Yogesh Shankar | Engineering | Innovative Research Award

Published on by Academic Excellence

Innovative Research Award

Yogesh shankar
Infineon Technologies Asia Pacific, Singapore

Yogesh shankar
Affiliation Infineon Technologies Asia Pacific
Country Singapore
Scopus ID 57215433281
Documents 2
Citations 21
h-index 2
Subject Area Engineering
Event International Academic Excellence Awards

Yogesh shankar is an engineering researcher associated with Infineon Technologies Asia Pacific in Singapore. The supplied indexed record identifies research involving radar-based sensing, non-intrusive motion recognition, and deformable convolutional neural networks. The available bibliometric information reports two documents, 21 citations, and an h-index of 2. The documented publication record provides a focused example of applying deep-learning methods to sensing and recognition problems. [1]

Abstract

The supplied research profile concerns engineering applications of intelligent sensing and machine learning. Its identified publication, presented at the 18th IEEE International Conference on Machine Learning and Applications in 2019, investigates radar-based non-intrusive fall motion recognition using a deformable convolutional neural network. Such work combines radar sensing with deep-learning-based recognition, addressing the computational interpretation of motion without relying on direct physical contact. [2]

Keywords

Engineering; radar sensing; fall recognition; motion recognition; deep learning; convolutional neural networks; deformable convolution; non-intrusive sensing; machine learning; intelligent systems.

Introduction

Radar-based sensing provides a means of observing movement without requiring conventional wearable or contact-based instrumentation. Within this context, machine learning can be used to extract patterns from radar-derived information and classify specific human activities. The documented work by yogesh shankar and collaborators applies a deformable convolutional neural network to fall-motion recognition, placing the research at the intersection of radar sensing, signal interpretation, and artificial intelligence. [2]

Research Profile

The stated subject area is Engineering, with the available publication evidence specifically connected to machine learning and sensing applications. The supplied profile reports two documents, 21 citations, and an h-index of 2. These bibliometric indicators represent the supplied database snapshot and may change as additional publications and citations are indexed. [1]

Research Contributions

  • Investigation of radar-based non-intrusive sensing for human fall-motion recognition. [2]
  • Application of deformable convolutional neural networks to motion-recognition tasks. [2]
  • Integration of radar sensing and deep-learning-based computational recognition within an engineering research context.

Publications

Radar-based non-intrusive fall motion recognition using deformable convolutional neural network was published as a conference paper in the Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). The listed authors are Y. Shankar, Yogesh Shankar, Souvik Hazra, and Avik Santra. The supplied record reports 12 citations for this publication. [2]

Research Impact

The supplied Scopus information reports 21 citations across two documents and an h-index of 2. The identified conference paper accounts for 12 citations in the supplied results. Citation counts are dynamic bibliometric measures and can differ between indexing services; therefore, they are best interpreted as indicators of documented scholarly visibility rather than as a complete measure of research significance. [1] [2]

Award Suitability

The documented publication provides evidence of research activity relevant to an Innovative Research Award within the Engineering subject area. Its focus on radar-based non-intrusive sensing and deformable convolutional neural networks represents an application of contemporary computational methods to human-motion recognition. Consideration for an award should be made alongside the complete research record and the applicable criteria of the International Academic Excellence Awards.

Conclusion

yogesh shankar’s supplied academic record demonstrates focused research at the intersection of engineering, radar sensing, and machine learning. The documented work on non-intrusive fall-motion recognition illustrates the use of deformable convolutional neural networks in an applied sensing context. The available bibliometric indicators and publication evidence provide a concise basis for academic recognition within the International Academic Excellence Awards framework.

References

  1. Elsevier. (n.d.). Scopus author details: Yogesh Shankar, Author ID 57215433281. Scopus. The supplied Scopus record reports two documents, 21 citations, and an h-index of 2.
  2. Shankar, Y., Shankar, Y., Hazra, S., & Santra, A. (2019). Radar-based non-intrusive fall motion recognition using deformable convolutional neural network. Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). The supplied record reports 12 citations.
  3. IEEE. (2019). 18th IEEE International Conference on Machine Learning and Applications (ICMLA 2019). Conference publication record associated with the documented research.
  4. International Academic Excellence Awards. (n.d.). Academic Excellence Awards.
    https://academicexcellenceawards.com/

Vidya Nandikolla | Engineering | Best Researcher Award

Published on by Academic Excellence

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.

Eddy Chevallier | Engineering | Best Researcher Award

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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

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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.

Yuxiang Tian | Engineering | Best Researcher Award

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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.

Sayavur Bakhtiyarov | Engineering | Best Researcher Award

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Prof. Dr. Sayavur Bakhtiyarov | Engineering | Best Researcher Award

👤 Prof. Dr. Sayavur Bakhtiyarov, New Mexico Institute of Mining and Technology, United States

Dr. Sayavur I. Bakhtiyarov is a distinguished mechanical engineer and educator with over four decades of academic and research experience. Currently, a tenured Full Professor at New Mexico Institute of Mining and Technology (NMT), he has contributed significantly to advancements in thermal fluid systems and materials engineering. A US citizen fluent in multiple languages, Dr. Bakhtiyarov combines his global academic exposure from institutions in Azerbaijan, the UK, and the US to foster innovative solutions in engineering education and research. His leadership extends to roles as a department chair, senior lecturer, and chief scientist, including significant contributions to the US Department of Defense. With numerous accolades and publications, his work continues to inspire the next generation of engineers.

Professional Profile

Scopus

🌟  Evaluation of Dr. S. A. Yavur I. Bakhtiyarov for the Research for Best Researcher Award

Summary of Suitability:

Dr. S. A. Yavur I. Bakhtiyarov, a distinguished professor at the New Mexico Institute of Mining and Technology, demonstrates exceptional qualifications for the Research for Best Researcher Award. With a prolific academic career spanning decades, Dr. Bakhtiyarov’s contributions to mechanical engineering, space safety, and nuclear safety are noteworthy. His international academic journey, which includes education and teaching in Azerbaijan, the United Kingdom, China, and the United States, highlights his global perspective and expertise.

His tenure as a researcher and educator is complemented by his extensive service to the U.S. Department of Defense and NASA. He has reviewed critical space safety protocols, contributed to nuclear safety assessments for space missions, and provided thought leadership in safety design for space operations. This unique combination of academic excellence and real-world application reflects his unparalleled dedication to advancing science and technology.

🎓 Education

Dr. Bakhtiyarov’s academic journey began with an Engineering Diploma in Petroleum Engineering from Azerbaijan Institute of Oil and Chemistry in 1974. He earned his Ph.D. in Mechanical Engineering in 1978, focusing on thermophysics at the Institute of Thermophysics of the Siberian Branch of the Russian Academy of Sciences. His exceptional work led to a Sc.D. in Mechanical Engineering from Azerbaijan National Academy of Sciences in collaboration with Birmingham University, UK, in 1992. This rigorous training equipped him with a strong foundation in engineering principles and advanced research methods. His educational background reflects a blend of diverse cultural and scientific insights, which he integrates into his teaching and research.

💼 Professional Experience

Dr. Bakhtiyarov has held prestigious academic and research positions globally. Since 2016, he has been a tenured Full Professor at NMT, after serving as an Associate Professor and Department Chair. His career includes impactful roles such as Senior Lecturer under the Fulbright Program in Turkey and Research Professor at Auburn University. Notably, he contributed as Chief Scientist and Permanent Coordinator for the Interagency Nuclear Safety Review Panel with the US Department of Defense. Earlier, he served in academic roles at the Azerbaijan State Oil Academy, focusing on mechanical engineering innovations. His professional trajectory highlights leadership in engineering education, groundbreaking research, and safety standards in aerospace and defense projects.

🏅Awards and Recognition

Dr. Bakhtiyarov’s contributions have earned him recognition as a leader in mechanical engineering and safety standards. He has received prestigious awards for his innovative research and service, including accolades from NASA and the US Department of Defense. His Fulbright Senior Lectureship showcases his global influence in advancing engineering education. As a member of several safety review panels, he has been instrumental in shaping policies for space operations, including NASA’s Nuclear Flight Safety Assurance Reviews. Additionally, his contributions to thermal-fluid sciences and materials engineering have garnered respect from professional societies and institutions worldwide.

🌍 Research Skills On Engineering

Dr. Bakhtiyarov is renowned for his expertise in thermal-fluid dynamics, materials science, and system safety engineering. He excels in conducting interdisciplinary research on energy systems, advanced materials, and thermophysics, integrating computational modeling and experimental methods. His skills in nuclear safety and aerospace engineering have contributed to critical projects for NASA and the Department of Defense. He is adept at leading research teams, publishing high-impact findings, and translating complex engineering concepts into practical applications. His work emphasizes sustainable technologies, space safety systems, and innovations in engineering education, demonstrating a unique blend of technical knowledge and visionary problem-solving.

📖 Publication Top Notes

  • Title: An effect of Fe atom clusters doped CNTs on resistivity of PTFE dielectrics
    Authors: Bakhtiyarov, S.I., Kutelia, E.R., Gventsadze, D., Bakhtiyarova, A.S., White, S.M.
    Year: 2024
  • Title: Investigation of the Effect of Mutual Diffusion on Hydrodynamic Parameters under Fluid Displacement
    Authors: Mamedov, I., Panahov, G., Bakhtiyarov, S., Museibli, P.
    Year: 2024
    Citations: 1
  • Title: Radiant flux reflectivity model of nanocomposite dielectric materials
    Authors: Bakhtiyarov, S.I., Hassanalian, M., Bakhtiyarova, A.S., White, S.M.
    Year: 2024
  • Title: SEM/EDS Investigation of Aluminized Deformable Austempered Ductile Iron with Al and AlCr Particle Slurries Before and After High-Temperature Oxidation
    Authors: Tsurtsumia, O., Nadaraia, L., Kutelia, E., Khidasheli, N., Bakhtiyarov, S.
    Year: 2024
  • Title: Hemispherical reflectance of PTFE + 10% wt. Fe Doped CNTs at simulated GEO electron irradiation conditions
    Authors: Bakhtiyarov, S.I., Ferguson, D.C., Kutelia, E.R., Gventsadze, D.
    Year: 2022
    Citations: 2
  • Title: Linear and nonlinear aspects of space charge phenomena
    Authors: Bakhtiyarov, S.I., Ferguson, D.C.
    Year: 2022 (Book Chapter)
  • Title: Hemispherical reflectance of pristine PTFE at simulated GEO electron irradiation conditions
    Authors: Bakhtiyarov, S.I., Ferguson, D.C., Kutelia, E.R., Gventsadze, D.
    Year: 2022
    Citations: 2
  • Title: Lab-on-A-chip compatible design laying over nanostructured silicon
    Authors: Kheyraddini Mousavi, B., Kheyraddini Mousavi, A., Bakhtiyarov, S.
    Year: 2021
    Citations: 1
  • Title: An Effect of Electrokinetics Phenomena on Nonlinear Wave Propagation in Bubbly Liquids
    Authors: Panahov, G., Abbasov, E., Bakhtiyarov, S., Museibli, P.
    Year: 2021
  • Title: The effect of high-amplitude deformation and high-frequency magnetic field exposure on the elastic/inelastic properties of PTFE-based hybrid nanocomposite filled with Fe cluster-doped CNTs
    Authors: Kutelia, E., Darsavelidze, G., Dzigrashvili, T., Kukava, T., Bakhtiyarov, S.
    Year: 2021