Samuel G. Finlayson

14 papers A* 1Misc 1Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research. CoRR Rulin Shao, Akari Asai, Shannon Zejiang Shen, Hamish Ivison, Varsha Kishore, Jingming Zhuo, Xinran Zhao, Molly Park, Samuel G. Finlayson, David A. Sontag, Tyler Murray, Sewon Min, Pradeep Dasigi, Luca Soldaini, Faeze Brahman, Wen-tau Yih, Tongshuang Wu, Luke Zettlemoyer, Yoon Kim, Hannaneh Hajishirzi, Pang Wei Koh
2021	J	`jnl`	Code-free deep learning for multi-modality medical image classification. Nat. Mach. Intell. Edward Korot, Zeyu Guan, Daniel Ferraz, Siegfried K. Wagner, Gongyu Zhang, Xiaoxuan Liu, Livia Faes, Nikolas Pontikos, Samuel G. Finlayson, Hagar Khalid, Gabriella Moraes, Konstantinos Balaskas, Alastair K. Denniston, Pearse A. Keane
2021	Misc	`conf`	Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles. PSB Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, Isaac S. Kohane
2020	J	`jnl`	ML4H Abstract Track 2019. CoRR Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Tristan Naumann, Brett K. Beaulieu-Jones, Adrian V. Dalca
2020	A*	`conf`	Subgraph Neural Networks. NeurIPS Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik
2020	J	`jnl`	Subgraph Neural Networks. CoRR Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Marinka Zitnik
2019	J	`jnl`	Approaching Small Molecule Prioritization as a Cross-Modal Information Retrieval Task through Coordinated Representation Learning. CoRR Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, William Yuan, Isaac S. Kohane
2019	—	`conf`	Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different? ML4H@NeurIPS Adrian V. Dalca, Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Corey Chivers, Andrew Beam, Tristan Naumann, Brett K. Beaulieu-Jones
2019	—	`ed.`	Machine Learning for Health Workshop, ML4H@NeurIPS 2019, Vancouver, BC, Canada, 13 December 2019 ML4H@NeurIPS Adrian V. Dalca, Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Brett K. Beaulieu-Jones
2018	J	`jnl`	Adversarial Attacks Against Medical Deep Learning Systems. CoRR Samuel G. Finlayson, Isaac S. Kohane, Andrew L. Beam
2018	J	`jnl`	Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene Chen, Corey Chivers, Adrian V. Dalca, Samuel G. Finlayson, Madalina Fiterau, Jason Alan Fries, Marzyeh Ghassemi, Mike Hughes, Bruno Jedynak, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi
2018	J	`jnl`	Privacy-Preserving Distributed Deep Learning for Clinical Data. CoRR Brett K. Beaulieu-Jones, William Yuan, Samuel G. Finlayson, Zhiwei Steven Wu
2018	J	`jnl`	Towards generative adversarial networks as a new paradigm for radiology education. CoRR Samuel G. Finlayson, Hyunkwang Lee, Isaac S. Kohane, Luke Oakden-Rayner
2016	J	`jnl`	Toward rapid learning in cancer treatment selection: An analytical engine for practice-based clinical data. J. Biomed. Informatics Samuel G. Finlayson, Mia A. Levy, Sunil Reddy, Daniel L. Rubin

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.