David OBrien

Ph.D. Student in Computer Science at Iowa State University
Conducting Research in Software Engineering

Education:

  • CS PhD Student at Iowa State University (2021 - Present)
  • CS BS at University of Northern Iowa (2017-2021)
  • Publications:

    David OBrien, Sumon Biswas, Sayem Imtiaz, Rabe Abdalkareem, Emad Shihab, Hridesh Rajan. 23 Shades of Self-Admitted Technical Debt: An Empirical Study on Machine Learning Software. In 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), 2022.

    Past Internships & Projects

    ISU Research Assistant (Current)

    Conduct research published in top-tier Software Engineering venues. Maintaining and improving upon the Boa Language and Infrastructure.


    ESEC/FSE 2022 Paper
    Boa Language and Infrastructure

    AI Engineer Internship

    Interned at Collins Aerospace, responsible for maintaining software estimated at 9.8 million dollars. Additionally, created an internal tool applying reusable supervised and reinforcement techniques on autonomous driving data extracted from multiple sensors.

    Bird Watcher

    Experimented with Convolutional Neural Network architectures both built from scratch and pre-trained upon a dataset of 365 unique bird species. Best performing model achieved 92% accuracy. Created a user-friendly streamlit app to enable users to experiment with models.


    GitHub Repository

    Compiler Construction Project

    Created the inner workings of a Compiler in one semester according to the language specification provided. Typically done in a group of 3 members, this project was undertaken by myself because the original class was cancelled due to COVID-19.



    GitHub Repository

    Technical Skills

    Machine Learning

  • Proficient in Python & Jupyter Notebooks
  • Previous projects involving supervised learning, unsupervised learning, and reinforcement learning
  • Experience with Sklearn, Keras, Surprise, Numpy, Pandas, NLTK, and Spacy
  • Created a Recommender System using over 25 million recorded ratings with a RMSE of ~0.85
  • Contributed and reapplied text extraction software to unseen business documents
  • Designed a system architecture and trained a neural network that achieved 89% correct classification rate on ~1000 samples to identify Self-Admitted Techncial Debt comments for my undergraduate research project.
  • Familiar with Matlab
  • Programming Languages

  • Proficient in Python
  • Proficient in Object-Oriented Programming
  • Comfortable in Java & JUnit Testing
  • Experience in C
  • Experience improving parallelized programs
  • Experience in Racket & Functional Programming
  • Familiar with Ruby







  • Data Storage

  • Comfortable with JSON
  • Comfortable with XML
  • Experience interacting with REST APIs
  • Experience with SQL
  • Experience with MariaDB
  • Familiar with Luigi

  • Web Development & Version Control

  • Comfortable with Git
  • Experience with HTML & CSS
  • Experience deploying web app with Azure services
  • Familiar with MVC Frameworks

  • Personal

  • I have sung in many choruses, my favorite being the UNI Varsity Men's Glee Club, where I also served on the Council for a year as the Head of Social Media. Listen to us here
  • I am a Los Angeles Rams fan (not super seriously, though.)
  • Favorite books have been "How to Win Friends and Influence People" by Dale Carnegie, and "Last Lecture" by Dr. Randy Pausch