Oluwaseyi Feyisetan

36 papers A* 3A 5B 2Misc 3Journal 18Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	A	`conf`	Universal Semantic Disentangled Privacy-preserving Speech Representation Learning. INTERSPEECH Biel Tura Vecino, Subhadeep Maji, Aravind Varier, Antonio Bonafonte, Ivan Valles, Michael Owen, Constantinos Papayiannis, Leif Rädel, Grant P. Strimel, Oluwaseyi Feyisetan, Roberto Barra-Chicote, Ariya Rastrow, Volker Leutnant, Trevor Wood
2024	J	`jnl`	Fast Training Dataset Attribution via In-Context Learning. CoRR Milad Fotouhi, Mohammad Taha Bahadori, Oluwaseyi Feyisetan, Payman Arabshahi, David Heckerman
2024	J	`jnl`	Removing Spurious Correlation from Neural Network Interpretations. CoRR Milad Fotouhi, Mohammad Taha Bahadori, Oluwaseyi Feyisetan, Payman Arabshahi, David Heckerman
2023	A	`conf`	TEM: High Utility Metric Differential Privacy on Text. SDM Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan, Ke Wang
2022	A	`conf`	Reconstructing Test Labels from Noisy Loss Functions. AISTATS Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier
2021	J	`jnl`	BRR: Preserving Privacy of Text Data Efficiently on Device. CoRR Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan
2021	Misc	`conf`	Density-Aware Differentially Private Textual Perturbations Using Truncated Gumbel Noise. FLAIRS Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier
2021	A*	`conf`	Label Inference Attacks from Log-loss Scores. ICML Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier
2021	J	`jnl`	Label Inference Attacks from Log-loss Scores. CoRR Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier
2021	J	`jnl`	On Codomain Separability and Label Inference from (Noisy) Loss Functions. CoRR Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier
2021	J	`jnl`	On a Utilitarian Approach to Privacy Preserving Text Generation. CoRR Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, Nathanael Teissier
2021	Misc	`conf`	Research Challenges in Designing Differentially Private Text Generation Mechanisms. FLAIRS Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier
2021	J	`jnl`	TEM: High Utility Metric Differential Privacy on Text. CoRR Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan
2020	J	`jnl`	A Differentially Private Text Perturbation Method Using a Regularized Mahalanobis Metric. CoRR Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, Nathanael Teissier
2020	—	`conf`	Calibrating Mechanisms for Privacy Preserving Text Analysis. PrivateNLP@WSDM Oluwaseyi Feyisetan, Borja Balle, Tom Diethe, Thomas Drake
2020	J	`jnl`	Differentially Private Adversarial Robustness Through Randomized Perturbations. CoRR Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier
2020	—	`conf`	Hyperbolic Embeddings for Preserving Privacy and Utility in Text. PrivateNLP@WSDM Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake
2020	J	`jnl`	On Primes, Log-Loss Scores and (No) Privacy. CoRR Abhinav Aggarwal, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier
2020	—	`conf`	Preserving Privacy in Analyses of Textual Data. PrivateNLP@WSDM Tom Diethe, Oluwaseyi Feyisetan
2020	A	`conf`	Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. WSDM Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe
2020	—	`conf`	Privacy-Preserving Textual Analysis via Calibrated Perturbations. PrivateNLP@WSDM Oluwaseyi Feyisetan, Borja Balle
2020	—	`ed.`	Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing - Colocated with WSDM 2020, Houston, USA, Feb 7, 2020. PrivateNLP@WSDM Oluwaseyi Feyisetan, Sepideh Ghanavati, Oleg Rokhlenko, Patricia Thaine
2020	J	`jnl`	Research Challenges in Designing Differentially Private Text Generation Mechanisms. CoRR Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier
2020	A	`conf`	Workshop on Privacy in NLP (PrivateNLP 2020). WSDM Oluwaseyi Feyisetan, Sepideh Ghanavati, Patricia Thaine
2019	J	`jnl`	Beyond Monetary Incentives: Experiments in Paid Microtask Contests. ACM Trans. Soc. Comput. Oluwaseyi Feyisetan, Elena Simperl
2019	J	`jnl`	Beyond monetary incentives: experiments in paid microtask contests modelled as continuous-time markov chains. CoRR Oluwaseyi Feyisetan, Elena Simperl
2019	A*	`conf`	Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text. ICDM Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake
2019	J	`jnl`	Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text. CoRR Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake
2019	J	`jnl`	Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. CoRR Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe
2019	J	`jnl`	Privacy-preserving Active Learning on Sensitive Data for User Intent Classification. CoRR Oluwaseyi Feyisetan, Thomas Drake, Borja Balle, Tom Diethe
2018	J	`jnl`	An extended study of content and crowdsourcing-related performance factors in named entity annotation. Semantic Web Oluwaseyi Feyisetan, Elena Simperl, Markus Luczak-Rösch, Ramine Tinati, Nigel Shadbolt
2017	J	`jnl`	Social Incentives in Paid Collaborative Crowdsourcing. ACM Trans. Intell. Syst. Technol. Oluwaseyi Feyisetan, Elena Simperl
2016	B	`conf`	Please Stay vs Let's Play: Social Pressure Incentives in Paid Collaborative Crowdsourcing. ICWE Oluwaseyi Feyisetan, Elena Simperl
2015	A*	`conf`	Improving Paid Microtasks through Gamification and Adaptive Furtherance Incentives. WWW Oluwaseyi Feyisetan, Elena Simperl, Max Van Kleek, Nigel Shadbolt
2015	B	`conf`	Towards Hybrid NER: A Study of Content and Crowdsourcing-Related Performance Factors. ESWC Oluwaseyi Feyisetan, Markus Luczak-Rösch, Elena Simperl, Ramine Tinati, Nigel Shadbolt
2014	Misc	`conf`	Quick-and-clean extraction of linked data entities from microblogs. SEMANTiCS Oluwaseyi Feyisetan, Elena Simperl, Ramine Tinati, Markus Luczak-Rösch, Nigel Shadbolt

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.