Prof. Akhilesh A. Waoo

@aksuniversity.ac.in

Dean, Professor and Head, CS/IT/CSE
AKS University, SATNA, India

Prof. Akhilesh A. Waoo


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https://researchid.co/akhilesh_waoo

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Artificial Intelligence, Computer Science Applications, Computer Networks and Communications
21

Scopus Publications

782

Scholar Citations

13

Scholar h-index

20

Scholar i10-index

Scopus Publications

  • Advance Collaborative AI-Driven Bots Using RPA to Enhance Workplace Inclusivity for Employees with Disabilities in India
    Sweta Nigam, Akhilesh A. Waoo
    2025 IEEE 14th International Conference on Communication Systems and Network Technologies Csnt 2025, 2025
    AI-powered bots are designed to assist workers with disabilities in various work environments. It explores adaptive interfaces and supportive features that enable these bots to meet the diverse needs of individuals facing visual, auditory, motor, and cognitive challenges. By synthesizing existing research, this review emphasizes the possibility of AI to explore workplace inclusivity, assesses the effectiveness of different assistive technologies, and identifies critical gaps in current studies. Furthermore, the paper highlights emerging trends in AI-driven accessibility tools and provides recommendations for future research and development initiatives.
  • Modelling of Insider Threat Detection Based on Anomalous Behaviour of Users for Cyber Security
    Nitin Barsagde, Akhilesh A. Waoo
    2025 International Conference on Sustainability Innovation and Technology Icsit 2025, 2025
    Insider threats pose a significant challenge to organizations, as malicious activities often mimic legitimate user behavior and bypass traditional security mechanisms. This paper presents a novel hybrid framework for insider threat detection based on anomalous user behavior analysis using multi-source log data. Detection of insider threats is a significant concern in the realm of cybersecurity. Insiders pose the greatest threat due to their unique access. Insider risks can be identified by the atypical activity of a user. The individual is engaged at his place of employment. All user activity on the device is recorded. The recorded data is utilized to analyze user behaviour and identify unusual activities. The user's log, device, and file data were curated, sanitized, and standardized in this study. Features are derived from insider log data. The statistical analysis has been conducted to determine the central tendency and dispersion of the data. It facilitated the classification of normative and abnormal user activity. The interrelationship between the user and the PC is depicted in an undirected bipartite graph. Anomalous user behaviour is analyzed for insider risks based on data. Significant risk mitigation measures may be implemented when the user is identified as a potential insider threat. A medium risk rating is established when the user is identified as anomalous in 50 percent of insider threat activities. Low-level risk measures are implemented against the user upon a determination of guilt in 25 percent of potential risk activities. The measures used against the user include warnings, penalties, account suspension, termination, and reporting to management for additional action on the insider danger about their risk level.
  • Machine Learning Revolutionizing Brain Health
    Santosh Soni, Pramod Singh, Akhilesh A. Waoo
    Brain Informatics Technology, 2025
    The chapter “Machine Learning Revolutionizing Brain Health: Innovations and Future Directions” provides an in-depth exploration of Machine learning's (ML) revolutionary effects on the brain and neuroscience. It begins with an overview of ML's pivotal role in healthcare, emphasizing its potential to revolutionize the diagnosis, treatment, and understanding of neurological conditions. The chapter outlines fundamental ML concepts, including various learning types, key algorithms, and essential processes such as training and testing models. Machine learning (ML) is driving significant advancements in brain health by enhancing early diagnosis, personalizing treatment, and developing innovative interventions. Innovations include improved neuroimaging analysis for early disease detection, predictive models for disease onset, personalized therapies based on individual profiles, and adaptive cognitive interventions. Real-time monitoring through wearable technology and smart implants also showcases ML's transformative potential. Future directions involve integrating multi-omics data, addressing ethical and privacy concerns, fostering interdisciplinary collaboration, and ensuring equitable access to new technologies. These developments promise a comprehensive and personalized approach to neurological and psychiatric conditions, revolutionizing the field of brain health. To provide practical insights, the chapter presents case studies on early detection of Alzheimer's, prediction of epilepsy seizures, and ML in detecting and treating depression. It also covers essential tools and technologies, including popular ML frameworks (TensorFlow, PyTorch, Scikit-learn), data processing tools, and cloud-based platforms for scalable ML solutions. The chapter recaps the transformative potential of ML in brain health, underscoring its significant impact on diagnosis, treatment, and patient care, and provides a future outlook on ongoing advancements in this dynamic field.
  • Cognitive Brain Imaging Techniques and Their Applications in Intelligent Decision-Making
    Raginee Tiwari, Ashwini A. Waoo, Akhilesh A. Waoo
    Brain Informatics Technology, 2025
    This chapter comprises the functional aspects of the brain for making decisions and technical approaches for imaging the physical and psychological deformity. This is a detailed study about the intelligent decision-making and relationship models due to psychological disorders. What behavioral implications of the human brain influence if suffering from neuro-developmental issues and how has technical imaging made it possible to record human brain implication mapping? We are presenting the numerous theories behind the technological approaches that explain the functional areas of the human brain during decision-making intelligently. The chapter summarizes the behavioral patterns of brain functioning and different decision-making models explained by eminent psychiatrists. A detailed technological study of mapping the functioning areas of the human brain for various kinds of decision-making such as taking risky decisions, suicidal decisions, emotional decisions, strict decisions, creative decisions, etc.
  • Federated Learning for Cyberattack Detection in Multi-Cloud Platforms
    D. Kalpana, M. Kanthimathi, JhansiRani Ganapa, Dhirendra Kumar Tripathi, Sunil Tiwari, Akhilesh A. Waoo
    Proceedings of the 2025 3rd International Conference on Advances in Computation Communication and Information Technology Icaiccit 2025, 2025
    More companies now use several cloud services to grow easily, avoid disruptions, save money. Because systems are growing quickly, this creates big security problems. Attacks can take advantage of networks that are spread out, containing different kinds of technology. Old ways to spot network attacks use central computers learning patterns from all the data flowing across a network. This practice creates issues with keeping data private, following regulations, also uses a lot of network capacity. Teams can build better computer programs together using information from many sources, yet they don't need to reveal private data. This works by letting each source contribute to the learning process without directly exchanging information. This research details building a security system for many cloud services. It uses a learning approach where information stays on each service, improving privacy. We detail how it's built, the design of its parts working nearby, its parts working across distances, safe ways it shares information, then how it learns. Testing with CICIDS2017, UNSW-NB15 datasets shows FL-IDS finds threats as well as traditional systems. It does this with far less data transfer, keeping information secure. The findings show it's possible to use security systems built with federated learning across different cloud services that a business actually uses.
  • Fuzzy-Guided Genetic Algorithm Routing for Energy Conservation in Wireless Sensor Networks
    Virendra Tiwari, Shankar Bera, Anand Kumar Dwivedi, Balendra Kumar Garg, Akhilesh A. Waoo
    Learning and Analytics in Intelligent Systems, 2024
  • Strategizing IoT Network Layer Security Through Advanced Intrusion Detection Systems and AI-Driven Threat Analysis
    , Piyush Piyush, , , , , , Akhilesh A. Waoo, Murlidhar Prasad Singh, Piyush Kumar Pareek, Shoaib Kamal, Shraddha V. Pandit
    Journal of Intelligent Systems and Internet of Things, 2024
    This research introduces an algorithmic framework for enhancing the security of Internet of Things (IoT) networks. The Enhanced Anomaly Detection (EAD) algorithm initiates the process by detecting anomalies in real-time IoT data, serving as the foundational layer. The Behavior Analysis for Profiling (BAP) algorithm builds upon EAD, adding behavior analysis for profiling and adaptive identification of abnormal behavior. Signature-Based Detection (SBD) involves pre-identified attack signatures, which supports detection of known attacks and provides proactive defense measures against documented threats. The MLID, or the Machine Learning-Based Intrusion Detection, algorithm uses trained machine learning models in order to detect anomalies and the adaptability to changing security risks. The Real-Time Threat Intelligence Integration (RTI) algorithm integrates updated threat intelligence feeds, which improves the framework's responsiveness to emerging threats. The visual representations illustrate once again the idea of the new framework being very accurate at intergration, applicability, and overal security effectiveness. The research makes a standard solution which proves to be a smart and responsive way guarding the IoT networks reducing and even fighting known and potential threats in a real-time mode.
  • Intelligent agriculture system
    Ashwini A. Waoo, Akhilesh A. Waoo
    Intelligent Sensor Node Based Systems Applications in Engineering and Science, 2023
    Integrated and interdisciplinary technology is now the prime wealth of knowledge in all aspects of life. Interdisciplinary research brings new opportunities for the benefits of short-term projects. Agriculture is the main foundation of the Indian economy; it is possible to sustain the agricultural system with innovative interdisciplinary approaches so that India will emerge as a “Superpower” of the world. The present chapter proposal is a prototype demonstrating agriculture engineering at a mass scale with an intelligent system and minimum expenditure. Various factors, such as drastic population growth, climate change, global warming, and food security concerns, have driven the research communities to seek more innovative approaches for improving crop yield and food protection. This content will explore applications of artificial intelligence (AI) for the agricultural sector and its modernization.
  • Intelligent University Monitoring System (i-UMS)
    Akhilesh A. Waoo, Ashwini A. Waoo
    Intelligent Sensor Node Based Systems Applications in Engineering and Science, 2023
    Intelligent University Management System (i-UMS), is a specially designed software application for precisely regulating a university/ educational Institution’s functions. It has real-time information available for the smooth functioning of each department of the university. Indian universities and academic institutions are facing many challenges during the pandemic of providing high-quality online education and management and monitoring of all aspects of a university. Students want user-friendly access to learning tools as well as admission, enrolment, and result-oriented information at their fingertips. i-UMS fulfills all these requirements with a great experience. Faculty members require online academic support for enhanced blended classroom teaching, and parents like to watch the progress of their children to secure their future. This can also be made possible by the i-UMS model. Overall, i-UMS is academically, technically, and socially helping the university to maintain the decorum and faith in the institution. This chapter focused on the models, features, significance, and applications of i-UMS.
  • Deep learning: Tools and models
    Innovative Engineering with AI Applications, 2023
  • Artificial intelligence in agricultural engineering
    Ashwini A. Waoo, Jyoti Pandey, Akhilesh A. Waoo
    Innovative Engineering with AI Applications, 2023
  • Packet Delivery Comparison Using Artificial Bee Colony Algorithm with Dynamic Technique
    Mirza Samiulla Beg, Akhilesh A. Waoo
    Smart Innovation Systems and Technologies, 2023
  • Convolutional neural network model for identifying neurological visual disorder
    Brijesh K. Soni, Akhilesh A. Waoo
    Artificial Intelligence for Neurological Disorders, 2022
  • Recurrent neural network model for identifying neurological auditory disorder
    Akhilesh A. Waoo, Brijesh K. Soni
    Artificial Intelligence for Neurological Disorders, 2022
  • Analysis of Energy Efficient Coverage and Prolonging Lifetime by Comparing Homogenous and Heterogeneous Wireless Sensor Networks
    Akhilesh A Waoo, Sanjay Sharma
    2018 International Conference on Advanced Computation and Telecommunication Icacat 2018, 2018
  • Drop rate minimization using MIB under media access control (MAC) layer in MANET
    A. Gupta, A. A. Waoo, P. S. Patheja, S. Sharma
    International Conference on Advanced Computing and Communication Technologies Acct, 2013
  • An efficient approach for cloud computing based on hierarchical secure paravirtualization system resource model
    International Journal of Applied Engineering Research, 2012
  • An artificial neural network model for weather forecasting in Bhopal
    IEEE International Conference on Advances in Engineering Science and Management Icaesm 2012, 2012
  • An enhanced approach for weather forecasting using neural network
    Ratna Nayak, P. S. Patheja, Akhilesh Waoo
    Advances in Intelligent and Soft Computing, 2012
  • A novel and distributed method of distance measurement and localization for MWSN based on AOA
    Anil Bhawarkar, P. S. Patheja, Akhilesh A. Waoo
    Advances in Intelligent and Soft Computing, 2012
  • Comparison of efficient and rand index fitness function for clustering gene expression data
    P. S. Patheja, Akhilesh A. Waoo, Ragini Sharma
    Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering, 2012

RECENT SCHOLAR PUBLICATIONS

  • Artificial Intelligence in Sustainability Spanning Climate, Energy, Biodiversity, Agriculture, and Waste Management
    A Tiwari, AA Waoo
    Artificial Intelligence 10 (05) , 2026
    2026
  • A Review of the Comparative Study of Anomaly Detection Techniques for Enhancing Security in AI-Driven Medical Applications
    S THAKUR, M BHATELE, A WAOO
    Next Research, 101744 , 2026
    2026
    Citations: 1
  • Reinforcement Techniques for Dynamic Adaptive Learning
    A Tiwari, P Singh, AA Waoo
    International Journal of Pharmacy Research & Technology (IJPRT) 16 (1), 164-169 , 2026
    2026
  • Cognitive Brain Imaging Techniques and Their Applications in Intelligent Decision‐Making
    R Tiwari, AA Waoo, AA Waoo
    Brain Informatics Technology, 305-323 , 2025
    2025
    Citations: 1
  • Machine Learning Revolutionizing Brain Health: Innovations and Future Directions
    S Soni, P Singh, AA Waoo
    Brain Informatics Technology, 231-252 , 2025
    2025
    Citations: 1
  • Dynamic and Intelligent Firewall Systems for Robust Network Protection
    AA Waoo, AK Gautam
    JOURNAL OF ADVANCE AND FUTURE RESEARCH 3 (11), 497-501-497-501 , 2025
    2025
  • Advanced security framework for DICOM images using triple watermarking with DWT and SVD for role-based access control
    S Verma, M Bhatele, AA Waoo
    Next Research 2 (3), 100524 , 2025
    2025
    Citations: 1
  • Modelling of Insider Threat Detection Based on Anomalous Behaviour of Users for Cyber Security
    N Barsagde, AA Waoo
    2025 International Conference on Sustainability, Innovation & Technology … , 2025
    2025
  • ANALYZING SUPERVISED LEARNING MODELS FOR INTRUSION DETECTION: TOWARDS ROBUST WIRELESS SENSOR NETWORK
    K Soni, Arunendar, K Dwivedi, Vinay, AA Waoo
    International Journal of Advanced Research (IJAR) 13 (07), 500-504 , 2025
    2025
  • Routing Algorithms in Wireless Sensor Networks
    S Payasi, AA Waoo
    International Journal of Scientific Development and Research (IJSDR) www … , 2025
    2025
  • Efficient Traffic Flow Prediction with CNN-Based Deep Learning Techniques
    P Bhartiya, M Bhatele, AA Waoo
    International Conference on Advances and Applications in Artificial … , 2025
    2025
    Citations: 2
  • Advance Collaborative AI-Driven Bots Using RPA to Enhance Workplace Inclusivity for Employees with Disabilities in India
    AA Waoo
    2025 IEEE 14th International Conference on Communication Systems and Network … , 2025
    2025
  • Big Data Analytics in E-Commerce with Data Mining Methods
    P Verma, AA Waoo
    International Journal of Advance Research in Science and Engineering (IJARSE … , 2025
    2025
  • Role-based access control framework using dynamic watermarking for secure DICOM medical image communication
    S Verma, M Bhatele, AA Waoo
    GRADIVA Review Journal 11 (5) , 2025
    2025
    Citations: 2
  • AI-Powered Driven Intrusion Systems in Cyber Security and Zero-Day Attack Detection
    HS Patel, CS Gautam, AA Waoo
    2025
  • Machine Learning Algorithms for Intrusion Detection in WSNs
    A Kumar Soni, Arunendar, A Waoo, Dr
    International Journal of Scientific Research in Engineering and Management … , 2025
    2025
  • Ensemble-Based Machine Learning Models for Real-Time Traffic Flow Prediction
    P Bhartiya, M Bhatele, AA Waoo
    Journal of Neonatal Surgery 14 (32s) , 2025
    2025
  • Face Detection Under Low-Light and Low-Resolution Conditions Using Contrast-Limited Adaptive Histogram Equalization and a Modified Convolutional Neural Network
    LN Soni, AA Waoo
    Journal of Neonatal Surgery 14 (32s), 2620-2631 , 2025
    2025
    Citations: 9
  • A Lightweight and Efficient Hybrid CNN Model for Face Detection
    LN Soni, AA Waoo
    International Journal of Environmental Sciences 11 (8s), 583-591 , 2025
    2025
    Citations: 5
  • Sustainable Development Goals
    AA Waoo
    Forever Shinings Publication, 220 , 2024
    2024
    Citations: 17

MOST CITED SCHOLAR PUBLICATIONS

  • Strategizing IoT network layer security through advanced intrusion detection systems and AI-driven threat analysis
    DD Rao, AA Waoo, MP Singh, PK Pareek, S Kamal, SV Pandit
    Full Length Article 12 (2), 195-207 , 2024
    2024
    Citations: 115
  • Performance analysis of sigmoid and relu activation functions in deep neural network
    AA Waoo, BK Soni
    Intelligent systems: proceedings of SCIS 2021, 39-52 , 2021
    2021
    Citations: 72
  • An artificial neural network technique for prediction of cyber-attack using intrusion detection system
    JK Jain, AA Waoo
    Journal of Artificial Intelligence, Machine Learning and Neural Network 3 (2 … , 2023
    2023
    Citations: 36
  • Transforming healthcare: the synergistic fusion of AI and IoT for intelligent, personalized well-being
    M Tiwari, AA Waoo
    Revolutionizing Healthcare: AI Integration with IoT for Enhanced Patient … , 2024
    2024
    Citations: 26
  • Energy efficient adaptive routing algorithm in MANET with sleep mode
    T Nema, A Waoo, PS Patheja, S Sharma
    International Journal of Advanced Computer Research 2 (4), 431 , 2012
    2012
    Citations: 26
  • RFID-Based Digital Door Locking System
    S Soni, R Soni, AA Waoo
    Indian Journal of Microprocessors and Microcontroller (IJMM) 1 (2), 17-21 , 2021
    2021
    Citations: 25
  • An enhanced approach for weather forecasting using neural network
    R Nayak, PS Patheja, A Waoo
    Proceedings of the International Conference on Soft Computing for Problem … , 2012
    2012
    Citations: 22
  • Sustainable Development Goals
    AA Waoo
    Forever Shinings Publication, 220 , 2024
    2024
    Citations: 17
  • An artificial neural network model for weather forecasting in Bhopal
    R Nayak, PS Patheja, AA Waoo
    IEEE-international conference on advances in engineering, science and … , 2012
    2012
    Citations: 17
  • A review of recent advances methodologies for face detection
    L Soni, A Waoo
    International Journal of Current Engineering and Technology 13 (02), 86-92 , 2023
    2023
    Citations: 16
  • A literature review on machine learning for cyber security issues
    JK Jain, AA Waoo, D Chauhan
    International Journal of Scientific Research in Computer Science … , 2022
    2022
    Citations: 16
  • Attack detection in watermarked images with PSNR and RGB intensity
    N Chauhan, AA Waoo, PS Patheja
    International Journal of Advanced Computer Research 3 (1), 2249-7277 , 2013
    2013
    Citations: 15
  • Energy based AODV Routing Algorithm with Sleep Mode in MANETs
    AA Waoo, T Nema, PS Patheja, S Sharma
    International Journal of Computer Applications 58 (19) , 2012
    2012
    Citations: 14
  • New load balanced multi-path dynamic source routing protocol for mobile ad-hoc network
    L Malviya, AA Waoo, S Sharma
    International Journal of Computer Applications 61 (19), 25-27 , 2013
    2013
    Citations: 12
  • A MACHINE LEARNING APPROACH FOR PREDICTIVE ANALYSIS OF TRAFFIC FLOW
    P Bhartiya, M Bhatele, AA & Waoo
    ShodhKosh:Journal of Visual and Performing Arts 5 (5), 422–430. , 2024
    2024
    Citations: 11
  • IoT based Smart Home Cyber-Attack Detection and Defense
    A Tiwari, AA Waoo
    TIJER-International Research Journal 10 (8) , 2023
    2023
    Citations: 11
  • Customer Behavior Analysis in E-Commerce using Machine Learning Approach: A Survey
    S Sharma, AA Waoo
    International Journal of Scientific Research in Computer Science … , 2023
    2023
    Citations: 11
  • DESIGN A NOVEL APPROACH FOR TOKEN BASED AUTHENTICATION IN IOT NETWORKS.
    BB Rao, AA Waoo
    Ilkogretim Online 20 (4), 2401-2406 , 2021
    2021
    Citations: 11
  • A Research Paper on Comparison between Energy Efficient Routing Protocol with Energy and Location in MANET
    R Gupta, AA Waoo, S Sharma, PS Patheja
    IOSR Journal of Computer Engineering (IOSR-JCE) 9 (4), 70-75 , 2013
    2013
    Citations: 11
  • REVIEW OF GAMMA CORRECTION TECHNIQUES IN DIGITAL IMAGING
    S Soni, P Singh, AA Waoo
    ShodhKosh:Journal of Visual and Performing Arts 5 (5), 473–479. , 2024
    2024
    Citations: 10