Yanfei Kang - RankMe

29 papers B 1C 1Journal 25Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Predict+Optimize Problem in Renewable Energy Scheduling. IEEE Access Christoph Bergmeir, Frits de Nijs, Evgenii Genov, Abishek Sriramulu, Mahdi Abolghasemi, Richard Bean, John M. Betts, Quang Bui, Nam Trong Dinh, Nils Einecke, Rasul Esmaeilbeigi, Scott Ferraro, Priya Galketiya, Robert Glasgow, Rakshitha Godahewa, Yanfei Kang, Steffen Limmer, Luis Magdalena, Pablo Montero-Manso, Daniel Peralta, Yogesh Pipada Sunil Kumar, Alejandro Rosales-Pérez, Julian Ruddick, Akylas C. Stratigakos, Peter J. Stuckey, Guido Tack, Isaac Triguero, Rui Yuan
2024	J	`jnl`	Combining probabilistic forecasts of intermittent demand. Eur. J. Oper. Res. Shengjie Wang, Yanfei Kang, Fotios Petropoulos
2024	J	`jnl`	Discrete forecast reconciliation. Eur. J. Oper. Res. Bohan Zhang, Anastasios Panagiotelis, Yanfei Kang
2023	J	`jnl`	A hybrid ensemble method with negative correlation learning for regression. Mach. Learn. Yun Bai, Ganglin Tian, Yanfei Kang, Suling Jia
2023	J	`jnl`	Feature-based intermittent demand forecast combinations: accuracy and inventory implications. Int. J. Prod. Res. Li Li, Yanfei Kang, Fotios Petropoulos, Feng Li
2023	J	`jnl`	Forecasting large collections of time series: feature-based methods. CoRR Li Li, Feng Li, Yanfei Kang
2023	J	`jnl`	Improving forecasting by subsampling seasonal time series. Int. J. Prod. Res. Xixi Li, Fotios Petropoulos, Yanfei Kang
2023	—	`conf`	Infinite forecast combinations based on Dirichlet process. ICDM (Workshops) Yinuo Ren, Feng Li, Yanfei Kang, Jue Wang
2023	J	`jnl`	Infinite forecast combinations based on Dirichlet process. CoRR Yinuo Ren, Feng Li, Yanfei Kang, Jue Wang
2023	J	`jnl`	Optimal reconciliation with immutable forecasts. Eur. J. Oper. Res. Bohan Zhang, Yanfei Kang, Anastasios Panagiotelis, Feng Li
2023	—	`conf`	Probabilistic Forecast Reconciliation with Kullback-Leibler Divergence Regularization. ICDM (Workshops) Guanyu Zhang, Feng Li, Yanfei Kang
2023	J	`jnl`	Probabilistic Forecast Reconciliation with Kullback-Leibler Divergence Regularization. CoRR Guanyu Zhang, Feng Li, Yanfei Kang
2022	J	`jnl`	Comparison and Evaluation of Methods for a Predict+Optimize Problem in Renewable Energy. CoRR Christoph Bergmeir, Frits de Nijs, Abishek Sriramulu, Mahdi Abolghasemi, Richard Bean, John M. Betts, Quang Bui, Nam Trong Dinh, Nils Einecke, Rasul Esmaeilbeigi, Scott Ferraro, Priya Galketiya, Evgenii Genov, Robert Glasgow, Rakshitha Godahewa, Yanfei Kang, Steffen Limmer, Luis Magdalena, Pablo Montero-Manso, Daniel Peralta, Yogesh Pipada Sunil Kumar, Alejandro Rosales-Pérez, Julian Ruddick, Akylas C. Stratigakos, Peter J. Stuckey, Guido Tack, Isaac Triguero, Rui Yuan
2022	J	`jnl`	Forecast with forecasts: Diversity matters. Eur. J. Oper. Res. Yanfei Kang, Wei Cao, Fotios Petropoulos, Feng Li
2022	J	`jnl`	The uncertainty estimation of feature-based forecast combinations. J. Oper. Res. Soc. Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos, Feng Li
2021	J	`jnl`	Enhancing the Diversity of Predictions Combination by Negative Correlation Learning. CoRR Yun Bai, Ganglin Tian, Yanfei Kang, Suling Jia
2021	J	`jnl`	Exploring the representativeness of the M5 competition data. CoRR Evangelos Theodorou, Shengjie Wang, Yanfei Kang, Evangelos Spiliotis, Spyros Makridakis, Vassilios Assimakopoulos
2021	J	`jnl`	Exploring the social influence of Kaggle virtual community on the M5 competition. CoRR Xixi Li, Yun Bai, Yanfei Kang
2021	J	`jnl`	Improving the accuracy of global forecasting models using time series data augmentation. Pattern Recognit. Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir
2020	J	`jnl`	Forecasting with time series imaging. Expert Syst. Appl. Xixi Li, Yanfei Kang, Feng Li
2020	J	`jnl`	Forecasting: theory and practice. CoRR Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos, Mohamed Zied Babai, Devon K. Barrow, Souhaib Ben Taieb, Christoph Bergmeir, Ricardo J. Bessa, Jakub Bijak, John E. Boylan, Jethro Browell, Claudio Carnevale, Jennifer L. Castle, Pasquale Cirillo, Michael P. Clements, Clara Cordeiro, Fernando Luiz Cyrino Oliveira, Shari De Baets, Alexander Dokumentov, Joanne Ellison, Piotr Fiszeder, Philip Hans Franses, David T. Frazier, Michael Gilliland, Mustafa Sinan Gönül, Paul Goodwin, Luigi Grossi, Yael Grushka-Cockayne, Mariangela Guidolin, Massimo Guidolin, Ulrich Gunter, Xiaojia Guo, Renato Guseo, Nigel Harvey, David F. Hendry, Ross Hollyman, Tim Januschowski, Jooyoung Jeon, Victor Richmond R. Jose, Yanfei Kang, Anne B. Koehler, Stephan Kolassa, Nikolaos Kourentzes, Sonia Leva, Feng Li
2020	J	`jnl`	GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. Stat. Anal. Data Min. Yanfei Kang, Rob J. Hyndman, Feng Li
2020	J	`jnl`	Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation. CoRR Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir
2020	J	`jnl`	Probabilistic forecasting with temporal convolutional neural network. Neurocomputing Yitian Chen, Yanfei Kang, Yixiong Chen, Zizhuo Wang
2019	J	`jnl`	Forecasting with time series imaging. CoRR Xixi Li, Yanfei Kang, Feng Li
2019	J	`jnl`	GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. CoRR Yanfei Kang, Rob J. Hyndman, Feng Li
2019	J	`jnl`	Probabilistic Forecasting with Temporal Convolutional Neural Network. CoRR Yitian Chen, Yanfei Kang, Yixiong Chen, Zizhuo Wang
2013	C	`conf`	How to extract meaningful shapes from noisy time-series subsequences? CIDM Yanfei Kang, Kate Smith-Miles, Danijel Belusic
2012	B	`conf`	Real-time change detection in time series based on growing feature quantization. IJCNN Yanfei Kang

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.