Rajat K. De - RankMe

82 papers A 1B 2C 1Journal 58Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	G-NeuroDAVIS: A generative model for data visualization through a generalized embedding. Neural Networks Chayan Maitra, Rajat K. De
2026	J	`jnl`	Integrating state-space modeling, parameter estimation, deep learning, and docking techniques in drug repurposing: a case study on COVID-19 cytokine storm. J. Am. Medical Informatics Assoc. Abhisek Bakshi, Kaustav Gangopadhyay, Sujit Basak, Rajat K. De, Souvik Sengupta, Abhijit Dasgupta
2026	J	`jnl`	TiMePReSt: Time and memory efficient pipeline parallel DNN training with removed staleness. Future Gener. Comput. Syst. Ankita Dutta, Nabendu Chaki, Rajat K. De
2025	—	`ed.`	Applied Algorithms - Second International Conference, ICAA 2025, Kolkata, India, January 8-10, 2025, Proceedings ICAA Subhas C. Nandy, Rajat K. De, Prosenjit Gupta
2025	J	`jnl`	CMET: Clustering guided METric for quantifying embedding quality. CoRR Sourav Ghosh, Chayan Maitra, Rajat K. De
2025	J	`jnl`	Efficient parameter estimation in biochemical pathways: Overcoming data limitations with constrained regularization and fuzzy inference. Expert Syst. Appl. Abhisek Bakshi, Souvik Sengupta, Rajat K. De, Abhijit Dasgupta
2025	J	`jnl`	Forward-Cooperation-Backward (FCB) learning in a Multi-Encoding Uni-Decoding neural network architecture. CoRR Prasun Dutta, Koustab Ghosh, Rajat K. De
2025	J	`jnl`	Memory Efficient and Staleness Free Pipeline Parallel DNN Training Framework with Improved Convergence Speed. CoRR Ankita Dutta, Nabendu Chaki, Rajat K. De
2024	J	`jnl`	A Game-Theoretic Approach to Privacy-Utility Tradeoff in Sharing Genomic Summary Statistics. CoRR Tao Zhang, Rajagopal Venkatesaramani, Rajat K. De, Bradley A. Malin, Yevgeniy Vorobeychik
2024	J	`jnl`	Bayes-Nash Generative Privacy Protection Against Membership Inference Attacks. CoRR Tao Zhang, Rajagopal Venkatesaramani, Rajat K. De, Bradley A. Malin, Yevgeniy Vorobeychik
2024	J	`jnl`	DN3MF: deep neural network for non-negative matrix factorization towards low rank approximation. Pattern Anal. Appl. Prasun Dutta, Rajat K. De
2024	J	`jnl`	ENLIGHTENMENT: A Scalable Annotated Database of Genomics and NGS-Based Nucleotide Level Profiles. IEEE ACM Trans. Comput. Biol. Bioinform. Rituparna Sinha, Rajat Kumar Pal, Rajat K. De
2024	J	`jnl`	G-NeuroDAVIS: A Neural Network model for generalized embedding, data visualization and sample generation. CoRR Chayan Maitra, Rajat K. De
2024	J	`jnl`	Input Guided Multiple Deconstruction Single Reconstruction neural network models for Matrix Factorization. CoRR Prasun Dutta, Rajat K. De
2024	—	`conf`	NeuroDAVIS-FS: Feature Selection Through Visualization Using NeuroDAVIS. ICPR (26) Chayan Maitra, Anwesha Sengupta, Rajat K. De
2024	J	`jnl`	NeuroDAVIS: A neural network model for data visualization. Neurocomputing Chayan Maitra, Dibyendu Bikash Seal, Rajat K. De
2024	J	`jnl`	TiMePReSt: Time and Memory Efficient Pipeline Parallel DNN Training with Removed Staleness. CoRR Ankita Dutta, Nabendu Chaki, Rajat K. De
2023	J	`jnl`	CASSL: A cell-type annotation method for single cell transcriptomics data using semi-supervised learning. Appl. Intell. Dibyendu Bikash Seal, Vivek Das, Rajat K. De
2023	J	`jnl`	NeuroDAVIS: A neural network model for data visualization. CoRR Chayan Maitra, Dibyendu Bikash Seal, Rajat K. De
2023	—	`ed.`	Pattern Recognition and Machine Intelligence - 10th International Conference, PReMI 2023, Kolkata, India, December 12-15, 2023, Proceedings PReMI Pradipta Maji, Tingwen Huang, Nikhil R. Pal, Santanu Chaudhury, Rajat K. De
2023	—	`conf`	UMINT-FS: UMINT-guided Feature Selection for multi-omics datasets. BIBM Chayan Maitra, Dibyendu Bikash Seal, Vivek Das, Yevgeniy Vorobeychik, Rajat K. De
2022	J	`jnl`	Block Search Stochastic Simulation Algorithm (BlSSSA): A Fast Stochastic Simulation Algorithm for Modeling Large Biochemical Networks. IEEE ACM Trans. Comput. Biol. Bioinform. Debraj Ghosh, Rajat K. De
2022	J	`jnl`	Epidemiological challenges in pandemic coronavirus disease (COVID-19): Role of artificial intelligence. WIREs Data Mining Knowl. Discov. Abhijit Dasgupta, Abhisek Bakshi, Srijani Mukherjee, Kuntal Das, Soumyajeet Talukdar, Pratyayee Chatterjee, Sagnik Mondal, Puspita Das, Subhrojit Ghosh, Archisman Som, Pritha Roy, Rima Kundu, Akash Sarkar, Arnab Biswas, Karnelia Paul, Sujit Basak, Krishnendu Manna, Chinmay Saha, Satinath Mukhopadhyay, Nitai P. Bhattacharyya, Rajat K. De
2022	J	`jnl`	GenSeg and MR-GenSeg: A Novel Segmentation Algorithm and its Parallel MapReduce Based Approach for Identifying Genomic Regions With Copy Number Variations. IEEE ACM Trans. Comput. Biol. Bioinform. Rituparna Sinha, Rajat Kumar Pal, Rajat K. De
2022	—	`conf`	scARMF: Association Rule Mining-based feature selection Framework for Single-Cell transcriptomics data. BIBM Dibyendu Bikash Seal, Vivek Das, Rajat K. De
2020	J	`jnl`	ASAPP: Architectural Similarity-Based Automated Pathway Prediction System and Its Application in Host-Pathogen Interactions. IEEE ACM Trans. Comput. Biol. Bioinform. Rishika Sen, Somnath Tagore, Rajat K. De
2020	J	`jnl`	Metabolic pathway engineering: Perspectives and applications. Comput. Methods Programs Biomed. Abhijit Dasgupta, Nirmalya Chowdhury, Rajat K. De
2020	J	`jnl`	Pattern and Rule Mining for Identifying Signatures of Epileptic Patients from Clinical EEG Data. Fundam. Informaticae Abhijit Dasgupta, Losiana Nayak, Ritankar Das, Debasis Basu, Preetam Chandra, Rajat K. De
2019	J	`jnl`	A Model for Distributed Processing and Analyses of NGS Data under Map-Reduce Paradigm. IEEE ACM Trans. Comput. Biol. Bioinform. Sandip Samaddar, Rituparna Sinha, Rajat K. De
2019	J	`jnl`	Cluster Quality based Non-Reductional (CQNR) oversampling technique and effector protein predictor based on 3D structure (EPP3D) of proteins. Comput. Biol. Medicine Rishika Sen, Somnath Tagore, Rajat K. De
2019	J	`jnl`	PyPredT6: A python-based prediction tool for identification of Type VI effector proteins. J. Bioinform. Comput. Biol. Rishika Sen, Losiana Nayak, Rajat K. De
2019	—	`conf`	Two-Class in Silico Categorization of Intermediate Epileptic EEG Data. PReMI (2) Abhijit Dasgupta, Ritankar Das, Losiana Nayak, Ashis Datta, Rajat K. De
2018	J	`jnl`	Succinate aggravates NAFLD progression to liver cancer on the onset of obesity: An J. Bioinform. Comput. Biol. Indrani Ray, Abhijit Dasgupta, Rajat K. De
2017	—	`conf`	Feature Selection and Fuzzy Rule Mining for Epileptic Patients from Clinical EEG Data. PReMI Abhijit Dasgupta, Losiana Nayak, Ritankar Das, Debasis Basu, Preetam Chandra, Rajat K. De
2017	J	`jnl`	OCDD: an obesity and co-morbid disease database. BioData Min. Indrani Ray, Anindya Bhattacharya, Rajat K. De
2017	J	`jnl`	Slow update stochastic simulation algorithms for modeling complex biochemical networks. Biosyst. Debraj Ghosh, Rajat K. De
2016	J	`jnl`	Fuzzy Correlated Association Mining: Selecting altered associations among the genes, and some possible marker genes mediating certain cancers. Appl. Soft Comput. Anupam Ghosh, Rajat K. De
2016	J	`jnl`	Wnt signal transduction pathways: modules, development and evolution. BMC Syst. Biol. Losiana Nayak, Nitai P. Bhattacharyya, Rajat K. De
2015	—	`conf`	A module tree of Wnt signal transduction pathways. BIBM Losiana Nayak, Nitai P. Bhattacharyya, Rajat K. De
2015	—	`conf`	Analyzing epileptogenic brain connectivity networks using clinical EEG data. BIBM Abhijit Dasgupta, Ritankar Das, Losiana Nayak, Rajat K. De
2015	J	`jnl`	Concepts of relative sample outlier (RSO) and weighted sample similarity (WSS) for improving performance of clustering genes: co-function and co-regulation. Int. J. Data Min. Bioinform. Anindya Bhattacharya, Nirmalya Chowdhury, Rajat K. De
2015	J	`jnl`	Evolutionary growth of certain metabolic pathways involved in the functioning of GAD and INS genes in Type 1 Diabetes Mellitus: Their architecture and stability. Comput. Biol. Medicine Somnath Tagore, Rajat K. De
2014	J	`jnl`	Development of a fuzzy entropy based method for detecting altered gene-gene interactions in carcinogenic state. J. Intell. Fuzzy Syst. Anupam Ghosh, Rajat K. De
2014	J	`jnl`	Selection of genes mediating certain cancers, using a neuro-fuzzy approach. Neurocomputing Anupam Ghosh, Bibhas Chandra Dhara, Rajat K. De
2013	J	`jnl`	An Optimization Rule for In Silico Identification of Targeted Overproduction in Metabolic Pathways. IEEE ACM Trans. Comput. Biol. Bioinform. Mouli Das, C. A. Murthy, Rajat K. De
2013	—	`conf`	Gaussian Fuzzy Index (GFI) for Cluster Validation: Identification of High Quality Biologically Enriched Clusters of Genes and Selection of Some Possible Genes Mediating Lung Cancer. PReMI Anupam Ghosh, Rajat K. De
2012	—	`conf`	A Second-Order Learning Algorithm for Computing Optimal Regulatory Pathways. PerMIn Mouli Das, C. A. Murthy, Subhasis Mukhopadhyay, Rajat K. De
2012	J	`jnl`	Modeling the Optimal Central carbon metabolic pathways under Feedback Inhibition using flux Balance Analysis. J. Bioinform. Comput. Biol. Rajat K. De, Namrata Tomar
2011	—	`conf`	A Methodology for Handling a New Kind of Outliers Present in Gene Expression Patterns. PReMI Anindya Bhattacharya, Rajat K. De
2011	—	`conf`	A fuzzy entropy based approach for development of gene prediction networks (GPNs): detecting altered dependency in carcinogenic state. BCB Anupam Ghosh, Rajat K. De
2011	J	`jnl`	A novel noise handling method to improve clustering of gene expression patterns. BMC Bioinform. Anindya Bhattacharya, Rajat K. De
2011	J	`jnl`	Detecting breakdown points in metabolic networks. Comput. Biol. Chem. Somnath Tagore, Rajat K. De
2011	—	`conf`	Developmental Trend Derived from Modules of Wnt Signaling Pathways. PReMI Losiana Nayak, Rajat K. De
2011	—	`conf`	Neuro-fuzzy Methodology for Selecting Genes Mediating Lung Cancer. PReMI Rajat K. De, Anupam Ghosh
2010	J	`jnl`	Average correlation clustering algorithm (ACCA) for grouping of co-regulated genes with similar pattern of variation in their expression values. J. Biomed. Informatics Anindya Bhattacharya, Rajat K. De
2009	—	`conf`	A Constraint Based Method for Optimization in Metabolic Pathways. PReMI Mouli Das, Subhasis Mukhopadhyay, Rajat K. De
2009	J	`jnl`	Bi-correlation clustering algorithm for determining a set of co-regulated genes. Bioinform. Anindya Bhattacharya, Rajat K. De
2009	J	`jnl`	Interval based fuzzy systems for identification of important genes from microarray gene expression data: Application to carcinogenic development. J. Biomed. Informatics Rajat K. De, Anupam Ghosh
2009	J	`jnl`	Linguistic recognition system for identification of some possible genes mediating the development of lung adenocarcinoma. Inf. Fusion Rajat K. De, Anupam Ghosh
2008	B	`conf`	Determination of optimal metabolic pathways through a new learning algorithm. ICPR C. A. Murthy, Mouli Das, Rajat K. De, Subhasis Mukhopadhyay
2008	J	`jnl`	Divisive Correlation Clustering Algorithm (DCCA) for grouping of genes: detecting varying patterns in expression profiles. Bioinform. Anindya Bhattacharya, Rajat K. De
2008	J	`jnl`	Incorporation of enzyme concentrations into FBA and identification of optimal metabolic pathways. BMC Syst. Biol. Rajat K. De, Mouli Das, Subhasis Mukhopadhyay
2007	J	`jnl`	An algorithm for modularization of MAPK and calcium signaling pathways: Comparative analysis among different species. J. Biomed. Informatics Losiana Nayak, Rajat K. De
2007	—	`conf`	Identification of Gene Regulatory Pathways: A Regularization Method. PReMI Mouli Das, Rajat K. De, Subhasis Mukhopadhyay
2007	—	`ed.`	Pattern Recognition and Machine Intelligence, Second International Conference, PReMI 2007, Kolkata, India, December 18-22, 2007, Proceedings PReMI Ashish Ghosh, Rajat K. De, Sankar K. Pal
2006	B	`conf`	Connectionist Modelling of Dynamics of Gene Expression and Reverse Engineering Gene Regulatory Networks. IJCNN Rajat K. De, Kasturi Biswas
2006	J	`jnl`	Generation of Linguistic Rules on the Genes Mediating the Development of Lung Adenocarcinoma. Res. Comput. Sci. Anupam Ghosh, Rajat K. De
2006	C	`conf`	Identification of Over and Under Expressed Genes Mediating Allergic Asthma. IEA/AIE Rajat K. De, Anindya Bhattacharya
2005	A	`conf`	A hardware pipeline for function optimization using genetic algorithms. GECCO Malay Kumar Pakhira, Rajat K. De
2003	J	`jnl`	Extraction of Features Using M-Band Wavelet Packet Frame and Their Neuro-Fuzzy Evaluation for Multitexture Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. Mausumi Acharyya, Rajat K. De, Malay Kumar Kundu
2003	J	`jnl`	Segmentation of remotely sensed images using wavelet features and their evaluation in soft computing framework. IEEE Trans. Geosci. Remote. Sens. Mausumi Acharyya, Rajat K. De, Malay Kumar Kundu
2002	J	`jnl`	Unsupervised feature extraction using neuro-fuzzy approach. Fuzzy Sets Syst. Rajat K. De, Jayanta Basak, Sankar K. Pal
2001	J	`jnl`	A connectionist model for selection of cases. Inf. Sci. Rajat K. De, Sankar K. Pal
2001	—	`ch.`	Case Based Systems: A Neuro-Fuzzy Method for Selecting Cases. Soft Computing in Case Based Reasoning Rajat K. De, Sankar K. Pal
2000	J	`jnl`	Unsupervised feature evaluation: a neuro-fuzzy approach. IEEE Trans. Neural Networks Learn. Syst. Sankar K. Pal, Rajat K. De, Jayanta Basak
1999	J	`jnl`	Neuro-fuzzy feature evaluation with theoretical analysis. Neural Networks Rajat K. De, Jayanta Basak, Sankar K. Pal
1998	J	`jnl`	Fuzzy Feature Evaluation Index and Connectionist Realization - II. Theoretical Analysis. Inf. Sci. Jayanta Basak, Rajat K. De, Sankar K. Pal
1998	J	`jnl`	Fuzzy Feature Evaluation Index and Connectionist Realization. Inf. Sci. Sankar K. Pal, Jayanta Basak, Rajat K. De
1998	J	`jnl`	Unsupervised feature selection using a neuro-fuzzy approach. Pattern Recognit. Lett. Jayanta Basak, Rajat K. De, Sankar K. Pal
1997	J	`jnl`	Feature analysis: Neural network and fuzzy set theoretic approaches. Pattern Recognit. Rajat K. De, Nikhil R. Pal, Sankar K. Pal
1997	J	`jnl`	Knowledge-based fuzzy MLP for classification and rule generation. IEEE Trans. Neural Networks Sushmita Mitra, Rajat K. De, Sankar K. Pal
1996	—	`conf`	Feature selection: a neuro-fuzzy approach. ICNN Sankar K. Pal, Jayanta Basak, Rajat K. De

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.