Uday Singh Saini

31 papers A* 5A 3B 5Journal 15Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	TREASURE: A Transformer-Based Foundation Model for High-Volume Transaction Understanding. KDD (1) Chin-Chia Michael Yeh, Uday Singh Saini, Xin Dai, Xiran Fan, Shubham Jain, Yujie Fan, Jiarui Sun, Junpeng Wang, Menghai Pan, Yingtong Dou, Yuzhong Chen, Vineeth Rakesh, Liang Wang, Yan Zheng, Mahashweta Das
2025	—	`conf`	A Case Study of Low Ranked Self-Expressive Structures in Neural Network Representations. CPAL Uday Singh Saini, William Shiao, Yahya Sattar, Yogesh Dahiya, Samet Oymak, Evangelos E. Papalexakis
2025	J	`jnl`	A Compact Model for Large-Scale Time Series Forecasting. CoRR Chin-Chia Michael Yeh, Xiran Fan, Zhimeng Jiang, Yujie Fan, Huiyuan Chen, Uday Singh Saini, Vivian Lai, Xin Dai, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Yan Zheng
2025	B	`conf`	EiFormer: Improving Inverted Transformers for Efficient Time Series Forecasting in Large-Scale Spatial-Temporal Data. IEEE Big Data Jiarui Sun, Chin-Chia Michael Yeh, Yujie Fan, Xin Dai, Xiran Fan, Zhimeng Jiang, Uday Singh Saini, Vivian Lai, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Yan Zheng, Girish Chowdhary
2025	B	`conf`	Empowering Time Series Forecasting with LLM-Agents. IEEE Big Data Chin-Chia Michael Yeh, Vivian Lai, Uday Singh Saini, Xiran Fan, Yujie Fan, Junpeng Wang, Xin Dai, Yan Zheng
2025	J	`jnl`	Empowering Time Series Forecasting with LLM-Agents. CoRR Chin-Chia Michael Yeh, Vivian Lai, Uday Singh Saini, Xiran Fan, Yujie Fan, Junpeng Wang, Xin Dai, Yan Zheng
2025	J	`jnl`	TREASURE: A Transformer-Based Foundation Model for High-Volume Transaction Understanding. CoRR Chin-Chia Michael Yeh, Uday Singh Saini, Xin Dai, Xiran Fan, Shubham Jain, Yujie Fan, Jiarui Sun, Junpeng Wang, Menghai Pan, Yingtong Dou, Yuzhong Chen, Vineeth Rakesh, Liang Wang, Yan Zheng, Mahashweta Das
2025	J	`jnl`	TiCT: A Synthetically Pre-Trained Foundation Model for Time Series Classification. CoRR Chin-Chia Michael Yeh, Uday Singh Saini, Junpeng Wang, Xin Dai, Xiran Fan, Jiarui Sun, Yujie Fan, Yan Zheng
2025	J	`jnl`	Towards Efficient Large Scale Spatial-Temporal Time Series Forecasting via Improved Inverted Transformers. CoRR Jiarui Sun, Chin-Chia Michael Yeh, Yujie Fan, Xin Dai, Xiran Fan, Zhimeng Jiang, Uday Singh Saini, Vivian Lai, Junpeng Wang, Huiyuan Chen, Zhongfang Zhuang, Yan Zheng, Girish Chowdhary
2025	J	`jnl`	TransactionGPT. CoRR Yingtong Dou, Zhimeng Jiang, Tianyi Zhang, Mingzhi Hu, Zhichao Xu, Shubham Jain, Uday Singh Saini, Xiran Fan, Jiarui Sun, Menghai Pan, Junpeng Wang, Xin Dai, Liang Wang, Chin-Chia Michael Yeh, Yujie Fan, Vineeth Rakesh, Huiyuan Chen, Mangesh Bendre, Zhongfang Zhuang, Xiaoting Li, Prince Osei Aboagye, Vivian Lai, Minghua Xu, Hao Yang, Yiwei Cai, Mahashweta Das, Yuzhong Chen
2025	B	`conf`	UltraSTF: Ultra-Compact Model for Large-Scale Spatio-Temporal Forecasting. IEEE Big Data Chin-Chia Michael Yeh, Xiran Fan, Zhimeng Jiang, Yujie Fan, Huiyuan Chen, Uday Singh Saini, Vivian Lai, Xin Dai, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Yan Zheng
2025	B	`conf`	Visual Attention Exploration in Vision-Based Mamba Models. PacificVis Junpeng Wang, Chin-Chia Michael Yeh, Uday Singh Saini, Mahashweta Das
2025	J	`jnl`	Visual Attention Exploration in Vision-Based Mamba Models. CoRR Junpeng Wang, Chin-Chia Michael Yeh, Uday Singh Saini, Mahashweta Das
2024	A	`conf`	Analysis of Causal and Non-Causal Convolution Networks for Time Series Classification. SDM Uday Singh Saini, Zhongfang Zhuang, Chin-Chia Michael Yeh, Wei Zhang, Evangelos E. Papalexakis
2024	J	`jnl`	Has Your Pretrained Model Improved? A Multi-head Posterior Based Approach. CoRR Prince Osei Aboagye, Yan Zheng, Junpeng Wang, Uday Singh Saini, Xin Dai, Chin-Chia Michael Yeh, Yujie Fan, Zhongfang Zhuang, Shubham Jain, Liang Wang, Wei Zhang
2024	A*	`conf`	Matrix Profile for Anomaly Detection on Multidimensional Time Series. ICDM Chin-Chia Michael Yeh, Audrey Der, Uday Singh Saini, Vivian Lai, Yan Zheng, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Yujie Fan, Huiyuan Chen, Prince Osei Aboagye, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	J	`jnl`	Matrix Profile for Anomaly Detection on Multidimensional Time Series. CoRR Chin-Chia Michael Yeh, Audrey Der, Uday Singh Saini, Vivian Lai, Yan Zheng, Junpeng Wang, Xin Dai, Zhongfang Zhuang, Yujie Fan, Huiyuan Chen, Prince Osei Aboagye, Liang Wang, Wei Zhang, Eamonn J. Keogh
2024	A	`conf`	Neural Additive Tensor Decomposition for Sparse Tensors. CIKM Dawon Ahn, Uday Singh Saini, Evangelos E. Papalexakis, Ali Payani
2024	J	`jnl`	Preserving Individuality while Following the Crowd: Understanding the Role of User Taste and Crowd Wisdom in Online Product Rating Prediction. CoRR Liang Wang, Shubham Jain, Yingtong Dou, Junpeng Wang, Chin-Chia Michael Yeh, Yujie Fan, Prince Osei Aboagye, Yan Zheng, Xin Dai, Zhongfang Zhuang, Uday Singh Saini, Wei Zhang
2024	A*	`conf`	RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data. KDD Chin-Chia Michael Yeh, Yujie Fan, Xin Dai, Uday Singh Saini, Vivian Lai, Prince Osei Aboagye, Junpeng Wang, Huiyuan Chen, Yan Zheng, Zhongfang Zhuang, Liang Wang, Wei Zhang
2023	A*	`conf`	CARL-G: Clustering-Accelerated Representation Learning on Graphs. KDD William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis
2023	J	`jnl`	CARL-G: Clustering-Accelerated Representation Learning on Graphs. CoRR William Shiao, Uday Singh Saini, Yozen Liu, Tong Zhao, Neil Shah, Evangelos E. Papalexakis
2023	A	`conf`	Harvester: Principled Factorization-based Temporal Tensor Granularity Estimation. SDM Ravdeep S. Pasricha, Uday Singh Saini, Nicholas D. Sidiropoulos, Fei Fang, Kevin Chan, Evangelos E. Papalexakis
2022	B	`conf`	Multi-aspect Matrix Factorization based Visualization of Convolutional Neural Networks. DSAA Uday Singh Saini, Evangelos E. Papalexakis
2022	A*	`conf`	TENALIGN: Joint Tensor Alignment and Coupled Factorization. ICDM Yunshu Wu, Uday Singh Saini, Jia Chen, Evangelos E. Papalexakis
2021	—	`conf`	Subspace Clustering Based Analysis of Neural Networks. ECML/PKDD (3) Uday Singh Saini, Pravallika Devineni, Evangelos E. Papalexakis
2021	J	`jnl`	Subspace Clustering Based Analysis of Neural Networks. CoRR Uday Singh Saini, Pravallika Devineni, Evangelos E. Papalexakis
2020	J	`jnl`	Analyzing Representations inside Convolutional Neural Networks. CoRR Uday Singh Saini, Evangelos E. Papalexakis
2018	J	`jnl`	A Peek Into the Hidden Layers of a Convolutional Neural Network Through a Factorization Lens. CoRR Uday Singh Saini, Evangelos E. Papalexakis
2016	A*	`conf`	Relation Schema Induction using Tensor Factorization with Side Information. EMNLP Madhav Nimishakavi, Uday Singh Saini, Partha P. Talukdar
2016	J	`jnl`	Relation Schema Induction using Tensor Factorization with Side Information. CoRR Madhav Nimishakavi, Uday Singh Saini, Partha P. Talukdar

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.