CSI Ph.D. Programs

The Ph.D. program in Computer Science and Informatics is uniquely tailored to Emory's special strengths, both within the department and across the University's renowned health science departments.

Graduate studies and training are offered in close partnership with the Computational and Life Sciences and AI.Humanity strategic initiatives and students benefit greatly from the breadth and richness of a large scholarly community of faculty, postdocs, and research labs in these areas.

Aimed at educating the next generation of computer scientists and informaticists, the Ph.D. is suitable for those wishing to pursue careers in academics, industry, government, or healthcare.

Possible areas of research specialization include:

• Data and Information Management: Data security, information retrieval, statistical analysis, and data integration in the context of medical, public health, and biological data managment. Research projects and course offerings span multiple departments, and intersect with other research groups in Biology, the School of Medicine, the Winship Cancer Institute, and the Rollins School of Public Health.
• Bioinformatics and Biomedical Informatics: Coursework and student research opportunities include machine learning for precision medicine, privacy preserving health data mining, bioinformatics for protein structure prediction and genoma analysis, NLP in healthcare, AI for cognitive impairment detection, and related topics. In addition, our CSI graduate program involves faculty from Emory Schools of Medicine (Biomedical Informatics) and Public Health (Biostatistics and Bioinformatics) whose expertise spans numerous areas of health science informatics.
• Natural Language Processing: Students may study and conduct research on chatbot technology, carebots, conversational AI, text summarization, multiparty dialog, and LLMs. Additionally,
  

  faculty advisors also work in NLP for medical applications, computational linguistics and machine translation.

• Human Computer Interaction: HCI courses and research mentoring are offered in cognition and visualization, dialog and recommender systems, information visualization and bias, AI/computing ethics, future of work, sustainability and IoT, broadening participation in computing, human AI interaction, and similar topics. HCI-related research on bias and fairness, AI systems for health equity, data justice and related areas is conducted across Emory.
• Theory and Systems: Graph theory, theory of computation, approximation algorithms, combinatorial optimization, mathematical programming, and geometric algorithms. Research in traditional Computer Science as well as in BioInformatics and Computational Biology is pursued under this specialization.
• Distributed and High-Performance Computing: Metacomputing, distributed systems, collaboration technologies, networking, and high-performance computing. Students can work on research projects in Grid and Cloud computing, particularly for eScience and Healthcare, and major technology companies.
• Scientific Computing: Numerical linear algebra, image processing, iterative methods, optimization, partial differential equations, and computational fluid dynamics. Strong connections with Radiology, Medicine, and Pediatrics characterize research in this sub area.

Students admitted to the program, in full standing, should have an undergraduate degree in computer science, mathematics, or a related science and engineering field that includes basic and intermediate computer science courses. Students with insufficient preparation may be required to take courses beyond the minimum requirements. Students must complete each of the following requirements.

• Course requirements: Consisting of 7 courses and 2 rotation projects.
  • 3 core courses and 4 electives (see below).
  • Rotation projects are faculty-led and aim to:
    • provide practicum opportunities
    • explore potential dissertation topics within the faculty advisor's area
    • expose students to computational research problems in practical settings through interdisciplinary collaborations
• Qualifying Exams: This consists of an area exam that covers foundational materials within the student's area of research, and a thesis proposal in which the student describes a set of open research questions and the approaches that will be taken to answer them.
• Teaching Requirements: Each student must attend a two-day summer workshop and a one semester department seminar on teaching, and either (a) assist-teach one course, and independently teach one introductory-level undergraduate course or (b) assist-teach three courses.
• Ethics Requirement: Each student must attend a one-day summer workshop and attend a minimum of 4 workshops held in collaboration with the Laney Graduate School and the Emory Center for Ethics. Students must also attend a minimum of 6 hours of program-based ethics material (CS 590, the program's teaching seminar and CS 700, Graduate Seminar). CS 590 should be completed by the fall of the second or third year of study.
• Students must fulfill the Graduate School residency requirements.
• Each student must present a deparment graduate seminar, complete an acceptable dissertation and deliver an oral defense.

Students are required to take the following 3 core courses:

• CS 526: Algorithms (or CS 523 Data Structures and Algorithms I by permission)
• CS 534: Machine Learning
• CS 551: Systems Programming

In addition, students are required to take at least 4 courses from across the CS, BMI, BMED, or BIOS domains (including any 584’s or 700 level courses offered in that domain). These courses serve as building blocks of a broad and rigorous training in computer science and informatics. Students may take a qualifying exam once they have completed the minimum course requirements. Common and popular courses are listed below; a comprehensive list may be found in the handbok.

Representative Electives:

• CS 557: Artificial Intelligence
• CS 570: Data Mining
• CS 571: Natural Language Processing
• CS 572: Information Retrieval
• CS 573: Data Privacy and Security
• CS 730: Advanced Topics in Data and Info Management
• CS 555: Parallel Processing
• CS 556: Programming Languages and Compliers
• CS 562: Advanced Computer Systems.
• CS 580: Operating Systems.
• CS 581: High Performance Computing.
• CS 710: Advanced Topics in Computing Systems.
• BIOS: 506 Statistical Methods (4)
• CS 524: Theory of Computing
• CS 563: Digital Image Processing
• MATH 515: Numerical Analysis I
• MATH 516: Numerical Analysis II
• MATH 561: Matrix Analysis and Applications
• MATH 771/772/789: Advanced Topics in Computational Mathematics

A student may substitute elective courses with a relevant alternative from Mathematics, Computer Science, Biology, Chemistry, Biomedical Informatics, the Rollins School of Public Health, School of Medicine, and appropriate schools at Georgia Tech through the ARCHE program.

When substituting courses, a student must obtain prior written approval from their thesis advisor and the CSI Director of Graduate Studies. Students must complete their core courses with a grade of B+ or higher and complete all remaining coursework by year three with a GPA of 3.5 or higher.

The Biomedical Informatics Concentration (BMI) of the CSI PhD program focuses on the effective use of biomedical data, information, and knowledge for biomedical and clinical research, as well as decision support driven by efforts to improve human health.

Graduates will find careers in teaching and research facilities of educational and medical institutions; industry and hospitals; and law and government regulatory agencies. Graduate study will comprise of developing advanced computational techniques and strategies that directly impact patient care, and clinical and biomedical research.

This is a multidisciplinary concentration, jointly administered by departments of Biomedical Informatics,  Computer Science, and Biostatistics and Bioinformatics.

Students admitted to the program, in full standing, should have basic competencies in college-level calculus, undergraduate biology, statistics and computer programming. Strong applicants who are missing some of this background (e.g., an MD with no formal computer science training) can be accepted but will be required to take introductory courses in computer science as a condition of admission.

Similar accommodations will be made for strong computer science-oriented applicants who have no specific training or experience in the biomedical domain. Students must complete each of the following requirements.

• Course requirements:
  • 3 core courses and 4 electives (see below).
  • Complete an informatics and a clinical rotation project. These projects involve interdisciplinary work and will be co-supervised by a core faculty and an informatics or domain faculty member. It is expected that the projects will be in areas relevant to the student's dissertation topic. Students are required to submit a project proposal and a final report. Possible areas of rotation include Intensive Care Unit informatics, Biomedical informatics studies in HMOs, Medical Home, Imaging informatics and Radiation therapy, Data modeling and visualization, Transplant informatics, Natural Language Processing in biomedicine.
• Qualifying Exams: This consists of an area exam that covers foundational materials within the student's area of research, and a thesis proposal in which the student describes a set of open research questions and the approaches that will be taken to answer them.
• Teaching Requirements: Each student must attend a two-day summer workshop and a one semester department seminar on teaching, and either (a) co-teach one course, and independently teach one introductory-level undergraduate course, or (b) co-teach three courses.
• Ethics Requirement: Each student must attend a one-day summer workshop and attend a minimum of 4 workshops held in collaboration with the Laney Graduate School and the Emory Center for Ethics. Students must also attend a minimum of 6 hours of program-based ethics material (CS 590, the programs teaching program and CS 700, Graduate Seminar). CS 590 should be completed in the fall of the second or third year of study.
• Students must fulfill the Graduate School residency requirements.
• Each student must present a deparment graduate seminar, complete an acceptable dissertation and deliver an oral defense.

Students are required to take the following 3 core courses:

• BMI 500: Introduction to Biomedical Informatics
• CS 534 or BMI 534 or BIOS 534: Machine Learning
• BIOS 506: Biostatistical Methods (4)

In addition, students are required to take 4 courses that serve as building blocks of a sound biomedical informatics training. These courses are commonly offered by the BMI department or the Biostatistics and Bioinformatics departments. A full list of possible electives may be found in the handbook; some representative courses are listed below.

Sample Electives for the BMI concentration in the CSI PhD program: 

• BIOS 510: Probability Theory I
• BIOS 710: Probability Theory II
• BIOS 511: Statistical Inference I
• BIOS 711: Statistical Inference II
• BIOS 522: Survival Analysis
• BMI 510: Biostatistics for Machine Learning
• BMI 520: Practical Computing for Informatics
• BMI 532: Model-Based Machine Learning
• BMI 536: Intro to Deep Learning
• BMI 540: Time Series Analysis
• BMI 550: Applied Biomedical NLP
• BMI 555: Biomedical Image Analysis
• BMI 562: Cancer Single Cell Analysis
• EPI 504: Fundamentals of Epidemiology
• INFO 503: Management Principles for Informatics
• MATH 515: Numerical Analysis I
• IBS 523 Cancer Biology I
• IBS 524 Cancer Biology II
• IBS 534 Computational Neuroscience
• IBS 574 Computational Biology Bioinformatics
• BMI 614+ Machine Learning Computational Biology
• BMI 615+ Biomedical Imaging Informatics
• BMED 6760/6790 Info Process Model Neural
• BMED 6780 Medical Image Processing
• BMED 6789 Technology Ventures
• BMED 7411 Mathematical Models in Biology Medicine
• CS 551 Systems Programming
• CS 554 Database Systems
• CS 556 Programming Languages and Compilers
• CS 557 Artificial Intelligence
• CS 562 Advanced Computer Systems
• CS 563 Digital Image Processing
• CS 570 Data Mining
• CS 571 Natural Language Processing
• CS 572 Information Retrieval
• CS 573 Data Privacy and Security
• CS 580 Operating Systems
• CS 581 High Performance Computing (merged with CS 555)
• MATH 771 Numerical Optimization

To meet this requirement, students may opt for courses from Mathematics, Computer Science, Biology, Chemistry, Biomedical Informatics, the Rollins School of Public Health, School of Medicine, and appropriate schools at Georgia Tech through the ARCHE program. When substituting courses, a student must obtain prior written approval from their thesis advisor, the CSI DGS and the BMI program director.

Students must complete their core courses with a grade of B+ or higher and complete the remaining coursework by year three with a GPA of 3.5 or higher. Students may take a qualifying exam once they have completed the minimum course requirements.