Ramazan Aygun - RankMe

29 papers B 1C 3Misc 4Journal 7Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Cartempian model: a spatial perspective for temporal interval queries using graph databases. Distributed Parallel Databases Alex Fotso, Mallika Boyapati, Ramazan Aygun
2025	J	`jnl`	BalancerGNN: Balancer Graph Neural Networks for imbalanced datasets: A case study on fraud detection. Neural Networks Mallika Boyapati, Ramazan Aygun
2025	C	`conf`	Difficulty-Driven Fine Training for WisdomNet. ICMLA Ayomide Afolabi, Ramazan Aygun, Truong X. Tran
2025	—	`conf`	Emergent Biases in Large Language Models: A Critical Review of Taxonomy and Evaluations. CogMI Shawn Ismail, Ramazan Aygun
2024	—	`conf`	Design and Implementation of Multithreaded CAD-Enabled LoRa Simulator for Massive IoT. IMCOM Jui Mhatre, Ahyoung Lee, Hoseon Lee, Ramazan Aygun
2024	—	`conf`	Functional Validation of Supervised Learning Tasks for Reproducible Machine Learning. ICSC Ayush Patel, Ramazan Aygun
2024	C	`conf`	Qualitative Diagnosis of LLMs as Judges Using LevelEval. ICMLA Mallika Boyapati, Lokesh Meesala, Ramazan Aygun, Bill Franks, Hansook Choi, Sereres Riordan, Girish Modgil
2024	—	`conf`	Semanformer: Semantics-aware Embedding Dimensionality Reduction Using Transformer-Based Models. ICSC Mallika Boyapati, Ramazan Aygun
2023	—	`conf`	A Multistage Framework for Detection of Very Small Objects. ICMVA Duleep Rathgamage Don, Ramazan Aygun, Mahmut Karakaya
2023	J	`jnl`	Automation of Explainability Auditing for Image Recognition. Int. J. Multim. Data Eng. Manag. Duleep Rathgamage Don, Jonathan Boardman, Sudhashree Sayenju, Ramazan Aygun, Yifan Zhang, Bill Franks, Sereres Johnston, George Lee, Dan Sullivan, Girish Modgil
2023	—	`conf`	Default Prediction on Commercial Credit Big Data Using Graph-based Variable Clustering. ICSC Mallika Boyapati, Ramazan Aygun
2023	—	`conf`	Quantifying Domain Knowledge in Large Language Models. CAI Sudhashree Sayenju, Ramazan Aygun, Bill Franks, Sereres Johnston, George Lee, Hansook Choi, Girish Modgil
2022	—	`conf`	ConvoForest Classification of New and Familiar Faces using EEG. ICSC Femi William, Ramazan Aygun
2022	—	`conf`	Directional Pairwise Class Confusion Bias and Its Mitigation. ICSC Sudhashree Sayenju, Ramazan Aygun, Jonathan Boardman, Duleep Prasanna Rathgamage Don, Yifan Zhang, Bill Franks, Sereres Johnston, George Lee, Dan Sullivan, Girish Modgil
2022	—	`conf`	EEG-based audiovisual face-name association classifications using transfer learning. ACM Southeast Regional Conference Femi William, Ramazan Aygun, Feng Zhu
2022	Misc	`conf`	Explainability Audit: An Automated Evaluation of Local Explainability in Rooftop Image Classification. IRI Duleep Rathgamage Don, Jonathan Boardman, Sudhashree Sayenju, Ramazan Aygun, Yifan Zhang, Bill Franks, Sereres Johnston, George Lee, Dan Sullivan, Girish Modgil
2022	Misc	`conf`	ImpartialGAN: Fair and Unbiased Classification. IRI Neha Bhargava, Yves Junior Kwame Kamgaing, Ramazan Aygun
2022	J	`jnl`	Quantification and Mitigation of Directional Pairwise Class Confusion Bias in a Chatbot Intent Classification Model. Int. J. Semantic Comput. Sudhashree Sayenju, Ramazan Aygun, Jonathan Boardman, Duleep Prasanna Rathgamage Don, Yifan Zhang, Bill Franks, Sereres Johnston, George Lee, Dan Sullivan, Girish Modgil
2022	B	`conf`	Stereotype and Categorical Bias Evaluation via Differential Cosine Bias Measure. IEEE Big Data Sudhashree Sayenju, Ramazan Aygun, Bill Franks, Sereres Johnston, George Lee, Girish Modgil
2022	Misc	`conf`	Video Alignment of Lecture Notes Missing Corners. IRI Adeyemi Fagbemi, Ramazan Aygun, Mahmut Karakaya, Nesrin Sahin
2022	—	`conf`	Video Origin Camera Identification using Ensemble CNNs of Positional Patches. MIPR Maryna Veksler, Ramazan Aygun, Kemal Akkaya, S. Sitharama Iyengar
2021	Misc	`conf`	PRNU-based Source Camera Identification for Multimedia Forensics. IRI Eitan Flor, Ramazan Aygun, Suat Mercan, Kemal Akkaya
2021	—	`conf`	Spectra-based Classification of Audiovisual and Visuospatial Face-name Associative Memories using EEG. BIBM Femi William, Feng Zhu, Ramazan Aygun, Mattie Ponter
2020	—	`conf`	ERP Template Matching for EEG Single Trial Classification. BIBM Femi William, Ramazan Aygun, Feng Zhu
2018	—	`conf`	Multimedia Retrieval that Works. MIPR Ramazan Aygun, Wanda Benesova
2017	C	`conf`	Human Action Classification Using Temporal Slicing for Deep Convolutional Neural Networks. ISM Nathan Henderson, Ramazan Aygun
2016	J	`jnl`	A Survey of Social Network Forensics. J. Digit. Forensics Secur. Law Umit Karabiyik, Muhammed Abdullah Canbaz, Ahmet Aksoy, Tayfun Tuna, Esra Akbas, Bilal Gonen, Ramazan Aygun
2016	J	`jnl`	User characterization for online social networks. CoRR Tayfun Tuna, Esra Akbas, Ahmet Aksoy, Muhammed Abdullah Canbaz, Umit Karabiyik, Bilal Gonen, Ramazan Aygun
2016	J	`jnl`	User characterization for online social networks. Soc. Netw. Anal. Min. Tayfun Tuna, Esra Akbas, Ahmet Aksoy, Muhammed Abdullah Canbaz, Umit Karabiyik, Bilal Gonen, Ramazan Aygun

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.