Danial Dervovic

38 papers A* 4A 1C 1Journal 26Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Calibrating Non-Identifiable High-Dimensional Simulation Models: A Framework via Eligibility Set. ACM Trans. Model. Comput. Simul. Yuanlu Bai, Tucker Balch, Haoxian Chen, Danial Dervovic, Henry Lam, Svitlana Vyetrenko
2026	J	`jnl`	GenePlan: Evolving Better Generalized PDDL Plans using Large Language Models. CoRR Andrew Murray, Danial Dervovic, Alberto Pozanco, Michael Cashmore
2025	J	`jnl`	Balancing Fairness and Accuracy in Data-Restricted Binary Classification. ACM Trans. Knowl. Discov. Data Zachary McBride Lazri, Danial Dervovic, Antigoni Polychroniadou, Ivan Brugere, Dana Dachman-Soled, Furong Huang, Min Wu
2025	J	`jnl`	ELATE: Evolutionary Language model for Automated Time-series Engineering. CoRR Andrew Murray, Danial Dervovic, Michael Cashmore
2025	J	`jnl`	MAFE: Multi-Agent Fair Environments for Decision-Making Systems. CoRR Zachary McBride Lazri, Anirudh Nakra, Ivan Brugere, Danial Dervovic, Antigoni Polychroniadou, Furong Huang, Dana Dachman-Soled, Min Wu
2025	A	`conf`	Model Evaluation in the Dark: Robust Classifier Metrics with Missing Labels. AISTATS Danial Dervovic, Michael Cashmore
2025	J	`jnl`	Model Evaluation in the Dark: Robust Classifier Metrics with Missing Labels. CoRR Danial Dervovic, Michael Cashmore
2024	J	`jnl`	A Canonical Data Transformation for Achieving Inter- and Within-Group Fairness. IEEE Trans. Inf. Forensics Secur. Zachary McBride Lazri, Ivan Brugere, Xin Tian, Dana Dachman-Soled, Antigoni Polychroniadou, Danial Dervovic, Min Wu
2024	A*	`conf`	Are Logistic Models Really Interpretable? IJCAI Danial Dervovic, Freddy Lécué, Nicolas Marchesotti, Daniele Magazzeni
2024	J	`jnl`	Are Logistic Models Really Interpretable? CoRR Danial Dervovic, Freddy Lécué, Nicolas Marchesotti, Daniele Magazzeni
2024	J	`jnl`	Balancing Fairness and Accuracy in Data-Restricted Binary Classification. CoRR Zachary McBride Lazri, Danial Dervovic, Antigoni Polychroniadou, Ivan Brugere, Dana Dachman-Soled, Min Wu
2024	A*	`conf`	Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data. ICML Yvonne Zhou, Mingyu Liang, Ivan Brugere, Danial Dervovic, Antigoni Polychroniadou, Min Wu, Dana Dachman-Soled
2024	J	`jnl`	Bounding the Excess Risk for Linear Models Trained on Marginal-Preserving, Differentially-Private, Synthetic Data. CoRR Yvonne Zhou, Mingyu Liang, Ivan Brugere, Dana Dachman-Soled, Danial Dervovic, Antigoni Polychroniadou, Min Wu
2024	J	`jnl`	Characterizing Multimodal Long-form Summarization: A Case Study on Financial Reports. CoRR Tianyu Cao, Natraj Raman, Danial Dervovic, Chenhao Tan
2024	J	`jnl`	Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models. CoRR Wenzhuo Tang, Haitao Mao, Danial Dervovic, Ivan Brugere, Saumitra Mishra, Yuying Xie, Jiliang Tang
2024	J	`jnl`	Surrogate Assisted Monte Carlo Tree Search in Combinatorial Optimization. CoRR Saeid Amiri, Parisa Zehtabi, Danial Dervovic, Michael Cashmore
2023	J	`jnl`	A Canonical Data Transformation for Achieving Inter- and Within-group Fairness. CoRR Zachary McBride Lazri, Ivan Brugere, Xin Tian, Dana Dachman-Soled, Antigoni Polychroniadou, Danial Dervovic, Min Wu
2023	C	`conf`	On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations. AIES Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic, Daniele Magazzeni
2023	J	`jnl`	On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations. CoRR Emanuele Albini, Shubham Sharma, Saumitra Mishra, Danial Dervovic, Daniele Magazzeni
2022	—	`conf`	Counterfactual Shapley Additive Explanations. FAccT Emanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni
2022	A*	`conf`	Optimal Admission Control for Multiclass Queues with Time-Varying Arrival Rates via State Abstraction. AAAI Marc Rigter, Danial Dervovic, Parisa Hassanzadeh, Jason Long, Parisa Zehtabi, Daniele Magazzeni
2022	J	`jnl`	Optimal Admission Control for Multiclass Queues with Time-Varying Arrival Rates via State Abstraction. CoRR Marc Rigter, Danial Dervovic, Parisa Hassanzadeh, Jason Long, Parisa Zehtabi, Daniele Magazzeni
2022	—	`conf`	Optimal Stopping with Gaussian Processes. ICAIF Kshama Dwarakanath, Danial Dervovic, Peyman Tavallali, Svitlana Vyetrenko, Tucker Balch
2022	J	`jnl`	Optimal Stopping with Gaussian Processes. CoRR Kshama Dwarakanath, Danial Dervovic, Peyman Tavallali, Svitlana S. Vyetrenko, Tucker Balch
2022	J	`jnl`	Rethinking Log Odds: Linear Probability Modelling and Expert Advice in Interpretable Machine Learning. CoRR Danial Dervovic, Nicolas Marchesotti, Freddy Lécué, Daniele Magazzeni
2021	J	`jnl`	Calibrating Over-Parametrized Simulation Models: A Framework via Eligibility Set. CoRR Yuanlu Bai, Tucker Balch, Haoxian Chen, Danial Dervovic, Henry Lam, Svitlana Vyetrenko
2021	J	`jnl`	Counterfactual Explanations for Arbitrary Regression Models. CoRR Thomas Spooner, Danial Dervovic, Jason Long, Jon Shepard, Jiahao Chen, Daniele Magazzeni
2021	J	`jnl`	Counterfactual Shapley Additive Explanations. CoRR Emanuele Albini, Jason Long, Danial Dervovic, Daniele Magazzeni
2021	A*	`conf`	Non-Parametric Stochastic Sequential Assignment With Random Arrival Times. IJCAI Danial Dervovic, Parisa Hassanzadeh, Samuel Assefa, Prashant Reddy
2021	J	`jnl`	Non-Parametric Stochastic Sequential Assignment With Random Arrival Times. CoRR Danial Dervovic, Parisa Hassanzadeh, Samuel Assefa, Prashant Reddy
2021	J	`jnl`	Tradeoffs in Streaming Binary Classification under Limited Inspection Resources. CoRR Parisa Hassanzadeh, Danial Dervovic, Samuel Assefa, Prashant Reddy, Manuela Veloso
2021	—	`conf`	Tradeoffs in streaming binary classification under limited inspection resources. ICAIF Parisa Hassanzadeh, Danial Dervovic, Samuel Assefa, Prashant Reddy, Manuela Veloso
2020	—	`conf`	Generating synthetic data in finance: opportunities, challenges and pitfalls. ICAIF Samuel A. Assefa, Danial Dervovic, Mahmoud Mahfouz, Robert E. Tillman, Prashant Reddy, Manuela Veloso
2020	—	`conf`	Get real: realism metrics for robust limit order book market simulations. ICAIF Svitlana Vyetrenko, David Byrd, Nick Petosa, Mahmoud Mahfouz, Danial Dervovic, Manuela Veloso, Tucker Balch
2020	—	`—`	Quantum computation, Markov chains and combinatorial optimisation Danial Dervovic
2019	J	`jnl`	Get Real: Realism Metrics for Robust Limit Order Book Market Simulations. CoRR Svitlana Vyetrenko, David Byrd, Nick Petosa, Mahmoud Mahfouz, Danial Dervovic, Manuela Veloso, Tucker Hybinette Balch
2018	J	`jnl`	Constructing graphs with limited resources. CoRR Danial Dervovic, Avinash Mocherla, Simone Severini
2018	J	`jnl`	Quantum linear systems algorithms: a primer. CoRR Danial Dervovic, Mark Herbster, Peter Mountney, Simone Severini, Naïri Usher, Leonard Wossnig

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.