Yakshansh Kumar | Engineering | Best Researcher Award

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Mr. Yakshansh Kumar | Engineering | Best Researcher Award

Mr. Yakshansh Kumar, Delhi Technological University, India

Yakshansh Kumar is a highly motivated researcher and academician in the field of Civil Engineering, with a specialization in Pavement-Soil Dynamics. Currently pursuing his PhD at Delhi Technological University, he focuses on dynamic response analysis of pavement-soil systems using piezo sensors. He has actively contributed to several publications and international conferences, establishing himself as a promising expert in geotechnical engineering. Passionate about advancing knowledge and fostering innovation, Yakshansh is also involved in mentoring students and advancing research projects. His dedication and commitment are evident in his academic achievements and research pursuits.

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Summary of Suitability for the โ€œResearch for Best Researcher Awardโ€

Yakshansh Kumar is a promising and dedicated researcher with a strong academic foundation and a demonstrated commitment to advancing the field of civil and geotechnical engineering, particularly in pavement-soil dynamics. Currently pursuing a Ph.D. at Delhi Technological University, his research focus on dynamic response analysis of pavement-soil systems using piezo sensors exemplifies his innovative approach to solving complex engineering challenges. His research is not only theoretically robust but also applied, with funding from the universityโ€™s IRD and the use of experimental testing and finite element analysis in his investigations.

Kumarโ€™s publication record is impressive, with multiple articles in high-impact journals such as International Journal of Non-Linear Mechanics (SCIE, Q1) and Journal of Vibration Engineering and Technologies (SCIE, Q2). He has contributed to the scientific community with key insights on dynamic load vibrations, piezo-dynamics, and the role of machine learning in geotechnical analysis. His research has garnered attention on both national and international platforms, demonstrated by his active participation in numerous conferences, where he has won awards for best technical papers.

๐ŸŽ“  Education

Yakshansh Kumar holds a PhD in Civil Engineering from Delhi Technological University (DTU), where he is conducting research on the dynamic analysis of pavement-soil systems. He earned his Masterโ€™s degree in Geotechnical Engineering from DTU, achieving a CGPA of 7.49. He completed his Bachelorโ€™s degree in Civil Engineering at Hindu College of Engineering (affiliated with DCRUSTM) with a CGPA of 6.37. Throughout his academic career, Yakshansh has demonstrated a strong foundation in engineering principles, with a specific interest in soil dynamics and pavement systems. His rigorous research work has led to multiple scholarly contributions in well-regarded journals and international conferences.

๐Ÿ’ผ Professional Experience

Yakshansh Kumar has an extensive academic and research background. He is currently working on his PhD project, funded by the IRD-DTU, which focuses on pavement-soil dynamics using piezo sensors for experimental testing and finite element analysis. As part of his professional journey, Yakshansh has contributed to several research papers, conferences, and has collaborated with experts in geotechnical engineering. He has also participated as a reviewer in esteemed journals such as Transportation Infrastructure Geotechnology. In addition to his research, he has attended workshops and seminars, including a national seminar on Science Day and faculty development programs, showcasing his dedication to continuous learning. His involvement in teaching and research continues to shape his career path.

๐Ÿ…  Awards and Recognition

Yakshansh Kumar has been recognized for his outstanding contributions to research and academic excellence. He was awarded the Best Technical Paper Award for his work on โ€œVelocity Induced Post Elastic Response of Pavementsโ€ presented at the Sustainable Infrastructure: Innovations, Opportunities, and Challenges (SIIOC 2024). In addition, his paper on โ€œPost Elastic Response of Pavement Subjected to Moving Loadโ€ received the Best Paper Award at the International Online Conference on Energy Science (ICES 2021). His work has been published in high-impact journals such as the International Journal of Non-Linear Mechanics and Journal of Vibration Engineering and Technologies. He has also been recognized as a reviewer for journals and international conferences, reflecting his academic credibility and recognition in the field of geotechnical engineering.

๐ŸŒ Research Skills On Engineering

Yakshansh Kumar possesses strong research skills, particularly in the areas of pavement-soil dynamics, finite element analysis, and piezo-dynamics of geomaterials. His expertise lies in dynamic response analysis using experimental testing and numerical modeling. His ongoing PhD project focuses on piezo sensors and their application to pavement systems, supported by funding from IRD-DTU. Yakshansh has demonstrated his proficiency in using advanced software for computational modeling and simulations, as well as conducting real-world experimental tests. His research contributes to understanding the behavior of pavements under dynamic loads, which is vital for improving infrastructure performance. His skills are complemented by his ability to collaborate with peers, present research at conferences, and publish in well-regarded journals.

๐Ÿ“– Publication Top Notes

  • Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2023). Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing. Transportation Infrastructure Geotechnology, 11(3), 922-933.
    • Year: 2023

  • Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Damage evaluation in pavement-geomaterial system using finite element-scaled accelerated pavement testing. Transportation Infrastructure Geotechnology, 11(3), 922-933.
    • Year: 2024

  • Deflections governed by the cyclic strength of rigid pavement subjected to structural vibration due to high-velocity moving loads

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Deflections governed by the cyclic strength of rigid pavement subjected to structural vibration due to high-velocity moving loads. Journal of Vibration Engineering & Technologies, 12(3), 3543-3562.
    • Year: 2024

  • Investigating the Influence of Frequency on Piezo-dynamics of Polyvinylidene Fluoride (PVDF) Films Embedded in Confined Geomaterials

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Investigating the Influence of Frequency on Piezo-dynamics of Polyvinylidene Fluoride (PVDF) Films Embedded in Confined Geomaterials. Journal of Vibration Engineering & Technologies, 1-20.
    • Year: 2024

  • Application of machine learning technique for dynamic analysis of confined geomaterial subjected to vibratory load

    • Authors: A Boban, P Pateriya, Y Kumar, K Gaur, A Trivedi
    • Citation: Boban, A., Pateriya, P., Kumar, Y., Gaur, K., & Trivedi, A. (2024). Application of machine learning technique for dynamic analysis of confined geomaterial subjected to vibratory load. AI in Civil Engineering, 3(1), 2.
    • Year: 2024

  • Influence of Jute Reinforcement on the Stiffness Capacity of Cohesionless Pavement Geomaterials

    • Authors: P Kumar, Y Kumar, A Trivedi
    • Citation: Kumar, P., Kumar, Y., & Trivedi, A. (2023). Influence of Jute Reinforcement on the Stiffness Capacity of Cohesionless Pavement Geomaterials. International Conference on Interdisciplinary Approaches in Civil Engineering.
    • Year: 2023

  • Numerical and Experimental Investigation of a Confined Geomaterial Subjected to Vibratory Load

    • Authors: A Boban, Y Kumar, A Trivedi
    • Citation: Boban, A., Kumar, Y., & Trivedi, A. (2023). Numerical and Experimental Investigation of a Confined Geomaterial Subjected to Vibratory Load. International Conference on Sustainable Infrastructure: Innovation.
    • Year: 2023

  • Impact of Moving Load Vibrations on Pavement Damage Supported by Flow-Controlled Geomaterials

    • Authors: Y Kumar, A Trivedi, SK Shukla
    • Citation: Kumar, Y., Trivedi, A., & Shukla, S. K. (2024). Impact of Moving Load Vibrations on Pavement Damage Supported by Flow-Controlled Geomaterials. Available at SSRN 5002829.
    • Year: 2024

Iustina Ivanova | Computer Science | Best Researcher Award

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Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

๐Ÿ‘ค Mrs. Iustina Ivanova, FBK, Italy

Iustina Ivanova is an accomplished researcher in the field of Artificial Intelligence (AI) with a focus on computer vision and machine learning applications in real-world scenarios. She holds a Masterโ€™s degree in Artificial Intelligence from the University of Southampton, where she earned distinction for her research on neural networks for object detection. Currently, Iustina is engaged in AI research in smart agriculture at the Fondazione Bruno Kessler in Italy. Over the years, she has contributed to a variety of high-impact projects, including developing a recommender system for outdoor sport climbers and researching sensors for sports activity analysis. Her work has earned her several well-regarded publications and recognition in the AI and computer vision communities.

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๐ŸŒŸ Summary of Suitability for the Research for Best Researcher Award

Iustina Ivanova demonstrates exceptional qualifications for the โ€œResearch for Best Researcher Award.โ€ Her academic background, professional experience, and research contributions highlight her significant impact on the fields of artificial intelligence (AI), machine learning, and computer vision. Her academic journey is distinguished by a Masterโ€™s degree in Artificial Intelligence with distinction from the University of Southampton and ongoing research pursuits during her Ph.D. studies. While her Ph.D. remains incomplete, the work she has undertakenโ€”such as her contributions to recommender systems and computer visionโ€”showcases her ability to address complex, real-world problems.

Professionally, Iustinaโ€™s research experience is diverse and impactful. At the Fondazione Bruno Kessler, she has been actively involved in applying AI to smart agriculture, addressing sustainability and innovation in the domain. Her previous roles, including as a Computer Vision Data Scientist and Data Science Moderator, further demonstrate her ability to bridge academia and industry.

๐ŸŽ“ Education

Iustina Ivanova has an impressive academic background in computer science and AI. She completed her Master of Science in Artificial Intelligence with distinction at the University of Southampton, UK, in 2018. Before that, she earned a Specialist degree in Software Engineering from Bauman Moscow State Technical University, Russia, in 2013. In 2019, she pursued a PhD in Computer Science at the Free University of Bolzano, Italy, although she later decided to focus more on practical AI applications. Her academic journey includes notable achievements such as developing research in neural networks for object detection, which has been the cornerstone of her professional career in AI.

๐Ÿ’ผ  Professional Experience 

Iustina Ivanova has a diverse and robust professional background in AI and computer vision. She currently works as a researcher at the Fondazione Bruno Kessler, Italy, specializing in the use of AI for smart agriculture. Prior to this, Iustina served as a Data Science Moderator at Netology, Russia, where she designed and delivered online courses in statistics and mathematics for data science students. She also worked as a Computer Vision Data Scientist at OCRV, Russia, where she helped develop a video-based tracking system for railway workers, focusing on object detection and worker time measurement. Iustinaโ€™s role as a teacher of informatics and mathematics at Repetitor.ru involved preparing high school students for their final exams, ensuring that many students successfully entered top universities. Throughout her career, she has collaborated on numerous innovative projects in AI, particularly in outdoor sports and smart agriculture.

๐Ÿ…Awards and Recognition 

Iustina Ivanovaโ€™s dedication and excellence in the field of AI have been recognized through multiple prestigious awards and accolades. Notably, she won several editions of the NOI Hackathon, including the SFSCON Edition (2021, 2022, 2024) and the Open Data Hub Edition (2022), showcasing her ability to create cutting-edge solutions in AI and data science. Her contributions to research and development in AI for sports activity analysis and computer vision have been published in highly regarded journals and conferences, such as the ACM Conference on Recommender Systems and IEEE Conferences. Iustina has also received recognition for her teaching contributions, inspiring future generations of data scientists. Her projects, especially those related to sports climbersโ€™ recommender systems and sensor data analysis, have received wide acclaim for their innovation and real-world impact.

๐ŸŒ Research Skills On Computer Science

Iustina Ivanovaโ€™s research expertise spans artificial intelligence, machine learning, computer vision, and recommender systems. She is particularly skilled in using AI techniques to solve complex problems in real-world applications. Her work with neural networks for object detection and sensor data analysis has led to significant advancements in both sports and smart agriculture sectors. Iustina is proficient in Python, OpenCV, machine learning frameworks like PyTorch and TensorFlow, and data analysis tools such as Jupyter Notebook and Git. She is well-versed in the development of recommender systems and has implemented innovative solutions for outdoor sports, including climbing crag recommendations. Her interdisciplinary approach combines knowledge from software engineering, data science, and AI to design systems that enhance user experience and improve decision-making. Iustina is committed to the continual development of her skills, evident in her participation in advanced data science and deep learning courses, as well as her extensive practical work in AI.

๐Ÿ“– Publication Top Notes

  • Climbing crags repetitive choices and recommendations
    • Author: Ivanova, I.
    • Citation: Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023
    • Year: 2023
    • Pages: 1158โ€“1164
  • How can we model climbersโ€™ future visits from their past records?
    • Authors: Ivanova, I., Wald, M.
    • Citation: UMAP 2023 โ€“ Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2023
    • Pages: 60โ€“65
  • Introducing Context in Climbing Crags Recommender System in Arco, Italy
    • Authors: Ivanova, I.A., Wald, M.
    • Citation: International Conference on Intelligent User Interfaces, Proceedings IUI
    • Year: 2023
    • Pages: 12โ€“15
  • Climbing crags recommender system in Arco, Italy: a comparative study
    • Authors: Ivanova, I., Wald, M.
    • Citation: Frontiers in Big Data
    • Year: 2023
    • Volume: 6, Article: 1214029
  • Map and Content-Based Climbing Recommender System
    • Authors: Ivanova, I.A., Buriro, A., Ricci, F.
    • Citation: UMAP2022 โ€“ Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2022
    • Pages: 41โ€“45
  • Climbing Route Difficulty Grade Prediction and Explanation
    • Authors: Andric, M., Ivanova, I., Ricci, F.
    • Citation: ACM International Conference Proceeding Series
    • Year: 2021
    • Pages: 285โ€“292
  • Climber behavior modeling and recommendation
    • Author: Ivanova, I.
    • Citation: UMAP 2021 โ€“ Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2021
    • Pages: 298โ€“303
  • Knowledge-based recommendations for climbers
    • Authors: Ivanova, I., Andriฤ‡, M., Ricci, F.
    • Citation: CEUR Workshop Proceedings
    • Year: 2021
    • Volume: 2960
  • Climbing activity recognition and measurement with sensor data analysis
    • Authors: Ivanova, I., Andric, M., Janes, A., Ricci, F., Zini, F.
    • Citation: ICMI 2020 Companion โ€“ Companion Publication of the 2020 International Conference on Multimodal Interaction
    • Year: 2020
    • Pages: 245โ€“249
  • Video and Sensor-Based Rope Pulling Detection in Sport Climbing
    • Authors: Ivanova, I., Andriฤ‡, M., Moaveninejad, S., Janes, A., Ricci, F.
    • Citation: MMSports 2020 โ€“ Proceedings of the 3rd International Workshop on Multimedia Content Analysis in Sports
    • Year: 2020
    • Pages: 53โ€“60