Software Testing · Robustness · SE ∩ AI
PhD student in Computer Science at North Carolina State University, advised by Marcelo d'Amorim. I work on software testing and improving the robustness of software systems.
Previously, I earned my MS in Computer Engineering from NYU and worked with Andrea Stocco at TU Munich as a DAAD scholar. This summer I joined the Max Planck Institute for Security and Privacy as a research intern, advised by Marcel Böhme.
under submission
A training-free property-testing methodology that augments VLM prompts with automatically mined visual properties of correct gameplay, covering collision, gravity, and animation coherence. It contributes 32 generic and 120 game-specific properties, improving bug detection recall by up to +14.8 pp across 7 VLMs while keeping precision high.
IEEE Transactions on Software Engineering (TSE) · major revision
A large-scale study showing that regression tests, transplanted across runtimes and reused as fuzzing seeds, uncover more WebAssembly runtime bugs than fuzzing with established corpora. Introduces RTBENCH, a corpus of 584 real-world regression tests, and reports 34 previously unknown bugs.
DeepTest '26, IEEE/ACM Int'l Workshop on Deep Learning for Testing (ICSEW)
Explores latent-space regularization in style-based GANs to generate more realistic, diverse, and fault-revealing test inputs for deep learning image classifiers.
ACM Transactions on Software Engineering and Methodology (TOSEM)
Introduces Mimicry, a targeted boundary testing technique using disentangled StyleGAN latent spaces to find inputs near decision boundaries across 5 image classification datasets.
Research Intern · Bochum, Germany
Advisor: Dr. Marcel Böhme
Research Assistant · Raleigh, NC
Advisor: Dr. Marcelo d'Amorim
Game testing: developed MR-guided VLM glitch detection for gameplay videos. WebAssembly runtime analysis: transplanting regression tests across runtimes and using them as seed corpora for fuzzing.
Research Intern · Munich, Germany
Advisor: Dr. Andrea Stocco
Conducted research on automated testing for deep learning systems. Developed latent space interpolation methods for boundary testing and improved validity of generated test pairs.
Computer Vision Engineer · New York, NY
Worked on real-time object detection systems for tracking enemy robots. Trained and tested models on hardware provided by the mechanical team.
Teaching Assistant · CSC 326: Software Engineering
Instructor: Dr. Wesley Klewerton Guez Assuncao
Led two weekly lab sections for undergraduate software engineering students, supporting team-based development and core engineering practices.
Research Mentor · UIUC++ Program
Advisor: Dr. Marcelo d'Amorim
Mentored three undergraduate students on PingPong, an adaptive fuzzing project that coordinates AFL++ and AFLGo using coverage-growth plateau detection.
PhD in Computer Science · GPA 3.4
Coursework: Software Engineering, Advanced Software Testing and Analysis, Design and Analysis of Algorithms.
MS in Computer Engineering · GPA 3.80
Coursework: Machine Learning, Deep Learning, ML for Cybersecurity, Probability and Stochastic Processes.
BS in Information Technology · GPA 3.95 · Summa Cum Laude
Honors Thesis: "Robotics and Environmental Issues", NE Regional Honors Conference 2023.