Yanjue Song

11 papers C 1Misc 2Journal 4Unranked 4

Year	Rank	Type	Title / Venue / Authors
2024	—	`conf`	Enhancing Neural Speech Embeddings for Generative Speech Models. APSIPA Doyeon Kim, Yanjue Song, Nilesh Madhu, Hong-Goo Kang
2024	J	`jnl`	Evaluation of BLE-based audio broadcasting under probabilistic interference. Comput. Commun. Mathias Baert, Bart Moons, Jowan Pittevils, Yanjue Song, Nilesh Madhu, Jeroen Hoebeke
2024	—	`conf`	On the Disentanglement and Robustness of Self-Supervised Speech Representations. ICEIC Yanjue Song, Doyeon Kim, Nilesh Madhu, Hong-Goo Kang
2024	Misc	`conf`	Phase Reconstruction in Single Channel Speech Enhancement Based on Phase Gradients and Estimated Clean-Speech Amplitudes. ICASSP Yanjue Song, Nilesh Madhu
2024	—	`conf`	Salient sound extraction using deep neural networks predicting complex masks. SPA Tomasz Grzywalski, Dick Botteldooren, Yanjue Song, Nilesh Madhu
2024	—	`conf`	Spectrum-Aware Neural Vocoder Based on Self-Supervised Learning for Speech Enhancement. EUSIPCO Yanjue Song, Doyeon Kim, Hong-Goo Kang, Nilesh Madhu
2023	Misc	`conf`	Aiding Speech Harmonic Recovery in DNN-Based Single Channel Noise Reduction Using Cepstral Excitation Manipulation (CEM) Components. ICASSP Yanjue Song, Nilesh Madhu
2023	J	`jnl`	Investigations on the Optimal Estimation of Speech Envelopes for the Two-Stage Speech Enhancement. Sensors Yanjue Song, Nilesh Madhu
2022	C	`conf`	Drone Ego-Noise Cancellation for Improved Speech Capture using Deep Convolutional Autoencoder Assisted Multistage Beamforming. FUSION Yanjue Song, Stijn Kindt, Nilesh Madhu
2022	J	`jnl`	Improved CEM for Speech Harmonic Enhancement in Single Channel Noise Suppression. IEEE ACM Trans. Audio Speech Lang. Process. Yanjue Song, Nilesh Madhu
2022	J	`jnl`	Portable and Non-Intrusive Fill-State Detection for Liquid-Freight Containers Based on Vibration Signals. Sensors Yanjue Song, Ernest Van Hoecke, Nilesh Madhu

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.