Samantha Syeda Khairunnesa

Samantha Syeda Khairunnesa

Assistant Professor

    Bradley Hall 177
    (309) 677-2386


Ph.D., Computer Science, Iowa State University, 2021
M.S., Computer Science, Iowa State University, 2017
B.Sc., Computer Science & Engineering, Khulna University of Engineering & Technology, 2011


Samantha Khairunnesa, Ph.D., is the Assistant Professor in the Department of Computer Science and Information Systems at Bradley University, where she has been since January 2022. She has held an assistant professor position at the Florida Gulf Coast University before joining Bradley University. She has also taught undergraduate courses as an independent instructor at Iowa State University (ISU) while being a CS Ph.D. student herself at ISU. Dr. Khairunnesa has received the ISU research excellence award (2020) and teaching excellence awards (2019). She specializes in software engineering, programming languages, and machine learning. Prof. Khairunnesa served as the student volunteer chair, publicity chair, and on the program committees of several conferences, doctoral symposiums, workshops, and as a referee for top journals in her area. She is a professional member of ACM.

Area of Expertise

  • Software Engineering
  • Machine Learning
  • Programming Languages
  • Mining Software Repositories


Courses currently teaching at Bradley University:

  • CS 215 - Computability, Formal Languages, and Heuristics
  • CS 390 - Introduction to Software Engineering
  • CIS 475/575 - Computer Information Systems Analysis. Design and Integration
  • CS 590 - Fundamentals of Software Engineering
  • CS 101 - Introduction to Programming
  • CS 102 - Data Structures
  • CS 493/593 - Agile Software Development

Courses taught before joining Bradley University:

  • Principles of Programming Languages
  • Software Engineering Fundamentals

Prospective Students (Research Assistants)

I am actively seeking collaboration with motivated and talented undergraduate and graduate students.

Before contacting me, please do your homework: read my home page and at least one recent paper. After reading a paper, if you don't have any interesting ideas, I am probably not someone you want to work with. On the bright side, if you have an idea you want to discuss further, send me a brief introductory email explaining your interest in my research.