Dan Lim

12 papers A 4Journal 8

Year	Rank	Type	Title / Venue / Authors
2023	A	`conf`	FastFit: Towards Real-Time Iterative Neural Vocoder by Replacing U-Net Encoder With Multiple STFTs. INTERSPEECH Won Jang, Dan Lim, Heayoung Park
2023	J	`jnl`	FastFit: Towards Real-Time Iterative Neural Vocoder by Replacing U-Net Encoder With Multiple STFTs. CoRR Won Jang, Dan Lim, Heayoung Park
2022	A	`conf`	JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speech. INTERSPEECH Dan Lim, Sunghee Jung, Eesung Kim
2022	J	`jnl`	JETS: Jointly Training FastSpeech2 and HiFi-GAN for End to End Text to Speech. CoRR Dan Lim, Sunghee Jung, Eesung Kim
2021	A	`conf`	UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation. Interspeech Won Jang, Dan Lim, Jaesam Yoon, Bongwan Kim, Juntae Kim
2021	J	`jnl`	UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation. CoRR Won Jang, Dan Lim, Jaesam Yoon, Bongwan Kim, Juntae Kim
2020	A	`conf`	JDI-T: Jointly Trained Duration Informed Transformer for Text-To-Speech without Explicit Alignment. INTERSPEECH Dan Lim, Won Jang, Gyeonghwan O, Heayoung Park, Bongwan Kim, Jaesam Yoon
2020	J	`jnl`	JDI-T: Jointly trained Duration Informed Transformer for Text-To-Speech without Explicit Alignment. CoRR Dan Lim, Won Jang, Gyeonghwan O, Hyeyeong Park, Bongwan Kim, Jaesam Yoon
2020	J	`jnl`	Universal MelGAN: A Robust Neural Vocoder for High-Fidelity Waveform Generation in Multiple Domains. CoRR Won Jang, Dan Lim, Jaesam Yoon
2017	J	`jnl`	Convolutional Attention-based Seq2Seq Neural Network for End-to-End ASR. CoRR Dan Lim
2007	J	`jnl`	Characterisation of heat spreader materials for pulsed IGBT operation. IET Circuits Devices Syst. Dan Lim, Susan Helen Pulko
1999	J	`jnl`	Ubiquitous Mobile Computing: UMC's model and success. J. Educ. Technol. Soc. Dan Lim

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.