Qidong Yang - RankMe

13 papers Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Conformal Prediction for Generative Models via Adaptive Cluster-Based Density Estimation. CoRR Qidong Yang, Qianyu Julie Zhu, Jonathan Giezendanner, Youssef Marzouk, Stephen Bates, Sherrie Wang
2026	J	`jnl`	Partial recovery of meter-scale surface weather. CoRR Jonathan Giezendanner, Qidong Yang, Eric Schmitt, Anirban Chandra, Daniel Salles Civitarese, Johannes Jakubik, Jeremy Vila, Detlef Hohl, Campbell D. Watson, Sherrie Wang
2025	J	`jnl`	Observation-driven correction of numerical weather prediction for marine winds. CoRR Matteo Peduto, Qidong Yang, Jonathan Giezendanner, Devis Tuia, Sherrie Wang
2024	J	`jnl`	A Monte Carlo Framework for Calibrated Uncertainty Estimation in Sequence Prediction. CoRR Qidong Yang, Weicheng Zhu, Joseph Keslin, Laure Zanna, Tim G. J. Rudner, Carlos Fernandez-Granda
2024	J	`jnl`	Evaluating the transferability potential of deep learning models for climate downscaling. CoRR Ayush Prasad, Paula Harder, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2024	J	`jnl`	Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling. J. Mach. Learn. Res. Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2024	J	`jnl`	Multi-modal graph neural networks for localized off-grid weather forecasting. CoRR Qidong Yang, Jonathan Giezendanner, Daniel Salles Civitarese, Johannes Jakubik, Eric Schmitt, Anirban Chandra, Jeremy Vila, Detlef Hohl, Christopher Hill, Campbell D. Watson, Sherrie Wang
2023	J	`jnl`	Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling. CoRR Qidong Yang, Alex Hernández-García, Paula Harder, Venkatesh Ramesh, Prasanna Sattigeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2023	J	`jnl`	Hard-Constrained Deep Learning for Climate Downscaling. J. Mach. Learn. Res. Paula Harder, Alex Hernández-García, Venkatesh Ramesh, Qidong Yang, Prasanna Sattegeri, Daniela Szwarcman, Campbell D. Watson, David Rolnick
2022	J	`jnl`	A Method of Inversing Dynamic Aerosol Extinction-to-Backscattering Ratio Based on Lidar Echo Signal and Ground Aerosol Extinction Coefficient or Aerosol Optical Depth. IEEE Trans. Geosci. Remote. Sens. Chuwei Zhang, Jian Wu, Wenxuan Fan, Jingchuan Zhao, Qidong Yang, Jinlin Zha, Deming Zhao, Peishi Sun
2022	J	`jnl`	Generating physically-consistent high-resolution climate data with hard-constrained neural networks. CoRR Paula Harder, Qidong Yang, Venkatesh Ramesh, Prasanna Sattigeri, Alex Hernández-García, Campbell D. Watson, Daniela Szwarcman, David S. Rolnick
2022	J	`jnl`	Tropical Cyclone Intensity Estimation Using Himawari-8 Satellite Cloud Products and Deep Learning. Remote. Sens. Jinkai Tan, Qidong Yang, Junjun Hu, Qiqiao Huang, Sheng Chen
2018	J	`jnl`	Multimodal Emotion Recognition Method Based on Convolutional Auto-Encoder. Int. J. Comput. Intell. Syst. Zhou Jian, Xianwei Wei, Chunling Cheng, Qidong Yang, Qun Li

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.