Yan Han - RankMe

34 papers A* 4A 2Misc 2Journal 21Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Rethinking the Value of Multi-Agent Workflow: A Strong Single Agent Baseline. CoRR Jiawei Xu, Arief Koesdwiady, Sisong Bei, Yan Han, Baixiang Huang, Dakuo Wang, Yutong Chen, Zheshen Wang, Peihao Wang, Pan Li, Ying Ding
2025	J	`jnl`	Beyond Believability: Accurate Human Behavior Simulation with Fine-Tuned LLMs. CoRR Yuxuan Lu, Jing Huang, Yan Han, Bennet Bei, Yaochen Xie, Dakuo Wang, Zheshen Jessie Wang, Qi He
2025	—	`conf`	Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models. ACL (Findings) Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei Dai, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He
2025	J	`jnl`	Stepwise Perplexity-Guided Refinement for Efficient Chain-of-Thought Reasoning in Large Language Models. CoRR Yingqian Cui, Pengfei He, Jingying Zeng, Hui Liu, Xianfeng Tang, Zhenwei Dai, Yan Han, Chen Luo, Jing Huang, Zheng Li, Suhang Wang, Yue Xing, Jiliang Tang, Qi He
2025	J	`jnl`	WEBSERV: A Browser-Server Environment for Efficient Training of Reinforcement Learning-based Web Agents at Scale. CoRR Yuxuan Lu, Jing Huang, Hui Liu, Jiri Gesi, Yan Han, Shihan Fu, Tianqi Zheng, Dakuo Wang
2024	J	`jnl`	A Survey of Calibration Process for Black-Box LLMs. CoRR Liangru Xie, Hui Liu, Jingying Zeng, Xianfeng Tang, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Qi He
2024	—	`conf`	Turning A Curse into A Blessing: Data-Aware Memory-Efficient Training of Graph Neural Networks by Dynamic Exiting. WWW (Companion Volume) Yan Han, Kaiqi Chen, Shan Li, Ji Yan, Baoxu Shi, Lei Zhang, Fei Chen, Jaewon Yang, Yunpeng Xu, Xiaoqiang Luo, Qi He, Ying Ding, Zhangyang Wang
2023	J	`jnl`	Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs. IEEE Data Eng. Bull. Yan Han, Yuning You, Wenqing Zheng, Scott Hoang, Tianxin Wei, Majdi Hassan, Tianlong Chen, Ying Ding, Yang Shen, Zhangyang Wang
2023	A*	`conf`	Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. NeurIPS Haotao Wang, Ziyu Jiang, Yuning You, Yan Han, Gaowen Liu, Jayanth Srinivasa, Ramana Kompella, Zhangyang Wang
2023	J	`jnl`	Graph Mixture of Experts: Learning on Large-Scale Graphs with Explicit Diversity Modeling. CoRR Haotao Wang, Ziyu Jiang, Yan Han, Zhangyang Wang
2023	A*	`conf`	PINAT: A Permutation INvariance Augmented Transformer for NAS Predictor. AAAI Shun Lu, Yu Hu, Peihao Wang, Yan Han, Jianchao Tan, Jixiang Li, Sen Yang, Ji Liu
2023	J	`jnl`	Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays. IEEE Trans. Medical Imaging Yan Han, Gregory Holste, Ying Ding, Ahmed H. Tewfik, Yifan Peng, Zhangyang Wang
2023	A	`conf`	Search Behavior Prediction: A Hypergraph Perspective. WSDM Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian
2023	A*	`conf`	Vision HGNN: An Image is More than a Graph of Nodes. ICCV Yan Han, Peihao Wang, Souvik Kundu, Ying Ding, Zhangyang Wang
2022	A	`conf`	Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop. WACV Yan Han, Chongyan Chen, Ahmed H. Tewfik, Benjamin S. Glicksberg, Ying Ding, Yifan Peng, Zhangyang Wang
2022	J	`jnl`	Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays. CoRR Yan Han, Gregory Holste, Ying Ding, Ahmed H. Tewfik, Yifan Peng, Zhangyang Wang
2022	J	`jnl`	Search Behavior Prediction: A Hypergraph Perspective. CoRR Yan Han, Edward W. Huang, Wenqing Zheng, Nikhil Rao, Zhangyang Wang, Karthik Subbian
2021	J	`jnl`	Cross-Modal Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop. CoRR Yan Han, Chongyan Chen, Ahmed H. Tewfik, Benjamin S. Glicksberg, Ying Ding, Yifan Peng, Zhangyang Wang
2021	—	`conf`	Pneumonia Detection On Chest X-Ray Using Radiomic Features And Contrastive Learning. ISBI Yan Han, Chongyan Chen, Ahmed H. Tewfik, Ying Ding, Yifan Peng
2021	J	`jnl`	Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning. CoRR Yan Han, Chongyan Chen, Ahmed H. Tewfik, Ying Ding, Yifan Peng
2021	A*	`conf`	SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. ICDM Ajay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin F. Rousseau, Yifan Peng, Ying Ding
2021	J	`jnl`	SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. CoRR Ajay Jaiswal, Tianhao Li, Cyprian Zander, Yan Han, Justin F. Rousseau, Yifan Peng, Ying Ding
2021	Misc	`conf`	Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays. AMIA Yan Han, Chongyan Chen, Liyan Tang, Mingquan Lin, Ajay Jaiswal, Song Wang, Ahmed H. Tewfik, George Shih, Ying Ding, Yifan Peng
2020	—	`conf`	Generating EEG features from Acoustic features. EUSIPCO Gautam Krishna, Co Tran, Mason Carnahan, Yan Han, Ahmed H. Tewfik
2020	J	`jnl`	Generating EEG features from Acoustic features. CoRR Gautam Krishna, Co Tran, Mason Carnahan, Yan Han, Ahmed H. Tewfik
2020	—	`conf`	Robust End-to-End Speaker Verification Using EEG. EUSIPCO Yan Han, Gautam Krishna, Co Tran, Mason Carnahan, Ahmed H. Tewfik
2020	Misc	`conf`	Speech Synthesis Using EEG. ICASSP Gautam Krishna, Co Tran, Yan Han, Mason Carnahan, Ahmed H. Tewfik
2020	J	`jnl`	Using Radiomics as Prior Knowledge for Abnormality Classification and Localization in Chest X-rays. CoRR Yan Han, Chongyan Chen, Liyan Tang, Mingquan Lin, Ajay Jaiswal, Ying Ding, Yifan Peng
2019	J	`jnl`	Improving EEG based Continuous Speech Recognition. CoRR Gautam Krishna, Co Tran, Mason Carnahan, Yan Han, Ahmed H. Tewfik
2019	J	`jnl`	Robust End to End Speaker Verification Using EEG. CoRR Yan Han, Gautam Krishna, Co Tran, Mason Carnahan, Ahmed H. Tewfik
2019	J	`jnl`	Speech Recognition With No Speech Or With Noisy Speech Beyond English. CoRR Gautam Krishna, Co Tran, Yan Han, Mason Carnahan, Ahmed H. Tewfik
2019	J	`jnl`	Spoken Speech Enhancement using EEG. CoRR Gautam Krishna, Yan Han, Co Tran, Mason Carnahan, Ahmed H. Tewfik
2019	J	`jnl`	State-of-the-art Speech Recognition using EEG and Towards Decoding of Speech Spectrum From EEG. CoRR Gautam Krishna, Yan Han, Co Tran, Mason Carnahan, Ahmed H. Tewfik
2019	J	`jnl`	Voice Activity Detection in presence of background noise using EEG. CoRR Gautam Krishna, Co Tran, Yan Han, Mason Carnahan, Ahmed H. Tewfik

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.