Salma Afifi - RankMe

19 papers A 3C 1Journal 12Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ASTRA: A Stochastic Transformer Neural Network Accelerator with Silicon Photonics. ACM Trans. Embed. Comput. Syst. Salma Afifi, Oluwaseun Adewunmi Alo, Ishan G. Thakkar, Sudeep Pasricha
2026	J	`jnl`	Accelerating Diffusion Models for Generative AI Applications with Silicon Photonics. CoRR Tharini Suresh, Salma Afifi, Sudeep Pasricha
2026	J	`jnl`	DiffLight: Generative Diffusion Model Acceleration With Silicon Photonics. IEEE Des. Test Tharini Suresh, Salma Afifi, Sudeep Pasricha
2025	—	`conf`	A Light-Speed Large Language Model Accelerator with Optical Stochastic Computing. ACM Great Lakes Symposium on VLSI Salma Afifi, Oluwaseun Adewunmi Alo, Ishan G. Thakkar, Sudeep Pasricha
2025	—	`conf`	PhotoGAN: Generative Adversarial Neural Network Acceleration with Silicon Photonics. ISQED Tharini Suresh, Salma Afifi, Sudeep Pasricha
2025	J	`jnl`	PhotoGAN: Generative Adversarial Neural Network Acceleration with Silicon Photonics. CoRR Tharini Suresh, Salma Afifi, Sudeep Pasricha
2025	J	`jnl`	STAR: A Mixed Analog Stochastic In-DRAM Convolutional Neural Network Accelerator. IEEE Des. Test Salma Afifi, Ishan G. Thakkar, Sudeep Pasricha
2025	A	`conf`	SafeLight: Enhancing Security in Optical Convolutional Neural Network Accelerators. DATE Salma Afifi, Ishan G. Thakkar, Sudeep Pasricha
2025	C	`conf`	Sustainable Acceleration of Generative AI Neural Network Models with Silicon Photonics. ICCD Tharini Suresh, Salma Afifi, Sudeep Pasricha
2024	J	`jnl`	ARTEMIS: A Mixed Analog-Stochastic In-DRAM Accelerator for Transformer Neural Networks. CoRR Salma Afifi, Ishan G. Thakkar, Sudeep Pasricha
2024	J	`jnl`	ARTEMIS: A Mixed Analog-Stochastic In-DRAM Accelerator for Transformer Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. Salma Afifi, Ishan G. Thakkar, Sudeep Pasricha
2024	A	`conf`	Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonics. DATE Salma Afifi, Febin Sunny, Mahdi Nikdast, Sudeep Pasricha
2024	J	`jnl`	Accelerating Neural Networks for Large Language Models and Graph Processing with Silicon Photonics. CoRR Salma Afifi, Febin Sunny, Mahdi Nikdast, Sudeep Pasricha
2024	J	`jnl`	SafeLight: Enhancing Security in Optical Convolutional Neural Network Accelerators. CoRR Salma Afifi, Ishan G. Thakkar, Sudeep Pasricha
2024	A	`conf`	Shedding Light on LLMs: Harnessing Photonic Neural Networks for Accelerating LLMs. ICCAD Mahdi Nikdast, Salma Afifi, Sudeep Pasricha
2023	J	`jnl`	GHOST: A Graph Neural Network Accelerator using Silicon Photonics. CoRR Salma Afifi, Febin Sunny, Amin Shafiee, Mahdi Nikdast, Sudeep Pasricha
2023	J	`jnl`	GHOST: A Graph Neural Network Accelerator using Silicon Photonics. ACM Trans. Embed. Comput. Syst. Salma Afifi, Febin Sunny, Amin Shafiee, Mahdi Nikdast, Sudeep Pasricha
2023	—	`conf`	TRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonics. ACM Great Lakes Symposium on VLSI Salma Afifi, Febin Sunny, Mahdi Nikdast, Sudeep Pasricha
2023	J	`jnl`	TRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonics. CoRR Salma Afifi, Febin Sunny, Mahdi Nikdast, Sudeep Pasricha

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.