Patricia Pauli

30 papers A* 1C 1Journal 19Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Convolutional neural networks as 2-D systems. Autom. Dennis Gramlich, Patricia Pauli, Carsten W. Scherer, Christian Ebenbauer
2026	J	`jnl`	LipKernel: Lipschitz-bounded convolutional neural networks via dissipative layers. Autom. Patricia Pauli, Ruigang Wang, Ian R. Manchester, Frank Allgöwer
2024	J	`jnl`	Learning Soft Constrained MPC Value Functions: Efficient MPC Design and Implementation providing Stability and Safety Guarantees. CoRR Nicolas Chatzikiriakos, Kim Peter Wabersich, Felix Berkel, Patricia Pauli, Andrea Iannelli
2024	—	`conf`	Learning soft constrained MPC value functions: Efficient MPC design and implementation providing stability and safety guarantees. L4DC Nicolas Chatzikiriakos, Kim Peter Wabersich, Felix Berkel, Patricia Pauli, Andrea Iannelli
2024	J	`jnl`	LipKernel: Lipschitz-Bounded Convolutional Neural Networks via Dissipative Layers. CoRR Patricia Pauli, Ruigang Wang, Ian R. Manchester, Frank Allgöwer
2024	J	`jnl`	Lipschitz constant estimation for general neural network architectures using control tools. CoRR Patricia Pauli, Dennis Gramlich, Frank Allgöwer
2024	A*	`conf`	Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations. ICLR Patricia Pauli, Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu
2024	J	`jnl`	Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations. CoRR Patricia Pauli, Aaron J. Havens, Alexandre Araujo, Siddharth Garg, Farshad Khorrami, Frank Allgöwer, Bin Hu
2024	J	`jnl`	State space representations of the Roesser type for convolutional layers. CoRR Patricia Pauli, Dennis Gramlich, Frank Allgöwer
2023	J	`jnl`	Convolutional Neural Networks as 2-D systems. CoRR Dennis Gramlich, Patricia Pauli, Carsten W. Scherer, Frank Allgöwer, Christian Ebenbauer
2023	—	`conf`	Lipschitz constant estimation for 1D convolutional neural networks. L4DC Patricia Pauli, Dennis Gramlich, Frank Allgöwer
2023	—	`conf`	Lipschitz-Bounded 1D Convolutional Neural Networks using the Cayley Transform and the Controllability Gramian. CDC Patricia Pauli, Ruigang Wang, Ian R. Manchester, Frank Allgöwer
2023	J	`jnl`	Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian. CoRR Patricia Pauli, Ruigang Wang, Ian R. Manchester, Frank Allgöwer
2022	—	`conf`	Bounding the Difference Between Model Predictive Control and Neural Networks. L4DC Ross Drummond, Stephen Duncan, Matthew C. Turner, Patricia Pauli, Frank Allgöwer
2022	J	`jnl`	Bounding the difference between model predictive control and neural networks. CoRR Ross Drummond, Stephen R. Duncan, Matthew C. Turner, Patricia Pauli, Frank Allgöwer
2022	J	`jnl`	Lipschitz constant estimation for 1D convolutional neural networks. CoRR Patricia Pauli, Dennis Gramlich, Frank Allgöwer
2022	—	`conf`	Neural network training under semidefinite constraints. CDC Patricia Pauli, Niklas Funcke, Dennis Gramlich, Mohamed Amine Msalmi, Frank Allgöwer
2022	J	`jnl`	Neural network training under semidefinite constraints. CoRR Patricia Pauli, Niklas Funcke, Dennis Gramlich, Mohamed Amine Msalmi, Frank Allgöwer
2022	J	`jnl`	Robustness analysis and training of recurrent neural networks using dissipativity theory. Autom. Patricia Pauli, Julian Berberich, Frank Allgöwer
2022	J	`jnl`	Training Robust Neural Networks Using Lipschitz Bounds. IEEE Control. Syst. Lett. Patricia Pauli, Anne Koch, Julian Berberich, Paul Kohler, Frank Allgöwer
2021	—	`conf`	Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers. CDC Patricia Pauli, Dennis Gramlich, Julian Berberich, Frank Allgöwer
2021	J	`jnl`	Linear systems with neural network nonlinearities: Improved stability analysis via acausal Zames-Falb multipliers. CoRR Patricia Pauli, Dennis Gramlich, Julian Berberich, Frank Allgöwer
2021	—	`conf`	Offset-free setpoint tracking using neural network controllers. L4DC Patricia Pauli, Johannes Köhler, Julian Berberich, Anne Koch, Frank Allgöwer
2021	J	`jnl`	Robust and optimal predictive control of the COVID-19 outbreak. Annu. Rev. Control. Johannes Köhler, Lukas Schwenkel, Anne Koch, Julian Berberich, Patricia Pauli, Frank Allgöwer
2021	C	`conf`	Training Robust Neural Networks Using Lipschitz Bounds. ACC Patricia Pauli, Anne Koch, Julian Berberich, Paul Kohler, Frank Allgöwer
2020	J	`jnl`	Offset-free setpoint tracking using neural network controllers. CoRR Patricia Pauli, Johannes Köhler, Julian Berberich, Anne Koch, Frank Allgöwer
2020	J	`jnl`	Robust and optimal predictive control of the COVID-19 outbreak. CoRR Johannes Köhler, Lukas Schwenkel, Anne Koch, Julian Berberich, Patricia Pauli, Frank Allgöwer
2020	J	`jnl`	Training robust neural networks using Lipschitz bounds. CoRR Patricia Pauli, Anne Koch, Julian Berberich, Frank Allgöwer
2019	—	`conf`	Optimal Delay Assignment in Delay-Aware Control of Cyber-Physical Systems: A Machine Learning Approach. CDC Patricia Pauli, Seyed Mehran Dibaji, Anuradha M. Annaswamy, Aranya Chakrabortty
2018	—	`conf`	The Sharing Economy for Residential Solar Generation. CDC Rodrigo Henriquez-Auba, Patricia Pauli, Dileep M. Kalathil, Duncan S. Callaway, Kameshwar Poolla

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.