Amar Deep Maurya | Civil Engineering | Best Researcher Award

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Mr. Amar Deep Maurya | Civil Engineering | Best Researcher Award 

Mr. Amar Deep Maurya | Rajkiya Engineering College | India 

Mr. Amar Deep Maurya is an emerging civil engineering professional with a strong academic background and practical experience in sustainable construction practices. He is pursuing a Bachelor of Technology degree in Civil Engineering from Rajkiya Engineering College, Mainpuri, where he has built a solid foundation in structural design, materials engineering, and environmental sustainability. Amar has completed multiple internships with the Public Works Department in Uttar Pradesh, where he gained hands-on experience in project estimation, road cost analysis, and planning. Additionally, he has worked with Earth5R in a virtual internship, where he learned about environmental science, sustainability, and energy conversion, broadening his understanding of eco-friendly engineering practices. He has undertaken several significant projects that demonstrate his research and technical skills, including a study on the statistical modeling and optimization of waste glass-based paver block properties. In this project, he applied Response Surface Methodology to analyze the effects of waste glass incorporation on mechanical strength and durability, achieving notable improvements in compressive strength and water absorption characteristics. Another key project involved developing a new mortar testing method that integrates advanced analytical techniques and precision equipment to evaluate durability and structural integrity. He also worked on 2D and 3D architectural designs using AutoCAD, applying his creativity and technical knowledge to design building plans and house structures. Amar is proficient in various technical tools such as AutoCAD, MATLAB, Autodesk Revit, Google SketchUp, and Adobe Photoshop. His ability to combine engineering principles with design software has enabled him to produce innovative and efficient solutions for civil engineering challenges.

Profiles : ORCID

Featured Publications : 

Yadav, B., Rusia, S., Pandey, J. S., Singh, H. S., Maurya, A. D., Chauhan, A., Mathur, U., & Pal, K. (2025). Statistical modeling and optimization of waste glass-based paver block properties. Next Materials, 10, 101236.

Maurya, A. D. (2024). A novel approach to crack repair: Self-healing concrete using bacteria. International Research Journal of Engineering and Technology (IRJET).

Jiayi Luo | Geotechnics | Best Researcher Award

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Mr. Jiayi Luo – Geotechnics- Best Researcher Award

University of Illinois Urbana-Champaign | United States

Profiles 

Scopus

📍Current Position

He currently serves as a Software Engineer at A&C Technology, Inc. since May 2023. In this role, Jiayi has demonstrated exceptional skills in architecting hybrid consensus systems and implementing scalable AI solutions. The work primarily involves integrating slot-based Proof of Credit generation and Byzantine Fault Tolerance (BFT) finalization algorithms. This integration is fortified with homomorphic encryption for privacy and enabled by a Trustful Execution Environment for real-time transactions. Additionally, Jiayi has led the implementation of a multi-faceted AI for enhanced biometric feature extraction, streamlining operations with a token-based framework for registration, login, and recovery.

📝Publication Achievements 

He has made significant contributions to the field through numerous publications. Some notable works include: Luo, J., Huang, H., Ding, K., Qamhia, I. I., Tutumluer, E., Hart, J. M., … & Sussmann, T. R. (2023). “Toward Automated Field Ballast Condition Evaluation: Algorithm Development Using a Vision Transformer Framework.” Transportation Research Record. Luo, J., Ding, K., Huang, H., Hart, J. M., Qamhia, I. I., Tutumluer, E., … & Sussmann, T. R. (2023). “Toward Automated Field Ballast Condition Evaluation: Development of a Ballast Scanning Vehicle.” Transportation Research Record. Luo, J., Ding, K., Huang, H., Hart, J. M., Qamhia, I. I., Tutumluer, E., … & Sussmann, T. R. (2023). “A Deep Learning Approach for Automated Railroad Ballast Condition Evaluation.” Manuscript submitted for publication.

 

🔍Ongoing Research 

His ongoing research includes the development of advanced computer vision-based techniques for evaluating ballast conditions and degradation. This involves creating image segmentation frameworks using Mask R-CNN and Swin Transformer backbones and enhancing these frameworks through contrastive learning with unlabeled field ballast images. Another notable project is the design of a synthetic ballast data generator using Unreal Engine, aimed at enriching the ballast database with ground-truth labels and various environmental conditions.

🔬Research Interests 

His research interests are diverse and include: Transportation systems and infrastructure. Civil engineering with a focus on ballast condition and degradation evaluation. Advanced computer vision techniques. Deep learning and AI applications in civil engineering. Development of numerical analysis engines for flexible pavement evaluation.

🎓Academic Background 

He has an impressive academic record, having achieved high GPAs in multiple programs at the University of Illinois at Urbana-Champaign: Ph.D. in Transportation (3.92/4.00), 2018–2023. Master of Computer Science (4.00/4.00), 2016–2018. Master of Science in Transportation (4.00/4.00), 2016–2018. Additionally, Jiayi holds a Bachelor of Engineering in Civil Engineering with a Minor in Economic Management from Tsinghua University, Beijing, China (GPA: 88/100).

🏆Scholarships and Awards 

His academic excellence is reflected in numerous scholarships and awards: Outstanding Student Medal Award, Civil & Environmental Engineering Department, UIUC, 2022. Geological and Geoenvironmental Engineering Section Best Paper Award, TRB, 2019. Scholarships of academic excellence, 1st and 2nd prizes in 2014 and 2015 respectively. 1st prize in the Chinese National Mathematics Competition, 2013. 2nd prize in the Chinese National Physics Competition, 2013.

🌐Professional Associations 

He is an active member of several professional associations, contributing to the advancement of civil engineering and transportation research through continuous engagement and collaboration.

 📚Training & Workshops 

He has participated in numerous training sessions and workshops, staying updated with the latest technologies and methodologies in civil engineering and computer science.

🎤Oral Presentations 

He  has presented research findings at various esteemed conferences, including the Transportation Research Board (TRB) and the International Conference on Soil Mechanics and Geotechnical Engineering. These presentations have highlighted innovative techniques and tools developed for transportation infrastructure evaluation.

🧑‍🔬Tasks Completed as a Researcher 

As a researcher, he has completed various significant tasks, including: Developing and implementing image segmentation frameworks. Designing synthetic data generators. Building finite element analysis engines for pavement evaluation. Creating generative models for 2D particle shape completion. Conducting experimental investigations on concrete behavior at ultra-low temperatures.

🚀Success Factors 

His success can be attributed to a combination of deep technical knowledge, innovative thinking, and a strong academic foundation. Their ability to integrate advanced technologies like AI and deep learning into practical engineering solutions has been a key factor in their professional achievements.

🧪Publications & Laboratory Experience

His extensive publication record and laboratory experience showcase their expertise and contributions to civil engineering and transportation research. The ability to translate complex research into practical applications has significantly advanced the field and set a high standard for future research.

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