Gabriele Atzeni

18 papers Journal 6Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	19.10 A 4.6GHz 63.3fs ISSCC Can Livanelioglu, Long He, Jiang Gong, Sina Arjmandpour, Gabriele Atzeni, Taekwang Jang
2025	J	`jnl`	A 4.6-GHz 54.5-fs IEEE J. Solid State Circuits Can Livanelioglu, Long He, Jiang Gong, Sina Arjmandpour, Gabriele Atzeni, Taekwang Jang
2024	J	`jnl`	A Sub-mm IEEE J. Solid State Circuits Jungho Lee, Joseph G. Letner, Jongyup Lim, Gabriele Atzeni, Jiawei Liao, Abhilasha Kamboj, Bhavika Mani, Seokhyeon Jeong, Yejoong Kim, Yi Sun, Beomseo Koo, Julianna M. Richie, Elena Della Valle, Paras R. Patel, Dennis Sylvester, Hun-Seok Kim, Taekwang Jang, Jamie Phillips, Cynthia A. Chestek, James D. Weiland, David T. Blaauw
2024	J	`jnl`	An Impedance-Boosted Transformer-First Discrete-Time Analog Front-End Achieving 0.34 NEF and 389-MΩ Input Impedance. IEEE J. Solid State Circuits Gabriele Atzeni, Can Livanelioglu, Sina Arjmandpour, Taekwang Jang
2023	—	`conf`	A 1, 024-Channel, 64-Interconnect, Capacitive Neural Interface Using a Cross-Coupled Microelectrode Array and 2-Dimensional Code-Division Multiplexing. VLSI Technology and Circuits Woojun Choi, Yiyang Chen, Donghwan Kim, Sean Weaver, Tilman Schlotter, Can Livanelioglu, Jiawei Liao, Rosario M. Incandela, Parham Davami, Gabriele Atzeni, Sina Arjmandpour, SeongHwan Cho, Taekwang Jang
2023	—	`conf`	A 4.1W/mm² Peak Power Density and 77% Peak Efficiency Fully Integrated DC-DC Converter based on Electromagnetically Coupled Class-D LC Oscillators and a Resonant LC Flying Impedance in 22nm FDSOI CMOS. VLSI Technology and Circuits Alessandro Novello, Gabriele Atzeni, Tim Keller, Taekwang Jang
2023	—	`conf`	A Wireless Neural Stimulator IC for Cortical Visual Prosthesis. VLSI Technology and Circuits Jungho Lee, Joseph G. Letner, Jongyup Lim, Yi Sun, Seokhyeon Jeong, Yejoong Kim, Beomseo Koo, Gabriele Atzeni, Jiawei Liao, Julianna M. Richie, Elena Della Valle, Paras R. Patel, Taekwang Jang, Cynthia A. Chestek, Jamie Phillips, James D. Weiland, Dennis Sylvester, Hun-Seok Kim, David T. Blaauw
2023	—	`conf`	An Energy-Efficient Impedance-Boosted Discrete-Time Amplifier Achieving 0.34 Noise Efficiency Factor and 389 MΩ Input Impedance. VLSI Technology and Circuits Gabriele Atzeni, Can Livanelioglu, Lavinia Recchioni, Sina Arjmandpour, Taekwang Jang
2022	J	`jnl`	A 1.01 NEF Low-Noise Amplifier Using Complementary Parametric Amplification. IEEE Trans. Circuits Syst. I Regul. Pap. Gabriele Atzeni, Jérémy Guichemerre, Alessandro Novello, Taekwang Jang
2022	—	`conf`	A 260×274 μm VLSI Technology and Circuits Gabriele Atzeni, Jongyup Lim, Jiawei Liao, Alessandro Novello, Jungho Lee, Eunseong Moon, Michael Barrow, Joseph G. Letner, Joseph T. Costello, Samuel R. Nason, Paras R. Patel, Parag G. Patil, Hun-Seok Kim, Cynthia A. Chestek, Jamie Phillips, David T. Blaauw, Taekwang Jang
2022	J	`jnl`	A Light-Tolerant Wireless Neural Recording IC for Motor Prediction With Near-Infrared-Based Power and Data Telemetry. IEEE J. Solid State Circuits Jongyup Lim, Jungho Lee, Eunseong Moon, Michael Barrow, Gabriele Atzeni, Joseph G. Letner, Joseph T. Costello, Samuel R. Nason, Paras R. Patel, Yi Sun, Parag G. Patil, Hun-Seok Kim, Cynthia A. Chestek, Jamie Phillips, David T. Blaauw, Dennis Sylvester, Taekwang Jang
2022	—	`conf`	An Impedance-boosted Switched-capacitor Low-noise Amplifier Achieving 0.4 NEF. VLSI Technology and Circuits Gabriele Atzeni, Rosario M. Incandela, Youngwoo Ji, Alessandro Novello, Hesam Ghiasi, Giorgio Cristiano, Jiawei Liao, Qiuting Huang, Taekwang Jang
2021	—	`conf`	17.3 A 1.25GHz Fully Integrated DC-DC Converter Using Electromagnetically Coupled Class-D LC Oscillators. ISSCC Alessandro Novello, Gabriele Atzeni, Giorgio Cristiano, Mathieu Coustans, Taekwang Jang
2021	J	`jnl`	A 1.25-GHz Fully Integrated DC-DC Converter Using Electromagnetically Coupled Class-D LC Oscillators. IEEE J. Solid State Circuits Alessandro Novello, Gabriele Atzeni, Jonas Künzli, Giorgio Cristiano, Mathieu Coustans, Taekwang Jang
2021	—	`conf`	A 2.3GHz Fully Integrated DC-DC Converter based on Electromagnetically Coupled Class-D LC Oscillators achieving 78.1% Efficiency in 22nm FDSOI CMOS. VLSI Circuits Alessandro Novello, Gabriele Atzeni, Giorgio Cristiano, Mathieu Coustans, Taekwang Jang
2021	—	`conf`	A Light Tolerant Neural Recording IC for Near-Infrared-Powered Free Floating Motes. VLSI Circuits Jongyup Lim, Jungho Lee, Eunseong Moon, Michael Barrow, Gabriele Atzeni, Joseph G. Letner, Joseph T. Costello, Samuel R. Nason, Paras R. Patel, Parag G. Patil, Hun-Seok Kim, Cynthia A. Chestek, Jamie Phillips, David T. Blaauw, Dennis Sylvester, Taekwang Jang
2020	—	`conf`	A 8.7ppm/°C, 694nW, One-Point Calibrated RC Oscillator using a Nonlinearity-Aware Dual Phase-Locked Loop and DSM-Controlled Frequency-Locked Loops. VLSI Circuits Giorgio Cristiano, Jiawei Liao, Alessandro Novello, Gabriele Atzeni, Taekwang Jang
2020	—	`conf`	An Energy-Efficient Low-Noise Complementary Parametric Amplifier Achieving 0.89 NEF. MWSCAS Gabriele Atzeni, Jérémy Guichemerre, Alessandro Novello, Taekwang Jang

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.