Arun Kumar Gudivada | Statistical Applications in Engineering | Best Researcher Award

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Assoc Prof. Dr. Arun Kumar Gudivada | Statistical Applications in Engineering | Best Researcher Award

Aditya University | India

Assoc. Prof. Dr. Arun Kumar, currently Associate Professor in the Department of Electronics & Communication Engineering at Aditya University, Surampalem, is an emerging researcher whose work spans VLSI, quantum computing, and quantum communication. Born in Kakinada, Andhra Pradesh, he obtained his B.Tech and M.Tech from a JNTU Kakinada–affiliated college, and earned his Ph.D. from Pondicherry University. Dr. Arun Kumar has published multiple peer-reviewed articles in well-recognized journals such as the Journal of Computational Science and Journal of Supercomputing, and has also presented at numerous international conferences. He serves as a reviewer for several Springer journals. According to his Google Scholar profile, he currently holds an h-index of 7 with a total of 129 citations across 19 published documents. His research contributions explore the theoretical and practical frontiers of quantum-enabled electronics and communication systems, seeking to bridge classical VLSI design with emerging quantum paradigms. He is committed to mentoring students and fostering collaborative research in the evolving fields of quantum technologies and nano-electronics.

Profiles: Scopus | Google Scholar

Featured Publications

Reddy, T. V., Kandadi, R., Suresh, R., Arunkumar, G. A., Kalli, S. R., & D, S. (2025). Design, modeling and comparative analysis of SRAM performance and functionality under the subthreshold regime for various technologies. 2025 Fourth International Conference on Smart Technologies, Communication …

Gudivada, A. A., Sattibabu, G., & Relangi, A. K. (2025). Power, area, and delay efficient synchronous ring counter using clock gating and multi-bit flip-flops in QCA technology. International Journal of Electronics Letters, 1–11.

Bhoopathi, A. A., R., R., Sailaja, C., Jennifer, D., & Gudivada, A. (2025). A study on microstructures and physical properties of high-entropy alloys and materials. Oxidation Communications, 48(1), 162–171.

Gudivada, A. A., Avala, E., Gummarekula, S., & Tulasi, V. R. (2025). ST-QCA based error free and area efficient 4:2 compressor design. Recent Trends in VLSI and Semiconductor Packaging, 111–118.

Noorbasha, S. K. (2024). VME-EFD: A novel framework to eliminate the electrooculogram artifact from single-channel EEGs. Biomedical Physics & Engineering Express, 11(1), 015041.

Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

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Dr. Abhijeet Das | Statistical Applications in Engineering | Machine Learning Award

C.V. Raman Global University | India

Dr. Abhijeet Das, Ph.D. in Water Resource Engineering from C.V. Raman Global University, Bhubaneswar, is an accomplished civil engineering researcher specializing in watershed hydrology, hydrological modeling, climate change impact assessment, and GIS-based water resources management. With a strong academic foundation, including M.Tech and B.Tech degrees from Biju Patnaik University of Technology, he has combined rigorous research with nearly a decade of professional and teaching experience. Dr. Das has contributed extensively to collaborative national and international projects across Tunisia, USA, Oman, UK, South Africa, Syria, and Lebanon, focusing on water quality, hydrologic extremes, and sustainable water management through remote sensing, machine learning, and optimization techniques. He has published 88 documents indexed in Scopus, which have received 199 citations, achieving an h-index of 7, reflecting both productivity and the growing impact of his research contributions. His intellectual property portfolio includes over 30 patents filed in water resource engineering, geoinformatics, and environmental sustainability, showcasing innovation and applied problem-solving capacity. Dr. Das has actively engaged in more than 30 seminars, workshops, and international conferences, presenting advancements in civil and water resource engineering. His career trajectory illustrates a blend of academic excellence, applied research, and industry collaboration, making him a promising contributor to the advancement of sustainable infrastructure and water management systems.

Profiles: Scopus | Orcid

Featured Publications

Das, A. (2025). An optimization-based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance. Discover Environment.

Das, A., & Mishra, S. (2025). Reimagining biofiltration for sustainable industrial wastewater treatment. Discover Sustainability.

Das, A. (2025). A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in Mahanadi River Basin, Odisha, India. Discover Sustainability.

Das, A. (2025). Evaluation and prediction of surface water quality status for drinking purposes using integrated water quality indices, GIS approaches, and machine learning techniques. Desalination and Water Treatment.

Das, A., Mishra, S., & Tripathy, B. (2025). Bioplastics: A sustainable alternative or a hidden microplastic threat? Innovative Infrastructure Solutions.