Rajesh Wadhvani

19 papers C 1Journal 15Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Data complexity measures for classification of a multi-concept dataset. Multim. Tools Appl. Sowkarthika B., Manasi Gyanchandani, Rajesh Wadhvani, Sanyam Shukla
2025	J	`jnl`	Deep learning-based real-time diagnosis of cardiac diseases through behavioral changes in ECG signals. Biomed. Signal Process. Control. Muktesh Gupta, Rajesh Wadhvani, Akhtar Rasool
2025	J	`jnl`	Enhance differential privacy mechanisms for clinical data analysis using CNNs and reinforcement learning. J. Big Data Rakesh Batchala, Priyank Jain, Manasi Gyanchandani, Sanyam Shukla, Rajesh Wadhvani
2025	J	`jnl`	Handling heteroscedasticity in kernelized extreme learning machine based regression and deep learning models for traffic sign detection using box cox and Yeo Johnson transformations. Signal Image Video Process. Manali Chandnani, Sanyam Shukla, Rajesh Wadhvani
2024	—	`conf`	Comprehensive ECG Signal Analysis for Heart Disease Classification: Integrating Neural Networks with Random Forest. ICCCNT Akshita Gour, Rajesh Wadhvani, Muktesh Gupta
2024	J	`jnl`	Comprehensive analysis of change-point dynamics detection in time series data: A review. Expert Syst. Appl. Muktesh Gupta, Rajesh Wadhvani, Akhtar Rasool
2024	J	`jnl`	Multistage traffic sign recognition under harsh environment. Multim. Tools Appl. Manali Chandnani, Sanyam Shukla, Rajesh Wadhvani
2023	J	`jnl`	A real-time adaptive model for bearing fault classification and remaining useful life estimation using deep neural network. Knowl. Based Syst. Muktesh Gupta, Rajesh Wadhvani, Akhtar Rasool
2023	J	`jnl`	A residual ensemble learning approach for solar irradiance forecasting. Multim. Tools Appl. Banalaxmi Brahma, Rajesh Wadhvani
2023	J	`jnl`	Data complexity-based dynamic ensembling of SVMs in classification. Expert Syst. Appl. Sowkarthika B., Manasi Gyanchandani, Rajesh Wadhvani, Sanyam Shukla
2023	—	`conf`	ECG Based Heart Disease Classification: Advancement and Review of Techniques. ICMLDE Akshita Gour, Muktesh Gupta, Rajesh Wadhvani, Sanyam Shukla
2022	J	`jnl`	Real-time Change-Point Detection: A deep neural network-based adaptive approach for detecting changes in multivariate time series data. Expert Syst. Appl. Muktesh Gupta, Rajesh Wadhvani, Akhtar Rasool
2022	—	`conf`	Selective Review on Adaptive Normalization Techniques. WINS Vivek Panday, Rajesh Wadhvani, Manasi Gyanchandani
2022	J	`jnl`	Trend triplet based data clustering for eliminating nonlinear trend components of wind time series to improve the performance of statistical forecasting models. Multim. Tools Appl. Anil Kumar Kushwah, Rajesh Wadhvani
2022	J	`jnl`	Visualizing solar irradiance data in ArcGIS and forecasting based on a novel deep neural network mechanism. Multim. Tools Appl. Banalaxmi Brahma, Rajesh Wadhvani
2020	J	`jnl`	Solar Irradiance Forecasting Based on Deep Learning Methodologies and Multi-Site Data. Symmetry Banalaxmi Brahma, Rajesh Wadhvani
2019	J	`jnl`	An analysis of "A feature reduced intrusion detection system using ANN classifier" by Akashdeep et al. expert systems with applications (2017). Expert Syst. Appl. Trupti Chandak, Sanyam Shukla, Rajesh Wadhvani
2018	J	`jnl`	Dynamic selection of normalization techniques using data complexity measures. Expert Syst. Appl. Sukirty Jain, Sanyam Shukla, Rajesh Wadhvani
2017	C	`conf`	Comparative Analysis of Adaptive Filters for Predicting Wind-Power Generation (SLMS, NLMS, SGDLMS, WLMS, RLMS). ISDA Ashima Arora, Rajesh Wadhvani

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.