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Personal website of Gabriel Ryan, PhD Candidate at Columbia University studying applications of Deep Learning to Cybersecurity. Read more

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Personal website of Gabriel Ryan, PhD Candidate at Columbia University studying applications of Deep Learning to Cybersecurity. Read more

 
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Current Trends in Security Research from Oakland 2019  

(Medium Post) I attended the IEEE Oakland Security and Privacy Conference last week and thought I would share a few thoughts on the major trends I observed in the papers at the conference. These are heavily biased towards my interests in Machine Learning and by no means intended to be comprehensive. Read more

Measuring Visual Complexity with Pixel Approximate Entropy  

(Medium Post) When designing visualizations, making charts that are straightforward to read and interpret is usually desirable. This becomes especially important in settings where users may have to make fast judgements based on the visualizations, such as in emergency rooms or on financial trading floors. In our recent paper in IEEE INFOVIS 2018, we introduce a new method for quantifying visual complexity, Pixel Approximate Entropy, that can be used to develop better visualizations in these types of settings. Read more

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publications

[Oceans 2012] Oversampling MAVS for Reduction of Vortex-Shedding Velocity Sensing Noise. Albert J. Williams, Gabriel Ryan, and Fredrik Thwaites. [paper]

[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]

[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 2019] Poster: Precise Dynamic Dataflow Tracking with Proximal Gradients. Gabriel Ryan, Abhishek Shah, Dongdong She, Koustubha Bhat, and Suman Jana. [paper] [poster]

[ICLR 2020] CLN2INV: Learning Loop Invariants with Continuous Logic Networks. Gabriel Ryan*, Justin Wong*, Jianan Yao*, Ronghui Gu, 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]

[USENIX Security 2021] Fine Grained Dataflow Tracking with Proximal Gradients. Gabriel Ryan, Abhishek Shah, Dongdong She, Koustubha Bhat, and Suman Jana. [paper] [code]

talks

Talk 1 on Relevant Topic in Your Field  

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Conference Proceeding talk 3 on Relevant Topic in Your Field  

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teaching

Teaching experience 1  

Undergraduate course, University 1, Department, 2014

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Teaching experience 2  

Workshop, University 1, Department, 2015

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