Bastian Pfeifer

41 papers C 1Journal 30Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Calibrated kNN classification via second-layer neighborhood analysis. Adv. Data Anal. Classif. Bastian Pfeifer, Markus Kreuzthaler
2026	J	`jnl`	Robust Node Affinities via Jaccard-Biased Random Walks and Rank Aggregation. CoRR Bastian Pfeifer, Michael G. Schimek
2025	J	`jnl`	Correction: Generating Explanations for Conceptual Validation of Graph Neural Networks. Künstliche Intell. Bettina Finzel, Anna Saranti, Alessa Angerschmid, David E. Tafler, Bastian Pfeifer, Andreas Holzinger
2025	J	`jnl`	Explaining and visualizing black-box models through counterfactual paths. Pattern Anal. Appl. Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki, Andreas Holzinger, Przemyslaw Biecek
2025	J	`jnl`	Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping. BioData Min. Christel Sirocchi, Martin Urschler, Bastian Pfeifer
2025	J	`jnl`	Tree smoothing: Post-hoc regularization of tree ensembles for interpretable machine learning. Inf. Sci. Bastian Pfeifer, Arne Gevaert, Markus Loecher, Andreas Holzinger
2024	J	`jnl`	CLARUS: An interactive explainable AI platform for manual counterfactuals in graph neural networks. J. Biomed. Informatics Jacqueline Michelle Metsch, Anna Saranti, Alessa Angerschmid, Bastian Pfeifer, Vanessa Klemt, Andreas Holzinger, Anne-Christin Hauschild
2024	J	`jnl`	Correction to: Effective signal reconstruction from multiple ranked lists via convex optimization. Data Min. Knowl. Discov. Michael G. Schimek, Luca Vitale, Bastian Pfeifer, Michele La Rocca
2024	J	`jnl`	Detection and quantification of introgression using Bayesian inference based on conjugate priors. Bioinform. Bastian Pfeifer, Durrell D. Kapan, Sereina A. Herzog
2024	J	`jnl`	Effective signal reconstruction from multiple ranked lists via convex optimization. Data Min. Knowl. Discov. Michael G. Schimek, Luca Vitale, Bastian Pfeifer, Michele La Rocca
2024	J	`jnl`	Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping. CoRR Christel Sirocchi, Martin Urschler, Bastian Pfeifer
2024	J	`jnl`	Federated unsupervised random forest for privacy-preserving patient stratification. Bioinform. Bastian Pfeifer, Christel Sirocchi, Marcus D. Bloice, Markus Kreuzthaler, Martin Urschler
2024	J	`jnl`	Federated unsupervised random forest for privacy-preserving patient stratification. CoRR Bastian Pfeifer, Christel Sirocchi, Marcus D. Bloice, Markus Kreuzthaler, Martin Urschler
2024	J	`jnl`	From 3D point-cloud data to explainable geometric deep learning: State-of-the-art and future challenges. WIREs Data. Mining. Knowl. Discov. Anna Saranti, Bastian Pfeifer, Christoph Gollob, Karl Stampfer, Andreas Holzinger
2024	—	`conf`	Hierarchical Clustering with an Ensemble of Principle Component Trees for Interpretable Patient Stratification. CIBB Bastian Pfeifer, Marcus D. Bloice, Christel Sirocchi, Markus Loecher
2023	J	`jnl`	Bayesian post-hoc regularization of random forests. CoRR Bastian Pfeifer
2023	J	`jnl`	Be Careful When Evaluating Explanations Regarding Ground Truth. CoRR Hubert Baniecki, Maciej Chrabaszcz, Andreas Holzinger, Bastian Pfeifer, Anna Saranti, Przemyslaw Biecek
2023	—	`conf`	Data-Driven Identification of Clinical Real-World Expressions Linked to ICD. MIE Amila Kugic, Bastian Pfeifer, Stefan Schulz, Markus Kreuzthaler
2023	J	`jnl`	Embedding-based terminology expansion via secondary use of large clinical real-world datasets. J. Biomed. Informatics Amila Kugic, Bastian Pfeifer, Stefan Schulz, Markus Kreuzthaler
2023	J	`jnl`	Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification. Bioinform. Bastian Pfeifer, Hryhorii Chereda, Roman Martin, Anna Saranti, Sandra Clemens, Anne-Christin Hauschild, Tim Beißbarth, Andreas Holzinger, Dominik Heider
2023	J	`jnl`	Explainable AI with counterfactual paths. CoRR Bastian Pfeifer, Mateusz Krzyzinski, Hubert Baniecki, Anna Saranti, Andreas Holzinger, Przemyslaw Biecek
2023	C	`conf`	Human-in-the-Loop Integration with Domain-Knowledge Graphs for Explainable Federated Deep Learning. CD-MAKE Andreas Holzinger, Anna Saranti, Anne-Christin Hauschild, Jacqueline Michelle Beinecke, Dominik Heider, Richard Röttger, Heimo Müller, Jan Baumbach, Bastian Pfeifer
2023	—	`conf`	Improving the Reliability of Tree-Based Feature Importance via Consensus Signals. CIBB Bastian Pfeifer, Michael G. Schimek
2023	—	`conf`	Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment. MIE Markus Kreuzthaler, Bastian Pfeifer, Diether Kramer, Stefan Schulz
2022	J	`jnl`	Actionable Explainable AI (AxAI): A Practical Example with Aggregation Functions for Adaptive Classification and Textual Explanations for Interpretable Machine Learning. Mach. Learn. Knowl. Extr. Anna Saranti, Miroslav Hudec, Erika Mináriková, Zdenko Takác, Udo Großschedl, Christoph Koch, Bastian Pfeifer, Alessa Angerschmid, Andreas Holzinger
2022	J	`jnl`	GNN-SubNet: disease subnetwork detection with explainable graph neural networks. Bioinform. Bastian Pfeifer, Anna Saranti, Andreas Holzinger
2022	J	`jnl`	Generating Explanations for Conceptual Validation of Graph Neural Networks: An Investigation of Symbolic Predicates Learned on Relevance-Ranked Sub-Graphs. Künstliche Intell. Bettina Finzel, Anna Saranti, Alessa Angerschmid, David E. Tafler, Bastian Pfeifer, Andreas Holzinger
2022	J	`jnl`	Parea: multi-view ensemble clustering for cancer subtype discovery. CoRR Bastian Pfeifer, Marcus D. Bloice, Michael G. Schimek
2022	—	`conf`	Robust Random Forest-Based All-Relevant Feature Ranks for Trustworthy AI. MIE Bastian Pfeifer, Andreas Holzinger, Michael G. Schimek
2022	—	`conf`	Terminology Expansion via Co-occurrence Analysis of Large Clinical Real-World Datasets. ICHI Markus Kreuzthaler, Bastian Pfeifer, Stefan Schulz
2021	J	`jnl`	A hierarchical clustering and data fusion approach for disease subtype discovery. J. Biomed. Informatics Bastian Pfeifer, Michael G. Schimek
2021	—	`conf`	Integrative hierarchical ensemble clustering for improved disease subtype discovery. BIBM Bastian Pfeifer, Andrei Voicu-Spineanu, Michael G. Schimek, Nikolaos Alachiotis
2021	J	`jnl`	Network Module Detection from Multi-Modal Node Features with a Greedy Decision Forest for Actionable Explainable AI. CoRR Bastian Pfeifer, Anna Saranti, Andreas Holzinger
2021	J	`jnl`	Towards multi-modal causability with Graph Neural Networks enabling information fusion for explainable AI. Inf. Fusion Andreas Holzinger, Bernd Malle, Anna Saranti, Bastian Pfeifer
2019	J	`jnl`	EHR problem list clustering for improved topic-space navigation. BMC Medical Informatics Decis. Mak. Markus Kreuzthaler, Bastian Pfeifer, José Antonio Vera Ramos, Diether Kramer, Victor Grogger, Sylvia Bredenfeldt, Markus Pedevilla, Peter Krisper, Stefan Schulz
2019	J	`jnl`	Estimates of introgression as a function of pairwise distances. BMC Bioinform. Bastian Pfeifer, Durrell D. Kapan
2018	J	`jnl`	BlockFeST: Bayesian calculation of region-specific FST to detect local adaptation. Bioinform. Bastian Pfeifer, Martin J. Lercher
2018	—	`conf`	EHR Text Categorization for Enhanced Patient-Based Document Navigation. eHealth Markus Kreuzthaler, Bastian Pfeifer, José Antonio Vera Ramos, Diether Kramer, Victor Grogger, Sylvia Bredenfeldt, Markus Pedevilla, Peter Krisper, Stefan Schulz
2018	—	`conf`	Problem List Clustering for Improved Patient-Based Disease Perception. ICHI Workshops Markus Kreuzthaler, Bastian Pfeifer, José Antonio Vera Ramos, Diether Kramer, Victor Grogger, Sylvia Bredenfeldt, Markus Pedevilla, Peter Krisper, Stefan Schulz
2015	—	`—`	Whole-genome population genomic analyses. Bastian Pfeifer
2015	J	`jnl`	WhopGenome: high-speed access to whole-genome variation and sequence data in R. Bioinform. Ulrich Wittelsbürger, Bastian Pfeifer, Martin J. Lercher

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.