Benjamin M. Rottman

26 papers B 20Journal 4Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	WinLeak: A Thermal and RGB Image Dataset for Window Air Leakage Detection in Residential Buildings. BuildSys Anveshika Kamble, Naman Gupta, Nishanth Pullabhotla, Daniel Mossé, Stephen Lee, Benjamin M. Rottman, Dilip Teja
2024	B	`conf`	Can People Accurately Draw Statistical Inferences from Dot Plots? CogSci Sara Jaramillo, Benjamin M. Rottman
2021	B	`conf`	Causal Learning With Delays Up to 21 Hours. CogSci Yiwen Zhang, Benjamin M. Rottman
2021	B	`conf`	Causal Learning With Interrupted Time Series. CogSci Yiwen Zhang, Benjamin M. Rottman
2021	J	`jnl`	Motivated Reasoning in an Explore-Exploit Task. Cogn. Sci. Zachary A. Caddick, Benjamin M. Rottman
2021	J	`jnl`	The Accuracy of Causal Learning Over Long Timeframes: An Ecological Momentary Experiment Approach. Cogn. Sci. Ciara L. Willett, Benjamin M. Rottman
2021	B	`conf`	Using Causality to Map Difficulties in a Qualitative Physics Problem. CogSci Sara Jaramillo, Eric Kuo, Timothy Nokes-Malach, Benjamin M. Rottman
2020	B	`conf`	Causal Learning with Two Causes over Weeks. CogSci Ciara L. Willett, Benjamin M. Rottman
2020	—	`conf`	Using Causal Networks to Examine Resource Productivity and Coordination in Learning Science. ICLS Eric Kuo, Nolan Weinlader, Benjamin M. Rottman, Timothy J. Nokes-Malach
2019	B	`conf`	Motivated Reasoning in Causally Ambiguous Explore-Exploit Situations. CogSci Zachary A. Caddick, Benjamin M. Rottman
2019	B	`conf`	Politically Motivated Causal Evaluations of Economic Performance. CogSci Zachary A. Caddick, Benjamin M. Rottman
2019	B	`conf`	The Accuracy of Causal Learning over 24 Days. CogSci Ciara L. Willett, Benjamin M. Rottman
2018	B	`conf`	Causal Learning from Trending Time-Series. CogSci Kevin Soo, Benjamin M. Rottman
2018	B	`conf`	Comparing Mediation Inferences and Explaining Away Inferences on Three Variable Causal Structures. CogSci Cory Derringer, Benjamin M. Rottman
2016	B	`conf`	Causal Learning With Continuous Variables Over Time. CogSci Kevin Soo, Benjamin M. Rottman
2016	B	`conf`	Temporal Causal Strength Learning with Multiple Causes. CogSci Cory Derringer, Benjamin M. Rottman
2015	B	`conf`	Do Markov Violations and Failures of Explaining Away Persist with Experience? CogSci Benjamin M. Rottman, Reid Hastie
2015	B	`conf`	Elemental Causal Learning from Transitions. CogSci Kevin Soo, Benjamin M. Rottman
2015	B	`conf`	How Causal Mechanism and Autocorrelation Beliefs Inform Information Search. CogSci Benjamin M. Rottman
2015	B	`conf`	Informative Transitions: A Heuristic for Conditionalized Causal Strength Learning. CogSci Cory Derringer, Benjamin M. Rottman
2014	J	`jnl`	Children Use Temporal Cues to Learn Causal Directionality. Cogn. Sci. Benjamin M. Rottman, Jonathan F. Kominsky, Frank C. Keil
2014	B	`conf`	Information Search in an Autocorrelated Causal Learning Environment. CogSci Benjamin M. Rottman
2014	B	`conf`	Learning Causal Direction from Transitions with Continuous and Noisy Variables. CogSci Kevin Soo, Benjamin M. Rottman
2012	J	`jnl`	Causal Systems Categories: Differences in Novice and Expert Categorization of Causal Phenomena. Cogn. Sci. Benjamin M. Rottman, Dedre Gentner, Micah B. Goldwater
2011	B	`conf`	Learning Causal Direction from Repeated Observations over Time. CogSci Benjamin M. Rottman, Frank Keil
2011	B	`conf`	Which Parts of Scientific Explanations are Most Important? CogSci Benjamin M. Rottman, Frank Keil

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.