Academics

Pre-Doctoral Program

Program Overview

The Pre-Doctoral Master of Science in Computer Science is a highly selective, 12-course program tailored for students who are committed to pursuing advanced research-in computer science. This program is designed for those aiming to strengthen their research background in preparation for PhD studies. Participants have the opportunity to work closely with a faculty member as a research advisor. The Pre-Doctoral MS in CS is a full-time program that begins in the Autumn quarter and is completed in 15 months.

Please Note: Admission to the Pre-Doctoral MS is extremely competitive, with a very limited number of students admitted each year. Due to its specific focus on academic research, this program is not designed for students primarily seeking industry careers. Admission is entirely separate from other MPCS tracks, and transfers into this program are not permitted.

15 Months

Time to Degree

Full-Time

Schedule

Hyde Park, Chicago

Location

$82.2K *

Program Tuition

Research

Academic Focus

Yes

STEM OPT Extension Eligible

* The total tuition cost provided is an estimate based on the current academic year’s rates and is subject to change. Additional fees and expenses, such as books, supplies, and living costs, are not included. If required, immersion coursework is an additional expense.

 

Application Deadlines

Round Application Deadline Decision Release
Round 1 February 5, 2025 Early March 2025
Round 2 April 2, 2025 Early May 2025

 

Pre-Doc Curriculum

Core course requirements (4 courses)

  • ​1 Theory course (MPCS or PhD level)
  • 2 Systems core classes (MPCS or approved 300-level PhD level)
  • 1 Machine Learning (MPCS 53111 or approved 300-level PhD course)

Research requirements (4 courses)

  • 2 Practicum courses with MS research advisor
  • 2 Reading & Research courses to work on research

Elective course requirements (4 courses)

  • CMSC 300-level PhD courses providing depth in a specific area.
  • MPCS courses can be taken with permission of Pre-Doc faculty advisor.

Internship requirements

  • Pre-doctoral students should plan to work with their MS research advisor in the summer after their first academic year of study.

Sample Pre-Doc Course Schedule

Pre-Doctoral students are expected to concentrate most of their research work in their first year, allowing them to build a competitive PhD application in their final quarter. A typical schedule could look like this (research courses appear highlighted in bold):

 

Autumn
Winter
Spring
Summer
Autumn
Reading & Research Practicum Practicum Research with advisor Elective
Theory Systems Reading & Research Elective
Systems Elective Machine Learning Elective
Pre-Doctoral Research Advisors 2025-2026

Below is the list of Department of Computer Science faculty who have expressed interest in advising students in the MPCS Pre-Doctoral program, and their research interest(s) for the 2025 – 2026 academic year.

Please note: these are the only CS faculty that have agreed to review Pre-Doctoral applications for the 2025-2026 academic year. If you submit an application to work with a faculty member not listed here, or in a research area not listed, your application will not be reviewed.

  • Diana Franklin–Quantum Computing Education
  • Haryadi Gunawi–Operating, Storage, and Distributed systems
  • Rana Hanocka– Computer Graphics, Computer Vision, Deep Learning, Generative AI
  • Grant Ho – Security and Privacy, AI/ML and Security, Data Science
  • William Hoza– Computational Complexity Theory, Pseudorandomness, Derandomization, Circuit Complexity
  • Junchen Jiang– Computer Networks, Machine Learning, Mobile Computing
  • Tian Li–Efficient and Trustworthy Machine Learning, Optimization
  • Yanjing Li– Computer Architecture, Systems and Machine Learning, Emerging Technologies, Robust System Design
  • Pedro Lopes– Wearables, Haptics and New Sensory Experiences in Virtual/Augmented Reality, Human Computer Interaction
  • Ken Nakagaki– Human-Computer Interaction, Interaction Design, Actuated and Shape-Changing Tangible User Interfaces, Interactive Media Art
  • Kexin Pei–Security, Software Engineering, Machine Learning, Machine Learning for Code
  • Aaron Potechin– Theory
  • Chenhao Tan– Human-Centered AI, Natural Language Process, Computational Social Science, Human-Computer Interaction

 

These research advisors are only available to students admitted to the Pre-Doctoral program.

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