Adam H. Marblestone

12 papers A* 1A 1Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	NeuroAI for AI Safety. CoRR Patrick J. Mineault, Niccoló Zanichelli, Joanne Zichen Peng, Anton Arkhipov, Eli Bingham, Julian Jara-Ettinger, Emily Mackevicius, Adam H. Marblestone, Marcelo Mattar, Andrew Payne, Sophia Sanborn, Karen Schroeder, Zenna Tavares, Andreas S. Tolias
2022	J	`jnl`	Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao
2020	A*	`conf`	Gaussian Gated Linear Networks. NeurIPS David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Gregory Wayne, Joel Veness
2020	J	`jnl`	Gaussian Gated Linear Networks. CoRR David Budden, Adam H. Marblestone, Eren Sezener, Tor Lattimore, Greg Wayne, Joel Veness
2020	J	`jnl`	Product Kanerva Machines: Factorized Bayesian Memory. CoRR Adam H. Marblestone, Yan Wu, Greg Wayne
2019	A	`conf`	Malthusian Reinforcement Learning. AAMAS Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
2018	J	`jnl`	Malthusian Reinforcement Learning. CoRR Joel Z. Leibo, Julien Pérolat, Edward Hughes, Steven Wheelwright, Adam H. Marblestone, Edgar A. Duéñez-Guzmán, Peter Sunehag, Iain Dunning, Thore Graepel
2017	J	`jnl`	Feasibility of 3D Reconstruction of Neural Morphology Using Expansion Microscopy and Barcode-Guided Agglomeration. Frontiers Comput. Neurosci. Young-Gyu Yoon, Peilun Dai, Jeremy Wohlwend, Jae-Byum Chang, Adam H. Marblestone, Edward S. Boyden III
2016	J	`jnl`	Toward an Integration of Deep Learning and Neuroscience. Frontiers Comput. Neurosci. Adam H. Marblestone, Greg Wayne, Konrad P. Körding
2013	J	`jnl`	Physical principles for scalable neural recording. Frontiers Comput. Neurosci. Adam H. Marblestone, Bradley M. Zamft, Yael Maguire, Mikhail G. Shapiro, Thaddeus Cybulski, Joshua I. Glaser, Dario Amodei, P. Benjamin Stranges, Reza Kalhor, David Dalrymple, Dongjin Seo, Elad Alon, Michel M. Maharbiz, Jose M. Carmena, Jan M. Rabaey, Edward S. Boyden III, George M. Church, Konrad P. Körding
2013	J	`jnl`	Statistical Analysis of Molecular Signal Recording. PLoS Comput. Biol. Joshua I. Glaser, Bradley M. Zamft, Adam H. Marblestone, Jeffrey R. Moffitt, Keith E. J. Tyo, Edward S. Boyden III, George M. Church, Konrad P. Körding
2009	—	`conf`	Design and self-assembly of DNA into nanoscale 3D shapes. SIGGRAPH Talks Shawn M. Douglas, Hendrik Dietz, Tim Liedl, Björn Högberg, Franziska Graf, Adam H. Marblestone, Surat Teerapittayanon, Alejandro Vazquez, George M. Church, William M. Shih

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.