Zeyu Liu - RankMe

19 papers A* 2A 2C 1Misc 3Journal 9Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Dynamic SpikFormer: Low-Latency & Energy-Efficient Spiking Neural Networks with Dynamic Time Steps for Vision Transformers. ICASSP Gourav Datta, Zeyu Liu, Anni Li, Peter A. Beerel
2025	—	`conf`	LAWCAT: Efficient Distillation from Quadratic to Linear Attention with Convolution across Tokens for Long Context Modeling. EMNLP (Findings) Zeyu Liu, Souvik Kundu, Lianghao Jiang, Anni Li, Srikanth Ronanki, Sravan Babu Bodapati, Gourav Datta, Peter Anthony Beerel
2025	J	`jnl`	LAWCAT: Efficient Distillation from Quadratic to Linear Attention with Convolution across Tokens for Long Context Modeling. CoRR Zeyu Liu, Souvik Kundu, Lianghao Jiang, Anni Li, Srikanth Ronanki, Sravan Bodapati, Gourav Datta, Peter A. Beerel
2025	J	`jnl`	When SNN meets ANN: Error-Free ANN-to-SNN Conversion for Extreme Edge Efficiency. Trans. Mach. Learn. Res. Gourav Datta, Zeyu Liu, James Diffenderfer, Bhavya Kailkhura, Peter Anthony Beerel
2024	—	`conf`	AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models. ACL (Short Papers) Zeyu Liu, Souvik Kundu, Anni Li, Junrui Wan, Lianghao Jiang, Peter A. Beerel
2024	J	`jnl`	AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models. CoRR Zeyu Liu, Souvik Kundu, Anni Li, Junrui Wan, Lianghao Jiang, Peter Anthony Beerel
2024	A*	`conf`	Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision? ICLR Gourav Datta, Zeyu Liu, Peter Anthony Beerel
2024	A*	`conf`	LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units. ICLR Zeyu Liu, Gourav Datta, Anni Li, Peter Anthony Beerel
2024	J	`jnl`	LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units. CoRR Zeyu Liu, Gourav Datta, Anni Li, Peter Anthony Beerel
2024	Misc	`conf`	Training Ultra-Low-Latency Spiking Neural Networks from Scratch. ICASSP Gourav Datta, Zeyu Liu, Peter A. Beerel
2023	A	`conf`	Bridging the Gap Between Spiking Neural Networks & LSTMs for Latency & Energy Efficiency. ISLPED Gourav Datta, Haoqin Deng, Robert Aviles, Zeyu Liu, Peter A. Beerel
2023	A	`conf`	Enabling ISPless Low-Power Computer Vision. WACV Gourav Datta, Zeyu Liu, Zihan Yin, Linyu Sun, Akhilesh R. Jaiswal, Peter A. Beerel
2023	Misc	`conf`	In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision. ICASSP Gourav Datta, Zeyu Liu, Md. Abdullah-Al Kaiser, Souvik Kundu, Joe Mathai, Zihan Yin, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
2023	J	`jnl`	Spiking Neural Networks with Dynamic Time Steps for Vision Transformers. CoRR Gourav Datta, Zeyu Liu, Anni Li, Peter A. Beerel
2023	J	`jnl`	When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks. CoRR Gourav Datta, Zeyu Liu, James Diffenderfer, Bhavya Kailkhura, Peter A. Beerel
2022	J	`jnl`	Enabling ISP-less Low-Power Computer Vision. CoRR Gourav Datta, Zeyu Liu, Zihan Yin, Linyu Sun, Akhilesh R. Jaiswal, Peter A. Beerel
2022	J	`jnl`	Hoyer regularizer is all you need for ultra low-latency spiking neural networks. CoRR Gourav Datta, Zeyu Liu, Peter A. Beerel
2022	J	`jnl`	In-Sensor & Neuromorphic Computing are all you need for Energy Efficient Computer Vision. CoRR Gourav Datta, Zeyu Liu, Md. Abdullah-Al Kaiser, Souvik Kundu, Joe Mathai, Zihan Yin, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
2022	C	`conf`	P VLSI-SoC Gourav Datta, Souvik Kundu, Zihan Yin, Joe Mathai, Zeyu Liu, Zixu Wang, Mulin Tian, Shunlin Lu, Ravi Teja Lakkireddy, Andrew G. Schmidt, Wael Abd-Almageed, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel

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.