CV

Education

Experian: Machine Learning Engineer

Developing internal LLM-based tools designed to support the Experian AI Assistant.

George Mason University: Research Assistant (2022 – Present)

Input Generation: Leveraging Large Language Models (LLMs) to generate pathological inputs for performance testing and debugging to help developers identify worst-case execution scenarios.
Complexity Analysis: Designed and implemented an algorithm to analyze worst-case running time complexity of recursive programs to help developers evaluate performance bottlenecks regardless of programming language.

University of Nebraska Lincoln: Research Assistant (2018 – 2021)

Verification: Developing developer tools to efficiently prove numerical assertions and resource bounds often found in safety-critical systems.
Predictive Failure Avoidance: Developed an algorithm to abstract inputs leading to program failures (e.g., assertion violations) and automatically repair them to ensure successful program execution.
Dynamic Invariant Generation: Produced non-trivial numerical invariants from execution traces useful for verifying the absence of errors in safety-critical systems.

Purdue University: Research Assistant (Summer 2017)

NanoCluster Evolution Prediction: Built a simulation tool to visualize and predict the size evolution of irradiation-induced nanoclusters in iron-based materials.

George Mason University: Adjunct Professor
Courses: Formal Methods & Models
Responsibilities include:

Designed and developed course content to align with university learning objectives.
Create quizzes, assignments and exams tailored to reinforce key learning goals.
Delivered weekly lectures and held office hours for students support and engagement.
Managed a team of teaching assistants responsible for tutoring and grading.
Conducted individual student meetings to discuss academic progress and strategies for success.

University of Nebraska Lincoln: Teaching Assistant

Ishimwe, D., (2023, November). Inferring Complexity Bounds from Recurrence Relations. Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering.
Ishimwe, D., Nguyen, T., & Nguyen, K. (2022, May). Dynaplex: inferring asymptotic runtime complexity of recursive programs. Proceedings of the ACM/IEEE 44th International Conference on Software Engineering: Companion Proceedings.
Ishimwe, D., Nguyen, K., & Nguyen, T. (2021). Dynaplex: analyzing program complexity using dynamically inferred recurrence relations. Proceedings of the ACM on Programming Languages, 5(OOPSLA).
Nguyen, T., Ishimwe, D., Malyshev, A., Antonopoulos, T., & Phan, Q. S. (2020, November). Using dynamically inferred invariants to analyze program runtime complexity. Proceedings of the 3rd ACM SIGSOFT International Workshop on Software Security from Design to Deployment.

Preferred Languages: Python, C, OCaml
Technical Skills: Git, Bash, Docker, LLMs, Machine Learning
Leadership & Communication: Research Publication & Presentation, Technical Event (Seminar) Coordination, Academic Mentorship.

VA-WHPC Organizing Committee: Serve as an Organizing Committee member for Virginia Women in High Performance Computing (VA-WHPC); maintain the official website and organize events to empower and advance women and allies in HPC across the Commonwealth of Virginia.
Research Communication: Published and presented original research at top-tier conferences (FSE, ICSE, OOPSLA) and delivered invited seminar talks at universities.
Academic Organization: Organized and led specialized seminars on Software Engineering topics.
Community Building: Served as the Social Event Coordinator for the Software Engineering group at George Mason University.