Sagar Verma - RankMe

35 papers A* 4A 2B 3C 5Misc 1Journal 14Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Wavelet based numerical method for Abel inversion. J. Comput. Appl. Math. Sagar Verma, Sandeep Dixit
2025	A	`conf`	Constraint Discovery for Structured Generation via LLM-Guided SMT Inference. ICSME Hrishikesh Karmarkar, Supriya Agrawal, Siddhesh Pagar, Vaibhavi Joshi, Sagar Verma, Naman Paul
2025	J	`jnl`	Deterministic Suffix-reading Automata. CoRR R. Keerthan, B. Srivathsan, R. Venkatesh, Sagar Verma
2025	J	`jnl`	emg2tendon: From sEMG Signals to Tendon Control in Musculoskeletal Hands. CoRR Sagar Verma
2024	—	`conf`	Deterministic Suffix-reading Automata. GandALF R. Keerthan, B. Srivathsan, R. Venkatesh, Sagar Verma
2023	—	`conf`	1 WACV (Workshops) Benjamin Kiefer, Matej Kristan, Janez Pers, Lojze Zust, Fabio Poiesi, Fabio Augusto de Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Höfer, Qiming Zhang, Yufei Xu, Jing Zhang, Dacheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtech Bartl, Jakub Spanhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang Song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Ziqiang Zheng, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang
2023	J	`jnl`	CertViT: Certified Robustness of Pre-Trained Vision Transformers. CoRR Kavya Gupta, Sagar Verma
2023	—	`—`	Deep Neural Network Modeling of Electric Motors. (Modélisation, contrôle et supervision de moteurs électriques par réseaux de neurones profonds). Sagar Verma
2023	C	`conf`	Have Foundational Models Seen Satellite Images? IGARSS Akash Panigrahi, Sagar Verma, Matthieu Terris, Maria Vakalopoulou
2023	C	`conf`	Investigating Model Robustness Against Sensor Variation. IGARSS Matthieu Terris, Sagar Verma
2023	J	`jnl`	Neural Speed-Torque Estimator for Induction Motors in the Presence of Measurement Noise. IEEE Trans. Ind. Electron. Sagar Verma, Nicolas Henwood, Marc Castella, Al Kassem Jebai, Jean-Christophe Pesquet
2023	—	`conf`	Post Wildfire Burnt-up Detection Using Siamese UNet. PKDD/ECML Workshops (5) Sagar Verma, Kavya Gupta
2022	J	`jnl`	1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results. CoRR Benjamin Kiefer, Matej Kristan, Janez Pers, Lojze Zust, Fabio Poiesi, Fabio Augusto de Alcantara Andrade, Alexandre Bernardino, Matthew Dawkins, Jenni Raitoharju, Yitong Quan, Adem Atmaca, Timon Höfer, Qiming Zhang, Yufei Xu, Jing Zhang, Dacheng Tao, Lars Sommer, Raphael Spraul, Hangyue Zhao, Hongpu Zhang, Yanyun Zhao, Jan Lukas Augustin, Eui-ik Jeon, Impyeong Lee, Luca Zedda, Andrea Loddo, Cecilia Di Ruberto, Sagar Verma, Siddharth Gupta, Shishir Muralidhara, Niharika Hegde, Daitao Xing, Nikolaos Evangeliou, Anthony Tzes, Vojtech Bartl, Jakub Spanhel, Adam Herout, Neelanjan Bhowmik, Toby P. Breckon, Shivanand Kundargi, Tejas Anvekar, Chaitra Desai, Ramesh Ashok Tabib, Uma Mudengudi, Arpita Vats, Yang Song, Delong Liu, Yonglin Li, Shuman Li, Chenhao Tan, Long Lan, Vladimir Somers, Christophe De Vleeschouwer, Alexandre Alahi, Hsiang-Wei Huang, Cheng-Yen Yang, Jenq-Neng Hwang, Pyong-Kun Kim, Kwangju Kim, Kyoungoh Lee, Shuai Jiang, Haiwen Li, Ziqiang Zheng, Tuan-Anh Vu, Hai Nguyen-Truong, Sai-Kit Yeung, Zhuang Jia, Sophia Yang, Chih-Chung Hsu, Xiu-Yu Hou, Yu-An Jhang, Simon Yang, Mau-Tsuen Yang
2022	C	`conf`	Europa: Increasing Accessibility of Geospatial Datasets. IGARSS Hal Shin, Natanael Exe, Ujwal Dutta, Tanka Raj Joshi, Sagar Verma, Siddharth Gupta
2022	A*	`conf`	GeoEngine: A Platform for Production-Ready Geospatial Research. CVPR Sagar Verma, Siddharth Gupta, Hal Shin, Akash Panigrahi, Shubham Goswami, Shweta Pardeshi, Natanael Exe, Ujwal Dutta, Tanka Raj Joshi, Nitin Bhojwani
2021	A*	`conf`	EImprove - Optimizing Energy and Comfort in Buildings based on Formal Semantics and Reinforcement Learning. DAC Sagar Verma, Supriya Agrawal, R. Venkatesh, Ulka Shrotri, Srinarayana Nagarathinam, Rajesh Jayaprakash, Aabriti Dutta
2021	—	`conf`	QFabric: Multi-Task Change Detection Dataset. CVPR Workshops Sagar Verma, Akash Panigrahi, Siddharth Gupta
2021	A*	`conf`	Sparsifying Networks via Subdifferential Inclusion. ICML Sagar Verma, Jean-Christophe Pesquet
2020	A*	`conf`	Modeling Electrical Motor Dynamics Using Encoder-Decoder with Recurrent Skip Connection. AAAI Sagar Verma, Nicolas Henwood, Marc Castella, François Malrait, Jean-Christophe Pesquet
2020	J	`jnl`	Modeling Electrical Motor Dynamics using Encoder-Decoder with Recurrent Skip Connection. CoRR Sagar Verma, Nicolas Henwood, Marc Castella, François Malrait, Jean-Christophe Pesquet
2020	C	`conf`	Neural Networks based Speed-Torque Estimators for Induction Motors and Performance Metrics. IECON Sagar Verma, Nicolas Henwood, Marc Castella, Al Kassem Jebai, Jean-Christophe Pesquet
2020	A	`conf`	Scaling Test Case Generation For Expressive Decision Tables. ICST Supriya Agrawal, R. Venkatesh, Ulka Shrotri, Amey Zare, Sagar Verma
2019	J	`jnl`	Collaborative Filtering with Label Consistent Restricted Boltzmann Machine. CoRR Sagar Verma, Prince Patel, Angshul Majumdar
2019	C	`conf`	Detecting Urban Changes with Recurrent Neural Networks from Multitemporal Sentinel-2 Data. IGARSS Maria Papadomanolaki, Sagar Verma, Maria Vakalopoulou, Siddharth Gupta, Konstantinos Karantzalos
2019	J	`jnl`	Detecting Urban Changes with Recurrent Neural Networks from Multitemporal Sentinel-2 Data. CoRR Maria Papadomanolaki, Sagar Verma, Maria Vakalopoulou, Siddharth Gupta, Konstantinos Karantzalos
2019	J	`jnl`	Diversity in Fashion Recommendation using Semantic Parsing. CoRR Sagar Verma, Sukhad Anand, Chetan Arora, Atul Rai
2019	B	`conf`	MAPEL: Multi-Agent Pursuer-Evader Learning using Situation Report. IJCNN Sagar Verma, Richa Verma, P. B. Sujit
2019	J	`jnl`	MAPEL: Multi-Agent Pursuer-Evader Learning using Situation Report. CoRR Sagar Verma, Richa Verma, P. B. Sujit
2019	J	`jnl`	Making Third Person Techniques Recognize First-Person Actions in Egocentric Videos. CoRR Sagar Verma, Pravin Nagar, Divam Gupta, Chetan Arora
2019	J	`jnl`	Multi Label Restricted Boltzmann Machine for Non-Intrusive Load Monitoring. CoRR Sagar Verma, Shikha Singh, Angshul Majumdar
2019	Misc	`conf`	Multi Label Restricted Boltzmann Machine for Non-intrusive Load Monitoring. ICASSP Sagar Verma, Shikha Singh, Angshul Majumdar
2018	B	`conf`	Diversity in Fashion Recommendation Using Semantic Parsing. ICIP Sagar Verma, Sukhad Anand, Chetan Arora, Atul Rai
2018	B	`conf`	Making Third Person Techniques Recognize First-Person Actions in Egocentric Videos. ICIP Sagar Verma, Pravin Nagar, Divam Gupta, Chetan Arora
2018	J	`jnl`	Tooling Framework for Instantiating Natural Language Querying System. Proc. VLDB Endow. Manasa Jammi, Jaydeep Sen, Ashish R. Mittal, Sagar Verma, Vardaan Pahuja, Rema Ananthanarayanan, Pranay Lohia, Hima Karanam, Diptikalyan Saha, Karthik Sankaranarayanan
2017	—	`conf`	Collaborative Filtering with Label Consistent Restricted Boltzmann Machine. ICAPR Sagar Verma, Prince Patel, Angshul Majumdar

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.