Homepage of David Gens

About

I am a Postdoctoral Researcher at the University of California, Irvine.

My interests span a wide range of complex computational systems such as OS kernels, compilers, and deep neural networks. I am especially interested in understanding performance characteristics as well as failure modes of these systems. My past work includes self-supervised representation learning, automated compiler-level software analysis, hardware security research, and memory-corruption attacks.

Projects and Publications

The full list of publications is here. I have occasionally acted as an external reviewer to several conferences and journals (including IEEE S&P, IEEE TDSC, NDSS, and ACM CCS). Some recent project examples:

Estimating Stack Frame Sizes using Transformers (ACM CCS'21 - AISec Workshop) in Stripped and Optimized Binaries (AMD64 and AArch64)
Camera Calibration (Comma.ai Challenge 2021) using Convolutional Neural Networks
V0LTpwn (USENIX Security 2020) (remote-fault injection from software on x86 that breaks SGX)
NoJITsu (NDSS 2020 & BH20) (data-only attack against interpreters in JIT engines)
K-Miner (NDSS 2018) (a static analysis framework to uncover memory corruption in Linux at scale)

CV

since '19	Postdoctoral Researcher at the Secure Systems and Software Laboratory of Professor Michael Franz
'16 to '19	Research Assistant and PhD student at the Intel Collaborative Research Institute and the System Security Lab of Professor Ahmad-Reza Sadeghi
'14 to '16	Computer Science (M.Sc.), focus on InfoSec, at TU Darmstadt
'13 to '14	developed trade-workflow and performance-analysis tools at 360T for their OTC/FX-trading platform
'10 to '13	Computer Science (B.Sc.) at HSRM
'09 to '10	studied Mathematics at Gutenberg Universität