Dr Mehul S. Raval is a leading academic and researcher with more than 27+ years of distinguished experience in higher education, specialising in Electronics and Communication Engineering, Information and Communication Technology, and Computer Science and Engineering. He earned his Bachelor’s (Electronics and Telecommunication Engineering, 1996), Master’s (Digital Systems, 2002), and PhD (Electronics and Telecommunication Engineering, 2008) from the University of Pune, India. Currently he serves as a Professor at Ahmedabad University. Dr Raval has held pivotal roles including Associate Dean for Experiential Learning at Ahmedabad University from 2020 to 2024. He was the founding head and professor of the ICT department at the School of Technology, PDPU, Gandhinagar, and has previously served as faculty at SCET, Surat, DA-IICT Gandhinagar, and Ahmedabad University.
Dr Raval’s research portfolio is extensive, spanning computer vision, image processing, machine learning, data analytics,
EDUCATION
PhD Electronics and Telecommunication Engineering, University of Pune
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Computer Science
Assistive Robots in Agriculture Mehul S. Raval, Paawan Sharma, Sanjay Chaudhary Assistive Robotics Perspectives Challenges and Firmware, 2026 Agriculture is one of the most critical aspects of the development of the human race. It is essential to meet the growing demand for food, which can be attained with the help of technology. Robotics is rapidly evolving to support agricultural practices on and off the farm. This chapter provides an overview of how robots assist in agriculture. It surveys the research landscape and studies different agriculture levels at which robots help humans. The introduction discusses the types of robots with their sensor systems and how they assist. It also presents the motivation and challenges of using robotics in agriculture. Robots are helpful in crop monitoring and management, especially using remote sensing. Moreover, it may support ground-level agriculture processes like seeding, planting, health monitoring, and nutrient measurements. Section 5.2 covers the type and specifications of such robots. The robots have also been found to be extremely useful in harvesting operations like fruit picking with autonomous driving ability, and they are also valuable for packaging and managing the warehouse during storage. These aspects are covered in Sections 5.3 and 5.4. This chapter also examines the impact of robotics from economic, social, and environmental perspectives. It concludes by discussing the future and emerging technologies that may further help penetrate robotics in agriculture in Section 5.5.
Efficient Beam Prediction for 6G V2I Networks using Liquid Time-Constant Neural Networks Kirtan Kalaria, Dhaval K. Patel, Mehul S. Raval, Mukesh Zaveri International Conference on Communication Systems and Networks Comsnets, 2026 Millimeter-wave (mmWave) and terahertz (THz) frequencies enable high data rate applications in modern wireless communication, with vehicle-to-everything (V2X) communication being critical for traffic management, safety, and autonomous driving. Beam prediction in highly mobile V2X scenarios seeks to reduce the significant overhead of traditional beam training in mmWave systems. Prior studies on beam prediction are often limited to current-time beam selection or rely solely on synthetic datasets, lacking real-world validation. This study proposes a Liquid Time Constant Neural Network (LTC-NN)-based framework for future beam prediction, leveraging its adaptive time constants to handle dynamic vehicular data. We evaluate the approach on the real-world DeepSense 6G and simulated DeepMIMO datasets using lookback lengths ℓ ∈{5,8} for prediction horizons τ ∈ {1,3}. Averaged across all scenarios and settings, LTC-NN achieves a top-1 accuracy of 48.65% versus 44.23% for LSTM and reduces average power loss to 0.309 dB compared to 0.447 dB for LSTM. At a 90% reliability threshold, beam training overhead savings exceed 94.4% for LTC-NN, compared to 93.6% for LSTM. These results highlight the novel application of LTC-NN for V2I beam prediction, addressing a critical gap in efficient, accurate beam management. This research offers a practical approach to enhance mmWave V2I communication systems, paving the way for robust, energy-efficient solutions in dynamic vehicular environments.
Novel Crash Prevention Framework for C-V2X using Deep Learning Foram N. Shah, Dhaval K. Patel, Kashish D. Shah, Mehul S. Raval, Mukesh Zaveri, S.N. Merchant 2023 15th International Conference on Communication Systems and Networks Comsnets 2023, 2023
Defense Against Adversarial Examples Using Beneficial Noise Param Raval, Harin Khakhi, Minoru Kuribayashi, Mehul S. Raval Proceedings of 2022 Asia Pacific Signal and Information Processing Association Annual Summit and Conference Apsipa ASC 2022, 2022
Experiments with multinational cross-course project Mehul S Raval, Tolga Kaya, Mazad Zaveri, Paawan Sharma Proceedings of 2020 IEEE International Conference on Teaching Assessment and Learning for Engineering Tale 2020, 2020
Brain tumor segmentation and survival prediction Rupal R. Agravat, Mehul S. Raval Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020
Prediction for the Second Wave of COVID-19 in India Shweta Thakur, Dhaval K. Patel, Brijesh Soni, Mehul Raval, Sanjay Chaudhary Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2020
CheckIt-A low cost mobile OMR system Rahul Patel, Shashwat Sanghavi, Dhruv Gupta, Mehul S Raval IEEE Region 10 Annual International Conference Proceedings TENCON, 2016
Identifying vandalized regions in facial images of statues for inpainting Milind G. Padalkar, Manali V. Vora, Manjunath V. Joshi, Mukesh A. Zaveri, Mehul S. Raval Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2013
Discrete wavelet transform based multiple watermarking scheme IEEE Region 10 Annual International Conference Proceedings TENCON, 2003
RECENT SCHOLAR PUBLICATIONS
Single-Camera Barbell Trajectory Analysis for the Snatch Lift D Shah, H Raval, C Taber, T Kaya, E Maddox, MS Raval SN Computer Science 7 (4), 297 , 2026 2026
Data-Driven Imputation for Cohort Studies Using Collegiate Basketball Data S Sharma, H Raval, V Barot, S Divakaran, T Kaya, C Taber, MS Raval SN Computer Science 7 (4), 288 , 2026 2026
Descriptor: Drone Nadir-view Annotated Images of Vehicles Detection Dataset for India with Heading-angle Oriented Bounding Box (DRASHTI-HaOBB) YM Bhavsar, MS Zaveri, MS Raval, KR Patel, SB Zaveri IEEE Data Descriptions , 2026 2026
Attention-gated U-Net model for semantic segmentation of brain tumors and feature extraction for survival prognosis R Pate, S Rajput, MS Raval, RA Kapdi, M Roy arXiv preprint arXiv:2602.15067 , 2026 2026
Interpretable Athlete Performance Modelling in Collegiate Basketball: A Review of Machine Learning and Computer Vision Methods S Sharma, S Divakaran, T Kaya, C Taber, MS Raval TechRxiv, 1 - 54 , 2026 2026
Efficient Beam Prediction for 6G V2I Networks using Liquid Time-Constant Neural Networks K Kalaria, DK Patel, MS Raval, M Zaveri 2026 18th International Conference on COMmunication Systems and NETworks … , 2026 2026
Sports Data Analytics: Techniques, Applications, and Innovations MS Raval, T Kaya, NS Artan, C Taber Springer Singapore, ISBN: 978-981-95-5131-6 , 2026 2026
Designing a Data-Driven Athlete Management System for Optimizing Basketball Performance S Sharma, S Naik, S Senbel, MS Raval Sports Data Analytics: Techniques, Applications, and Innovations, 31-49 , 2026 2026
An Analytical Framework for Modelling, Analysis and Prediction of Athletes’ Game Performance S Sharma, T Kaya, MS Raval, S Divakaran Sports Data Analytics: Techniques, Applications, and Innovations, 73-88 , 2026 2026
Enhancing Basketball Strategy: Recommending Optimal Athlete Lineups S Sharma, S Divakaran, T Kaya, CB Taber, MS Raval Sports Data Analytics: Techniques, Applications, and Innovations, 163-185 , 2026 2026
Hydrodynamics in a Both-Side-Heated Square Enclosure in Laminar Regime Under Constant Heat Flux Using Computational Fluid Dynamics and Deep Learning Methodology AA Ganguli, SS Deshpande, MS Raval Fluids 10 (12), 309 , 2025 2025
Multi-Query Person Retrieval on Edge Devices J Chaudhari, H Raval, H Galiyawala, P Sharma, MS Raval International Symposium on Visual Computing, 340-351 , 2025 2025
A systematic review on deep learning for atmospheric correction of satellite images M Shah, MS Raval, S Divakaran Archives of Computational Methods in Engineering, 1-31 , 2025 2025 Citations: 4
A Data-Driven Imputation Scheme for Cohort Studies: A Collegiate Basketball Casestudy S Sharma, V Barot, S Divakaran, T Kaya, CB Taber, MS Raval International Sports Analytics Conference and Exhibition, 235-252 , 2025 2025
Barbell Trajectory Tracking for Performance Analysis During Snatch Movement in Weightlifting D Shah, C Taber, T Kaya, E Maddox, MS Raval International Sports Analytics Conference and Exhibition, 218-234 , 2025 2025 Citations: 1
Evaluating defensive driving behaviour based on safe distance between vehicles: A case study using computer vision on UAV videos at urban roundabout YM Bhavsar, MS Zaveri, MS Raval, SB Zaveri Multimodal Transportation 4 (3), 100227 , 2025 2025 Citations: 4
Performance Evaluation and Analysis of Deep Learning Based Season-Aware Atmospheric Correction Model on Nvidia Jetson Agx Orin M Shah, J Chaudhari, MS Raval, S Divakaran IGARSS 2025-2025 IEEE International Geoscience and Remote Sensing Symposium … , 2025 2025 Citations: 1
Dynamic Spectrum Coexistence of NR-V2X and Wi-Fi 6E using Deep Reinforcement Learning KD Shah, DK Patel, B Soni, S Govindasamy, MS Raval, M Zaveri IEEE Open Journal of the Computer Society , 2025 2025 Citations: 2
Analysis of Weightlifting Success Predictability Using Machine Learning J Camaran, Y Ukawa, T Reis, C Taber, WG Hornsby, A Long, M Raval, ... International Conference on Computational Science and Its Applications, 179-199 , 2025 2025 Citations: 1
BEACON: Beam Prediction with Efficiency for Advanced V2I Communication Networks K Kalaria, DK Patel, MS Raval, M Zaveri, SN Merchant 2025
MOST CITED SCHOLAR PUBLICATIONS
Discrete wavelet transform based multiple watermarking scheme MS Raval, PP Rege TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region 3 … , 2003 2003 Citations: 296
A robust and secure watermarking scheme based on singular values replacement AK Gupta, MS Raval Sadhana 37 (4), 425-440 , 2012 2012 Citations: 160
Disease Detection and Severity Estimation in Cotton Plant from Unconstrained Images A Parikh, MS Raval, S Chaudhary 3rd IEEE International Conference on Data Science and Advanced Analytics … , 2016 2016 Citations: 118
Brain Tumor Segmentation and Survival Prediction R Agravat, MS Raval Lecture Notes in Computer Science 11922 (1), 338 - 348 , 2020 2020 Citations: 85
3D Semantic Segmentation of Brain Tumor for Overall Survival Prediction R Agravat, MS Raval LNCS - Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain … , 2021 2021 Citations: 65
Image and Video Compression: Fundamentals, Techniques and Applications MA Joshi, MS Raval, YH Dandawate, KR Joshi, SP Metkar CRC Press / Chapman and Hall , 2014 2014 Citations: 53
Deep Learning for Brain Tumor Segmentation R Agravat, MS Raval Soft Computing Based Medical Image Analysis , 2018 2018 Citations: 48
Impact of sleep and training on game performance and injury in division-1 women’s basketball amidst the pandemic S Senbel, S Sharma, MS Raval, C Taber, J Nolan, NS Artan, D Ezzeddine, ... Ieee Access 10, 15516-15527 , 2022 2022 Citations: 41
A holistic approach to performance prediction in collegiate athletics: player, team, and conference perspectives C Taber, S Sharma, MS Raval, S Senbel, A Keefe, J Shah, E Patterson, ... Scientific Reports 114 (1162) , 2024 2024 Citations: 38
A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Prediction R Agravat, MS Raval Archives of Computational Methods in Engineering - State of the art reviews , 2021 2021 Citations: 38
Prediction of overall survival of brain tumor patients RR Agravat, MS Raval TENCON 2019-2019 IEEE Region 10 Conference (TENCON), 31-35 , 2019 2019 Citations: 37
Insider threat detection: machine learning way MS Raval, R Gandhi, S Chaudhary Versatile cybersecurity, 19-53 , 2018 2018 Citations: 37
Identification of free-ranging mugger crocodiles by applying deep learning methods on UAV imagery B Desai, A Patel, V Patel, S Shah, MS Raval, R Ghosal Ecological Informatics 72, 101874 , 2022 2022 Citations: 35
Interpretable machine learning model to predict survival days of malignant brain tumor patients S Rajput, RA Kapdi, MS Raval, M Roy Machine Learning: Science and Technology 4 (2), 025025 , 2023 2023 Citations: 34
A Data-Driven Stochastic Approach for Unmixing Hyperspectral Imagery J Bhatt, M Joshi, MS Raval IEEE Journal of Selected Topics in Applied Earth Observations and Remote … , 2014 2014 Citations: 33
Vision-based investigation of road traffic and violations at urban roundabout in India using UAV video: A case study YM Bhavsar, MS Zaveri, MS Raval, SB Zaveri Transportation Engineering 14, 100207 , 2023 2023 Citations: 32
Person Retrieval in Surveillance Video using Height, Color and Gender H Galiyawala, K Shah, V Gajjar, MS Raval 15th IEEE International Conference on Advanced Video and Signal Based … , 2019 2019 Citations: 31
A triplanar ensemble model for brain tumor segmentation with volumetric multiparametric magnetic resonance images S Rajput, R Kapdi, M Roy, MS Raval Healthcare Analytics 5, 100307 , 2024 2024 Citations: 26
Multiresolution Image Fusion: Use of Compressive Sensing and Graph Cuts V Harikumar, PP Gajjar, MV Joshi, MS Raval IEEE Journal of Selected Topics in Applied Earth Observations and Remote … , 2014 2014 Citations: 26
CheckIt-A low cost mobile OMR system R Patel, S Sanghavi, D Gupta, MS Raval TENCON 2015-2015 IEEE Region 10 Conference, 1-5 , 2015 2015 Citations: 24