Pasi Kolinummi

14 papers C 6Journal 3Unranked 5

Year	Rank	Type	Title / Venue / Authors
2000	J	`jnl`	Chained backplane communication architecture for scalable multiprocessor systems. J. Syst. Archit. Pasi Kolinummi, Timo Hämäläinen, Jukka Saarinen
2000	—	`conf`	H.263 video encoder implementation on a scalable DSP system. EUSIPCO Pasi Kolinummi, Juha Sarkijarvi, Timo Hämäläinen, Jukka Saarinen
2000	J	`jnl`	PARNEU: general-purpose partial tree computer. Microprocess. Microsystems Pasi Kolinummi, Panu Hämäläinen, Timo Hämäläinen, Jukka Saarinen
2000	C	`conf`	Parallel DSP implementation of wavelet transform in image compression. ISCAS Kaisa Haapala, Pasi Kolinummi, Timo D. Hämäläinen, Jukka Saarinen
2000	J	`jnl`	Parallel Implementation of Self-Organizing Map on the Partial Tree Shape Neurocomputer. Neural Process. Lett. Pasi Kolinummi, Pasi Pulkkinen, Timo Hämäläinen, Jukka Saarinen
2000	—	`conf`	Scalable DSP implementation of DCT-based motion estimation algorithm. EUSIPCO Miia Viitanen, Pasi Kolinummi, Timo Hämäläinen, Jukka Saarinen
2000	—	`conf`	Scalable DSP realization of wavelet transform in image coding. EUSIPCO Kaisa Haapala, Pasi Kolinummi, Timo Hämäläinen, Jukka Saarinen
2000	—	`conf`	Scalable Realization of Sparse Distributed Memory on a Multiprocessor System. IS Pasi Kolinummi, Kimmo Tikkanen, Timo Hämäläinen, Jukka Saarinen
2000	C	`conf`	Scalable implementation of H.263 video encoder on a parallel DSP system. ISCAS Pasi Kolinummi, Juha Sarkijarvi, Timo D. Hämäläinen, Jukka Saarinen
1999	C	`conf`	Software support for low latency communication in scalable multimedia DSP system. MMSP Pasi Kolinummi, Pasi Pulkkinen, Timo Hämäläinen, Jukka Saarinen
1997	C	`conf`	Mapping of Radial Basis Function Networks to Partial Tree Shape Parallel Neurocomputer. ICANN Pasi Kolinummi, Timo Hämäläinen, Jukka Saarinen
1997	—	`conf`	Mappings of SOM and LVQ on the partial tree shape neurocomputer. ICNN Pasi Kolinummi, Timo Hämäläinen, Kimmo Kaski
1996	C	`conf`	Linearly Expandable Partial Tree Shape Architecture for Parallel Neurocomputer. ICANN Timo Hämäläinen, Pasi Kolinummi, Kimmo Kaski
1996	C	`conf`	Mapping of Multilayer Perceptron Networks to Partial Tree Shaped Parallel Neurocomputer. ICANN Pasi Kolinummi, Timo Hämäläinen, Harri Klapuri, Kimmo Kaski

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.