Jayabhaduri Radhakrishnan

@alliance.edu.in

Professor, Department of Information Technology
Alliance School of Advanced Computing, Alliance University

Jayabhaduri Radhakrishnan


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https://researchid.co/jayabhaduri17

RESEARCH, TEACHING, or OTHER INTERESTS

Artificial Intelligence, Human-Computer Interaction, Human Factors and Ergonomics, Multidisciplinary
8

Scopus Publications

17

Scholar Citations

2

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Ambient Intelligence in Smart Hospital Rooms: A Context-Aware System for Patient Centric Healthcare
    Jayabhaduri Radhakrishnan, R. Shekhar
    Communications in Computer and Information Science, 2026
  • AI- Enabled Multi-Sensor Drones for Real- Time Maritime Search and Rescue
    Jayabhaduri Radhakrishnan, R. Shekhar
    Emerging Technologies in Vessels and Automated Drones for Maritime Innovation, 2025
    Maritime Search and rescue (MSAR) solutions must be intelligent, nimble, and autonomous due to the growing frequency and complexity of maritime emergencies, which are caused by climate change, growing coastal populations, and increased marine traffic. This study introduces a multi-sensor, AI-enabled unmanned aerial vehicle (UAV) system intended to improve maritime SAR operations in real time. To provide synchronized data collection, in-situ processing, and quick decision-making, the suggested framework combines thermal, RGB, and LiDAR sensors with a Pixhawk 4 flight controller and a Jetson Xavier NX edge computing module. The domain-specific AI4SAR dataset is used to train YOLOv5s, a compact deep learning architecture that is enhanced with both synthetic and real marine scenes to guarantee resilience in a range of environmental circumstances. Transfer learning, ONNX export, and TensorRT acceleration are used to optimize the model, allowing for inference speeds exceeding 30 frames per second with 92.1% precision, 88.7% recall, and 90.3% mAP@0.5. The outcomes highlight the system's applicability for use in actual SAR situations, where operational resilience and real-time item detection are essential for saving lives in hazardous maritime environments.
  • Reducing Digital CO2 Footprint in IT Systems Using Temporal Difference Learning for Energy-Aware Scheduling
    Jayabhaduri Radhakrishnan, Shekhar R.
    Proceedings of the 2025 12th International Conference on Computing for Sustainable Global Development Indiacom 2025, 2025
    Optimizing resource allocation is critical for reducing power consumption and minimizing carbon emissions in high-performance computing environments. This research presents a Deep-Q-Network based Reinforcement Learning DQNAgent to enhance decision-making in CPU/GPU allocation, and workload allocation. For better decision making, the proposed DQNAgent follows an epsilon-greedy policy to balance exploration and exploitation. The agent is trained for 1000 episodes, keeping exploration rate (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\epsilon$</tex>) decreases from 1.0 (random action selection) to 0.01 (optimal policy execution), which enables the DQNAgent to make more informed decisions. The DQNAgent is trained on a CPU/GPU workstation. The experimental results clearly indicate that training the agent on a CPU-based system to learn an optimal policy to minimize emissions takes approximately 7 hours and 17 minutes, while utilizing a GPU workstation significantly reduces execution time to less than 2 minutes, thereby accelerating real-time decision-making. Results indicate that the proposed method effectively optimizes energy efficiency, reducing overall power consumption while maintaining computational performance. This research work paves way for leveraging Artificial Intelligence driven reinforcement learning for sustainable and intelligent computing systems.
  • Image Processing Based Machine Vision System For Datum Setting In Computer Numeric Control Machine
    Jayabhaduri Radhakrishnan, Sathyavarthan Balachandar, Sadana Ulaganathan, Shivanee Ramesh, Ponnuvel S, Sridharan V
    Procedia Computer Science, 2025
    Datum setting is a preliminary process that is done prior to any drilling or milling process in Vertical Machining Centers. It is performed either manually using a trial-and-error method or with the assistance of touch trigger probes. In the manual method, the operator brings the cutting tool closer to the workpiece surface until a feather touch is achieved at the desired reference plane. This method is time consuming and prone to errors. The alternative for this would be the usage of touch trigger probes. However, touch trigger probes are expensive. This research work presents an Image Processing based Machine Vision mechanism for datum setting in Computer Numeric Control machine. The Datum Setting System network (DSS-net), a single stage object detection algorithm for tool detection employs perimeter crossing as the detection principle to indicate zero point on the reference plane. The DSS-net is trained on a manually curated dataset using several YOLO variants by varying batch sizes and workers in the GPU. Finally it is tested on CNC image sequences and achieves a 97.3% mean Average Precision (mAP) and F1-score of 99.9% for tool detection. DSS-net’s performance and its average inference rate of 50.85 frames per second meet the necessary standards for datum setting in CNC machines.
  • AI-Enhanced Cross-Modal Anime Recommendation System with Explainable Deep Learning
    Jayabhaduri Radhakrishnan, H. Naga R. Guna Vardhan, Akey Sungheetha, K. Dinesh Kumar Reddy, K. Danush Kumar, B. Charan Reddy
    2nd International Conference on IT Innovations and Knowledge Discovery Itikd 2024, 2025
    This paper presents an innovative approach to anime recommendation systems by integrating multi-modal deep learning with explainable AI techniques. We propose a novel framework that combines visual features, textual content, and user interaction data to create more accurate and interpretable recommendations. Our system addresses key challenges in ex-isting recommendation systems, including the cold-start problem and limited content understanding, through a hybrid architecture that leverages BERT-based natural language processing and convolutional neural networks for visual analysis. Experimental results demonstrate a 27% improvement in recommendation accuracy compared to traditional methods, while providing transparent explanations for recommendations through attention visualization.
  • AI-Driven Nutritional Intelligence: A Predictive Data Analytics Framework for Personalized Dietary Optimization
    Jayabhaduri R, Prabanjan U V, Akey Sungheetha, Gunashekara Reddy M R, Santhosh G, Yashas M R
    2nd International Conference on IT Innovations and Knowledge Discovery Itikd 2024, 2025
    Public health is critically dependent on nutrition, yet malnutrition and poor dietary habits persist globally. This study presents an AI-driven nutritional intelligence framework that leverages machine learning, behavioral insights, and real-time data analytics to enhance nutritional well-being. By integrating heterogeneous datasets-including dietary surveys, medical records, socioeconomic profiles, a nd g eospatial data-the proposed model identifies key nutritional deficiencies and risk factors for diet-related diseases. Predictive modeling is employed to generate personalized dietary recommendations, while wearable and mobile technologies facilitate real-time nutrient monitoring. Additionally, AI-powered learning platforms and community-driven interventions improve adherence to healthier eating habits. The study evaluates the framework through case studies and pilot programs, demonstrating measurable improvements in dietary outcomes and reduced nutritional disparities.
  • A deep LSTM recurrent learning approach for sentiment analysis on movie reviews
    G.R. Khanaghavalle, V. Rajalakshmi, R. Jayabhaduri, A. Kala, P. Sharon Femi
    Intelligent Systems and Sustainable Computational Models Concepts Architecture and Practical Applications, 2024
    Analysis of sentiments is an opinion mining technique that focuses on extraction of emotions of people towards a specific topic using structured or unstructured data. A lot of research work happens in text mining and natural language processing in recent times. It has an extensive range of applications since most of the activities happening today revolve around the opinions and feedback of people. Handling such immeasurable data manually is highly impossible and everyone finds the necessity of sentiment analysis using a deep learning algorithm. In a world where numerous movies of different genres are released daily, people cannot afford their time trying to figure out the best movie. A sentiment classification system built using deep learning would help in the movie recommender system and also assist people in classifying movies based on their reviews. To implement this, two deep learning algorithms namely CNN and RNN and its variant named LSTM are used, their performance is compared and the algorithm that gives better accuracy for the sentiment analysis is determined.
  • AI Powered Chatbot For Mental Health Treatment
    Jayabhaduri R, Aadesh Vijayaraghavan, Ajay Karthik R, Ceralaathan G, Sai Sailesh S
    Proceedings 2024 1st International Conference on Technological Innovations and Advance Computing Tiacomp 2024, 2024
    In the recent days, most people of all ages have their mental health affected by various factors like stress, anxiety, depression, fear, phobia and trauma. Hence it is mandatory for people to take care of their mental health. People may hesitate to approach therapists in real life due to societal stigmas. As many people are unable to access or afford mental health services, our research work aims at developing a SAAC Mental health chatbot to mimic a therapist to provide personalized support and guidance, learn about an individual’s unique needs and preferences, and tailor their responses accordingly with 24/7 support by handling speech and text queries. SAAC chatbot also maintains chat history and notifies users by sending alerts to ensure follow-ups.

RECENT SCHOLAR PUBLICATIONS

  • AI-Driven Multimodal Framework for Environmental Monitoring and Conservation
    J Radhakrishnan
    2026 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-6 , 2026
    2026
  • Ambient Intelligence in Smart Hospital Rooms: A Context-Aware System for Patient Centric Healthcare
    J Radhakrishnan, S R
    Artificial Intelligence Based Smart and Secured Applications, 78-86 , 2026
    2026
  • AI-Enabled Multi-Sensor Drones for Real-Time Maritime Search and Rescue
    J Radhakrishnan, S R
    Emerging Technologies in Vessels and Automated Drones for Maritime … , 2025
    2025
  • Adaptive Waste Collection Routing in Smart Cities Using Multi-agent Systems
    J Radhakrishnan, R Shekhar
    International Conference on Sustainable Computing and Intelligent Systems … , 2025
    2025
  • Reducing Digital CO2 Footprint in IT Systems Using Temporal Difference Learning for Energy-Aware Scheduling
    J Radhakrishnan, S R.
    2025 12th International Conference on Computing for Sustainable Global … , 2025
    2025
    Citations: 1
  • Reducing Digital CO2 Footprint in Information Technology Systems Using Reinforcement Learning - World Congress on Smart Computing
    J Radhakrishnan, S R
    World Congress on Smart Computing : Studies in Smart Technologies, 469-481 , 2025
    2025
  • AI-Enhanced Cross-Modal Anime Recommendation System with Explainable Deep Learning
    J Radhakrishnan, HNRG Vardhan, A Sungheetha, KDK Reddy, ...
    2024 International Conference on IT Innovation and Knowledge Discovery … , 2025
    2025
  • AI-Driven Nutritional Intelligence: A Predictive Data Analytics Framework for Personalized Dietary Optimization
    R Jayabhaduri, UV Prabanjan, A Sungheetha, MR Gunashekara Reddy, ...
    Second International Conference on IT Innovations and Knowledge Discovery … , 2025
    2025
  • Reducing Digital Footprint in Information Technology Systems Using Reinforcement Learning
    R Jayabhaduri, R Shekhar
    World Congress on Smart Computing, 469-481 , 2025
    2025
  • Image Processing Based Machine Vision System For Datum Setting In Computer Numeric Control Machine
    J Radhakrishnan, S Balachandar, S Ulaganathan, S Ramesh
    Procedia Computer Science 263, 463-470 , 2025
    2025
    Citations: 1
  • Real-Time 3D Human Pose Estimation Using Deep Learning Model for Ergonomics
    J Radhakrishnan, V Aadesh, R Ajay Karthik, G Ramana Prasath, ...
    International Journal of Technology and Engineering Studies 8 (1), 34-40 , 2024
    2024
  • A Deep LSTM Recurrent Learning Approach for Sentiment Analysis on Movie Reviews
    GR Khanaghavalle, V Rajalakshmi, R Jayabhaduri, A Kala, PS Femi
    Intelligent Systems and Sustainable Computational Models, 202-211 , 2024
    2024
  • AI Powered Chatbot For Mental Health Treatment
    R Jayabhaduri, V Aadesh, R Ajay Karthik, G Ceralaathan, S Sai Sailesh
    First International Conference on Technological Innovations and Advance … , 2024
    2024
    Citations: 11
  • AI-Enhanced Triboelectric Surface Analysis for Smart Urban Accessibility Pattern Detection​
    R Jayabhaduri, D Akey Sungheetha
    6th International Conference Futuristic Trends in Networks and Computing … , 2024
    2024
  • WSA: A NAVIGATION APP FOR WOMEN SAFETY
    R Jayabhaduri, S Saineha, M Madhumithaa, A Roshini
    Novyimir Research Journal 8 (7), 185-195 , 2023
    2023
    Citations: 2
  • IOT Based WiFi Enabled Smart Gardening System
    V Rajalakshmi, GR Khanaghavalle, A Kala, ...
    IN Patent App. 202,341,006,434 A , 2023
    2023
  • Landmark Recognition Using Transfer Learning
    V Tenkayala, R Jayabhaduri
    International Conference on Advanced Communication Control & Computing … , 2022
    2022
  • An Evolutionary Algorithmic Approach for Single Machine Early Tardy Scheduling Problem
    R Jayabhaduri
    Research Journal of Applied Sciences, Engineering and Technology 11 (6), 666-673 , 2015
    2015
  • An Evolutionary Algorithmic Approach for Airline Crew Scheduling Problem
    G Arul Charles, R Jayabhaduri
    International Journal of Applied Engineering Research 10 (70), 2015 , 2015
    2015
  • Automatic Discovery of Association Orders between Name and Aliases from the Web using Anchor Texts-based Co-occurrences
    R Jayabhaduri
    International Journal of Computer Applications 41 (19) , 2012
    2012
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • AI Powered Chatbot For Mental Health Treatment
    R Jayabhaduri, V Aadesh, R Ajay Karthik, G Ceralaathan, S Sai Sailesh
    First International Conference on Technological Innovations and Advance … , 2024
    2024
    Citations: 11
  • WSA: A NAVIGATION APP FOR WOMEN SAFETY
    R Jayabhaduri, S Saineha, M Madhumithaa, A Roshini
    Novyimir Research Journal 8 (7), 185-195 , 2023
    2023
    Citations: 2
  • Automatic Discovery of Association Orders between Name and Aliases from the Web using Anchor Texts-based Co-occurrences
    R Jayabhaduri
    International Journal of Computer Applications 41 (19) , 2012
    2012
    Citations: 2
  • Reducing Digital CO2 Footprint in IT Systems Using Temporal Difference Learning for Energy-Aware Scheduling
    J Radhakrishnan, S R.
    2025 12th International Conference on Computing for Sustainable Global … , 2025
    2025
    Citations: 1
  • Image Processing Based Machine Vision System For Datum Setting In Computer Numeric Control Machine
    J Radhakrishnan, S Balachandar, S Ulaganathan, S Ramesh
    Procedia Computer Science 263, 463-470 , 2025
    2025
    Citations: 1
  • AI-Driven Multimodal Framework for Environmental Monitoring and Conservation
    J Radhakrishnan
    2026 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-6 , 2026
    2026
  • Ambient Intelligence in Smart Hospital Rooms: A Context-Aware System for Patient Centric Healthcare
    J Radhakrishnan, S R
    Artificial Intelligence Based Smart and Secured Applications, 78-86 , 2026
    2026
  • AI-Enabled Multi-Sensor Drones for Real-Time Maritime Search and Rescue
    J Radhakrishnan, S R
    Emerging Technologies in Vessels and Automated Drones for Maritime … , 2025
    2025
  • Adaptive Waste Collection Routing in Smart Cities Using Multi-agent Systems
    J Radhakrishnan, R Shekhar
    International Conference on Sustainable Computing and Intelligent Systems … , 2025
    2025
  • Reducing Digital CO2 Footprint in Information Technology Systems Using Reinforcement Learning - World Congress on Smart Computing
    J Radhakrishnan, S R
    World Congress on Smart Computing : Studies in Smart Technologies, 469-481 , 2025
    2025
  • AI-Enhanced Cross-Modal Anime Recommendation System with Explainable Deep Learning
    J Radhakrishnan, HNRG Vardhan, A Sungheetha, KDK Reddy, ...
    2024 International Conference on IT Innovation and Knowledge Discovery … , 2025
    2025
  • AI-Driven Nutritional Intelligence: A Predictive Data Analytics Framework for Personalized Dietary Optimization
    R Jayabhaduri, UV Prabanjan, A Sungheetha, MR Gunashekara Reddy, ...
    Second International Conference on IT Innovations and Knowledge Discovery … , 2025
    2025
  • Reducing Digital Footprint in Information Technology Systems Using Reinforcement Learning
    R Jayabhaduri, R Shekhar
    World Congress on Smart Computing, 469-481 , 2025
    2025
  • Real-Time 3D Human Pose Estimation Using Deep Learning Model for Ergonomics
    J Radhakrishnan, V Aadesh, R Ajay Karthik, G Ramana Prasath, ...
    International Journal of Technology and Engineering Studies 8 (1), 34-40 , 2024
    2024
  • A Deep LSTM Recurrent Learning Approach for Sentiment Analysis on Movie Reviews
    GR Khanaghavalle, V Rajalakshmi, R Jayabhaduri, A Kala, PS Femi
    Intelligent Systems and Sustainable Computational Models, 202-211 , 2024
    2024
  • AI-Enhanced Triboelectric Surface Analysis for Smart Urban Accessibility Pattern Detection​
    R Jayabhaduri, D Akey Sungheetha
    6th International Conference Futuristic Trends in Networks and Computing … , 2024
    2024
  • IOT Based WiFi Enabled Smart Gardening System
    V Rajalakshmi, GR Khanaghavalle, A Kala, ...
    IN Patent App. 202,341,006,434 A , 2023
    2023
  • Landmark Recognition Using Transfer Learning
    V Tenkayala, R Jayabhaduri
    International Conference on Advanced Communication Control & Computing … , 2022
    2022
  • An Evolutionary Algorithmic Approach for Single Machine Early Tardy Scheduling Problem
    R Jayabhaduri
    Research Journal of Applied Sciences, Engineering and Technology 11 (6), 666-673 , 2015
    2015
  • An Evolutionary Algorithmic Approach for Airline Crew Scheduling Problem
    G Arul Charles, R Jayabhaduri
    International Journal of Applied Engineering Research 10 (70), 2015 , 2015
    2015