DR. V. Mahesh Kumar Reddy is currently working as an Professor in the Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Proddatur, YSR Kadapa, Andhra Pradesh. He has nearly twelve years of experience in teaching and one and half years of experience in Industry. He has completed his Ph.D. (2020) in Electrical Engineering from Naresuan University, Thailand. He received an M.E. (2012) degree from Hindustan University, Chennai in Department of EEE with Power Electronics and Drives specialization. He received B.Tech (2009) degree in EEE from JNTU, Hyderabad. His areas of interest are Electric Drives and Control, Integrating Internet of Things with Electrical Engineering, Power Electronics, AI and Fuzzy Logic, Communication Engineering. Moreover, he has published more number of papers in the International Journal and International Conference which are indexed by Scopus, Web of Science, etc. He has completed certification courses on “
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Control and Systems Engineering
16
Scopus Publications
253
Scholar Citations
9
Scholar h-index
9
Scholar i10-index
Scopus Publications
Hybrid Quantum Repeater Protocol for Long Distance Secure Quantum Communication Karthikhesvaran S. S., Mahesh Kumar Reddy Vennapusa, Prasanna Venkatesan G K D Conference Proceedings IEEE SOUTHEASTCON, 2026 So far, quantum communication has promised unconditionally secure information transfer through protocols such as quantum key distribution. The practical deployment of QKD faces severe limitations due to decoherence, photon loss, and limited transmission distances in optical fibers and free space. The current systems are not scalable and require trusted relays, which are costly and introduce security vulnerabilities. This paper solves the core problem of the range extension in quantum networks by proposing HQRP, a novel hybrid quantum repeater protocol, for high-rate entanglement distribution in which single-spin photon transducers are combined with multiplexed ensemble-based atomic frequency comb memories. The HQRP uniquely combines the principles of twin-field QKD and error-corrected entanglement swapping, achieving secret key rates of tens of bits per second over 1000 km with only nine repeater nodes. Simulations demonstrate a <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{5 x}$</tex> improvement of the key rate with respect to traditional measurement-device-independent QKD without repeaters, including robustness against 20 % photon loss. These results demonstrate the feasibility of using near-term hardware, such as room-temperature telecom-compatible memories, and pave the way toward global quantum networks. The effective efficiency of the protocol in practical environments is still affected by variations in environmental temperatures, which affect AFC memories, and require sub-nanosecond timing precision to coordinate nodes over <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{1 0 0 0 ~ k m}$</tex>. Future versions will employ adaptive timing based on machine learning to address these engineering issues. Index Terms-Quantum repeaters, entanglement distribution, QKD, decoherence mitigation, hybrid quantum networks.
A HYBRID STYLOMETRIC-TRANSFORMER EMBEDDING FRAMEWORK FOR ROBUST AUTHORSHIP VERIFICATION AGAINST GENERATIVE AI ADVERSARIES Journal of Theoretical and Applied Information Technology Journal of Theoretical and Applied Information Technology, 2026 Authorship verification (AV) remains critical to attribute text provenance and to limit misuse of large language models (LLMs). Existing detectors typically used handcrafted stylometric cues or deep transformer embeddings but lacked robustness to model mimicry and targeted obfuscation and often required large labeled corpora. This work proposes Hybrid Stylometric–Transformer Embedding Framework (HSTEF), a hybrid, explainable AV architecture that fuses multi-level stylometric descriptors with cross-attended transformer embeddings to form a compact verification representation. HSTEF integrated engineered lexical, orthographic and syntactic stylometric vectors, a pre-trained transformer encoder fine-tuned with contrastive and calibration objectives, and a cross-modal fusion module that enabled bidirectional style–semantic interaction while preserving interpretability. The method was evaluated on the PAN CLEF 2025 Voight-Kampff corpus containing human and machine authored texts across genres and including deliberate obfuscations. Experiments used one classical baseline (Linear SVM on TF-IDF, SVM) and one hybrid baseline (DistilBERT + stylometric features) under identical preprocessing and metrics (ROC-AUC, F1, Brier, C@1, and computation). HSTEF produced an absolute ROC-AUC increase of ≈0.07 and an absolute F1 increase of ≈0.07 over the hybrid baseline while improving calibration (Brier reduced ≈47%) at a controlled inference cost increase consistent with forensic deployment scenarios. These results indicate that a Hybrid Stylometric–Transformer Embedding Framework offers a tractable accuracy and robustness trade-off for AV against modern generative AI adversaries.
Enhancing cooling efficiency of pottery clay with rice husk for IoT- enabled off-grid water cooling system Ananya Das, Sanjib Moulick, Subhra Debdas, Vennapusa Mahesh Kumar Reddy, Pabitra Kumar Tripathy, Pankaj Kumar Energy Reports, 2025 Soil, widely available and known for leveraging the principles of evaporative cooling, has been historically used in pottery-based cooling systems. Enhancing the efficiency of cooling, soil requires improved porosity and water absorption capacity, which can be achieved by incorporating burnout additives like rice husk. Rice husk, an agricultural by-product, is abundant and environmentally problematic when discarded or burned, making its utilization in soil a sustainable solution. This research underscores the potential of rice husk-enhanced pottery soil combined with IoT technology as a transformative solution for eco-friendly and intelligent water-cooling applications. The study investigates to enhance the evaporative cooling efficiency in pottery soil through the integration of rice husk as additives. Soil samples are sourced from three distinct geographical locations in Bhubaneswar, Odisha, and characterized based on their geotechnical and physical properties, including porosity, and water absorption capacity, that directly influence the evaporative cooling. The research aims to determine the optimal soil-rice husk composition for maximizing cooling efficiency. Experimental earthen containers are fabricated with varying rice husk and sand proportions, fired at 1300 °C, and subjected to controlled water-cooling tests. For the research, an IoT-based temperature monitoring system, employing DS18B20 sensors and ESP32 microcontrollers, record temperature variations to assess performance. The results indicate that soil from a site is identified with its higher porosity and water absorption capacity, exhibited superior evaporative cooling efficiency. Containers made with 30 % rice husk of the total content demonstrate improved cooling performance due to enhanced porosity and water absorption capacity. The optimized soil composition is further implemented in an IoT-enabled dynamic flow earthen water-cooling system to evaluate continuous cooling performance. Integrated IoT sensors monitor and regulate key parameters such as water temperature, water level of the earthen chambers, and water flow rate, ensuring optimal cooling performance in real-time. The system cool water from 32.5 °C to 20 °C in 4 min and 18 s with a 3 % evaporation rate. In this research, IoT has been implemented for monitoring and regulation; however, it can be excluded in practical applications, with solar power integration ensuring operation without dependence on grid electricity. This system is highly useful in resource-limited areas, as it offers an eco-friendly, passive alternative for water cooling without relying on advanced infrastructures.
Design and Implementation of a Photovoltaic Solar Powered Ice Cube Making Machine for off Grid Applications Kumar Reddy Cheepati, Mahesh Kumar Reddy V, Avagaddi Prasad, Kamalakkannan S, Parimalasundar E, Dharmaprakash R Ssrg International Journal of Electrical and Electronics Engineering, 2025 Ice cube making machines are widely useful in beverages, hospitals, healthcare, retail stores, manufacturing, entertainment, seafood, agriculture, horticulture, construction and emergency services. Most of these are grid-connected and work on AC supply. For some of the applications, like mobile food vans, roadside vendors, and military and research stations, will require off-grid ice cube-making machines. Off grid ice cube-making machine works with solar power without any grid connection. Harnessing maximum solar power for an ice cube-making machine is a challenging task. In this paper, an off-grid ice cube-making system has been developed with the help of a solar PV panel, MPPT charge controller, solar battery and inverter. The proposed system has been developed to provide six to eight hours backup even when there is no irradiation during rainy, fog and dark conditions. The hardware results proved that the proposed ice cube-making machine is a novel solution, and it is ideal for off-grid applications.
Spatiotemporal Federated Learning for Privacy-Preserving Load Forecasting and Appliance Scheduling in Smart City Homes Suresh Thangakrishnan M, Mahesh Kumar Reddy V, Marimuthu Karuppiah, Sanjeev Thakur IEEE Transactions on Consumer Electronics, 2025 As smart cities evolve, optimizing energy use within residential environments via intelligent consumer electronics becomes crucial to ensure grid stability, enhance user comfort, and promote sustainability. This paper proposes a novel IoT-enabled demand response (DR) framework that integrates AI-based spatio-temporal load forecasting and intelligent appliance scheduling through federated learning (FL) across consumer electronics such as smart meters, home hubs, and smartphones. The system leverages household-level energy consumption data, which are inherently temporal and spatial in nature, to make localized, context-aware scheduling decisions while preserving data privacy. To address key challenges in home energy management, such as data heterogeneity, forecast uncertainty, and multi-objective optimization, the framework employs a Split Federated Learning (Split-FL) architecture with Gated Recurrent Units (GRU) for accurate, privacy-preserving load forecasting. Raw data remain on edge devices, ensuring compliance with privacy regulations while enabling collaborative model training. Additionally, a robust hybrid metaheuristic algorithm, combining the Improved Grey Wolf Optimizer (IGWO) and Teaching-Learning-Based Optimization (TLBO), is deployed at the Fog layer to solve the complex multi-objective appliance scheduling problem, explicitly accounting for forecast uncertainties modeled via ellipsoidal sets. Comprehensive experimental evaluations in real-world datasets (REDD, UK-DALE and Pecan Street) demonstrate that the proposed framework achieves an average reduction of 32% in total energy cost, a decrease of 51% in user discomfort, and a reduction of 40% in the peak to average ratio, while maintaining a compliance rate of demand response 92%. The Split-FL GRU forecasting model also outperforms centralized approaches in prediction accuracy. By enabling decentralized, adaptive, and privacy-preserving intelligence across heterogeneous consumer devices, this framework supports scalable and resilient energy optimization in smart homes. It directly contributes to the operational efficiency and sustainability of smart city infrastructures and lays the foundation for future location-sensitive energy recommender systems.
Cost-Effective Voltage Stability Enhancement via HEES-based Interline DC Flexible Voltage Restorer Kuruva Raju, K. Kiran, K. Lokesh, V Mahesh Kumar Reddy, R. Senthil Kumar, K. M. D. Rajesh Babu Proceedings of the 9th International Conference on Electronics Communication and Aerospace Technology Iceca 2025, 2025 The stability of DC distribution systems is often compromised by voltage sag, swell, and imbalance caused by renewable intermittency and nonlinear loads. Traditional battery storage systems, though cost-effective, suffer from limited dynamic response, while high-conducting electromagnetic energy storage (HEES) offers millisecond-level compensation at high cost. To address this trade-off, a novel Interline DC Flexible Voltage Restorer (IFVR) is proposed, where a single HEES module is shared across multiple distribution feeders. The novelty lies in its priority-based switching strategy and multilevel inverter topology, which allow rapid injection/absorption of compensating current with reduced hardware. The proposed design integrates HEES with line-selector and mode-selector switches to dynamically restore interline voltages. Simulation studies were performed in MATLAB/Simulink with load resistance variations from 0.4 Ω to 10.1 Ω under sag (180 V), swell (260 V), and normal (230 V) operating conditions. Results demonstrate a transient recovery time below 1 s, voltage regulation within ±2%, and harmonic distortion below 3%. Compared with conventional DVR-based methods, the IFVR achieves a 25% reduction in storage capacity requirements and 18% improvement in response speed. This makes the configuration highly suitable for renewable microgrids, data centers, and EV charging systems, ensuring cost-efficient, scalable, and reliable DC voltage stabilization.
CERVICAL CANCER CLASSIFICATION USING RANDOMISED STACKED DIFFERENTIAL DECISION TREE CLASSIFIER FOR SMART ECO-FRIENDLY SYSTEM Journal of Environmental Protection and Ecology, 2025
An Integrated Economic and Emissions Dispatch Problem using the Sparrow Search Algorithm Mahesh Kumar Reddy V, Venkatesh P, Dharmaprakash R, Sendil Kumar S Ssrg International Journal of Electrical and Electronics Engineering, 2023 - The economic dispatch of the Micro-Grid (MG) in the current scenario considers the scheduling cycle with the lowest cost and effectively manages multiple Distributed Generations (DGs) over an extended duration, making it a more appropriate choice for a functional system. The unpredictability of wind and solar energy poses a challenge in solving the economic dispatch problem. Implementing intelligent algorithms and multi-objective optimum dispatching systems has demonstrated significant cost reduction and enhanced environmental sustainability in microgrid operations. The primary objective of the economic dispatch algorithm in the context of a Micro-Grid (MG) is to minimize expenses throughout the scheduling cycle while efficiently coordinating many distributed generators over an extended duration. This makes it highly suitable for operational systems. Due to their inherent variability, the economic resolution of the dispatch problem associated with wind and solar energy requires significant time. Utilizing smart algorithms and multi-objective functions for optimized dispatching generator capacity can potentially.
Reactive power optimization in distribution systems considering load levels for economic benefit maximization G. Srinivasan, V. Mahesh Kumar Reddy, P. Venkatesh, E. Parimalasundar Electrical Engineering and Electromechanics, 2023 Introduction. The need for electrical energy has been increased sharply due to hasty growth in industrials, social and economic improvements. From the previous studies, it has been agreed that almost 13 % of the total power generated is wasted as heat loss at distribution level. It has been extensively recognized that the node voltage profile along the distribution system can be enhanced under steady state power transfer controlled by proper reactive power compensation. Capacitors have been acknowledged as reactive power compensating device in distribution systems to achieve technical and economical benefits. Novelty of this work is the application of Archimedes optimization algorithm for reactive power optimization in distribution systems so as to obtain an improved solution and also a real 94-bus Portuguese network and modified 12-bus network has been taken and validated for three different load levels which are totally new. Purpose of the proposed work is to maximize the economic benefit by reducing the power loss and capacitor purchase cost at three different load conditions subject to satisfaction of equality and inequality constraints. Methods. The economic benefit has been validated using Archimedes optimization algorithm for three load levels considering three distribution systems. Results. The computational outcomes indicated the competence of the proposed methodology in comparison with the previously published works in power loss minimization, bus voltage enhancement and more economical benefit and proved that the proposed methodology performs well compared to other methods in the literature.
IOT based Smart Meter Using Node-Red V Mahesh Kumar Reddy, Malavika K. V, Lokasree B S, K. Nanda Kumar 2023 International Conference on Artificial Intelligence and Smart Communication Aisc 2023, 2023
Development Of A Hybrid Controller For The Speed Control Of Single-Phase Induction Motor Arpn Journal of Engineering and Applied Sciences, 2021
Iot based platform for smart electric fans , Mahesh Kumar Reddy Vennapusa*, Suchart Yammen, and International Journal of Innovative Technology and Exploring Engineering, 2019
IoT based speed control of smart fan Suchart Yammen, Sureerat Tang, Mahesh Kumar Reddy Vennapusa Ecti Damt Ncon 2019 4th International Conference on Digital Arts Media and Technology and 2nd Ecti Northern Section Conference on Electrical Electronics Computer and Telecommunications Engineering, 2019
RECENT SCHOLAR PUBLICATIONS
Enhancing cooling efficiency of pottery clay with rice husk for IoT-enabled off-grid water cooling system A Das, S Moulick, S Debdas, VMK Reddy, PK Tripathy, P Kumar Energy Reports 14, 2642-2657 , 2025 2025.0
Spatiotemporal Federated Learning for Privacy-Preserving Load Forecasting and Appliance Scheduling in Smart City Homes M Karuppiah, S Thakur IEEE Transactions on Consumer Electronics , 2025 2025.0 Citations: 2
Preface: 1st International Conference on Innovative Approaches in Engineering and Technology (ICIAET-2024) MKR Vennapusa, A Shaik AIP Conference Proceedings 3237 (1), 010001 , 2025 2025.0
Optimizing intrusion detection systems using parallel metric learning M Sudha, VMK Reddy, WD Priya, SM Rafi, S Subudhi, S Jayachitra Computers And Electrical Engineering 110, 108869 , 2023 2023.0 Citations: 39
Reactive power optimization in distribution systems considering load levels for economic benefit maximization G Srinivasan, VMK Reddy, P Venkatesh, E Parimalasundar Electrical Engineering & Electromechanics, 83-89 , 2023 2023.0 Citations: 26
IOT based smart meter using node-red VMK Reddy, BS Lokasree, KN Kumar 2023 International Conference on Artificial Intelligence and Smart … , 2023 2023.0 Citations: 16
Modelling and simulation of grid connected photovoltaic inverter using incremental conductance method KV Malavika, KRV Mahesh, KK Nanda AIP Conference Proceedings 2452 (1), 040005 , 2022 2022.0 Citations: 26
Modeling of fuzzy logic based MPPT for PV array in Simulink/MATLAB TP Mish-Al, KK Nanda, KRV Mahesh AIP Conference Proceedings 2452 (1), 040007 , 2022 2022.0 Citations: 21
Energy Reports A Das, S Moulick, S Debdas, VMK Reddy, PK Tripathy, P Kumar 2022.0
Air Flow Control of a Smart Electric Fan using IoT Solutions SY Mahesh Kumar Reddy Vennapusa International Journal of Engineering and Advanced Technology (IJEAT) 9 (2 … , 2019 2019.0 Citations: 21
Iot Based Platform for Smart Electric Fans SY Mahesh Kumar Reddy Vennapusa International Journal of Innovative Technology and Exploring Engineering … , 2019 2019.0 Citations: 25
IoT based speed control of Smart Fan S Yammen, S Tang, MKR Vennapusa 2019 Joint International Conference on Digital Arts, Media and Technology … , 2019 2019.0 Citations: 34
IOT-BASED HOME APPLIANCE SYSTEM (SMART FAN) ST Mehran Ektesabi, Saman A. Gorji, Amir Moradi, 2 Suchart Yammen, V. Mahesh ... 8th International Conference on Artificial Intelligence, Soft Computing and … , 2018 2018.0 Citations: 9
Development Of A Hybrid Controller For The Speed Control Of Single-Phase Induction Motor MKR Vennapusa, SS Tang, S Yammen 2006.0 Citations: 33
An Integrated Economic and Emissions Dispatch Problem using the Sparrow Search Algorithm VMK Reddy, P Venkatesh, R Dharmaprakash, SS Kumar Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Optimizing intrusion detection systems using parallel metric learning M Sudha, VMK Reddy, WD Priya, SM Rafi, S Subudhi, S Jayachitra Computers And Electrical Engineering 110, 108869 , 2023 2023.0 Citations: 39
IoT based speed control of Smart Fan S Yammen, S Tang, MKR Vennapusa 2019 Joint International Conference on Digital Arts, Media and Technology … , 2019 2019.0 Citations: 34
Development Of A Hybrid Controller For The Speed Control Of Single-Phase Induction Motor MKR Vennapusa, SS Tang, S Yammen 2006.0 Citations: 33
Reactive power optimization in distribution systems considering load levels for economic benefit maximization G Srinivasan, VMK Reddy, P Venkatesh, E Parimalasundar Electrical Engineering & Electromechanics, 83-89 , 2023 2023.0 Citations: 26
Modelling and simulation of grid connected photovoltaic inverter using incremental conductance method KV Malavika, KRV Mahesh, KK Nanda AIP Conference Proceedings 2452 (1), 040005 , 2022 2022.0 Citations: 26
Iot Based Platform for Smart Electric Fans SY Mahesh Kumar Reddy Vennapusa International Journal of Innovative Technology and Exploring Engineering … , 2019 2019.0 Citations: 25
Modeling of fuzzy logic based MPPT for PV array in Simulink/MATLAB TP Mish-Al, KK Nanda, KRV Mahesh AIP Conference Proceedings 2452 (1), 040007 , 2022 2022.0 Citations: 21
Air Flow Control of a Smart Electric Fan using IoT Solutions SY Mahesh Kumar Reddy Vennapusa International Journal of Engineering and Advanced Technology (IJEAT) 9 (2 … , 2019 2019.0 Citations: 21
IOT based smart meter using node-red VMK Reddy, BS Lokasree, KN Kumar 2023 International Conference on Artificial Intelligence and Smart … , 2023 2023.0 Citations: 16
IOT-BASED HOME APPLIANCE SYSTEM (SMART FAN) ST Mehran Ektesabi, Saman A. Gorji, Amir Moradi, 2 Suchart Yammen, V. Mahesh ... 8th International Conference on Artificial Intelligence, Soft Computing and … , 2018 2018.0 Citations: 9
Spatiotemporal Federated Learning for Privacy-Preserving Load Forecasting and Appliance Scheduling in Smart City Homes M Karuppiah, S Thakur IEEE Transactions on Consumer Electronics , 2025 2025.0 Citations: 2
An Integrated Economic and Emissions Dispatch Problem using the Sparrow Search Algorithm VMK Reddy, P Venkatesh, R Dharmaprakash, SS Kumar Citations: 1
Enhancing cooling efficiency of pottery clay with rice husk for IoT-enabled off-grid water cooling system A Das, S Moulick, S Debdas, VMK Reddy, PK Tripathy, P Kumar Energy Reports 14, 2642-2657 , 2025 2025.0
Preface: 1st International Conference on Innovative Approaches in Engineering and Technology (ICIAET-2024) MKR Vennapusa, A Shaik AIP Conference Proceedings 3237 (1), 010001 , 2025 2025.0
Energy Reports A Das, S Moulick, S Debdas, VMK Reddy, PK Tripathy, P Kumar 2022.0
