I am a Senior Research Scientist at Microsoft, where I work in the CoreAI organization developing specialized models for AI-driven coding. Among other areas, my research involves improving models for Github Copilot code completions, SWE-agents, code review, and code search.
Background
I received my PhD from Columbia University in 2023, where I worked broadly in A.I. driven security and software development under Prof. Suman Jana and was fortunate to work with several other professors including Baishakhi Ray, Ronghui Gu, and Salvatore, Stolfo. During my PhD I participated in two internships in industry research groups, AWS A.I. Labs in 2023 and Microsoft Research RiSE in 2021, that resulted in successful publications in FSE ‘24 and ICSE ‘22 with a distinguished paper award.
Publications
[OOPSLA 2024] Accurate Data Race Prediction in the Linux Kernel through Sparse Fourier Learning. Gabriel Ryan, Burcu Cetin, Yonghwan Lim, Suman Jana. [paper] [code]
[FSE 2024] Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM. Gabriel Ryan, Siddhartha Jain, Mingyue Shang, Shiqi Wang, Xiaofei Ma, Murali Krishna Ramanathan, Baishakhi Ray. [paper]
[Oakland S&P 2023] Precise Detection of Kernel Data Races with Probabilistic Lockset Analysis. Gabriel Ryan, Abhishek Shah, Dongdong She, Suman Jana. [paper]
[ICSE 2022] TOGA: A Neural Method for Test Oracle Generation. Elizabeth Dinella*, Gabriel Ryan*, Todd Mytokowitz, Shuvendu Lahiri. [paper] [code] (ACM Sigsoft Distinguished Paper Award)
[OSDI 2021] DistAI: Data-Driven Automated Invariant Learning for Distributed Protocols. Jianan Yao, Runzhou Tao, Ronghui Gu, Jason Nieh, Suman Jana, Gabriel Ryan. [paper] [code] (OSDI Jay Lepreau Best Paper Award)
[USENIX Security 2021] Fine Grained Dataflow Tracking with Proximal Gradients. Gabriel Ryan, Abhishek Shah, Dongdong She, Koustubha Bhat, and Suman Jana. [paper] [code]
[PLDI 2020] Learning Nonlinear Loop Invariants with Gated Continuous Logic Networks. Jianan Yao*, Gabriel Ryan*, Justin Wong*, Suman Jana, and Ronghui Gu. [paper] [code]
[ICLR 2020] CLN2INV: Learning Loop Invariants with Continuous Logic Networks. Gabriel Ryan*, Justin Wong*, Jianan Yao*, Ronghui Gu, and Suman Jana. [paper] [code]
[Infovis 2018] At a Glance: Pixel Approximate Entropy as a Measure of Line Chart Complexity. Gabriel Ryan, Abigail Mosca, Remco Chang, and Eugene Wu. [paper] [code]
[Oakland S&P Workshops 2018] Simulated User Bots: Real Time Testing of Insider Threat Detection Systems. Preetam Dutta, Gabriel Ryan, Aleksander Zeiba, and Salvatore Stolfo. [paper]
[Oceans 2012] Oversampling MAVS for Reduction of Vortex-Shedding Velocity Sensing Noise. Albert J. Williams, Gabriel Ryan, and Fredrik Thwaites. [paper]
Awards
National Defense Science and Engineering Graduate Fellowship (NDSEG). Won NDSEG Fellowship for proposal “Proximal Gradient Analysis for Vulnerability Detection and Defense.” 2019 [proposal]
NSF Graduate Research Fellowship Honorable Mention. Received honorable mention for proposal “Modeling and Simulating Adversarial User Behavior with Sequential VAEs.” 2018