Muhammad Gulzar is an assistant professor of computer science at Virginia Tech and an Amazon Scholar who blends academic research with practical cloud experience across 11 years in software engineering and data systems. His Ph.D. work at UCLA—supported by a Google Ph.D. Fellowship—produced scalable automated fault localization and testing methods that bridge software engineering and big data, with publications in VLDB, ICSE, and FSE. He has industry experience from multiple Google internships and ongoing collaboration with AWS, bringing production-oriented perspectives to research. Muhammad’s background spans teaching, research labs, and early startup product work, giving him a rare mix of pedagogical clarity and delivery focus. He frequently translates theoretical advances into tools and scalable evaluations for real-world data-centric systems. Based in Blacksburg, VA, he is known for turning rigorous formal methods into practical debugging and testing solutions for big data developers.
11 years of coding experience
8 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at Lahore University of Management Sciences
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of California, Los Angeles
Learn Apache Spark in Scala, Python (PySpark) and R (SparkR) by building your own cluster with a JupyterLab interface on Docker. :zap:
Contributions:20 pushes in 4 years
pythondata-sciencejupyter-notebookspark-mldocker
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