Vishwanath Kumar Panangipalli | Mechanical | Most Reader’s Article Award

Dr. Vishwanath Kumar Panangipalli | Mechanical | Most Reader's Article Award

Associate Professor at Anurag University, India

Author Profile

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Summary

Dr. Vishwanath Kumar Panangipalli is an accomplished mechanical engineer specializing in experimental and computational thermal-fluid sciences. A Ph.D. graduate from Deakin University, Australia, he brings robust experience in advanced fluid dynamics, CFD modeling, and solar thermal systems. His academic journey includes supervising multiple student projects, leading industry-academic research, and publishing in high-impact journals. He has been instrumental in mentoring award-winning student teams at international events and is known for integrating practical innovation with academic rigor.

Education

Dr. Vishwanath Kumar holds a Ph.D. in Mechanical Engineering from Deakin University, Australia, which he completed in 2020. His doctoral dissertation focused on “Hydrodynamics and Heat Transfer Studies in Vacuum Fluidization,” highlighting advanced experimental and numerical investigations in thermal-fluid systems. Prior to this, he earned his M.Tech. in Mechanical Engineering from the Indian Institute of Technology (IIT) Madras in 2010, where his thesis involved the “Development and Performance Analysis of a Multi-Stage Evacuated Solar Desalination System,” reflecting his long-standing interest in sustainable energy technologies. He completed his undergraduate degree, B.Tech. in Mechanical Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal, India, in 2008, with a final project on “Prediction of Spring Back in V-Bending Using Finite Element Simulation.”

Professional Experience

Dr. Vishwanath Kumar is currently serving as an Associate Professor at Anurag University, Hyderabad, bringing with him over 13 years of academic and research experience. During his tenure at Deakin University, Australia, he contributed as a Teaching Assistant and Postdoctoral Researcher, engaging in industry-funded projects that dealt with quench tank modeling and fluid-thermal simulations. These projects combined experimental insights with high-fidelity computational approaches. Before his doctoral studies, he worked as an Assistant Professor at SISTec, Bhopal, where he guided more than 15 UG and PG student projects focused on thermal engineering, CFD, and solar energy systems. His dedication to education has earned him accolades such as the Dr. Sarvepalli Radhakrishnan Best Teacher Award, and he has also served as an international mentor and course coordinator for advanced engineering subjects.

Research Interests

Dr. Kumar’s research expertise lies primarily in experimental fluid flow and thermal sciences, with a strong foundation in Computational Fluid Dynamics (CFD) and heat transfer. He has made significant contributions to the study of multiphase flows and fluidization systems, particularly under vacuum and non-standard conditions. His work extends into solar thermal systems and desalination technologies, aiming to provide sustainable and efficient water solutions. Additionally, he is proficient in finite element modeling and simulation, which he applies in the design and analysis of complex engineering systems. Dr. Kumar is also actively involved in sustainable energy engineering, integrating clean energy concepts into real-world applications.

📊 Author Metrics

Dr. Kumar has published over 15 peer-reviewed papers, including journal articles and international conference proceedings. His work has been cited more than 370 times, reflecting the impact and relevance of his research. His most cited paper, titled “Solar stills system design: A review,” has garnered 264 citations, establishing it as a valuable resource in the field of renewable energy. With an estimated h-index of 8, Dr. Kumar demonstrates consistent scholarly productivity and citation strength. He maintains active research collaborations with leading institutions such as IIT Madras, Deakin University, and Anurag University, enriching his multidisciplinary research profile.

Top Noted Publication

1. Design and Development of a CanSat for Air Pollution Monitoring with RSSI‑Based Position Retrieval System

Authors: S. S. R. K. Swayampakula, K. V. Vedangi, V. K. Panangipalli, M. Gummadavelli, N. Mala, M. N. Banavath, N. Paladugu, A. Kallem
Journal: Advances in Space Research, Vol. 75, No. 9 (2025), pp. 6799–6816
Overview:
A miniaturized CanSat was designed to monitor air pollution via onboard sensors and transmit data for recovery using an RSSI-based localization system. It emphasized affordability, portability, and effective deployment for field experiments

2. Advancements in Lightweight Two‑Wheeler Rim Design: A Finite Element Analysis Approach with Diverse Materials

Authors: P. V. Kumar, P. M. S. Hallika, J. Singh
Journal: International Journal on Interactive Design and Manufacturing (IJIDeM), 2024, pp. 1–13
Published Online: 29 June 2024
Overview:
The paper reports finite element simulations on two-wheeler rim designs, created in SOLIDWORKS and analyzed in ANSYS. Materials assessed included LM13 aluminum alloy, carbon fiber composites, PEEK, and Tecapeek CF30, under loading scenarios simulating rider and passenger weight. Results show composites reduce stress but increase deformation and strain relative to aluminum.

3. AathreyaSat: A CanSat Model for Air Pollution Measurement in Competition

Authors: R. Reddy, V. K. Panangipalli, N. Mala, C. S. Bairu, R. Rumale
Conference: 2024 IEEE Wireless Antenna and Microwave Symposium (WAMS), February 2024, pp. 1–5
Overview:
This competition-grade CanSat (dubbed “AathreyaSat”) featured a triple-canopy parachute and LoRa Ra-02 telemetry. Equipped with CO₂ & particulate matter sensors, it successfully flew to ~500 m altitude and relayed air-quality data.

4. Performance of Single Slope Solar Stills: A Comparative Study of Conventional and Modified Stills with Nanofluid and Reflectors

Authors: V. K. Panangipalli, M. S. H. Pindiprolu, D. Maharana, N. Ghanapuram
Published In: E3S Web of Conferences, Vol. 552, Article 01023 (July 2024)
Overview:
Experimental testing in Hyderabad compared a conventional single-slope solar still (250 × 250 mm²) with a modified version using cerium oxide nanofluids (0.08% & 0.1 vol) and reflectors. Operating at 1 cm depth and with a cover angle of ~17.45°, the modified still achieved higher cumulative hourly yield in local climate conditions.

5. CFD Modelling and Experimental Validation of a Single‑Slope Passive Solar Still for Efficient Water Desalination

Authors: M. S. H. Pindiprolu, V. K. Panangipalli, C. V. S. D. Kartheek
Published In: E3S Web of Conferences, Vol. 552, Article 01084 (July 2024)
Overview:
This study utilized ANSYS Fluent (v19.2) to create a multiphase 2D CFD model of a single-slope solar still. Predicted distillate output (0.0692 kg/m²⋅h) closely matched experimental measurements (0.058 kg/m²⋅h), with a thermal prediction error of just 1.55%. Results confirm strong model accuracy and validate design parameters.

Conclusion 

Dr. Vishwanath Kumar Panangipalli is a strong contender for the Most Reader's Article Award, supported by the lasting impact of his highly cited research, particularly in solar thermal systems and sustainable desalination technologies. His ability to blend experimental insight with computational rigor makes his work both readable and practically influential. While minor improvements in outreach and access could elevate his influence further, his current profile clearly aligns with the intent and merit of this award category.

Sushant Yadav | Mathematical Modeling | Best Researcher Award

Mr. Sushant Yadav | Mathematical Modeling | Best Researcher Award

Senior Research Fellow at Malaviya National Institute of Technology Jaipur, India

Mr. Sushant Yadav is a Ph.D. scholar in Mathematics at MNIT Jaipur, with a strong academic foundation from MNNIT Allahabad and the University of Delhi. His research revolves around Spiking Neural Networks, biologically inspired neural models, and their applications in AI and healthcare. With a passion for mathematical innovation in artificial intelligence, Sushant has contributed to notable publications in reputed journals and conferences. He possesses comprehensive skills in scientific computing, programming, and data analysis, making him a versatile researcher in the evolving field of computational mathematics and AI.

Publication Profile

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Educational Details

  • Doctor of Philosophy in Mathematics (2021 – Present)
    Malaviya National Institute of Technology (MNIT), Jaipur, India
    CGPA: 8.67/10.00
  • Master of Science in Mathematics and Scientific Computing (2018 – 2020)
    Motilal Nehru National Institute of Technology (MNNIT), Allahabad, India
    CGPA: 7.05/10.00
  • Bachelor of Science (Hons.) in Mathematics (2015 – 2018)
    University of Delhi (DU), India
    CGPA: 6.7/10.00

Professional Experience

Mr. Sushant Yadav is a dedicated researcher and academic in the field of Applied Mathematics and Artificial Intelligence. He is currently pursuing his Ph.D. in Mathematics at MNIT Jaipur, where his research focuses on the intersection of Spiking Neural Networks (SNN) and biologically inspired computational models. Throughout his doctoral studies, he has actively contributed to cutting-edge research involving neuron models, plasticity mechanisms, and machine learning applications in healthcare and biological systems. His work involves developing new mathematical models and computational techniques to enhance AI systems’ performance and adaptability. With strong programming skills in Python, C/C++, and expertise in frameworks such as PyTorch, TensorFlow, and SnnTorch, he aims to bridge the gap between theoretical mathematics and AI applications.

Research Interest

  • Spiking Neural Networks (SNN)
  • Neuromorphic Computing
  • Artificial Intelligence and Machine Learning
  • Biologically Inspired Computation
  • Mathematical Modeling in Computational Neuroscience
  • Application of Machine Learning in Healthcare

Top Noted Publication

1. Comparative Analysis of Biological Spiking Neuron Models for Classification Task

  • Authors: S. Yadav, S. Chaudhary, R. Kumar
  • Conference: 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)
  • Publisher: IEEE
  • Pages: 1-6
  • Date: July 2023
  • DOI: https://doi.org/10.1109/ICCCNT57981.2023.10245626
  • Summary:
    This paper presents a comparative evaluation of various biological spiking neuron models with respect to their effectiveness in solving classification tasks. It focuses on models such as Leaky Integrate-and-Fire (LIF), Izhikevich, and Hodgkin-Huxley neurons, assessing their performance on benchmark datasets. The study provides insight into the suitability of each model for machine learning applications based on accuracy and computational efficiency.

2. Consciousness Driven Spike Timing Dependent Plasticity

  • Authors: S. Yadav, S. Chaudhary, R. Kumar
  • Journal: Expert Systems with Applications (Elsevier)
  • DOI: https://doi.org/10.1016/j.eswa.2025.126490
  • Preprint: arXiv preprint arXiv:2405.04546
  • Publication Year: 2024
  • Summary:
    This paper introduces a novel approach integrating consciousness-like behavior into the Spike Timing Dependent Plasticity (STDP) learning rule. The proposed mechanism enhances synaptic adaptability by incorporating contextual and attention-based weight adjustments, leading to improved learning outcomes in spiking neural networks (SNNs). The study demonstrates the effectiveness of this approach in enhancing performance in classification and pattern recognition tasks.

3. Machine Learning-Based Recognition of White Blood Cells in Juvenile Visayan Warty Pigs

  • Authors: S. Saxena, S. Yadav, B. Singh, R. Kumar, S. Chaudhary
  • Conference: 2023 International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI)
  • Publisher: IEEE
  • Date: December 2023
  • Summary:
    This research proposes a machine learning framework for the automated recognition and classification of White Blood Cells (WBCs) in juvenile Visayan Warty Pigs, a rare and endangered species. The system employs image processing and supervised learning algorithms to enhance diagnostic accuracy and aid veterinarians in wildlife health monitoring.

4. Deep Learning Solutions for WBC Classification in Juvenile Visayan Warty Pigs

  • Authors: S. Saxena, S. Yadav, B. Singh, R. Kumar, S. Chaudhary
  • Conference: 2023 IEEE Engineering Informatics
  • Publisher: IEEE
  • Pages: 1-6
  • Date: November 2023
  • Summary:
    This paper presents a deep learning-based approach leveraging Convolutional Neural Networks (CNNs) to classify White Blood Cells in juvenile Visayan Warty Pigs. The study demonstrates improved classification accuracy compared to traditional image processing techniques, showcasing the potential of deep learning in veterinary diagnostics and wildlife conservation.

Conclusion:

Mr. Sushant Yadav is a highly promising researcher with a robust foundation in mathematical modeling, spiking neural networks, and biologically inspired AI. His research contributions, particularly his innovative work on STDP and white blood cell classification using machine learning, position him as a deserving candidate for the Best Researcher Award. While his profile is strong, further enhancing his publication impact, international collaborations, and real-world implementations would elevate his standing in the global research community.