Zhecheng Sheng

16 papers A* 2Journal 10Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	"Is There Anything Else?": Examining Administrator Influence on Linguistic Features from the Cookie Theft Picture Description Cognitive Test. CoRR Changye Li, Zhecheng Sheng, Trevor Cohen, Serguei Pakhomov
2025	A*	`conf`	BBScoreV2: Learning Time-Evolution and Latent Alignment from Stochastic Representation. EMNLP Tianhao Zhang, Zhecheng Sheng, Zhexiao Lin, Chen Jiang, Dongyeop Kang
2025	—	`conf`	Mitigating Confounding in Speech-Based Dementia Detection through Weight Masking. ACL (1) Zhecheng Sheng, Xiruo Ding, Brian Hur, Changye Li, Trevor Cohen, Serguei V. S. Pakhomov
2025	J	`jnl`	Mitigating Confounding in Speech-Based Dementia Detection through Weight Masking. CoRR Zhecheng Sheng, Xiruo Ding, Brian Hur, Changye Li, Trevor Cohen, Serguei Pakhomov
2025	J	`jnl`	Tailoring task arithmetic to address bias in models trained on multi-institutional datasets. J. Biomed. Informatics Xiruo Ding, Zhecheng Sheng, Brian Hur, Justin Tauscher, Dror Ben-Zeev, Meliha Yetisgen, Serguei Pakhomov, Trevor Cohen
2025	J	`jnl`	Toward Unifying Group Fairness Evaluation from a Sparsity Perspective. CoRR Zhecheng Sheng, Jiawei Zhang, Enmao Diao
2024	A*	`conf`	BBScore: A Brownian Bridge Based Metric for Assessing Text Coherence. AAAI Zhecheng Sheng, Tianhao Zhang, Chen Jiang, Dongyeop Kang
2024	J	`jnl`	On the Sequence Evaluation based on Stochastic Processes. CoRR Tianhao Zhang, Zhexiao Lin, Zhecheng Sheng, Chen Jiang, Dongyeop Kang
2024	—	`conf`	Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies. ACL (Findings) Changye Li, Zhecheng Sheng, Trevor Cohen, Serguei Pakhomov
2024	J	`jnl`	Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies. CoRR Changye Li, Zhecheng Sheng, Trevor Cohen, Serguei Pakhomov
2023	J	`jnl`	A Dialogue System for Assessing Activities of Daily Living: Improving Consistency with Grounded Knowledge. CoRR Zhecheng Sheng, Raymond L. Finzel, Michael Lucke, Sheena Dufresne, Maria L. Gini, Serguei Pakhomov
2023	J	`jnl`	BBScore: A Brownian Bridge Based Metric for Assessing Text Coherence. CoRR Zhecheng Sheng, Tianhao Zhang, Chen Jiang, Dongyeop Kang
2023	J	`jnl`	Backdoor Adjustment of Confounding by Provenance for Robust Text Classification of Multi-institutional Clinical Notes. CoRR Xiruo Ding, Zhecheng Sheng, Meliha Yetisgen, Serguei Pakhomov, Trevor Cohen
2023	J	`jnl`	Enhancing Robustness of Foundation Model Representations under Provenance-related Distribution Shifts. CoRR Xiruo Ding, Zhecheng Sheng, Brian Hur, Feng Chen, Serguei V. S. Pakhomov, Trevor Cohen
2022	—	`conf`	Canine Parvovirus Diagnosis Classification Utilizing Veterinary Free-Text Notes. ICHI Zhecheng Sheng, Emma Bollig, Jennifer Granick, Rui Zhang, Amanda Beaudoin
2022	—	`conf`	NLP System for Mining Social Determinant of Health From Clinical Notes and its Fairness Evaluations. ICHI Zhecheng Sheng

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.