Daniel Kiefer

15 papers C 3Journal 1Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	A Framework for Explainable Root Cause Analysis in Manufacturing Systems - Combining Machine Learning, Explainable Artificial Intelligence and the Ishikawa Model for Industrial Manufacturing. HICSS Daniel Kiefer, Tim Straub, Günter Bitsch, Clemens van Dinther
2024	C	`conf`	Automatic Gear Tooth Alignment 2.0: Improved Image Segmentation for Better Rotation Angle Deviation Determination. ISM Florian Grimm, Daniel Kiefer, Tim Straub, Günter Bitsch, Clemens van Dinther
2024	—	`conf`	Taking a HINT on Industrial Anomaly Detection. INFORMATIK Jacqueline Höllig, Florian Grimm, Daniel Kiefer, Steffen Thoma
2023	C	`conf`	Anomaly Detection in Hobbing Tool Images: Using An Unsupervised Deep Learning Approach in Manufacturing Industry. ISM Daniel Kiefer, Stefan Wezel, Alexander Böttcher, Florian Grimm, Tim Straub, Günter Bitsch, Clemens van Dinther
2023	C	`conf`	Automatic Gear Tooth Alignment in Vision Based Preventive Maintenance. ISM Florian Grimm, Daniel Kiefer, Tim Straub, Günter Bitsch, Clemens van Dinther
2023	J	`jnl`	Practice Summary: GE Optimizes for Aircraft Engine Overhaul Scheduling and Shop Assignment. INFORMS J. Appl. Anal. Nitish Umang, Daniel Kiefer, Patricio Gonzalez, Henri Thevenot, Christopher D. Johnson, Jean Martin, Emily Stephenson, Jerrold Cline, Banu Gemici-Ozkan, Israel Beniaminy
2022	—	`conf`	Artificial Intelligence in Supply Chain Management: Investigation of Transfer Learning to Improve Demand Forecasting of Intermittent Time Series with Deep Learning. HICSS Daniel Kiefer, Florian Grimm, Clemens van Dinther
2022	—	`conf`	The Time has Come - Application of Artificial Intelligence in Small- and Medium-Sized Enterprises. Wirtschaftsinformatik Daniel Kiefer, Clemens van Dinther, Tim Straub
2021	—	`conf`	Demand Forecasting Intermittent and Lumpy Time Series: Comparing Statistical, Machine Learning and Deep Learning Methods. HICSS Daniel Kiefer, Florian Grimm, Markus Bauer, Clemens van Dinther
2021	—	`conf`	Digital Innovation Culture: A Systematic Literature Review. Wirtschaftsinformatik Daniel Kiefer, Clemens van Dinther, Julian Spitzmüller
2021	—	`conf`	Digital Skills of Procurement Employees and Their Attitudes Toward Digital Technologies. KES-HCIS Gerald Blessing, Daniel Kiefer
2021	—	`conf`	Sales Forecasting Under Economic Crisis: A Case Study of the Impact of the COVID19 Crisis to the Predictability of Sales of a Medium-Sized Enterprise. KES-HCIS Markus Bauer, Daniel Kiefer, Florian Grimm
2021	—	`conf`	Univariate Time Series Forecasting by Investigating Intermittence and Demand Individually. KES-HCIS Florian Grimm, Daniel Kiefer, Markus Bauer
2021	—	`conf`	Univariate Time Series Forecasting: Machine Learning Prediction of the Best Suitable Forecast Model Based on Time Series Characteristics. KES-HCIS Daniel Kiefer, Markus Bauer, Florian Grimm
2020	—	`conf`	Machine Learning in SME: An Empirical Study on Enablers and Success Factors. AMCIS Markus Bauer, Clemens van Dinther, Daniel Kiefer

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.