Introduction

Hi, I’m Safwat Ali Khan, a PhD candidate in Computer Science specializing in automated software testing for mobile applications. My research focuses on enhancing Automated Input Generation (AIG) tools using techniques from machine learning, natural language processing, and computer vision.

My work explores three key areas:

  • Improving Automated UI Exploration – Developing techniques to help AIG tools navigate complex UI elements that hinder automated testing.
  • Understanding App Usage During Testing – Using large language models (LLMs) to analyze execution traces and determine whether real-world use cases were exercised.
  • Enhancing Mobile App UI Design – Investigating age-related usability challenges to develop automated solutions that improve mobile app accessibility and ease of use.

My goal is to make mobile app testing more effective, efficient, and adaptable, ensuring more reliable and user-friendly applications. Feel free to connect if you’re interested in software testing, AI-driven automation, or tech innovations!

Safwat Ali Khan

Education

  • Undergraduate

    University of Dhaka
    Dhaka, Bangladesh
    Major: Computer Science & Engineering
    Degree: Bachelor of Science
    Timeline: 2010 - 2014

  • Graduate

    George Mason University
    VA, USA
    Major: Computer Science
    Degree: Doctor of Philosophy
    Timeline: 2019 - present

Publications

My research contributions in software testing and automated mobile UI analysis:

Testing Practices, Challenges, and Developer Perspectives in Open-Source IoT Platforms

ICST 2025

Daniel Rodriguez-Cardenas, Safwat Ali Khan, Prianka Mandal, Adwait Nadkarni, Kevin Moran, Denys Poshyvanyk

AURORA: Navigating UI Tarpits via Automated Neural Screen Understanding

ICST 2024

Safwat Ali Khan, Wenyu Wang, Yiran Ren, Bin Zhu, Jiangfan Shi, Alyssa McGowan, Wing Lam, Kevin Moran

On Using GUI Interaction Data to Improve Text Retrieval-Based Bug Localization

ICSE 2024

Junayed Mahmud, Nadeeshan De Silva, Safwat Ali Khan, Seyed Hooman Mostafavi, SM Hasan Mansur, Oscar Chaparro, Andrian Marcus, Kevin Moran

Avgust: A Tool for Generating Usage-Based Tests from Videos of App Executions

ICSE-Companion 2023

Saghar Talebipour, Hyojae Park, Kesina Baral, Leon Yee, Safwat Ali Khan, Kevin Moran, Yuriy Brun, Nenad Medvidovic, Yixue Zhao

Avgust: Automating Usage-Based Test Generation from Videos of App Executions

FSE 2022

Yixue Zhao, Saghar Talebipour, Kesina Baral, Hyojae Park, Leon Yee, Safwat Ali Khan, Yuriy Brun, Nenad Medvidovic, Kevin Moran

Work Experience

I have worked as a Software Test Engineer for 5 years at my home country (Bangladesh). During this period, I worked with various software solutions in the domain of health care for developmentally disabled individuals, central nervous system patients (ADHD, Alzheimer etc.) and data collection for under-served communities in the rural areas of Bangladesh. I have an affinity towards software automation, which drove me towards incorporating automated tests using state-of-the-art tools like Selenium, JMeter, JUnit, Xamarin Test Cloud etc. As a Graduate Teaching Assistant, I was assigned to CS-222 (Computer Programming for Engineers), CS-262 (Intro to Low Level Programming) and CS-550 (Database Systems). This was an entirely different experience for me. I found the opportunity to help students get a better understanding in computer science is rewarding itself. During the summer of 2020, I worked as a co-mentor for the Aspired Scientists' Summer Internship Program with Professor Thomas LaToza as the mentor. I worked with two under-graduate students for the project, AI Enhanced Presentation Helper. Currently I am working on a project called AutoSeq: Creating automated test sequences for android applications. I am looking forward to starting Graduate Research Assistantship position under Professor Kevin Moran in Spring 2022, and I am very excited about the prospects.

Contact

skhan89@gmu.edu
Department of Computer Science
George Mason University
4400 University Drive
Fairfax, VA 22030, United States