Dan Mikulincer

26 papers A* 8A 2Journal 16

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Fast mixing in Ising models with a negative spectral outlier via Gaussian approximation. CoRR Dan Mikulincer, Youngtak Sohn
2025	A*	`conf`	Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions. COLT Elisabetta Cornacchia, Dan Mikulincer, Elchanan Mossel
2025	J	`jnl`	Low-dimensional Functions are Efficiently Learnable under Randomly Biased Distributions. CoRR Elisabetta Cornacchia, Dan Mikulincer, Elchanan Mossel
2025	J	`jnl`	Size and Depth of Monotone Neural Networks: Interpolation and Approximation. IEEE Trans. Neural Networks Learn. Syst. Dan Mikulincer, Daniel Reichman
2025	A	`conf`	Time Lower Bounds for the Metropolis Process and Simulated Annealing. APPROX/RANDOM Zongchen Chen, Dan Mikulincer, Daniel Reichman, Alexander S. Wein
2024	J	`jnl`	How to Trap a Gradient Flow. SIAM J. Comput. Sébastien Bubeck, Dan Mikulincer
2023	A*	`conf`	Integrality Gaps for Random Integer Programs via Discrepancy. SODA Sander Borst, Daniel Dadush, Dan Mikulincer
2023	A	`conf`	Is This Correct? Let's Check! ITCS Omri Ben-Eliezer, Dan Mikulincer, Elchanan Mossel, Madhu Sudan
2023	A*	`conf`	Noise Stability on the Boolean Hypercube via a Renormalized Brownian Motion. STOC Ronen Eldan, Dan Mikulincer, Prasad Raghavendra
2023	J	`jnl`	Time Lower Bounds for the Metropolis Process and Simulated Annealing. CoRR Zongchen Chen, Dan Mikulincer, Daniel Reichman, Alexander S. Wein
2022	A*	`conf`	Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions. NeurIPS Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik
2022	J	`jnl`	Archimedes Meets Privacy: On Privately Estimating Quantiles in High Dimensions Under Minimal Assumptions. CoRR Omri Ben-Eliezer, Dan Mikulincer, Ilias Zadik
2022	J	`jnl`	Community detection and percolation of information in a geometric setting. Comb. Probab. Comput. Ronen Eldan, Dan Mikulincer, Hester Pieters
2022	J	`jnl`	Is this correct? Let's check! CoRR Omri Ben-Eliezer, Dan Mikulincer, Elchanan Mossel, Madhu Sudan
2022	J	`jnl`	Noise stability on the Boolean hypercube via a renormalized Brownian motion. CoRR Ronen Eldan, Dan Mikulincer, Prasad Raghavendra
2022	A*	`conf`	Size and depth of monotone neural networks: interpolation and approximation. NeurIPS Dan Mikulincer, Daniel Reichman
2022	J	`jnl`	Size and depth of monotone neural networks: interpolation and approximation. CoRR Dan Mikulincer, Daniel Reichman
2021	A*	`conf`	Non-asymptotic approximations of neural networks by Gaussian processes. COLT Ronen Eldan, Dan Mikulincer, Tselil Schramm
2021	J	`jnl`	Non-asymptotic approximations of neural networks by Gaussian processes. CoRR Ronen Eldan, Dan Mikulincer, Tselil Schramm
2020	J	`jnl`	Community detection and percolation of information in a geometric setting. CoRR Ronen Eldan, Dan Mikulincer, Hester Pieters
2020	A*	`conf`	How to Trap a Gradient Flow. COLT Sébastien Bubeck, Dan Mikulincer
2020	J	`jnl`	How to trap a gradient flow. CoRR Sébastien Bubeck, Dan Mikulincer
2020	A*	`conf`	Network size and size of the weights in memorization with two-layers neural networks. NeurIPS Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer
2020	J	`jnl`	Network size and weights size for memorization with two-layers neural networks. CoRR Sébastien Bubeck, Ronen Eldan, Yin Tat Lee, Dan Mikulincer
2019	J	`jnl`	Stability of the Shannon-Stam inequality via the Föllmer process. CoRR Ronen Eldan, Dan Mikulincer
2016	J	`jnl`	Information and dimensionality of anisotropic random geometric graphs. CoRR Ronen Eldan, Dan Mikulincer

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.