Bardh Prenkaj - RankMe

68 papers A* 8A 5Misc 1Journal 37Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Multi-Agent Framework for Interpreting Multivariate Physiological Time Series. CoRR Davide Gabrielli, Paola Velardi, Stefano Faralli, Bardh Prenkaj
2026	J	`jnl`	Analysing the Safety Pitfalls of Steering Vectors. CoRR Yuxiao Li, Alina Fastowski, Efstratios Zaradoukas, Bardh Prenkaj, Gjergji Kasneci
2026	J	`jnl`	Beyond Edge Deletion: A Comprehensive Approach to Counterfactual Explanation in Graph Neural Networks. CoRR Matteo De Sanctis, Riccardo De Sanctis, Stefano Faralli, Paola Velardi, Bardh Prenkaj
2026	J	`jnl`	COunterfactual Reasoning for Temporal EXplanations: Plausible and Robust Explanations for EEG-Based Seizure Detection. Trans. Mach. Learn. Res. Martina Zannotti, Bardh Prenkaj, Marco Piangerelli, Flavio Corradini, Gjergji Kasneci
2026	J	`jnl`	Moral Lenses, Political Coordinates: Towards Ideological Positioning of Morally Conditioned LLMs. CoRR Chenchen Yuan, Bolei Ma, Zheyu Zhang, Bardh Prenkaj, Frauke Kreuter, Gjergji Kasneci
2026	J	`jnl`	Reinforcement Unlearning via Group Relative Policy Optimization. CoRR Efstratios Zaradoukas, Bardh Prenkaj, Gjergji Kasneci
2026	J	`jnl`	Seamless monitoring of stress levels leveraging a foundational model for time sequences. Artif. Intell. Medicine Davide Gabrielli, Bardh Prenkaj, Paola Velardi
2025	A	`conf`	AI on the Pulse: Real-Time Health Anomaly Detection with Wearable and Ambient Intelligence. CIKM Davide Gabrielli, Bardh Prenkaj, Paola Velardi, Stefano Faralli
2025	J	`jnl`	AI on the Pulse: Real-Time Health Anomaly Detection with Wearable and Ambient Intelligence. CoRR Davide Gabrielli, Bardh Prenkaj, Paola Velardi, Stefano Faralli
2025	J	`jnl`	Agnostic Visual Recommendation Systems: Open Challenges and Future Directions. IEEE Trans. Vis. Comput. Graph. Luca Podo, Bardh Prenkaj, Paola Velardi
2025	—	`conf`	CURE: Controlled Unlearning for Robust Embeddings - Mitigating Conceptual Shortcuts in Pre-Trained Language Models. EMNLP (Findings) Aysenur Kocak, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	J	`jnl`	CURE: Controlled Unlearning for Robust Embeddings - Mitigating Conceptual Shortcuts in Pre-Trained Language Models. CoRR Aysenur Kocak, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	—	`ed.`	Discovering Drift Phenomena in Evolving Landscapes - First International Workshop, DELTA 2024, Barcelona, Spain, August 26, 2024, Proceedings DELTA Marco Piangerelli, Bardh Prenkaj, Ylenia Rotalinti, Ananya Joshi, Giovanni Stilo
2025	A*	`conf`	Doubling Your Data in Minutes: Ultra-fast Tabular Data Generation via LLM-Induced Dependency Graphs. EMNLP Shuo Yang, Zheyu Zhang, Bardh Prenkaj, Gjergji Kasneci
2025	J	`jnl`	Doubling Your Data in Minutes: Ultra-fast Tabular Data Generation via LLM-Induced Dependency Graphs. CoRR Shuo Yang, Zheyu Zhang, Bardh Prenkaj, Gjergji Kasneci
2025	—	`conf`	Exploring Ensemble Strategies for Graph Counterfactual Explanations. xAI (4) Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
2025	—	`conf`	From Confidence to Collapse in LLM Factual Robustness. EMNLP (Findings) Alina Fastowski, Bardh Prenkaj, Gjergji Kasneci
2025	J	`jnl`	From Confidence to Collapse in LLM Factual Robustness. CoRR Alina Fastowski, Bardh Prenkaj, Gjergji Kasneci
2025	A*	`conf`	Graph Inverse Style Transfer for Counterfactual Explainability. ICML Bardh Prenkaj, Efstratios Zaradoukas, Gjergji Kasneci
2025	J	`jnl`	Graph Style Transfer for Counterfactual Explainability. CoRR Bardh Prenkaj, Efstratios Zaradoukas, Gjergji Kasneci
2025	J	`jnl`	Injecting Falsehoods: Adversarial Man-in-the-Middle Attacks Undermining Factual Recall in LLMs. CoRR Alina Fastowski, Bardh Prenkaj, Yuxiao Li, Gjergji Kasneci
2025	—	`conf`	Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models. EMNLP (Findings) Zheyu Zhang, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	J	`jnl`	Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models. CoRR Zheyu Zhang, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	—	`conf`	Probabilistic Aggregation and Targeted Embedding Optimization for Collective Moral Reasoning in Large Language Models. ACL (Findings) Chenchen Yuan, Zheyu Zhang, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	J	`jnl`	Probabilistic Aggregation and Targeted Embedding Optimization for Collective Moral Reasoning in Large Language Models. CoRR Chenchen Yuan, Zheyu Zhang, Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	A*	`conf`	RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting. AAAI Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	A*	`conf`	SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification. ICML Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	J	`jnl`	SCISSOR: Mitigating Semantic Bias through Cluster-Aware Siamese Networks for Robust Classification. CoRR Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2025	A	`conf`	TRADES: Generating Realistic Market Simulations with Diffusion Models. ECAI Leonardo Berti, Bardh Prenkaj, Paola Velardi
2025	J	`jnl`	TRADES: Generating Realistic Market Simulations with Diffusion Models. CoRR Leonardo Berti, Bardh Prenkaj, Paola Velardi
2024	J	`jnl`	A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges. ACM Comput. Surv. Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo, Fosca Giannotti
2024	—	`conf`	GRETEL 2.0: Generation and Evaluation of Graph Counterfactual Explanations Evolved. ECML/PKDD (8) Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
2024	J	`jnl`	RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting. CoRR Shuo Yang, Bardh Prenkaj, Gjergji Kasneci
2024	A*	`conf`	Robust Stochastic Graph Generator for Counterfactual Explanations. AAAI Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
2024	J	`jnl`	Seamless Monitoring of Stress Levels Leveraging a Universal Model for Time Sequences. CoRR Davide Gabrielli, Bardh Prenkaj, Paola Velardi
2024	—	`conf`	Semantically Guided Representation Learning For Action Anticipation. ECCV (28) Anxhelo Diko, Danilo Avola, Bardh Prenkaj, Federico Fontana, Luigi Cinque
2024	J	`jnl`	Semantically Guided Representation Learning For Action Anticipation. CoRR Anxhelo Diko, Danilo Avola, Bardh Prenkaj, Federico Fontana, Luigi Cinque
2024	J	`jnl`	Towards Non-Adversarial Algorithmic Recourse. CoRR Tobias Leemann, Martin Pawelczyk, Bardh Prenkaj, Gjergji Kasneci
2024	—	`conf`	Towards Non-adversarial Algorithmic Recourse. xAI (3) Tobias Leemann, Martin Pawelczyk, Bardh Prenkaj, Gjergji Kasneci
2024	A*	`conf`	Unifying Evolution, Explanation, and Discernment: A Generative Approach for Dynamic Graph Counterfactuals. KDD Bardh Prenkaj, Mario Villaizán-Vallelado, Tobias Leemann, Gjergji Kasneci
2024	J	`jnl`	Unsupervised Detection of Behavioural Drifts With Dynamic Clustering and Trajectory Analysis. IEEE Trans. Knowl. Data Eng. Bardh Prenkaj, Paola Velardi
2024	A*	`conf`	Workshop on Discovering Drift Phenomena in Evolving Data Landscape (DELTA). KDD Marco Piangerelli, Bardh Prenkaj, Ylenia Rotalinti, Ananya Joshi, Giovanni Stilo
2023	J	`jnl`	A self-supervised algorithm to detect signs of social isolation in the elderly from daily activity sequences. Artif. Intell. Medicine Bardh Prenkaj, Dario Aragona, Alessandro Flaborea, Fabio Galasso, Saverio Gravina, Luca Podo, Emilia Reda, Paola Velardi
2023	—	`conf`	Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes. PKDD/ECML Workshops (1) Bardh Prenkaj, Mario Villaizán-Vallelado, Tobias Leemann, Gjergji Kasneci
2023	J	`jnl`	Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes. CoRR Bardh Prenkaj, Mario Villaizán-Vallelado, Tobias Leemann, Gjergji Kasneci
2023	—	`conf`	Are Generative-Based Graph Counterfactual Explainers Worth It? PKDD/ECML Workshops (3) Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
2023	—	`conf`	Are we certain it's anomalous? CVPR Workshops Alessandro Flaborea, Bardh Prenkaj, Bharti Munjal, Marco Aurelio Sterpa, Dario Aragona, Luca Podo, Fabio Galasso
2023	A	`conf`	Developing and Evaluating Graph Counterfactual Explanation with GRETEL. WSDM Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
2023	J	`jnl`	Machine Learning for Visualization Recommendation Systems: Open Challenges and Future Directions. CoRR Luca Podo, Bardh Prenkaj, Paola Velardi
2023	A*	`conf`	Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection. ICCV Alessandro Flaborea, Luca Collorone, Guido Maria D'Amely di Melendugno, Stefano D'Arrigo, Bardh Prenkaj, Fabio Galasso
2023	J	`jnl`	Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection. CoRR Alessandro Flaborea, Luca Collorone, Guido D'Amely, Stefano D'Arrigo, Bardh Prenkaj, Fabio Galasso
2023	—	`conf`	Revisiting CounteRGAN for Counterfactual Explainability of Graphs. Tiny Papers @ ICLR Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
2023	J	`jnl`	Robust Stochastic Graph Generator for Counterfactual Explanations. CoRR Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
2023	J	`jnl`	Unsupervised Detection of Behavioural Drifts with Dynamic Clustering and Trajectory Analysis. CoRR Bardh Prenkaj, Paola Velardi
2022	J	`jnl`	A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation. CoRR Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo, Fosca Giannotti
2022	J	`jnl`	Are we certain it's anomalous? CoRR Alessandro Flaborea, Bardh Prenkaj, Bharti Munjal, Marco Aurelio Sterpa, Dario Aragona, Luca Podo, Fabio Galasso
2022	—	`conf`	Ensemble Approaches for Graph Counterfactual Explanations. XAI.it@AI*IA Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo, Alessandro Celi, Ernesto Luis Estevanell-Valladares, Daniel Alejandro Valdés Pérez
2022	—	`—`	Latent deep sequential learning of behavioural sequences. Bardh Prenkaj
2021	J	`jnl`	A Survey of Machine Learning Approaches for Student Dropout Prediction in Online Courses. ACM Comput. Surv. Bardh Prenkaj, Paola Velardi, Giovanni Stilo, Damiano Distante, Stefano Faralli
2021	Misc	`conf`	C SAC Dario Aragona, Luca Podo, Bardh Prenkaj, Paola Velardi
2021	J	`jnl`	Hidden space deep sequential risk prediction on student trajectories. Future Gener. Comput. Syst. Bardh Prenkaj, Damiano Distante, Stefano Faralli, Paola Velardi
2021	—	`conf`	Unsupervised Boosting-Based Autoencoder Ensembles for Outlier Detection. PAKDD (1) Hamed Sarvari, Carlotta Domeniconi, Bardh Prenkaj, Giovanni Stilo
2020	A	`conf`	A Reproducibility Study of Deep and Surface Machine Learning Methods for Human-related Trajectory Prediction. CIKM Bardh Prenkaj, Paola Velardi, Damiano Distante, Stefano Faralli
2020	A	`conf`	Challenges and Solutions to the Student Dropout Prediction Problem in Online Courses. CIKM Bardh Prenkaj, Giovanni Stilo, Lorenzo Madeddu
2019	J	`jnl`	MIMOSE: multimodal interaction for music orchestration sheet editors - An integrable multimodal music editor interaction system. Multim. Tools Appl. Andrea Coletta, Maria De Marsico, Emanuele Panizzi, Bardh Prenkaj, Domenicomichele Silvestri
2019	J	`jnl`	Unsupervised Boosting-based Autoencoder Ensembles for Outlier Detection. CoRR Hamed Sarvari, Carlotta Domeniconi, Bardh Prenkaj, Giovanni Stilo
2018	J	`jnl`	House in the (Biometric) Cloud: A Possible Application. IEEE Cloud Comput. Maria De Marsico, Eugenio Nemmi, Bardh Prenkaj, Gabriele Saturni
2017	—	`conf`	A Smart Peephole on the Cloud. ICIAP Workshops Maria De Marsico, Eugenio Nemmi, Bardh Prenkaj, Gabriele Saturni

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.