortana, Alexa), chatbots, and smart word processors.
Program
Competence
Upon completion of the program requirements, the graduate will be able to:
- Develop a deep and comprehensive understanding of cutting-edge NLP algorithms with applications to real-life scenarios
- Implement, evaluate and benchmark existing state-of-the-art in NLP scholarly publications and weigh in their respective pros and cons.
- Grow capabilities to identify open research problems, the gaps in the existing body of knowledge, and formulate new research questions
- Independently develop innovative solutions, through extensive research and scholarship, to resolve research problems in high-impact real-life applications of NLP.
- Demonstrate expert knowledge and highly specialized cognitive and creative skills in NLP to deliver state of the art solutions to existing open research problems.
- Pursue an NLP project either independently, or as part of a team in a collegial manner, with minimal supervision.
- Initiate, manage, and complete research manuscripts that demonstrate expert self-evaluation and advanced skills in scientifically communicating highly complex ideas.
- Develop highly sophisticated skills in initiating, managing, and completing multiple project reports and critiques, on a variety of NLP problems, that demonstrate an expert understanding and advanced skills in communicating highly complex ideas.
The minimum degree requirements for the “PhD in Natural Language Processing” are 59 Credits, distributed as follows:
Core Courses
PhD in Natural Language Processing is primarily a research-based degree. The purpose of coursework is to equip students with the right skillset, so they can successfully accomplish their research project (thesis). Students are required to take COM701, as a mandatory course. They can select three core courses from a concentration pool of eight in the list provided below:
COM701 Research Communication and Dissemination*
NLP701 Natural Language Processing
NLP702 Advanced Natural Language Processing
NLP703 Speech Processing
NLP704 Deep Learning for Language Processing
NLP705 Topics in Advanced Natural Language Processing
NLP706 Advanced Speech Processing
AI701 Artificial Intelligence
AI702 Deep Learning
Elective Courses
Students will select a minimum of two elective courses, with a total of eight (or more) credit hours (CH) from a list of available elective courses based on interest, proposed research thesis, and career perspectives, in consultation with their supervisory panel. The elective courses available for the PhD in Natural Language Processing are listed in below table:
MTH701 Mathematical Foundations for Artificial Intelligence
MTH702 Optimization
CS701 Advanced Programming
CS702 Data Structures and Algorithms
DS701 Data Mining
DS702 Big Data Processing
ML701 Machine Learning
ML702 Advanced Machine Learning
ML703 Probabilistic and Statistical Inference
CV701 Human and Computer Vision
CV702 Geometry for Computer Vision
CV703 Visual Object Recognition and Detection
HC701 Medical Imaging: Physics and Analysis
Research Thesis
PhD thesis exposes students to cutting-edge and unsolved research problems in the field of Natural Language Processing, where they are required to propose new solutions and significantly contribute towards the body of knowledge. Students pursue an independent research study, under the guidance of a supervisory panel, for a period of 3 - 4 years.
NLP799 PhD Research Thesis