PhD Computational and Data Enabled Science and Engineering

Seeding high quality interdisciplinary research.

student at Center for Computational Research.

Center for Computational Research, University at Buffalo, North Campus

On this page:

Program Director

Varun Chandola
213 Capen Hall
chandola@buffalo.edu
(716) 645-4747

About the CDSE Program

The integration of large computing and big data is essential to tackle the urgent research problems in fields ranging from multi-scale modeling and design of materials to natural disasters, smart electric grids, and medical technologies.

We train scientists to analyze big data and multisource datasets to solve these grand challenges, by bringing together the talents of faculty across several departments including the Departments of Mechanical and Aerospace Engineering, Chemical and Biological Engineering, Computer Science and Engineering, Math, Physics, and Chemistry.

Program Requirements

  • A Master's degree in a related field is required for admission to the PhD program. Some related fields of study include engineering, mathematics, physics, chemistry, marketing, business, and pharmacy.
  • Complete a minimum of 72 credit hours
  • 30 credits of core classes
  • Pass qualifying exam
  • Prepare dissertation

Core Course Requirements

Our curriculum is designed around three core subjects:

  1. Data Science
  2. Applied Mathematics and Numerical Methods
  3. High Performance and Data Intensive Computing

A minimum of 9 credit hours from the approved list of core courses must be taken. The core course requirements total 30 credits with a minimum GPA of 3.2 on a 4.0 scale. Courses taken during your master's program may be transferred and used toward this requirement with the approval of your primary advisor, dissertation committee, and the Director of Graduate Studies. We strongly suggest you finish this course work within the first two years of the program.

Core Courses

Data Science

CSE 574: Intro Machine Learning

STA 521: Intro Theoretical Statistics 1

STA 522: Intro Theoretical Statistics 2

STA 534: Design of Experiments

STA 567: Bayesian Statistics

MAE 701 Special Topics: Bayesian Methods in Engineering Applications

CSE 704 Seminar: Big Data

CSE 740 Seminar: Big Data/Machine Learning

Applied Numerical Mathematics

MTH 539: Method of Applied Math 1

MTH 540: Method of Applied Math 2

MGF 636: Complex Fin Instruments

MAE 702 Seminar: Applied Functional Analysis

High Performance and Data Intensive Computing

MTH 563: Data-Oriented Computing for Mathematicians

CSE 570: Introduction to Parallel and Distributed Processing

CSE 587: Data Intensive Computing

CDA 609: High Performance Computing 1

CDA 610: High Performance Computing 2

Qualification Process

When you first start our program, you will select an advisor and your dissertation committee. Then you will decide on a research topic and submit a short proposal that articulates your topic and its relationship to the computational and data sciences field. This technical report must be completed no later than the end of the second semester.

Dissertation Committee Guidelines

We want each dissertation committee to reflect the intellectual diversity of our program. Because of this, the committee:

  • should not have more than 1 core member and 1 additional member with primary academic affiliation in the same department
  • must have a core member that is CDSE affiliated faculty

Oral Examination

Students must pass an oral examination on the needed background material to succeed in the field. Your dissertation committee will provide a written list of topics and courses. The exam may be retaken once within a 12-month period. This requirement should be met by the end of the third semester of study. Once the technical report and the oral examination have successfully been completed, you may file an application for PhD candidacy.

Dissertation

Students must take courses to support their dissertation research. These courses, totaling 12 credits, must be completed by the end of your fifth semester. Depending on your dissertation topic, you may be advised to take elective courses that inform your research topic, or you may be advised to take other courses to broaden your CDSE-related knowledge.

The dissertation must be original and contribute to the furthering of the field.