Daniel Dakota - RankMe

20 papers B 1C 1Misc 7Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	Misc	`conf`	Investigating Polarization in YouTube Comments via Aspect-Based Sentiment Analysis. RANLP Daniel Miehling, Daniel Dakota, Sandra Kübler
2025	Misc	`conf`	Performance Gaps in Acted and Naturalistic Speech: Insights from Speech Emotion Recognition Strategies on Customer Service Calls. RANLP Lily Kawaoto, Hita Gupta, Ning Yu, Daniel Dakota
2025	Misc	`conf`	Pushing the (Generative) Envelope: Measuring the Effect of Prompt Technique and Temperature on the Generation of Model-based Systems Engineering Artifacts. RANLP Erin Smith Crabb, Cedric Bernard, Matthew Jones, Daniel Dakota
2024	—	`conf`	Bits and Pieces: Investigating the Effects of Subwords in Multi-task Parsing across Languages and Domains. LREC/COLING Daniel Dakota, Sandra Kübler
2024	—	`conf`	Introducing a Parsed Corpus of Historical High German. LREC/COLING Christopher D. Sapp, Elliott Evans, Rex Sprouse, Daniel Dakota
2024	—	`conf`	Out-of-Domain Dependency Parsing for Dialects of Arabic: A Case Study. ArabicNLP Noor Abo Mokh, Daniel Dakota, Sandra Kübler
2024	—	`conf`	Scaling Up Authorship Attribution. NAACL (Industry Track) Jacob Striebel, Abishek R. Edikala, Ethan Irby, Alex Rosenfeld, J. Gage, Daniel Dakota, Sandra Kübler
2023	Misc	`conf`	Bigfoot in Big Tech: Detecting Out of Domain Conspiracy Theories. RANLP Matthew Fort, Zuoyu Tian, Elizabeth Gabel, Nina Georgiades, Noah Sauer, Daniel Dakota, Sandra Kübler
2022	B	`conf`	How to Parse a Creole: When Martinican Creole Meets French. COLING Ludovic Mompelat, Daniel Dakota, Sandra Kübler
2022	—	`conf`	Improving POS Tagging for Arabic Dialects on Out-of-Domain Texts. WANLP@EMNLP Noor Abo Mokh, Daniel Dakota, Sandra Kübler
2021	—	`conf`	Annotations Matter: Leveraging Multi-task Learning to Parse UD and SUD. ACL/IJCNLP (Findings) Zeeshan Ali Sayyed, Daniel Dakota
2019	Misc	`conf`	Investigating Multilingual Abusive Language Detection: A Cautionary Tale. RANLP Kenneth Steimel, Daniel Dakota, Yue Chen, Sandra Kübler
2018	—	`conf`	Practical Parsing for Downstream Applications. COLING (Tutorials) Daniel Dakota, Sandra Kübler
2017	Misc	`conf`	Non-Deterministic Segmentation for Chinese Lattice Parsing. RANLP Hai Hu, Daniel Dakota, Sandra Kübler
2017	—	`conf`	The Devil is in the Details: Parsing Unknown German Words. GSCL Daniel Dakota
2017	Misc	`conf`	Towards Replicability in Parsing. RANLP Daniel Dakota, Sandra Kübler
2016	—	`conf`	Brown clustering for unlexicalized parsing. KONVENS Daniel Dakota
2016	C	`conf`	From Discourse Representation Structure to Event Semantics: A Simple Conversion? FedCSIS Daniel Dakota, Sandra Kübler
2016	—	`conf`	IUCL at SemEval-2016 Task 6: An Ensemble Model for Stance Detection in Twitter. SemEval@NAACL-HLT Can Liu, Wen Li, Bradford Demarest, Yue Chen, Sara Couture, Daniel Dakota, Nikita Haduong, Noah Kaufman, Andrew Lamont, Manan Pancholi, Kenneth Steimel, Sandra Kübler
2014	—	`conf`	"My Curiosity was Satisfied, but not in a Good Way": Predicting User Ratings for Online Recipes. SocialNLP@COLING Can Liu, Chun Guo, Daniel Dakota, Sridhar Rajagopalan, Wen Li, Sandra Kübler, Ning Yu

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.