Sachin Shivakumar

20 papers C 3Journal 11Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Linear system analysis and optimal control of natural gas dynamics in pipeline networks. Autom. Luke S. Baker, Sachin Shivakumar, Dieter Armbruster, Rodrigo B. Platte, Anatoly Zlotnik
2026	J	`jnl`	MiMiCPy-FM: A User-Friendly Force Matching Tool for Extending the Time Scale of QM/MM MD MiMiC Simulations. J. Chem. Inf. Model. Sachin Shivakumar, Giorgia Frumenzio, Francesco Musiani, Fabio Affinito, Emiliano Ippoliti, Bharath Raghavan, Giulia Rossetti, Davide Mandelli, Paolo Carloni
2025	J	`jnl`	Extension of the Partial Integral Equation Representation to GPDE Input-Output Systems. IEEE Trans. Autom. Control. Sachin Shivakumar, Amritam Das, Siep Weiland, Matthew M. Peet
2025	—	`conf`	H2-Optimal Estimation of Linear Delayed and PDE Systems. CDC Danilo Braghini, Sachin Shivakumar, Matthew M. Peet
2025	J	`jnl`	Markov Kernels, Distances and Optimal Control: A Parable of Linear Quadratic Non-Gaussian Distribution Steering. CoRR Alexis M. H. Teter, Wenqing Wang, Sachin Shivakumar, Abhishek Halder
2025	J	`jnl`	Uniform Sampling From the Reachable Set Using Optimal Transport. IEEE Control. Syst. Lett. Karthik Elamvazhuthi, Sachin Shivakumar
2025	J	`jnl`	Uniform Sampling from the Reachable Set Using Optimal Transport. CoRR Karthik Elamvazhuthi, Sachin Shivakumar
2024	J	`jnl`	Sum-of-Squares Programming for Ma-Trudinger-Wang Regularity of Optimal Transport Maps. CoRR Sachin Shivakumar, Georgiy A. Bondar, Gabriel Khan, Abhishek Halder
2023	C	`conf`	Representation of linear PDEs with spatial integral terms as Partial Integral Equations. ACC Sachin Shivakumar, Amritam Das, Matthew M. Peet
2022	J	`jnl`	Computational stability analysis of PDEs with integral terms using the PIE framework. CoRR Sachin Shivakumar, Matthew M. Peet
2022	J	`jnl`	Efficient Data Structures for Exploiting Sparsity and Structure in Representation of Polynomial Optimization Problems: Implementation in SOSTOOLS. CoRR Declan Jagt, Sachin Shivakumar, Peter Seiler, Matthew M. Peet
2022	J	`jnl`	Efficient Data Structures for Representation of Polynomial Optimization Problems: Implementation in SOSTOOLS. IEEE Control. Syst. Lett. Declan Jagt, Sachin Shivakumar, Peter Seiler, Matthew M. Peet
2022	J	`jnl`	Representation of linear PDEs with spatial integral terms as Partial Integral Equations. CoRR Sachin Shivakumar, Amritam Das, Matthew M. Peet
2020	—	`conf`	Duality and H∞-Optimal Control Of Coupled ODE-PDE Systems. CDC Sachin Shivakumar, Amritam Das, Siep Weiland, Matthew M. Peet
2020	C	`conf`	PIETOOLS: A Matlab Toolbox for Manipulation and Optimization of Partial Integral Operators. ACC Sachin Shivakumar, Amritam Das, Matthew M. Peet
2020	—	`conf`	Robust Analysis of Uncertain ODE-PDE Systems Using PI Multipliers, PIEs and LPIs. CDC Amritam Das, Sachin Shivakumar, Matthew M. Peet, Siep Weiland
2019	—	`conf`	A Generalized LMI Formulation for Input-Output Analysis of Linear Systems of ODEs Coupled with PDEs. CDC Sachin Shivakumar, Amritam Das, Siep Weiland, Matthew M. Peet
2019	C	`conf`	Computing Input-Ouput Properties of Coupled Linear PDE systems. ACC Sachin Shivakumar, Matthew M. Peet
2019	—	`conf`	ℋ∞ Optimal Estimation for Linear Coupled PDE Systems. CDC Amritam Das, Sachin Shivakumar, Siep Weiland, Matthew M. Peet
2018	—	`conf`	Decentralized Control of Distributed Actuation in a Segmented Soft Robot Arm. CDC Azadeh Doroudchi, Sachin Shivakumar, Rebecca E. Fisher, Hamid Marvi, Daniel Aukes, Ximin He, Spring Berman, Matthew M. Peet

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.