Roshan Mukindrao Bodile

@nitj.ac.in

Assistant Professor and Electronics and Communication Engineering
Dr B R Ambedkar NIT Jalandhar

Roshan Mukindrao Bodile


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https://researchid.co/rmbodile

EDUCATION

B.E.
ME..
Ph.D.

RESEARCH INTERESTS

Biomedical Signal Processing, ECG/EEG Denoising, Source localization, Heart and Brain Diseases, Optimization Techniques, Machine Learning.
16

Scopus Publications

99

Scholar Citations

7

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Integrated AI and 6G Driven e-Health: A Trifecta for Smart Healthcare
    Rohit Singh, Roshan Bodile, Aryan Kaushik, Amit Dolas, Amandeep Kaur, Periklis Chatzimisios
    IEEE Communications Standards Magazine, 2026
    The integration of Artificial Intelligence (AI) and 6G wireless technology is transforming the future of healthcare services, allowing for real-time diagnostics, remote procedures, intelligent patient monitoring, and ultra-fast data processing. In light of this potential, this article explores creating a sophisticated e-health system by combining neuro-symbolic AI with 6G wireless networks. Firstly, 6G neuro-symbolic AI, an advanced AI tool that is the fusion of a 6G wireless network, a neural network, and symbolic AI, improves cognitive modeling and decision-making, and communication speed in e-healthcare is presented. Next, an integrated architecture of a 6G-neuro-symbolic AI healthcare system is proposed, which is a combination of various aspects of AI-assisted computing and 6G transmission capabilities. Moreover, we evaluated the performance of the proposed architecture by analyzing (a) false alarm rate, (b) detection accuracy, (c) computational cost, (d) latency, and (e) energy efficiency. The evaluation results prove that 6G neuro-Symbolic AI provides better results compared to the only federated learning (FL) method. Lastly, we explore practical potential challenges in AI and 6G-driven e-health-care systems, considering infrastructure readiness, interoperability issues, and ethical and legal issues.
  • Enhanced brain tumor classification in multi modal images: leveraging self-calculated missing modality compensation transformer with NetB7++
    Narmada Kari, Sanjay Kumar Singh, Roshan M. Bodile
    Expert Systems with Applications, 2026
  • Insights Review of Microelectronic Devices
    Rambabu Kusuma, Roshan Bodile
    Microelectronics Simulations Modeling and Applications, 2026
    The continued scaling of semiconductor devices to smaller dimensions has posed significant challenges for traditional planar MOSFETs, including short-channel effects, power dissipation, and leakage currents. To overcome these limitations, various advanced transistor architectures have emerged. FinFETs are widely adopted in sub-22-nm nodes due to their 3D fin structure, which improves electrostatic control, reduces leakage, and enhances drive current. This makes FinFETs ideal for both low-power systems and high-performance applications. Tunnel FETs (TFETs) use quantum tunneling to provide an alternate route to current conduction allowing for a subthreshold swing of less than 60 mV per decade. This feature makes TFETs particularly appealing for ultra-low-power applications, as they provide great energy efficiency. However, one major problem for TFETs is raising their on-state current, which is lower than that of traditional transistors, such as MOSFETs or FinFETs, restricting their use in high-performance applications. Despite this, the potential of TFETs for power-sensitive devices continues to drive research efforts aimed at improving their overall performance and scalability. Nanowire FETs (NW-FETs) utilize a cylindrical, multi-gate design that completely surrounds the channel offering excellent electrostatic control and scalability for future technology nodes. Similarly, nanosheet FETs provide a planar, multi-gate approach with stacked nanosheets enabling further scaling and enhanced performance. Emerging transistors, like the ferroelectric FET (Fe-FET) and negative capacitance FET (NC-FET), focus on reducing power consumption by integrating ferroelectric materials. Fe-FETs offer non-volatile memory capabilities, while NC-FETs utilize the negative capacitance effect to reduce the subthreshold slope enhancing switching speed and lowering power consumption. Additionally, planar nano-FETs and vertical nano-FETs are attracting growing interest for their ability to surpass the limitations of traditional MOSFETs. These advanced transistor designs offer improved scalability and enhanced electrostatic control positioning them as promising candidates for next-generation semiconductor technologies. Their unique architectures enable better performance in high-density and power-efficient applications making them key contenders in the future of nanoelectronics. Planar nano-FETs provide enhanced channel control, while vertical Nano-FETs stack transistors vertically improving device density and enabling 3D integration for next-generation chips. This chapter focuses on operational principles, advantages, and challenges of different types of FETs. By comparing their performance, scalability, and energy efficiency, these novel devices offer valuable insights into how they can drive future semiconductor innovations meeting the increasing demand for higher performance and lower power consumption in modern electronics. By overcoming old technology restrictions, they pave the way for more efficient, scalable solutions, which are increasingly important as devices shrink and power efficiency becomes a major aspect in next-generation applications.
  • HHM-ZUNet: hybrid hierarchical model based on Z-Net and modified U-Net++ with variable multi-attention for brain tumor detection and classification
    Narmada Kari, Sanjay Kumar Singh, Roshan M. Bodile
    European Physical Journal Plus, 2025
  • Exploring Elemental Properties of Intelligent Reflecting Surfaces
    Ravi Kushwaha, Rohit Chaurasiya, Roshan M. Bodile, Aryan Kaushik, Rohit Singh, Wonjae Shin
    2025 IEEE International Conference on Communications Workshops Icc Workshops 2025, 2025
    Intelligent Reflecting Surfaces (IRSs), renowned for their ability to reconfigure wireless signals, operate on the principle of dynamic phase tuning. The reflected signals are configured by controlling the induced capacitance at each element, typically through circuit components such as varactor diodes. Beyond the applied voltage, IRS operation is influenced by various aspects such as material selection, switching speed, and circuit-level characteristics, which are often overlooked in favor of wireless performance in existing research. To address this gap, this work explores the circuit properties of IRS unit cells, highlighting its significance and performance impact. Specifically, this work presents an equivalent electrical diagram of the IRS unit cells through transmission line modelling, illustrating its adjustable parameters and dependence on elemental driven circuit. Besides, a comparative analysis has been conducted by modelling the varactor diode, with simulation results demonstrating the effects of material properties and operating frequency for various IRS applications.
  • Advancing Healthcare Through 6G IoMT: Latest Opportunities, Trends, and Challenges
    Roshan M. Bodile, Aryan Kaushik, Rohit Singh, Richa Sharma, Amandeep Kaur, Ali Kashif Bashir
    IEEE Internet of Things Magazine, 2025
    The healthcare sector has been substantially influenced by the advancements in wireless communications. Moreover, the advent of the sixth generation (6G) tends to add even more capabilities to the forthcoming healthcare sector, advancing sensing precision and backbone support for Internet of medical things (IoMT). Leveraging 6G capabilities, the IoMT framework has the potential to transform healthcare practices and open new research possibilities. Realizing the growing importance of this topic, this work brings together several innovative aspects of 6G communication, highlighting its impact on human-centred technologies, particularly with the emergence of smart IoMT. As a proof of concept, an advanced healthcare architecture has been presented with a layer-wise operation arrangement that complements 6G references. To demonstrate the effectiveness of the proposed design, key results have been generated and analyzed. Additionally, this work explores 6G-enabled modern tools, highlighting specific requirements related to standardization and implementation. Finally, this work offers valuable insights into the role of wireless technology in shaping the forthcoming healthcare sector, including associated challenges, opportunities, and planning for the future.
  • Diagnosis of Clustered Microcalcifications in Breast Cancer Using Mammograms
    Narmada Kari, Sanjay Kumar Singh, Roshan M. Bodile
    Lecture Notes in Electrical Engineering, 2024
  • Integrated AI and 6G Driven e-Health: Enabling Design, Challenges, and Future Prospects
    Amit Dolas, Roshan Bodile, Aryan Kaushik, Amandeep Kaur, Rohit Singh, Periklis Chatzimisios
    2024 IEEE Conference on Standards for Communications and Networking Cscn 2024, 2024
    The next generation of wireless networks is set to leverage artificial intelligence (AI) algorithms for enhanced application support, which is currently intensifying through the fusion of modern learning techniques (e.g., symbolic AI and neural networks). Further, the fusion of these AI tools offers immense potential, addressing critical wireless use cases with a focus on driving advancements in the communication and healthcare industry. Observing these potentials, this paper explores the integration of AI with 6G networks to develop an advanced e-health system. Firstly, we provide an overview of how the fusion of symbolic AI, i.e., an advanced AI tool, enhances decision-making and cognitive modeling in e-healthcare in conjunction with the 6G network. Further, we propose an integrated 6G-neuro-symbolic AI healthcare architecture that leverages several enabling features of AI-assisted computing and 6G transmission support. Moreover, the performance of the proposed architecture has been evaluated, presenting prediction accuracy and latency. Finally, we discuss industrial and standardization challenges, offering recommendations for addressing infrastructure, scalability, and ethical concerns in AI-driven healthcare systems.
  • A deep neural network-correlation phase sensitive mask based estimation to improve speech intelligibility
    Shoba Sivapatham, Asutosh Kar, Roshan Bodile, Vladimir Mladenovic, Pitikhate Sooraksa
    Applied Acoustics, 2023
  • A software approach for analysis and reasoning of urban floods using GIS and SWMM
    International Conference on Structural Health Monitoring of Intelligent Infrastructure Transferring Research into Practice Shmii, 2022
  • Improved complete ensemble empirical mode decomposition with adaptive noise: quasi-oppositional Jaya hybrid algorithm for ECG denoising
    Roshan M. Bodile, T. V. K. Hanumantha Rao
    Analog Integrated Circuits and Signal Processing, 2021
  • Adaptive Filtering of Electrocardiogram Signal Using Hybrid Empirical Mode Decomposition-Jaya algorithm
    Roshan Bodile, T. V. K. Hanumantha Rao
    Journal of Circuits Systems and Computers, 2021
  • Removal of power-line interference from ECG using decomposition methodologies and kalman filter framework: A comparative study
    Roshan M. Bodile, Venkata K.H.R. Talari
    Traitement Du Signal, 2021
  • ANN based Scaling of Rainfall Data for Urban Flood Simulations
    Vinay Ashok Rangari, K. Veerendra Gopi, Umamahesh V Nanduri, Roshan Bodile
    Proceedings of B Htc 2020 1st IEEE Bangalore Humanitarian Technology Conference, 2020
  • ECG Denoising Using Cubature Quadrature Kalman Filter Approach
    Roshan M. Bodile, T. V. K. Hanumantha Rao
    Proceedings 2020 IEEE India Council International Subsections Conference Indiscon 2020, 2020
  • ECG Denoising using cubature kalman filter framework
    Proceedings of the 5th International Conference on Communication and Electronics Systems Icces 2020, 2020

RECENT SCHOLAR PUBLICATIONS

  • Insights Review of Microelectronic Devices
    R Kusuma, R Bodile
    Microelectronics: Simulations, Modeling and Applications , 2026
    2026
  • Integrated AI and 6G Driven e-Health: A Trifecta for Smart Healthcare
    R Singh, RM Bodile, A Kaushik, A Dolas, A Kaur, P Chatzimisios
    IEEE Communications Standards Magazine , 2026
    2026
  • Advanced Image Encryption Framework for Securing Gray and Color Medical Images
    SK Veeramalla, R Bodile, B Jailsingh
    Revolutionizing Metabolic Medicine With Artificial Intelligence, 253-272 , 2026
    2026
  • Advanced Image Encryption Framework for Securing Gray and Color Medical Images
    V Santhosh Kumar, R Bodile, J B.
    Revolutionizing Metabolic Medicine With Artificial Intelligence , 2025
    2025
  • Enhanced brain tumor classification in multi modal images: leveraging self-calculated missing modality compensation transformer with NetB7++
    N Kari, SK Singh, RM Bodile
    Expert Systems with Applications, 130102 , 2025
    2025
    Citations: 1
  • HHM-ZUNet: hybrid hierarchical model based on Z-Net and modified U-Net plus plus with variable multi-attention for brain tumor detection and classification
    N Kari, SK Singh, RM Bodile
    EUROPEAN PHYSICAL JOURNAL PLUS 140 (8) , 2025
    2025
  • Material Foundations of HEMT Performance: A Systematic Investigation of Substrate Effects in Dual-Channel AlGaN/AlN/GaN Heterostructures
    S Srivastava, BR Mukindrao
    2025 IEEE 6th India Council International Subsections Conference (INDISCON), 1-6 , 2025
    2025
  • Exploring Reflecting Phases in RIS-Assisted Indexed Multiplexing for 6G IoT Applications
    R Singh, A Kaushik, A Dolas, RM Bodile, W Shin
    024 IEEE Globecom Workshops (GC Wkshps), pp. 1-6 , 2025
    2025
  • HHM-ZUNet: hybrid hierarchical model based on Z-Net and modified U-Net++ with variable multi-attention for brain tumor detection and classification
    K Narmada, SS Kumar, B Roshan M.
    The European Physical Journal Plus 140 (805) , 2025
    2025
    Citations: 2
  • A Systematic Investigation of Substrate Effects in Dual-Channel AlGaN/AlN/GaN Heterostructures
    S Srivastava, R Bodile
    IEEE INDISCON 2025, 1-5 , 2025
    2025
  • Exploring Elemental Properties of Intelligent Reflecting Surfaces
    R Kushwaha, R Chaurasiya, RM Bodile, A Kaushik, R Singh, W Shin
    2025 IEEE International Conference on Communications (ICC) Workshop, 1-6 , 2025
    2025
  • Advancing Healthcare Through 6G IoMT: Latest Opportunities, Trends, and Challenges
    RM Bodile, A Kaushik, R Singh, R Sharma, A Kaur, AK Bashir
    IEEE Internet of Things Magazine 8 (no. 4), 37-44 , 2025
    2025
    Citations: 5
  • Exploring Reflecting Phases in RIS-Assisted Indexed Multiplexing for 6G IoT Applications
    R Singh, A Kaushik, A Dolas, RM Bodile, W Shin
    2024 IEEE Global Communications Conference (GLOBECOM) Workshop, 1-6 , 2024
    2024
  • Integrated AI and 6G driven e-health: Enabling design, challenges, and future prospects
    A Dolas, R Bodile, A Kaushik, A Kaur, R Singh, P Chatzimisios
    2024 IEEE Conference on Standards for Communications and Networking (CSCN … , 2024
    2024
    Citations: 8
  • A quick guide to quantum communication
    R Singh, RM Bodile
    arXiv preprint arXiv:2402.15707 , 2024
    2024
    Citations: 17
  • A deep neural network-correlation phase sensitive mask based estimation to improve speech intelligibility
    S Sivapatham, A Kar, R Bodile, V Mladenovic, P Sooraksa
    Applied Acoustics 212, 109592 , 2023
    2023
    Citations: 9
  • Alzheimer’s disease classification using random forest algorithm with optimal feature extraction
    N Kari, SK Singh, RM Bodile
    European Chemical Bulletin , 2023
    2023
    Citations: 2
  • Diagnosis of Clustered Microcalcifications in Breast Cancer Using Mammograms
    N Kari, SK Singh, RM Bodile
    International Conference on Sustainable Technology and Advanced Computing in … , 2023
    2023
  • Machine Learning-Based Arrhythmia Classification: A Comprehensive Review
    P Gautam, M Singh, BR Mukindrao
    Integrating Digital Health Strategies for Effective Administration, 345-377 , 2023
    2023
  • A comprehensive review on agriculture-based pesticide spraying robot
    KM Dange, RM Bodile, B Srinivasa Varma
    International Conference on Sustainable and Innovative Solutions for Current … , 2022
    2022
    Citations: 6

MOST CITED SCHOLAR PUBLICATIONS

  • A quick guide to quantum communication
    R Singh, RM Bodile
    arXiv preprint arXiv:2402.15707 , 2024
    2024.0
    Citations: 17
  • Improved complete ensemble empirical mode decomposition with adaptive noise: quasi-oppositional Jaya hybrid algorithm for ECG denoising
    RM Bodile, RHT V. K.
    Analog Integrated Circuits and Signal Processing , 2021
    2021.0
    Citations: 12
  • Adaptive filtering of electrocardiogram signal using hybrid empirical mode decomposition-Jaya algorithm
    R Bodile, TVKH Rao
    Journal of Circuits, Systems and Computers 30 (12), 2150209 , 2021
    2021.0
    Citations: 10
  • A deep neural network-correlation phase sensitive mask based estimation to improve speech intelligibility
    S Sivapatham, A Kar, R Bodile, V Mladenovic, P Sooraksa
    Applied Acoustics 212, 109592 , 2023
    2023.0
    Citations: 9
  • Ecg denoising using cubature kalman filter framework
    RM Bodile, TVKH Rao
    2020 5th International Conference on Communication and Electronics Systems … , 2020
    2020.0
    Citations: 9
  • Integrated AI and 6G driven e-health: Enabling design, challenges, and future prospects
    A Dolas, R Bodile, A Kaushik, A Kaur, R Singh, P Chatzimisios
    2024 IEEE Conference on Standards for Communications and Networking (CSCN … , 2024
    2024.0
    Citations: 8
  • Removal of Power-Line Interference from ECG Using Decomposition Methodologies and Kalman Filter Framework: A Comparative Study.
    RM Bodile, VKHR Talari
    Traitement du Signal 38 (3), 875-881 , 2021
    2021.0
    Citations: 7
  • A comprehensive review on agriculture-based pesticide spraying robot
    KM Dange, RM Bodile, B Srinivasa Varma
    International Conference on Sustainable and Innovative Solutions for Current … , 2022
    2022.0
    Citations: 6
  • ANN based scaling of rainfall data for urban flood simulations
    VA Rangari, KV Gopi, UV Nanduri, R Bodile
    2020 IEEE Bangalore Humanitarian Technology Conference (B-HTC), 1-6 , 2020
    2020.0
    Citations: 6
  • Advancing Healthcare Through 6G IoMT: Latest Opportunities, Trends, and Challenges
    RM Bodile, A Kaushik, R Singh, R Sharma, A Kaur, AK Bashir
    IEEE Internet of Things Magazine 8 (no. 4), 37-44 , 2025
    2025.0
    Citations: 5
  • HHM-ZUNet: hybrid hierarchical model based on Z-Net and modified U-Net++ with variable multi-attention for brain tumor detection and classification
    K Narmada, SS Kumar, B Roshan M.
    The European Physical Journal Plus 140 (805) , 2025
    2025.0
    Citations: 2
  • Alzheimer’s disease classification using random forest algorithm with optimal feature extraction
    N Kari, SK Singh, RM Bodile
    European Chemical Bulletin , 2023
    2023.0
    Citations: 2
  • ECG Denoising Using Cubature Quadrature Kalman Filter Approach
    RM Bodile, TVKH Rao
    2020 IEEE India Council International Subsections Conference (INDISCON), 216-220 , 2020
    2020.0
    Citations: 2
  • Removal of power-line interference from ECG using decomposition methodologies and kalman filter framework: a comparative study. Traitement Signal 38 (3), 875–881 (2021)
    RM Bodile, V Talari
    Citations: 2
  • Enhanced brain tumor classification in multi modal images: leveraging self-calculated missing modality compensation transformer with NetB7++
    N Kari, SK Singh, RM Bodile
    Expert Systems with Applications, 130102 , 2025
    2025.0
    Citations: 1
  • Removal of Baseline Wander from Electrocardiogram using Ensemble Empirical Mode Decomposition and Low Pass Filter
    RM Bodile, TVKH Rao
    2019.0
    Citations: 1
  • Insights Review of Microelectronic Devices
    R Kusuma, R Bodile
    Microelectronics: Simulations, Modeling and Applications , 2026
    2026.0
  • Integrated AI and 6G Driven e-Health: A Trifecta for Smart Healthcare
    R Singh, RM Bodile, A Kaushik, A Dolas, A Kaur, P Chatzimisios
    IEEE Communications Standards Magazine , 2026
    2026.0
  • Advanced Image Encryption Framework for Securing Gray and Color Medical Images
    SK Veeramalla, R Bodile, B Jailsingh
    Revolutionizing Metabolic Medicine With Artificial Intelligence, 253-272 , 2026
    2026.0
  • Advanced Image Encryption Framework for Securing Gray and Color Medical Images
    V Santhosh Kumar, R Bodile, J B.
    Revolutionizing Metabolic Medicine With Artificial Intelligence , 2025
    2025.0