Sajad Haghzad Klidbary

17 papers Journal 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A MILP-Based Optimization Framework for Joint Transmission Scheduling and Dynamic Channel Allocation in QoS-Constrained IoT Networks. Int. J. Commun. Syst. Neda Mazloomi, Sajad Haghzad Klidbary, Arash Zaretalab
2025	J	`jnl`	A novel data-driven algorithm for object detection, tracking, distance estimation, and size measurement in stereo vision systems. Multim. Tools Appl. Amirhossein Dadashzade Taromi, Sajad Haghzad Klidbary
2025	J	`jnl`	Energy-aware clustering method for cluster head selection to increasing lifetime in wireless sensor network. J. Supercomput. Edris Alimohammadi, Sajad Haghzad Klidbary, Mohammad Javadian
2025	J	`jnl`	Generating a large family of nonlinear activation functions (LFNAFs) in neural networks. J. Supercomput. Morteza Taheri, Sajad Haghzad Klidbary
2025	J	`jnl`	Hardware-Software Co-Design Low-Complexity Fuzzy Algorithm for High-Dimensional Feature Space With In-Situ Learning. IEEE Trans. Emerg. Top. Comput. Mohamad Momtaz Sheykh Ahmad, Sajad Haghzad Klidbary
2025	J	`jnl`	Modeling inflammation in allergic asthma: Exploring the role of mesenchymal stem cells in therapeutic strategies. Comput. Biol. Medicine Solmaz Neisari Tabrizi, Abazar Arabameri, Sajad Haghzad Klidbary
2024	J	`jnl`	A Novel Hierarchical High-Dimensional Unsupervised Active Learning Method. Int. J. Comput. Intell. Syst. Sajad Haghzad Klidbary, Mohammad Javadian
2024	J	`jnl`	Fcd-cnn: FPGA-based CU depth decision for HEVC intra encoder using CNN. J. Real Time Image Process. Hossein Dehnavi, Mohammad Dehnavi, Sajad Haghzad Klidbary
2024	J	`jnl`	Hardware architecture and memristor-crossbar implementation of type-2 fuzzy system with type reduction and in-situ training. J. Supercomput. Sajad Haghzad Klidbary, Mohammad Javadian
2022	J	`jnl`	Obtaining Fuzzy Membership Function of Clusters With the Memristor Hardware Implementation and On-Chip Learning. IEEE Trans. Emerg. Top. Comput. Intell. Mohammad Javadian, Arian Hejazi, Sajad Haghzad Klidbary
2020	J	`jnl`	Hardware-Algorithm Co-Design of a Compressed Fuzzy Active Learning Method. IEEE Trans. Circuits Syst. Ehsan Jokar, Sajad Haghzad Klidbary, Hadis Abolfathi, Saeed Bagheri Shouraki, Ramtin Zand, Arash Ahmadi
2019	J	`jnl`	An adaptive efficient memristive ink drop spread (IDS) computing system. Neural Comput. Appl. Sajad Haghzad Klidbary, Saeed Bagheri Shouraki, Iman Esmaili Paeen Afrakoti
2019	J	`jnl`	Digital hardware realization of a novel adaptive ink drop spread operator and its application in modeling and classification and on-chip training. Int. J. Mach. Learn. Cybern. Sajad Haghzad Klidbary, Saeed Bagheri Shouraki, Bernabé Linares-Barranco
2019	J	`jnl`	Optimization of dynamic mobile robot path planning based on evolutionary methods. CoRR Masoud Fetanat, Sajad Haghzad Klidbary, Saeed Bagheri Shouraki
2018	J	`jnl`	A novel adaptive learning algorithm for low-dimensional feature space using memristor-crossbar implementation and on-chip training. Appl. Intell. Sajad Haghzad Klidbary, Saeed Bagheri Shouraki
2017	J	`jnl`	Path planning of modular robots on various terrains using Q-learning versus optimization algorithms. Intell. Serv. Robotics Sajad Haghzad Klidbary, Saeed Bagheri Shouraki, Soroush Sheikhpour Kourabbaslou
2016	J	`jnl`	Fast IDS Computing System Method and its Memristor Crossbar-based Hardware Implementation. CoRR Sajad Haghzad Klidbary, Saeed Bagheri Shouraki, Iman Esmaili Pain Afrakoti

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.