Rahul Charles C M | Engineering | Best Researcher Award

Best Researcher Award

Rahul Charles C M
College of Engineering Muttathara, India

Rahul Charles C M
Affiliation College of Engineering Muttathara
Country India
Google Scholar Profile rpc75fsAAAAJ
Documents 3
Citations 32
h-index 2
Subject Area Engineering
Event International Academic Excellence Awards

Rahul Charles C M is an engineering researcher affiliated with the College of Engineering Muttathara, India. The supplied academic record identifies three publications, 32 citations and an h-index of 2. His documented research includes work on doubly fed induction generators, field-oriented control and battery energy storage in wind-energy systems. These publications place his research within the broader engineering fields of renewable-energy conversion, electrical-machine control and energy-storage integration. [1]

Abstract

This academic recognition profile summarizes the supplied research record of Rahul Charles C M. His publication activity focuses on renewable-energy systems involving doubly fed induction generators, field-oriented control and battery energy storage. The available scholarly record indicates an engineering research trajectory concerned with improving the control and operational integration of wind-energy conversion systems. [2]

Keywords

Renewable energy; wind energy; doubly fed induction generator; field-oriented control; battery energy storage; electrical engineering; energy conversion.

Introduction

Wind-energy systems require coordinated control of electrical machines, converters and storage technologies to maintain reliable operation under variable generation conditions. Research into doubly fed induction generators and associated control strategies addresses these engineering challenges and forms the principal theme of the publications supplied for this profile. [1]

Research Profile

The supplied bibliometric information records three documents, 32 citations and an h-index of 2. These indicators provide a quantitative description of scholarly visibility but should be interpreted in relation to career stage, publication chronology, authorship, field-specific citation patterns and the completeness of the underlying indexing record. [2]

Research Contributions

  • Investigation of field-oriented control for doubly fed induction generator-based wind-energy systems incorporating battery energy storage. [1]
  • Study of field-oriented control of doubly fed induction generators in wind-power applications. [2]
  • Contribution to engineering research concerning renewable-energy conversion, generator control and storage-assisted wind-energy operation.

Publications

Field oriented control of DFIG based wind energy system using battery energy storage system was published in Procedia Technology, volume 24, pages 1203–1210, in 2016, and is listed with 24 citations in the supplied Google Scholar record. [1] Field oriented control of Doubly Fed Induction Generator in wind power system appeared in the 2015 IEEE International Conference on Computational Intelligence and Computing Research and is listed with eight citations. [2]

Research Impact

The supplied record reports 32 citations across three documents, with the 2016 wind-energy publication accounting for a substantial portion of the listed citations. The work addresses technically relevant challenges in renewable-energy generation and electrical-machine control, while the incorporation of battery storage connects generator control with broader energy-management considerations. [1]

Award Suitability

Based on the information supplied, Rahul Charles C M has a focused engineering publication record with identifiable contributions to wind-energy systems and generator-control technologies. The reported citation activity provides an additional indicator of scholarly use. Eligibility and final selection for the International Academic Excellence Awards should, however, be determined using the award’s official criteria and independently verified academic records.

Conclusion

The available record presents Rahul Charles C M as an engineering researcher whose documented work concerns doubly fed induction generators, field-oriented control and battery-supported wind-energy systems. His publications and reported citation record provide a measurable basis for academic recognition within renewable-energy and electrical-engineering research. [1] [2]

References

  1. Charles, C. M. R., Vinod, V., & Jacob, A. (2016). Field oriented control of DFIG based wind energy system using battery energy storage system. Procedia Technology, 24, 1203–1210.
    Google Scholar record
  2. Charles, C. M. R., Vinod, V., & Jacob, A. (2015). Field oriented control of Doubly Fed Induction Generator in wind power system. 2015 IEEE International Conference on Computational Intelligence and Computing Research.
    Google Scholar record
  3. Google Scholar. (n.d.). Rahul Charles C M publication profile. Google Scholar.
    https://scholar.google.com/citations?hl=en&user=rpc75fsAAAAJ&view_op=list_works&sortby=title
  4. IEEE. (2015). 2015 IEEE International Conference on Computational Intelligence and Computing Research. Conference publication record.
    Publication record
  5. Procedia Technology. (2016). Field oriented control of DFIG based wind energy system using battery energy storage system. Volume 24, pages 1203–1210.
    Publication record
  6. International Academic Excellence Awards. (n.d.). Official award website.
    https://academicexcellenceawards.com/

Vidya Nandikolla | Engineering | Best Researcher Award

Best Researcher Award

Dr Vidya Nandikolla
Affiliation California State University Northridge
Country United States
Scopus ID 8339231200
Documents 25
Citations 136
h-index 5
Subject Area Engineering
Event International Academic Excellence Awards
ORCID 0000-0002-4151-4783

Dr Vidya Nandikolla
California State University Northridge,United States

Dr Vidya Nandikolla is an engineering researcher affiliated with California State University Northridge in the United States. Her documented research output includes work in autonomous vehicles, robotics, brain-computer interfaces, and simultaneous localization and mapping (SLAM), reflecting an interdisciplinary interest in intelligent robotic and autonomous systems. Available bibliographic indicators record 25 documents, 136 citations, and an h-index of 5.

Abstract

Dr Vidya Nandikolla’s research profile is situated within engineering applications involving robotics, autonomous systems, human-machine interaction, and computational sensing. Her publication record includes research on a hybrid EEG-based brain-computer interface (BCI) arm manipulator controlled through ROS and work concerning autonomous vehicles and LiDAR-based localization. These topics connect sensing, control, perception, and intelligent automation, all of which are central areas of contemporary engineering research.

Keywords

Robotics; autonomous vehicles; LiDAR; SLAM; brain-computer interface; ROS; robotic control; engineering; localization; intelligent systems.

Introduction

Modern autonomous and robotic platforms depend on reliable perception, localization, control, and human-machine communication. SLAM methods allow robotic systems to estimate their position while constructing representations of an environment, while BCI technologies investigate alternative mechanisms for controlling assistive robotic devices. Nandikolla’s documented work intersects these engineering challenges, providing a research profile that combines robotics with emerging sensing and control technologies. [2]

Research Profile

The available record identifies Engineering as the principal subject area. Her research themes include ROS-enabled robotic control, EEG-based BCI systems, autonomous vehicle technologies, and LiDAR SLAM. ROS is widely used as a framework for developing modular robotic applications, making its use relevant to experimental robotics and autonomous-system research. [3]

Research Contributions

  • Research involving a hybrid EEG-based BCI arm manipulator and ROS-based robotic control.
  • Investigation of autonomous vehicle technologies, including custom battery-pack design using solar energy.
  • Evaluation of Extended Kalman Filter odometry for improving the performance of 2D LiDAR SLAM algorithms. [1]

Publications

Evaluating the Impact of Extended Kalman Filter Odometry on the Performance of 2D LiDAR SLAM Algorithms is listed as a working paper and carries. Another documented publication is Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS, published in the Journal of Robotics in 2022 and reported with five citations in the supplied record. A conference paper, Design and Analysis of an Custom Battery Pack Using Solar Energy for an Autonomous Vehicle, further demonstrates an application-oriented engineering focus.

Research Impact

The reported bibliometric record of 136 citations across 25 documents indicates measurable scholarly visibility. An h-index of 5 provides an additional bibliometric indicator of citation distribution. These metrics should be interpreted alongside publication quality, research relevance, technical contribution, and broader application potential rather than as standalone measures of research excellence. [4]

Award Suitability

Dr Vidya Nandikolla demonstrates characteristics relevant to consideration for a Best Researcher Award in Engineering, particularly through a research portfolio connecting robotics, autonomous mobility, BCI systems, and localization. The combination of published research, interdisciplinary engineering applications, and documented citation activity provides a reasonable academic basis for recognition. Final award assessment should consider the complete submitted evidence and the evaluation criteria established by the International Academic Excellence Awards.

Conclusion

Dr Vidya Nandikolla’s documented research reflects an engineering-oriented approach to robotics, autonomous systems, human-machine interfaces, and intelligent localization. Her publication activity and bibliometric indicators support recognition of sustained research engagement, while her work addresses practical challenges in emerging robotic technologies.

References

  1. Nandikolla, Vidya K. et al. (2026). Evaluating the Impact of Extended Kalman Filter Odometry on the Performance of 2D LiDAR SLAM Algorithms. Preprints.
    https://doi.org/10.20944/preprints202607.1435.v1
  2. Cadena, C. et al. (2016). Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age. IEEE Transactions on Robotics, 32(6), 1309–1332.
    https://doi.org/10.1109/TRO.2016.2624754
  3. Quigley, M. et al. (2009). ROS: an open-source Robot Operating System. ICRA Workshop on Open Source Software.
  4. Elsevier. (n.d.). Scopus author details: Vidya Nandikolla, Author ID 8339231200. Scopus.
    https://www.scopus.com/pages/authors/8339231200
  5. Nandikolla, Vidya K., and Medina Portilla, Daniel A. (2022). Teleoperation Robot Control of a Hybrid EEG-Based BCI Arm Manipulator Using ROS. Journal of Robotics.
  6. Nandikolla, Vidya K. et al. Design and Analysis of an Custom Battery Pack Using Solar Energy for an Autonomous Vehicle. Conference paper.

Rahul Diwate | Engineering | Best Researcher Award

Best Researcher Award

Rahul Diwate
Vishwakarma Institute of Technology, India

Rahul Diwate
Affiliation Vishwakarma Institute of Technology
Country India
Scopus ID 57223038655
Documents 36
Citations 70
h-index 5
Subject Area Engineering
Event International Academic Excellence Awards
Google Scholar Profile A66xQuoAAAAJ

Rahul Diwate is an engineering researcher affiliated with Vishwakarma Institute of Technology whose supplied scholarly record includes work in pattern matching, data mining, computer vision, machine learning, flood prediction, and intelligent surveillance systems. The available profile reports 36 documents, 70 citations, and an h-index of 5. His publications demonstrate a progression from foundational computational methods toward applied machine learning and computer-vision problems, including object detection, fire detection, and predictive environmental modelling. [1] [3]

Abstract

Rahul Diwate’s supplied publication record reflects research across computer science and engineering applications, with particular emphasis on algorithms, data mining, machine learning, and computer vision. His work includes studies of pattern matching and association-rule mining as well as more recent investigations into YOLO-based object detection, flood prediction, and lightweight convolutional neural networks for fire detection. [1] [2] [4] Together, these publications indicate an applied research orientation toward computational methods capable of addressing practical engineering and information-processing challenges.

Keywords

Engineering; machine learning; data mining; pattern matching; computer vision; object detection; YOLO; convolutional neural networks; flood prediction; fire detection; intelligent systems.

Introduction

Engineering research increasingly uses computational intelligence to process complex data and support automated decision-making. Diwate’s publication record illustrates this development through research that moves from established algorithmic techniques toward machine-learning applications. Early work addressed pattern matching and association-rule mining, while later publications examined object detection, predictive modelling, and compact neural-network architectures. [1] [2] This trajectory places his research within a broader engineering effort to develop efficient computational solutions for real-world problems.

Research Profile

The supplied profile shows a multidisciplinary computational focus. Pattern matching provides a foundation for identifying structures within data, while association-rule mining supports the discovery of relationships among variables. More recent studies apply machine learning to visual recognition and environmental prediction. The work on YOLO v3 addresses object detection, whereas the flood-prediction study applies machine-learning techniques to an environmental forecasting problem. [3] [4]

Research Contributions

  • Research into algorithmic approaches for pattern matching, addressing fundamental computational search and recognition problems. [1]
  • Review-oriented research on association-rule data mining and its applications in information analysis. [2]
  • Application of YOLO v3 for object detection, demonstrating the use of deep-learning methods in computer-vision systems. [3]
  • Development and evaluation of machine-learning approaches for flood occurrence prediction and lightweight CNN-based fire detection. [4] [5]

Publications

  1. Study of different algorithms for pattern matching. MRB Diwate and SJ Alaspurkar, International Journal, 2013. The supplied record reports 23 citations. [1]
  2. Data mining techniques in association rule: A review. RB Diwate and A Sahu, International Journal of Computer Science and Information Technologies, 2014. The supplied record reports 16 citations. [2]
  3. Optimization in object detection model using YOLO v3. RB Diwate, A Zagade, MR Khodaskar and VR Dange, 2022 International Conference on Emerging Smart Computing and Informatics. The supplied record reports 9 citations. [3]
  4. A predictive model for occurrence of floods using machine learning techniques. A Sarkar, AM Kulkarni, MR Khodaskar, SP Tidake and RB Diwate, resmilitaris, 2023, 13(2), 5054–5072. [4]
  5. Lower complex CNN model for fire detection in surveillance videos. RB Diwate, LV Patil, MR Khodaskar and NP Kulkarni, 2021 International Conference on Emerging Smart Computing and Informatics. [5]

Research Impact

The supplied bibliometric profile reports 36 documents, 70 citations, and an h-index of 5. Individual publications have also accumulated measurable citations, with the pattern-matching study listed at 23 citations and the data-mining review at 16 citations in the supplied Google Scholar record. [1] [2] These figures indicate scholarly visibility within the relevant computational and engineering literature. Bibliometric measures, however, are best interpreted together with research quality, methodological contribution, authorship responsibility, and practical significance.

Award Suitability

The supplied evidence provides a suitable basis for considering Rahul Diwate for a Best Researcher Award in Engineering. His record demonstrates sustained engagement with computational research, progressing from algorithmic methods and data mining to machine learning, object detection, environmental prediction, and intelligent surveillance. The combination of 36 reported documents and 70 citations provides quantitative support for an established scholarly record. Final award evaluation should additionally consider verified publication records, originality, individual research contribution, technical rigor, and practical or scientific outcomes.

Conclusion

Rahul Diwate’s supplied academic profile reflects a coherent engineering research trajectory centered on computational intelligence and applied machine learning. His publications cover pattern matching, data mining, object detection, flood prediction, and fire detection, demonstrating applications across information processing, computer vision, and engineering problem-solving. The reported scholarly indicators and publication record provide relevant evidence for consideration within the Best Researcher Award category.

References

  1. Diwate, M. R. B., and Alaspurkar, S. J. (2013). Study of different algorithms for pattern matching. International Journal, 3(3). Google Scholar record.
    Publication record
  2. Diwate, R. B., and Sahu, A. (2014). Data mining techniques in association rule: A review. International Journal of Computer Science and Information Technologies. Google Scholar record.
    Publication record
  3. Diwate, R. B., Zagade, A., Khodaskar, M. R., and Dange, V. R. (2022). Optimization in object detection model using YOLO v3. 2022 International Conference on Emerging Smart Computing and Informatics.
    Publication record
  4. Sarkar, A., Kulkarni, A. M., Khodaskar, M. R., Tidake, S. P., and Diwate, R. B. (2023). A predictive model for occurrence of floods using machine learning techniques. resmilitaris, 13(2), 5054–5072.
    Publication record
  5. Diwate, R. B., Patil, L. V., Khodaskar, M. R., and Kulkarni, N. P. (2021). Lower complex CNN model for fire detection in surveillance videos. 2021 International Conference on Emerging Smart Computing and Informatics.
    Publication record
  6. Elsevier. (n.d.). Scopus author details: Rahul Diwate, Author ID 57223038655. Scopus.
    https://www.scopus.com/pages/authors/57223038655

KARTHIK M | Engineering | Research Excellence Award

Dr. KARTHIK M | Engineering | Research Excellence Award

SRM Madurai College for Engineering and Tchnology | India

Dr. M. Karthik is a dedicated academician and researcher in the field of Electrical and Electronics Engineering, with a strong specialization in High Voltage Engineering. He currently serves as a Senior Grade Assistant Professor in the Department of Electrical and Electronics Engineering at SRM Madurai College for Engineering and Technology, Tamil Nadu. With over nine years of teaching experience across reputed engineering institutions, he has consistently contributed to academic excellence, curriculum delivery, and student mentorship. Dr. Karthik earned his Ph.D. (Part-Time) in High Voltage Engineering from Anna University, Chennai, completing his doctoral coursework at the Government College of Technology, Coimbatore, with outstanding academic performance. He also holds an M.E. degree in High Voltage Engineering, graduating as a university topper with distinction, and a B.E. degree in Electrical and Electronics Engineering. His strong academic foundation reflects his commitment to technical rigor and continuous learning. His primary research interests include liquid and solid dielectrics, high voltage insulation, and related reliability studies in power systems. Dr. Karthik has actively disseminated his research through multiple national-level conference paper presentations, covering interdisciplinary themes such as biomedical signal processing, intrusion detection systems, SCADA technology, energy conservation, fuel cell technologies, and advanced power electronics applications. An active contributor to the research community, Dr. Karthik maintains profiles on ORCID, Scopus, Google Scholar, Publons, and Vidwan, highlighting his scholarly engagement and research impact. Through his teaching, research, and academic service, he remains committed to advancing knowledge in high voltage engineering and fostering innovation in electrical engineering education.

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Featured Publications

An efficient waste management technique with IoT based smart garbage system
– Materials Today: Proceedings, 2023
Frequency control of PV-connected micro grid system using fuzzy logic controller
– Materials Today: Proceedings, 2021
Visualization of virtual environment through LabVIEW platform
– Materials Today: Proceedings, 2021
Studies on critical properties of vegetable oil based insulating fluids
– IEEE INDICON, 2015
Appropriate analysis on properties of various compositions on fluids with and without additives for liquid insulation in power system transformer applications
– Scientific Reports, 2024

Peter Anyin | Engineering | Research Excellence Award

Dr. Peter Anyin | Engineering | Research Excellence Award

Institute for Intermodal Transports and Logistics Systems | Germany

Anyin, Peter Betianabeshe, Ph.D., is a transportation engineer and researcher specializing in traffic planning, simulation, and quantitative modeling of complex mobility systems. His academic and professional work is centered on developing data-driven and system-oriented approaches to improve traffic operations, urban mobility, and infrastructure planning, particularly in rapidly growing metropolitan regions. He is currently engaged in advanced research at Technische Universität Braunschweig, Germany, where his doctoral studies focus on transportation planning and traffic simulation, with a strong emphasis on designing quantitative metrics for evaluating microscopic traffic simulators and systemic planning frameworks. His Ph.D. research addresses the systemic planning of traffic in Lagos, Nigeria, integrating simulation-based methodologies with real-world mobility challenges. Dr. Anyin’s research expertise spans microscopic traffic simulation, queueing theory, statistical traffic data analysis, and computational modeling. He has extensive experience working with industry-standard simulation tools such as VISSIM, SUMO, Aimsun, and MATSim, alongside programming and analytical platforms including Python, MATLAB, Simulink, and SQL. His interdisciplinary research also extends into machine learning applications, such as generative adversarial networks and physics-informed neural networks, applied to traffic systems and pavement modeling. He has authored multiple peer-reviewed journal articles and conference papers on traffic simulation comparison, queueing models, sustainable transportation systems, and computational methodologies. His work has been published in reputable international journals and presented at global conferences. In addition to research, he actively supervises graduate students, contributes to collaborative urban planning projects, and engages with stakeholders to translate simulation research into practical transportation solutions.

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Featured Publications

Analytical Determination of Queueing System Performance for Sustainable Economic Development
– Arid Zone Journal of Engineering, Technology and Environment, 2022
MATLAB SimEvent for Traffic Queue Model
– Arid Zone Journal of Engineering, Technology and Environment, 2024
Simplified Octahedral Shear Stress Theory for Plane Elements
– Nnamdi Azikiwe University Journal of Civil Engineering, 2025
Formulation of Limit State Deflection Equation for Thin Rectangular Steel Plates Analysis
– Nnamdi Azikiwe University Journal of Civil Engineering, 2025
Pertuzumab Overcomes Chemotherapy/Trastuzumab Resistance in ER+/HER2+ Tumors Classified as Luminal Functional Subtype
– Cancer Research (Supplement), 2016

Sumaraj S | Engineering | Academic Excellence Award

Dr. Sumaraj S | Engineering | Academic Excellence Award

Dr. Sumaraj is a Civil and Environmental Engineer with over a decade of academic and research experience, specializing in water and environmental sustainability. He holds a Ph.D. in Civil and Environmental Engineering from the University of Auckland, New Zealand, where his doctoral research contributed to advancing sustainable approaches in water and wastewater treatment systems. His strong academic foundation also includes a Master of Technology in Environmental Engineering and Management from the Indian Institute of Technology Kharagpur, where he graduated with distinction, and a Bachelor of Engineering in Civil Engineering from the National Institute of Engineering, Mysore. Dr. Sumaraj’s research interests span water and wastewater treatment engineering, sustainable technologies, nutrient contaminant remediation, carbon-based materials such as biochar and activated carbon, adsorption mechanisms, surface chemistry, analytical chemistry, and air pollution monitoring. His work reflects an interdisciplinary approach that integrates environmental science, engineering solutions, and sustainability-driven innovation, leading to peer-reviewed publications, conference presentations, and award-winning student research projects. Currently serving as an Assistant Professor in the Department of Civil Engineering at Nitte Meenakshi Institute of Technology, Bengaluru, Dr. Sumaraj is actively involved in teaching, mentoring, and academic leadership. He has designed and delivered courses in green technology, environmental sustainability, wastewater treatment, water supply engineering, and research methodology. Beyond the classroom, he plays a key role in industry–academia collaboration, skill development initiatives, and sustainability-focused training programs. A recipient of multiple scholarships and honors, including the University of Auckland Doctoral Scholarship and recognition under national and international sustainability programs, Dr. Sumaraj is also a certified Green-Belt Career and Higher Education Counsellor. His professional journey reflects a strong commitment to research excellence, environmental stewardship, and the development of future-ready engineers.

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Featured Publications

Eddy Chevallier | Engineering | Best Researcher Award

Dr. Eddy Chevallier | Engineering | Best Researcher Award

LAMIH – UPHF/CNRS 8201 | France

Dr. Eddy Chevallier is a distinguished researcher in Engineering Sciences, specializing in electromechanical systems that utilize static or dynamic electrical contact as a channel for information or power transmission. Currently serving as an Ingénieur de Recherche at the LAMIH Laboratory (UMR CNRS 8201, UPHF) in Famars, France, he focuses on understanding how surface topography influences multi-physical phenomena occurring at interfaces. His work spans electrical, thermal, and mechanical properties, integrating experimental measurement, numerical programming, and theoretical modeling to advance industrial applications that rely on surface-dependent interactions. His research aims to identify and quantify the relationships between topographic parameters and functional surface behavior, enabling the development of hybrid methodologies for optimizing surface designs based on precise performance requirements. Dr. Chevallier is qualified in the French national academic sections 28 (Physics of Materials), 60 (Mechanics), and 63 (Electrical Engineering), reflecting the interdisciplinary breadth of his expertise. He earned his Doctorate in 2014 from the Université de Picardie Jules Verne, where his thesis, supervised by Jérôme Fartin and co-advised by Robert Rouzereau and Valéry Bourny, focused on defining quality indices for metallic sliding contact using electrical signatures of surface condition. His doctoral work received the distinction of “Très Honorable.” He also holds a Master’s degree in physical characterization and modeling of complex materials from the same institution. Dr. Chevallier has contributed to leading scientific journals such as Tribology International, Journal of Tribology, Journal of Applied Physics, and has presented his work at numerous international and national conferences, reinforcing his role as a key contributor to tribology and electromechanical interface research.

Profile: Google Scholar

Featured Publications

Chevallier, E., Bourny, V., Bouzerar, R., Fortin, J., Durand-Drouhin, O., & others. (2014). Voltage noise across a metal/metal sliding contact as a probe of the surface state. Journal of Applied Physics, 115(15).

Chevallier, E. (2014). Définition d’indices de qualité du contact glissant métallique: Signatures électriques de l’état de surface (Doctoral dissertation, Université de Picardie Jules Verne). Université de Picardie Jules Verne.

Chevallier, E. (2020). Mechanical model of the electrical response from a ring–wire sliding contact. Tribology Transactions, 63(2), 215–221.

Jonckheere, B., Bouzerar, R., Bourny, V., Bausseron, T., Foy, N., & Chevallier, E. (2017). Assessment of the real contact area of a multi-contact interface from electrical measurements. In 23ème Congrès Français de Mécanique (CFM), France.

Guessasma, M., Bourny, V., Haddad, H., Machado, C., Chevallier, E., Tekaya, A., & others. (2018). Multi-scale and multi-physics modeling of the contact interface using DEM and coupled DEM-FEM approach. In Advances in Multi-Physics and Multi-Scale Couplings in Geo-Environmental Engineering.

Srikanth Nandoori | Engineering | Best Researcher Award

Dr. Srikanth Nandoori | Engineering | Best Researcher Award

Anurag University | India

Dr. Nandoori Srikanth is an accomplished academician and training strategist with over eleven years of combined experience in teaching, training, placements, and industry engagement. He holds a Ph.D. in Wireless Communications from KL University, where his research focused on developing energy-efficient cluster-based routing protocols to enhance the lifetime and performance of Wireless Sensor Networks. His academic background spans VLSI System Design at the postgraduate level and Electronics & Communication Engineering at both graduation and diploma levels, forming a strong foundation for his technical expertise. Throughout his career, Dr. Srikanth has contributed significantly to engineering education through his roles as Associate Professor, Assistant Professor, Placement Coordinator, Training & Placement Officer, and currently as Dean of Placements at St. Peter’s Engineering College. His leadership has strengthened institutional-industry collaboration, resulting in the establishment of multiple Centers of Excellence with global organizations such as Microsoft, IDS Blockchain, Movate, and Juniper Networks. He has also led the signing of key MoUs with Google Cloud, Infosys Springboard, Eduskills, Internshala, and several emerging technology firms, enabling students to access high-value skilling, internship, and hiring opportunities. Dr. Srikanth’s efforts in fostering employability have earned him prestigious recognitions, including the All-India 4th Rank and State 2nd Rank in Internshala Rankings, the Best SPOC Award from Eduskills (received three times), and commendations for promoting Google Cloud certifications. Additionally, he holds professional certifications in Google Cloud Associate, ServiceNow, and Microsoft Azure Fundamentals. His work reflects a deep commitment to academic excellence, student development, and innovation-driven education.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Srikanth, N., & Prasad, M. S. G. (2018). Efficient clustering protocol using fuzzy K-means and midpoint algorithm for lifetime improvement in WSNs. International Journal of Intelligent Engineering and Systems, 11(4), 61–71.

Srikanth, N., & Prasad, M. S. (2019). Energy efficient trust node based routing protocol (EETRP) to maximize the lifetime of wireless sensor networks in plateaus. International Journal of Online & Biomedical Engineering, 15(6).

Srikanth, N., & Prasad, M. S. G. (2019). A compressive family based efficient trust routing protocol (C-FETRP) for maximizing the lifetime of WSN. In Data Communication and Networks: Proceedings of GUCON 2019 (pp. 69–80).

Srikanth, N., & Prasad, M. S. G. (2019). Family based efficient routing protocol (FERP) for lifetime improvement in heterogeneous wireless sensor networks. Journal of Advanced Research in Dynamical and Control Systems, 11(6), 131–140.

Sangari, M. S., Thangaraj, K., Vanitha, U., Srikanth, N., Sathyamoorthy, J., … (2023). Deep learning-based object detection in underwater communications system. In 2023 Second International Conference on Electrical, Electronics, Information and Communication Technology.

Moulya H.V | Engineering | Women Researcher Award

Mrs. Moulya H.V | Engineering | Women Researcher Award

Nitte Meenakshi Institute Of Technology | India

Moulya Hosagadhe Venkataramana is an accomplished academic and construction engineering professional with extensive experience in Concrete Technology, Construction Management, and Quality Assurance and Quality Control (QA/QC). With over nine years of combined teaching and industry exposure, she has significantly contributed to engineering education, laboratory development, project execution, and applied research in sustainable construction materials. Her academic tenure includes impactful roles at Nitte Meenakshi Institute of Technology, Dayananda Sagar College of Engineering, and BTL Institute of Technology and Management, where she strengthened curriculum delivery, advanced laboratory infrastructure, and supported institutional development. Her research focuses on Geopolymer Concrete, sustainable materials, and modern construction technologies, reflecting her commitment to environmental responsibility and innovative engineering practices. She has published ten research papers, including contributions in Q2, Q3, and Q4 journals, and presented her work at eight national and international conferences. Her scholarly excellence has been recognized through multiple awards, including Best Paper Presentation at ICCSI 2024 and a Research Award for Journal Publications at NMIT. In the engineering domain, she has served in QA/QC and site engineering roles, managing material procurement, batching, testing, safety compliance, and process optimization for major construction projects. She contributed to the execution of large-scale works such as building facilities and commercial complexes, demonstrating precision in quality oversight and project coordination. She has also guided numerous student projects in geopolymer concrete and sustainable construction technologies, fostering innovation among emerging engineers. With expertise spanning project management, engineering design, laboratory establishment, and academic leadership, she continues to advance research and teaching in civil engineering.

Profile: Google Scholar

Featured Publications

  • Moulya, H. V., & Chandrashekhar, A. (2022). Experimental investigation of effect of recycled coarse aggregate properties on the mechanical and durability characteristics of geopolymer concrete. Materials Today: Proceedings, 59, 1700–1707.

  • Moulya, H. V., Vasu, V. K., Praveena, B. A., Rajesh, M., Ruthuparna, S. A., & Rahul, K. (2022). Study on acoustic properties of polyester–fly ash cenosphere/nanographene composites. Materials Today: Proceedings, 52, 1272–1277.

  • Choudhari, R. M., Kharche, N. A., Shekokar, S. R., Kharche, Y. A., Kharat, D. P., … Moulya, H. V. (2025). Examining dielectric constant improvement techniques for ferroelectric applications using PVDF-HFP/TFO composite films. Journal of Materials Science: Materials in Engineering, 20(1), 137.

  • Moulya, M. H. V. (2025). Self-healing concrete using nanomaterials to extend infrastructure longevity.

  • Moulya, M. H. V., Chandrashekhar, A., & Angadi, S. V. (2024). Geopolymer recycling process for sustainable construction materials management. B. Nitte Meenakshi Institute of Technology.

Yuxiang Tian | Engineering | Best Researcher Award

Mr. Yuxiang Tian | Engineering | Best Researcher Award

China Three Gorges University | China

Yuxiang Tian, born on May 20, 2002, is an emerging researcher and engineer specializing in mechanical design, manufacturing, and automation. He earned his Bachelor of Engineering degree from China Three Gorges University in June 2024, with a strong academic performance. During his undergraduate studies, he demonstrated an exceptional ability to merge theoretical knowledge with practical applications, particularly in the fields of structural optimization, dynamic detection systems, and intelligent automation. Tian has actively participated in significant research projects, including the structural design and optimization of egg carriers for dynamic egg slit detection platforms and the development of robotic systems for lithium battery disassembly. His research contributions have resulted in multiple publications in reputable journals such as PLOS ONE and Aerospace Science and Technology. He also holds a patent related to automated bolt and nut disassembly systems, reflecting his innovative approach to solving real-world engineering challenges. Beyond research, Tian has gained professional experience through internships at DHC Software Co., Ltd., where he supported mechanical design, finite element analysis, and technical documentation. His active involvement in national competitions, such as the “Challenge Cup” and “Internet+” contests, earned him awards at both college and provincial levels. Tian has presented his work at international conferences on digital twins, applied mathematics, and industrial big data, further expanding his academic network. With strong technical expertise in SolidWorks, ANSYS, MATLAB, and Plant Simulation, alongside creative interests in music, photography, and basketball, Tian exemplifies a well-rounded young researcher committed to innovation and academic excellence.

Profiles: Scopus | Orcid

Featured Publications

Tian, Y. (2026). Locally optimal aerodynamic shape design for stratospheric airships: A GA-driven MDO framework with CAD/CFD validation. Aerospace Science and Technology.

Meng, R., Narayan, S., Tian, Y., & Huang, S. (2025). Structural design and optimization of egg carrier for dynamic egg slit detection platforms. PLOS ONE.