Dr.Vanajaroselin Chirchi

@dsatm.edu.in

Professor and Department of Information Science & Engineering
Dayanand Sagar Academy of Technology and Management,DSATM, Bengaluru

Dr.Vanajaroselin Chirchi


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https://researchid.co/vrchirchi

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Multidisciplinary, Biomedical Engineering
16

Scopus Publications

283

Scholar Citations

8

Scholar h-index

6

Scholar i10-index

Scopus Publications

  • Deep Learning-Driven Melanoma Detection: A Convolutional Neural Network-Based Classification Approach
    Vanajaroselin Chirchi, Emmanvelraj M. Chirchi, Sangeeta Uranakar, Pavani Cherukuru, S. N. Prajwala Simha, Khushi Chirchi
    Lecture Notes in Networks and Systems, 2026
  • Bio inspired optimization techniques for disease detection in deep learning systems
    A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah
    Scientific Reports, 2025
    Numerous contemporary computer-aided disease detection methodologies predominantly depend on feature engineering techniques; yet, they possess several drawbacks, including the presence of redundant features and excessive time consumption. Conventional feature engineering necessitates considerable manual effort, resulting in issues from superfluous features that diminish the model's performance potential. In contrast to recent effective deep-learning models, these may address these issues while concurrently obtaining and capturing intricate structures inside extensive medical image datasets. Deep learning models autonomously develop feature extraction abilities but require substantial computational resources and extensive datasets to yield significant abstraction methods. The dimensionality problem is a key challenge in healthcare research. Despite the hopeful advancements in illness identification with deep learning architectures in recent years, attaining high performance remains notably tough, particularly in scenarios with limited data or intricate feature spaces. This research endeavors to elucidate the integration of bio-inspired optimization techniques that improve disease diagnostics through deep learning models. The targeted feature selection of bio-inspired methods enhances computational efficiency and operational efficacy by minimizing model redundancy and computational costs, particularly when data availability is constrained. These algorithms employ natural selection and social behavior models to efficiently explore feature spaces, enhancing the robustness and generalizability of deep learning systems. This paper seeks to elucidate the efficacy of deep learning models in medical diagnostics by employing concepts and strategies derived from biological system ontologies, such as genetic algorithms, particle swarm optimization, ant colony optimization, artificial immune systems, and swarm intelligence. Bio-inspired methodologies have exhibited significant potential in addressing critical challenges in illness detection across many data types. It seeks to tackle the problem by creating bio-inspired optimization methods to enhance efficient and equitable deep learning for illness diagnosis. This work assists researchers in selecting the most effective bio-inspired algorithm for disease categorization, prediction, and the analysis of high-dimensional biomedical data.
  • Medical Image Fusion Using Unified Image Fusion Convolutional Neural Network
    Balasubramaniam S., Vanajaroselin Chirchi, Sivakumar T. A., Gururama Senthilvel P., Duraimutharasan N.
    International Journal of Intelligent Systems, 2025
    Medical image fusion (IF) is a process of registering and combining numerous images from multiple‐ or single‐imaging modalities to enhance image quality and lessen randomness as well as redundancy for increasing the clinical applicability of the medical images to diagnose and evaluate clinical issues. The information that is acquired additionally from fused images can be effectively employed for highly accurate positioning of abnormality. Since diverse kinds of images produce various information, IF becomes more complicated for conventional methods to generate fused images. Here, a unified image fusion convolutional neural network (UIFCNN) is designed for IF utilizing medical images. To execute the IF process, two input images, namely, native T1 and T2 fluid‐attenuated inversion recovery (T2‐FLAIR) are taken from a dataset. An input image‐T1 is preprocessed employing bilateral filter (BF), and it is segmented by a recurrent prototypical network (RP‐Net) to obtain segmented output‐1. Simultaneously, input image‐T2‐FLAIR is also preprocessed by BF and then segmented using RP‐Net to acquire segmented output‐2. The two segmented outputs are fused utilizing the UIFCNN that is introduced by assimilating unified and unsupervised end‐to‐end IF network (U2Fusion) with IF framework based on the CNN (IFCNN). In addition, the UIFCNN obtained maximal Dice coefficient and Jaccard coefficient of 0.928 and 0.920 as well as minimal mean square error (MSE) of 0.221.
  • Context-Aware Autonomous Driving System using Deep Reinforcement Learning and Edge-Assisted Trajectory Optimization Model
    Vanajaroselin Chirchi, Gulshan Dhasmana, Krishna Chaitanya Sunkara, Vishal Shukla, Girish Jadhav, Robert Halam
    3rd International Conference on Data Science and Information System Icdsis 2025, 2025
    Autonomous vehicles encounter multiple obstacles when controlling themselves in complex and dynamic environments during real-time operations. The presented system implements driving autonomy with deep reinforcement learning and edge-computed trajectory optimization in a context-dependent fashion. We established a dual architecture structure which uses deep Q-network(s) for strategic choices and moves trajectory optimization to edge nodes for efficiency. The system achieved enhanced contextual understanding through real-world environment simulations which used multimodal sensor combination techniques and semantic scene analysis methods. Experimental results showed enhanced performance because the system achieved obstacle avoidance accuracy of 94.7% together with 88.3% faster path planning and 76.2% reduced computational latency than traditional centralized systems. Consistent decision-making accuracy reached 91.5% throughout the system's operation across multiple weather conditions and traffic environments. The system offers a fundamental achievement in self-driving vehicles which resolves crucial performance issues through the combination of localized decision-making abilities.
  • Explainable Federated Learning for Secure and Transparent Medical Diagnosis in IoT-based Smart Hospitals
    Prajwalasimha S N, Nilesh Shelke, Dilip Kumar Jang Bahadur Saini, Amit Pimpalkar, Manoj Pal, Vanajaroselin Chirchi
    Proceedings of 5th International Conference on Soft Computing for Security Applications Icscsa 2025, 2025
    The fast uptake of IoT-enabled medical devices to create smart hospitals has revolutionized healthcare delivery, affording real-time monitoring and personalized diagnostics. But, the central training of AI models based on patient data raises serious issues of privacy, transparency, and trust. This work proposes an Explainable Federated Learning (XFL) framework that jointly integrates Explainable AI (XAI) mechanisms with Federated Learning (FL) to enable a secure, privacy-preserving, interpretable medical diagnostic across decentralized healthcare systems. The proposed XFL framework uses edge-based federated optimization to train deep neural models on decentralized patient data, maintaining the locality of that data. The framework enables mutual co-existence of model-agnostic explainability mechanisms such as SHAP and LIME which generate human-comprehensible justifications for a diagnostic decision, improving clinical trust and accountability. To enhance model robustness and confidentiality of the data, we integrate differential privacy, secure aggregation, and lightweight blockchain logging, allowing for auditability and protection against adversarial attacks. We provide experiments using real-world healthcare datasets such as COVIDx and MIMIC-III to demonstrate that our framework can build diagnostic models with competitive accuracy, while providing strong privacy assurances and information for clinicians. This work responds to an urgent requirement in AI-enabled healthcare; not only should it ensure what a model predicts, but also why, so that smart hospital ecosystems may be ethically aligned, safe, and transparent.
  • Quantum-Resilient Federated Learning for Secure and Scalable Cyber-Physical Systems
    Prajwalasimha S N, Dilip Kumar Jang Bahadur Saini, Nilesh Shelke, Amit Pimpalkar, G Hemanth Kumar, Vanajaroselin Chirchi
    Proceedings of 5th International Conference on Soft Computing for Security Applications Icscsa 2025, 2025
    Cyber-Physical Systems like smart grids, autonomous cars, and industrial IoT widely implement Federated Learning (FL) to provide distributed intelligence with privacy-protected data. Yet, the impending quantum threat makes conventional cryptographic methods in FL pipelines obsolete, exposing critical infrastructure to future security vulnerabilities. This paper presents Quantum-Resilient Federated Learning (QR-FL), a new framework integrating lattice-based post-quantum cryptography, light-weight zero-knowledge proofs, and trust-aware aggregation ensuring confidentiality, integrity, and quantum/classical attack resistance. Through comprehensive experimentation on real-world CPS datasets, QR-FL provides up to 48% enhanced adversarial robustness, 32% communication overhead savings, and 6.7% enhanced model accuracy compared to current state-of-the-art secure FL solutions. By achieving future-proof security with scalable federated intelligence, QR-FL provides an architecture foundation for future CPS, offering a landmark direction for secure, decentralized AI in the quantum age.
  • Digital Defenders: A Comprehensive AI Framework for Cyberbullying and Hate speech Detection
    Vanajaroselin Chirchi, Sowmya S R, Supriya R K, Adarsha K N, Pava R, Dhanush Gowda R
    Proceedings 2025 IEEE International Conference on Compute Control Network and Photonics Icccnp 2025, 2025
    The pervasive issues of hate speech and cyberbullying jeopardize the social and emotional well-being of online groups. In order to detect and classify hate speech and cyberbullying in real time, this study presents "Digital Defenders," an end-to-end artificial intelligence platform that integrates federated learning, emotion analysis, natural language processing (NLP), and advanced deep learning. Our method overcomes the drawbacks of human feature engineering and centralized data processing by utilizing multichannel architectures, such as transformer-based models (BERT) and sequential models (LSTM), and maintaining secrecy in federated learning. Extensive experiments on real Twitter datasets shown notable improvements in F1-score, accuracy, and memory, allowing for timely interventions and identifying the main components of safer online environments.
  • Pattern matching for the iris biometric recognition system uses KNN and fuzzy logic classifier techniques
    Vanajaroselin Chirchi, Emmanvelraj Chirchi, Khushi E Chirchi
    International Journal of Information Technology Singapore, 2024
  • Blockchain-based Voting System
    Vanajaroselin Chirchi, Bindyashree, S. Visalini, S Balasubramaniam
    AI Based Advancements in Biometrics and Its Applications, 2024
    Blockchain is a gadget stack of decentralized digital technology that captures transactions throughout numerous computers. A blockchain incorporates a chain of blocks, with each block containing a collection of transactions or records. Blockchain has the power of capable to convert the balloting machine by way of addressing diverse demanding situations bearing on security, transparency, and trust in elections. It has dormant ease inclusive of Transparency and Immutability, protection, remote vote casting, Tamper Resistance, elimination of Double voting, decreased Intermediaries, and many others, there are challenges and concerns to address while imposing block chain-primarily based balloting structures including identification verification, user experience, Scalability, Cyber protection concerns. Numerous fashions and techniques can be used for enforcing a blockchain-based balloting machine. The selection of version relies upon at the precise necessities, security issues, and the extent of decentralization desired. The proposed version focuses on various blockchain model variations that can be used to voting devices to address obstacles and their usefulness in tandem with blockchain voting machine architecture.
  • Optical Sensor for Water Bacteria Detection using Machine Learning
    Vanajaroselin Chirchi, Emmanvelraj Chirchi, E C Khushi, S M Bairavi, K S Indu
    Proceedings of the 18th Indiacom 2024 11th International Conference on Computing for Sustainable Global Development Indiacom 2024, 2024
    The proposed method focuses on the detection of Escherichia coli bacterial contamination in water supplies. The proposed method uses a photonic-based sensor to examine photonic crystals in order to identify bacterial contamination in water. The system accurately predicts and diagnoses water contamination caused by bacteria by integrating an optical sensor with a graphical user interface (GUI). By attentively scrutinizing the early sensor-generated output graphs, we are able to discover variations in drainage patterns that are signaling the presence of bacteria in water samples. These graphs offer crucial insights into the unique characteristics of many samples, such as their refractive index. The sensor’s sensitivity, specificity, and accuracy have all been thoroughly evaluated, and its results have been compared to those of established reference methods. A 95% accuracy rate is attained in the effective detection of the bacterium. These comparisons demonstrate the effectiveness of our AI-driven model and its intuitive graphical user interface (GUI), while also highlighting the potential of our machine learning techniques, such as Decision tree and Naive Bayes algorithm, for effective water bacterial detection.
  • Risk Assessment and Vulnerability Analysis in the IoT
    Vanajaroselin Chirchi, S. Nirmala, Emmanvelraj M. Chirchi, S. L. Karthik Raj, E. C. Khushi
    Secure Communication in Internet of Things Emerging Technologies Challenges and Mitigation, 2024
  • Diabetes Mellitus Diagnosis using Optical Ring Resonators
    Manush Prajwal, J Jesy Janet Kumari, Maanas Mitrahass Uppu, Vanajaroselin Chirchi, S Vishalatchi, D N Darshan
    Proceedings of the 18th Indiacom 2024 11th International Conference on Computing for Sustainable Global Development Indiacom 2024, 2024
  • The Road Ahead: Emerging Trends, Unresolved Issues, and Concluding Remarks in Generative AI—A Comprehensive Review
    Balasubramaniam S., Vanajaroselin Chirchi, Seifedine Kadry, Moorthy Agoramoorthy, Gururama Senthilvel P., Satheesh Kumar K., Sivakumar T. A.
    International Journal of Intelligent Systems, 2024
  • Context Monitoring of Patients using Wireless Network
    Vanajaroselin E Chirchi, Chettiyar Vani Vivekanand, N. Vini Antony Grace, R Saranya, S Venkataramana, K. Praveena
    6th International Conference on Inventive Computation Technologies Icict 2023 Proceedings, 2023
  • Big data processing in internet of things (IoT) systems
    Internet of Everything Smart Sensing Technologies, 2022
  • Enhanced isocentric segmentor and wavelet rectangular coder to Iris segmentation and recognition
    Vanaja Chirchi, , Laxman Waghmare, and
    International Journal of Intelligent Engineering and Systems, 2017

RECENT SCHOLAR PUBLICATIONS

  • Digital Defenders: A Comprehensive AI Framework for Cyberbullying and Hate speech Detection
    V Chirchi, SR Sowmya, RK Supriya, KN Adarsha, R Pava, D Gowda
    2025 IEEE International Conference on Compute, Control, Network & Photonics … , 2025
    2025
  • Explainable Federated Learning for Secure and Transparent Medical Diagnosis in IoT-based Smart Hospitals
    SN Prajwalasimha, N Shelke, DKJB Saini, A Pimpalkar, M Pal, V Chirchi
    2025 5th International Conference on Soft Computing for Security … , 2025
    2025
    Citations: 3
  • Quantum-Resilient Federated Learning for Secure and Scalable Cyber-Physical Systems
    SN Prajwalasimha, DKJB Saini, N Shelke, A Pimpalkar, GH Kumar, ...
    2025 5th International Conference on Soft Computing for Security … , 2025
    2025
    Citations: 2
  • Deep Learning-Driven Melanoma Detection: A Convolutional Neural Network-Based Classification Approach
    V Chirchi, EM Chirchi, S Uranakar, P Cherukuru, SN Prajwala Simha, ...
    International Conference on Artificial Intelligence: Theory and Applications … , 2025
    2025
  • Bio inspired optimization techniques for disease detection in deep learning systems
    A Ashwini, V Chirchi, S Balasubramaniam, MA Shah
    Scientific Reports 15 (1), 18202 , 2025
    2025
    Citations: 17
  • Context-Aware Autonomous Driving System using Deep Reinforcement Learning and Edge-Assisted Trajectory Optimization Model
    V Chirchi, G Dhasmana, KC Sunkara, V Shukla, G Jadhav, R Halam
    2025 3rd International Conference on Data Science and Information System … , 2025
    2025
  • Medical Image Fusion Using Unified Image Fusion Convolutional Neural Network
    S Balasubramaniam, V Chirchi, TA Sivakumar, SP Gururama, ...
    International Journal of Intelligent Systems 2025 , 2025
    2025
    Citations: 12
  • Blockchain-based Voting System
    V Chirchi, S Visalini, S Balasubramaniam
    AI Based Advancements in Biometrics and its Applications, 219-237 , 2024
    2024
    Citations: 2
  • IoT for health care: a sustainable approach
    V Chirchi, KE Chirchi, E Chirchi
    Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and … , 2024
    2024
    Citations: 8
  • Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and Applications
    VA Devi
    Springer , 2024
    2024
  • Pattern matching for the iris biometric recognition system uses KNN and fuzzy logic classifier techniques
    V Chirchi, E Chirchi, KE Chirchi
    International Journal of Information Technology 16 (5), 2937-2944 , 2024
    2024
    Citations: 9
  • Risk Assessment and Vulnerability Analysis in the IoT
    V Chirchi, S Nirmala, EM Chirchi, SLK Raj, EC Khushi
    Secure Communication in Internet of Things, 240-252 , 2024
    2024
    Citations: 1
  • Diabetes Mellitus Diagnosis using Optical Ring Resonators
    M Prajwal, JJJ Kumari, MM Uppu, V Chirchi, S Vishalatchi, DN Darshan
    2024 11th International Conference on Computing for Sustainable Global … , 2024
    2024
    Citations: 2
  • Optical sensor for water bacteria detection using machine learning
    V Chirchi, E Chirchi, EC Khushi, SM Bairavi, KS Indu
    2024 11th International Conference on Computing for Sustainable Global … , 2024
    2024
    Citations: 4
  • The road ahead: emerging trends, unresolved issues, and concluding remarks in generative AI—a comprehensive review
    S Balasubramaniam, V Chirchi, S Kadry, M Agoramoorthy, SP Gururama, ...
    International Journal of Intelligent Systems 2024 , 2024
    2024
    Citations: 66
  • Context monitoring of patients using wireless network
    VE Chirchi, CV Vivekanand, NVA Grace, R Saranya, S Venkataramana, ...
    2023 International Conference on Inventive Computation Technologies (ICICT … , 2023
    2023
    Citations: 4
  • Convergence of Deep Learning and Internet of Things: Computing and Technology: Computing and Technology
    T Kavitha, G Senbagavalli, D Koundal, Y Guo, D Jain
    IGI Global , 2022
    2022
    Citations: 3
  • Soil Classification for Planting and Monitoring Using FCNN-based IoT Smart Agriculture System
    DRK Dr.Vanajaroselin E.C
    Patent Journal , 2022
    2022
  • Scanning Method for segmentation in Iris Biometric Authentication for Security Systems
    DVE Chirchi
    GIS SCIENCE JOURNAL 9 (2), 1444-1450 , 2022
    2022
  • Authentication and recognition using iris biometric system
    DV E.C
    International Journal Of Multidisciplinary Educational Research 10 (8(5 … , 2021
    2021

MOST CITED SCHOLAR PUBLICATIONS

  • The road ahead: emerging trends, unresolved issues, and concluding remarks in generative AI—a comprehensive review
    S Balasubramaniam, V Chirchi, S Kadry, M Agoramoorthy, SP Gururama, ...
    International Journal of Intelligent Systems 2024 , 2024
    2024
    Citations: 66
  • Iris biometric recognition for person identification in security systems
    VRE Chirchi, LM Waghmare, ER Chirchi
    International Journal of Computer Applications 24 (9), 1-6 , 2011
    2011
    Citations: 52
  • OAODV routing algorithm for improving energy efficiency in MANET
    SP Bhatsangave, VR Chirchi
    International journal of computer applications 51 (21), 15-22 , 2012
    2012
    Citations: 27
  • Feature extraction and pupil detection algorithm used for iris biometric authentication system
    VRE Chirchi, LM Waghmare
    International Journal of Signal Processing, Image Processing and Pattern … , 2013
    2013
    Citations: 25
  • Bio inspired optimization techniques for disease detection in deep learning systems
    A Ashwini, V Chirchi, S Balasubramaniam, MA Shah
    Scientific Reports 15 (1), 18202 , 2025
    2025
    Citations: 17
  • Medical Image Fusion Using Unified Image Fusion Convolutional Neural Network
    S Balasubramaniam, V Chirchi, TA Sivakumar, SP Gururama, ...
    International Journal of Intelligent Systems 2025 , 2025
    2025
    Citations: 12
  • Pattern matching for the iris biometric recognition system uses KNN and fuzzy logic classifier techniques
    V Chirchi, E Chirchi, KE Chirchi
    International Journal of Information Technology 16 (5), 2937-2944 , 2024
    2024
    Citations: 9
  • Iris Biometric Authentication used for Security Systems.
    VR Chirchi, L Waghmare
    International Journal of Image, Graphics & Signal Processing 6 (9) , 2014
    2014
    Citations: 9
  • IoT for health care: a sustainable approach
    V Chirchi, KE Chirchi, E Chirchi
    Sustainable IoT and Data Analytics Enabled Machine Learning Techniques and … , 2024
    2024
    Citations: 8
  • Enhanced isocentric segmentor and wavelet rectangular coder to iris segmentation and recognition
    V Chirchi, LM Waghmare, L Waghmare
    Int J Intell Eng Syst 10, 1-10 , 2017
    2017
    Citations: 8
  • Friend recommendation system for online social networks
    DM Jadhavar, VR Chirchi
    International Journal of Computer Applications 153 (12) , 2016
    2016
    Citations: 7
  • Access control list provides security in network
    C AB, C VR
    International Journal of Computer Applications 121 (22), 14-16 , 2015
    2015
    Citations: 5
  • Optical sensor for water bacteria detection using machine learning
    V Chirchi, E Chirchi, EC Khushi, SM Bairavi, KS Indu
    2024 11th International Conference on Computing for Sustainable Global … , 2024
    2024
    Citations: 4
  • Context monitoring of patients using wireless network
    VE Chirchi, CV Vivekanand, NVA Grace, R Saranya, S Venkataramana, ...
    2023 International Conference on Inventive Computation Technologies (ICICT … , 2023
    2023
    Citations: 4
  • Result and analysis: data sharing between peer-to-peer using trust model
    J Kale, VR Chirchi
    International Journal of Computer Applications 157 (8), 30-33 , 2017
    2017
    Citations: 4
  • Explainable Federated Learning for Secure and Transparent Medical Diagnosis in IoT-based Smart Hospitals
    SN Prajwalasimha, N Shelke, DKJB Saini, A Pimpalkar, M Pal, V Chirchi
    2025 5th International Conference on Soft Computing for Security … , 2025
    2025
    Citations: 3
  • Convergence of Deep Learning and Internet of Things: Computing and Technology: Computing and Technology
    T Kavitha, G Senbagavalli, D Koundal, Y Guo, D Jain
    IGI Global , 2022
    2022
    Citations: 3
  • File Sharing between Peer-to-Peer using Network Coding Algorithm
    R Vijay, VR Chirchi
    International Journal of Computer Applications 129 (9), 24-29 , 2015
    2015
    Citations: 3
  • Multi-document Summarization Based on Cluster
    VM Khanapure, V Chirchi
    International Journal of Advanced Research in Electrical, Electronics and … , 2014
    2014
    Citations: 3
  • Enhancement of person identification using Iris pattern
    LM Waghmare, ER Chirchi
    International Journal of Scientific and Engineering Research 2 (4), 37-42 , 2011
    2011
    Citations: 3