Baiyun Chen

14 papers Journal 9Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Evaluating the Efficacy of Various Sampling Strategies on Enhancing Credit Card Fraud Detection Performance. ICECET Fan Zhang, Faria Brishti, Sameeruddin Mohammed, Fan Wu, Baiyun Chen
2025	J	`jnl`	Imbalanced classification with label noise: A systematic review and comparative analysis. ICT Express Faria Brishti, Fan Zhang, Sameeruddin Mohammed, Ling Bai, Fan Wu, Baiyun Chen
2024	J	`jnl`	A multi-modality and multi-granularity collaborative learning framework for identifying spatial domains and spatially variable genes. Bioinform. Xiao Liang, Pei Liu, Li Xue, Baiyun Chen, Wei Liu, Wanwan Shi, Yongwang Wang, Xiangtao Chen, Jiawei Luo
2024	J	`jnl`	GraphGI:A GNN Explanation Method using Game Interaction. CoRR Xingping Xian, Jianlu Liu, Tao Wu, Lin Yuan, Chao Wang, Baiyun Chen
2024	J	`jnl`	Promoting Community of Inquiry in Synchronous Team Design Activities for Remote Engineering Laboratory Instruction. IEEE Trans. Educ. Baiyun Chen, Ronald F. DeMara
2023	—	`conf`	Merging Human and Non-human (System) Data to Describe Students' Adaptive Learning Experience in Postsecondary Gateway Math Courses. HCI (34) James R. Paradiso, Tammy Muhs, Baiyun Chen
2022	J	`jnl`	mCRF and mRD: Two Classification Methods Based on a Novel Multiclass Label Noise Filtering Learning Framework. IEEE Trans. Neural Networks Learn. Syst. Shuyin Xia, Baiyun Chen, Guoyin Wang, Yong Zheng, Xinbo Gao, Elisabeth Giem, Zizhong Chen
2021	J	`jnl`	RSMOTE: A self-adaptive robust SMOTE for imbalanced problems with label noise. Inf. Sci. Baiyun Chen, Shuyin Xia, Zizhong Chen, Binggui Wang, Guoyin Wang
2019	J	`jnl`	An individual-group-merchant relation model for identifying fake online reviews: an empirical study on a Chinese e-commerce platform. Inf. Technol. Manag. Chuanming Yu, Yuheng Zuo, Bolin Feng, Lu An, Baiyun Chen
2018	—	`conf`	A Multi-Granular Relative Density Model for Class Noise Detection. IEEE BigData Xiao Liang, Shuyin Xia, Qun Liu, Yunsheng Liu, Baiyun Chen, Guoyin Wang
2018	J	`jnl`	Elevating Learner Achievement Using Formative Electronic Lab Assessments in the Engineering Laboratory: A Viable Alternative to Weekly Lab Reports. IEEE Trans. Educ. Baiyun Chen, Ronald F. DeMara, Soheil Salehi, Richard Hartshorne
2018	—	`conf`	Prediction of Aluminum Electrolysis Superheat Based on Improved Relative Density Noise Filter SMO. ICBK Yunsheng Liu, Shuyin Xia, Hong Yu, Yueguo Luo, Baiyun Chen, Kang Liu, Guoyin Wang
2018	—	`conf`	The k-Means Forest Classifier for High Dimensional Data. ICBK Zizhong Chen, Xin Ding, Shuyin Xia, Baiyun Chen
2012	J	`jnl`	Students' self-presentation on Facebook: An examination of personality and self-construal factors. Comput. Hum. Behav. Baiyun Chen, Justin Marcus

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.