Hiyam Farhat | Digital twins | Best Researcher Award

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Dr. Hiyam Farhat | Digital twins | Best Researcher Award

Lecturer | Tennessee Tech University | United States

Dr. Hiyam Farhat, a Lecturer and Assistant Director at the DOE Industrial Assessment Center in the Department of Mechanical and Nuclear Engineering at Tennessee Technological University, is a materials and mechanical engineering specialist whose work integrates advanced materials, manufacturing technologies, turbomachinery performance, and energy-efficiency research. She holds a PhD in Mechanical and Industrial Engineering, an MS in Mechanical and Materials Engineering, and a BS in Mechanical Engineering, underpinning a career that spans academic, research, and leadership roles across major engineering organizations. Her professional experience includes directing industrial assessment initiatives, managing engineering programs in the turbomachinery sector, contributing to quality and inspection systems, and teaching a broad range of engineering courses with demonstrated excellence. Her research focuses on AI-driven modeling, digital-twin development, materials degradation prediction, and clean-energy technologies, resulting in influential publications in areas such as hybrid digital-twin frameworks, gas turbine performance, flexible operation lifing criteria, and energy-storage applications. She has delivered invited presentations and contributed chapters to leading technical references, with her work supported by collaborations with national and international partners. Her recognitions include awards for technical presentations, and she maintains active engagement through memberships in professional societies such as ASME, KEEN, and the European Turbine Network. She also holds certifications in research ethics, nondestructive testing, welding inspection, quality auditing, and safety oversight. Dr. Farhat’s record reflects sustained innovation, cross-disciplinary expertise, and impactful contributions to advancing energy sustainability and intelligent engineering systems.

Profiles: Google Scholar | Scopus

Featured Publications

1. Farhat, H., & Salvini, C. (2022). Novel gas turbine challenges to support the clean energy transition. Energies, 15(15), 5474.

2. Farhat, H. (2021). Operation, maintenance, and repair of land-based gas turbines.

3. Farhat, H. (2021). Materials and coating technologies. In Operation, maintenance, and repair of land-based gas turbines (pp. 63–87).

4. Farhat, H., & Salvini, C. (2022). New lifing criterion for land-based gas turbines in flexible operation mode. Energy Reports, 8, 379–385.

5. Farhat, H. (2021). Lifetime extension: Assessment and considerations. In Operation, maintenance, and repair of land-based gas turbines (pp. 175–196).

Dr. Hiyam Farhat’s work advances intelligent energy systems by integrating AI-driven modeling, digital-twin technologies, and materials degradation analytics to enhance performance, reliability, and sustainability in turbomachinery and clean-energy applications. Her contributions support industry and national energy goals by improving efficiency, reducing emissions, and enabling data-informed lifecycle management for next-generation power systems.

Ranjith Kumar Ramakrishnan | Computer Science | Best Researcher Award

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Mr. Ranjith Kumar Ramakrishnan | Computer Science | Best Researcher Award

Senior Software Developer | N2 Services, Inc | United States

Mr. Ranjith Kumar Ramakrishnan is a highly accomplished Technical Lead and Architect with extensive expertise in cloud-native systems, AI-driven applications, and enterprise architecture. With a strong foundation in Java, Spring Boot, and modern design patterns such as Microservices, CQRS, and Event Sourcing, he has successfully architected scalable, resilient solutions for complex business domains. His proficiency spans AWS cloud services, serverless architectures, DevOps pipelines, and container orchestration, enabling efficient and secure system delivery. Ranjith is also skilled in integrating AI technologies, including RAG architectures, OpenAI APIs, and vector databases, to build intelligent, full-stack applications. He has led large-scale cloud modernization projects, transforming legacy monoliths into event-driven, high-performance architectures, while collaborating effectively with cross-functional teams in Agile environments. Known for his technical depth, innovative problem-solving, and leadership, Ranjith demonstrates exceptional potential to contribute to both practical enterprise solutions and cutting-edge research in AI and cloud computing.

Profile:  Google Scholar | ORCID

Featured Publications

1. R. K. Ramakrishnan and J. J. Lekkala, “Decentralized GitHub Management: Blockchain Solution,” Authorea Preprints, 2025.

2. R. K. Ramakrishnan and J. J. Lekkala, “Evolution and Adoption of Java Programming Features: A Comparative Study of Generics and Lambda Expressions,” Evolution, vol. 86, p. 23, 2025.

3. R. K. Ramakrishnan, “Financial and Technological Considerations for Deploying Applications on Cloud Computing Platforms: A Case Study of AWS,” 2025.

4. R. K. Ramakrishnan, M. Sadineni, and J. J. Lekkala, “Enhancing Distributed System Reliability through Request-Level Fault Injection and Fine-Grained Tracing,” Authorea Preprints, 2025.

5. R. K. Ramakrishnan, A. Nayak, and J. J. Lekkala, “Integrating Cloud, Edge, and IoT,” Authorea Preprints, 2025.

Guiying Zhang | Computer Vision | Best Researcher Award

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Dr. Guiying Zhang | Computer Vision | Best Researcher Award

Lecturer | Tianjin University of Technology and Education | China

Dr. Guiying Zhang is a dedicated researcher in microelectronics and communication engineering with expertise spanning electronic packaging reliability, wireless sensor networks, and antenna system design. Her notable contributions include advancing the understanding of lead-free solder joint reliability, developing innovative RFID chip structures, and proposing adaptive impedance matching systems capable of real-time optimization. Through her work, she has addressed critical challenges in electronic device reliability and wireless communication efficiency, demonstrating both technical depth and creativity. Her research outcomes are reflected in a strong record of publications in reputable journals and conferences, highlighting her sustained academic productivity. With an interdisciplinary approach integrating electronics, materials science, and signal processing, Dr. Zhang bridges theoretical research and practical applications. She continues to explore emerging technologies such as terahertz communication and intelligent sensor networks, positioning herself as a forward-looking scholar whose work has significant potential to influence future advancements in microelectronics and communication systems. She has six publications indexed in Scopus, with her work cited once by another document, reflecting an h-index of 1. These metrics demonstrate her emerging research contributions and measurable impact in her field.

Profile: Scopus

Featured Publication

1. Characterization of the Stress-optic Properties of Ceramics by Terahertz Time-domain Spectroscopy, Current Optics and Photonics, 2024.

 

Prashant Awasthi | Artificial Intelligence and Machine Learning | Best Researcher Award

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Mr. Prashant Awasthi | Artificial Intelligence and Machine Learning | Best Researcher Award

Tech Architecture Manager at Accenture LLP, United States

Mr. Prashant Awasthi is a seasoned technology leader and researcher with extensive experience in Generative AI, DevOps, Cloud Computing, and Machine Learning. With a strong professional background in managing large-scale projects for global clients, he has consistently bridged advanced research with practical industry applications. His contributions to academia include multiple publications in reputed journals and international conferences on diverse topics such as AI, cloud computing, IoT security, cryptocurrencies, and human activity recognition. Beyond publishing, he has played active roles as a reviewer, session chair, and invited speaker at global conferences, demonstrating his recognition and influence within the research community. He is also a member of IEEE and IAENG, further reflecting his engagement with international scientific networks. Known for his technical expertise, leadership, and dedication, Mr. Awasthi continues to make meaningful contributions that advance innovation and knowledge, establishing him as a strong candidate for research recognition and awards.

Professional Profile 

Google Scholar | Scopus Profile

Education

Mr. Prashant Awasthi has built a strong educational foundation that supports his extensive professional and research career. His academic journey reflects a balance between theoretical learning and practical application, with a focus on computer science, information technology, and software engineering. Throughout his education, he developed expertise in programming, system design, and emerging technologies, which laid the groundwork for his later specialization in cloud computing, DevOps, and artificial intelligence. His continuous learning mindset is evident in his pursuit of globally recognized professional certifications, including AWS Cloud Solutions Architect, HashiCorp Terraform, and ITIL V4. These advanced credentials demonstrate his commitment to staying updated with evolving technologies and applying them effectively in real-world environments. His academic and professional learning paths are closely integrated, allowing him to contribute significantly to both industry and research. This strong educational background has enabled him to engage in innovative research and knowledge-sharing at the global level.

Experience

Mr. Prashant Awasthi has more than eighteen years of experience in the IT industry, with a career spanning leadership roles in global organizations such as Accenture, HSBC, and Harbinger Systems. At Accenture LLP, he has served as a Tech Architecture Manager, overseeing end-to-end project lifecycles, from requirement analysis to deployment, while managing large teams and delivering solutions for Fortune 500 clients, particularly in the banking and finance sectors. His professional expertise extends across Generative AI, cloud computing, DevOps, CI/CD pipelines, software development, and middleware systems. He has consistently demonstrated strong leadership by guiding teams, driving client engagements, and ensuring the delivery of high-quality solutions. His background also includes hands-on technical skills in Java, Python, Unix/Linux, and database systems. This combination of managerial and technical expertise allows him to effectively integrate innovation into business solutions. His professional experience illustrates a successful balance between technical depth, organizational leadership, and research-driven development.

Research Focus

Mr. Prashant Awasthi’s research focus lies at the intersection of artificial intelligence, cloud computing, cybersecurity, and emerging digital technologies. His published work addresses critical areas such as reinforcement learning, heuristic algorithms, human activity recognition using CNNs, framework-agnostic JavaScript libraries, and the role of AI-powered systems like ChatGPT. He has also explored blockchain, cryptocurrencies, and IoT security frameworks, highlighting his multidisciplinary approach to solving contemporary technology challenges. His work often emphasizes integrating advanced algorithms with real-world applications, such as improving system efficiency, scalability, and security in cloud environments. He has a strong interest in sustainable and innovative computing solutions, as reflected in his research on digital twins, wireless fog-IoT networks, and environmental data analysis. By contributing to both applied and theoretical dimensions of research, he bridges academia and industry, ensuring that his work remains relevant and impactful. His focus on practical implementation ensures that his research benefits technological advancement globally.

Award and Honor

Mr. Prashant Awasthi has received recognition for his contributions to research, academia, and the professional community through various prestigious roles and honors. He has been invited as a speaker at international conferences, where he has shared his insights on artificial intelligence, machine learning, and generative AI. His expertise has also earned him appointments as a session chair and reviewer at globally recognized conferences, including events organized by Springer, Elsevier, and international academic bodies. By serving as a reviewer and technical committee member, he has contributed to maintaining research quality and supporting innovation within the global scientific community. His memberships with leading professional associations such as IEEE and IAENG further highlight his standing as a respected contributor to the field. These honors, combined with his published research in reputed journals and conferences, reflect his dedication to advancing technology and academia. His recognition underscores his credibility as a global researcher and thought leader.

Publication Top Notes

Title: Framework-Agnostic JavaScript Component Libraries: Benefits, Implementation Strategies, and Commercialization Models
Authors: KK Gupta, P Awasthi, M Shaik, PR Kaveri
Year: 2024
Citations: 6

Title: ChatGPT: The Power Of AI
Authors: P Awasthi, DPR Kaveri
Year: 2023
Citations: 2

Title: Effect of Prompt Engineering on Education Sector: A Mixed Case Study
Authors: P Awasthi
Year: 2021
Citations: 2

Title: Evaluating the Need of Reinforcement Learning by Implementing Heuristic Algorithms with Its Load Balancing and Performance Testing in Cloud
Authors: KDPA Prathamesh Vijay Lahande, Parag Ravikant Kaveri, Vinay Chavan
Year: 2025

Title: Explainability and Interpretability of Large Language Models in Critical Applications
Authors: PA Vinod Goje, Rohit Jarubula, Sai Krishna Kalakonda
Year: 2025

Title: Real-Time Human Motion Behaviour Recognition Using Deep Learning Models
Authors: P Awasthi
Year: 2025

Title: Integrating Human Motion Dynamics in CNN Architecture to Recognize Human Activity from Different Camera Angles
Authors: KK Gupta, JH Lee, PR Kaveri, P Awasthi
Year: 2025

Title: Seasonal Variations and Water Quality Dynamics: Analysis of Kanota Dam in Relation to WHO Standards
Authors: DK Meena, S Singh, SK Singh, V Pandey, RS Rana, B Sajan, P Awasthi, et al.
Year: 2024

Title: History, Current, and Prospective of Bitcoin and Cryptocurrency
Authors: MD Prashant Awasthi
Year: 2024

Conclusion

Mr. Prashant Awasthi’s publication record reflects a strong blend of technical innovation, academic contribution, and interdisciplinary research. His works span critical areas such as artificial intelligence, machine learning, cloud computing, blockchain, and applied deep learning, highlighting both depth and versatility. With multiple papers published in reputed conferences and journals, along with growing citation impact, his research demonstrates recognition and relevance in the scholarly community. Additionally, his contributions as a sole author and as part of collaborative teams show his ability to lead as well as integrate within diverse research environments. While some of his recent works are yet to accumulate citations, they address timely and impactful topics that are likely to gain traction in the coming years. Overall, his research portfolio establishes him as a promising and impactful contributor to academia and industry, making him a strong candidate for recognition in awards and honors related to research excellence.

Xiaolin Yang | Machine learning | Best Researcher Award

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Dr. Xiaolin Yang | Machine learning | Best Researcher Award

China university of mining and technology, China

📈 Xiaolin Yang is a highly skilled Business Analyst with a Ph.D. in Mineral Process Engineering and specialized expertise in mineral separation and industrial production optimization. Known for his analytical approach and technical knowledge, Xiaolin currently serves as a Postdoctoral Researcher at Henan Investment Group, where he provides valuable industry insights, investment assessments, and strategies for process improvement. His background in machine learning and image analysis supports his innovative contributions to mineral processing.

Publication Profile

ORCID

Education

🎓 Xiaolin Yang completed his Bachelor’s degree in Mineral Process Engineering at China University of Mining and Technology (2015-2019) and later earned a Doctorate in the same field from the same institution (2019-2024). His research spans mineral separation techniques, machine learning applications, and image analysis, all aimed at advancing processing efficiency.

Experience

💼 Xiaolin is currently a Postdoctoral Researcher at Henan Investment Group, where he contributes to industry research, investment evaluation, and production optimization. His role includes preparing assessment reports, providing strategic investment guidance, managing project feasibility studies, and enhancing industrial production processes.

Research Focus

🔬 Xiaolin’s research focuses on mineral processing, applying machine learning and image analysis to improve separation processes and equipment. His studies advance understanding of mineral properties and optimization techniques, contributing to the field’s progression toward smarter, data-driven methodologies.

Awards and Honors

🏅 Xiaolin has been recognized for his contributions to mineral process engineering, having published in prominent journals like Journal of Materials Research and Technology and Expert Systems with Applications. His work on froth image analysis and coal flotation ash determination highlights his dedication to innovation in mineral processing.

Publication Highlights

A comparative study on the influence of mono, di, and trivalent cations on chalcopyrite and pyrite flotation (2021). Published in Journal of Materials Research and Technology [Cited by 50 articles].

Ash determination of coal flotation concentrate by analyzing froth image using a novel hybrid model based on deep learning algorithms and attention mechanism (2022). Published in Energy [Cited by 35 articles].

Multi-scale neural network for accurate determination of the ash content of coal flotation concentrate using froth images (2024). Published in Expert Systems with Applications [Cited by 20 articles].

Arunabh Bora | Machine Learning | Best Researcher Award

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Mr. Arunabh Bora | Machine Learning | Best Researcher Award

AI Engineer, UTAP Tech, United Kingdom

🌟 Arunabh Bora is an innovative Artificial Intelligence Engineer currently at UTAP Tech, Louth, United Kingdom, specializing in cutting-edge computer vision and machine learning solutions. With a background in electronics, robotics, and autonomous systems, he brings a unique skill set to AI-driven problem-solving in agricultural and medical domains. His passion for tech is reflected in his hands-on experience with deep learning models and reinforcement learning for various applications. 💻🔬

Publication Profile

Google Scholar

Education

🎓 Arunabh holds a Master of Science in Robotics and Autonomous Systems (Distinction) from the University of Lincoln, UK, where he earned 95% on his dissertation exploring Large Language Models for medical chatbot applications. He also completed a Bachelor of Technology in Electronics and Communication Engineering from Gauhati University, India, where he published two research papers on IoT and machine learning for agriculture. 📚🌾

Experience

💼 As an Artificial Intelligence Engineer at UTAP Tech, Arunabh is leading the development of a computer vision-based cattle weight prediction system. He also gained research experience as a Research Assistant at the University of Lincoln, contributing to net zero strategy reviews and machine learning model optimizations for industrial processes under Dr. Pouriya H. Niknam’s supervision. 🤖🌍

Research Focus

🔍 Arunabh’s research interests lie in the integration of artificial intelligence with robotics and healthcare. His current focus is on applying deep learning, retrieval-augmented generation (RAG), and large language models (LLMs) for medical chatbots, computer vision applications in agriculture, and reinforcement learning for robotics. 🚜🏥

Awards and Honors

🏆 Arunabh’s excellence in academia is highlighted by his distinction in his master’s degree. He has also contributed to multiple impactful research projects and received recognition for his innovative work in AI, IoT, and machine learning. 🥇✨

Publications

📝 Arunabh has published research on various AI-driven applications. His notable works include:

“Systematic Analysis of Retrieval-Augmented Generation-Based LLMs for Medical Chatbot Applications” published in Machine Learning and Knowledge Extraction (2024), https://doi.org/10.3390/make6040116 cited by 10 articles.

“Monitoring and Control of Water Requirements as Part of an Agricultural Management System using IoT” presented at the 7th International Conference on Mathematics and Computers in Sciences and Industry (MCSI) in 2022, https://doi.org/10.1109/MCSI55933.2022.00025 cited by 15 articles.

 

 

NEHA KATIYAR | Machine Learning | Best Research Article Award

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MS. NEHA KATIYAR | Machine Learning | Best Research Article Award

RESEARCH SCHOLAR, Bennett university, India

 

Neha Katiyar is an Assistant Professor at Noida Institute of Technology, Greater Noida, India. With a robust background in Information Technology and Computer Science, she has contributed significantly to academia through teaching, research, and project management.

Profile

Scopus

Education

🎓 Doctorate
Bennett University, Greater Noida (July 2023 – Present)
Department: Computer Science & Engineering

🎓 Master of Technology
Madan Mohan Malviya University of Technology, Gorakhpur (Aug 2018 – July 2020)
Department: Information Technology and Computer Application
Percentage: 69% (First Division)

🎓 Bachelor of Technology
Sir Chootu Ram Institute of Engineering & Technology, Meerut (July 2015 – June 2018)
University: Chaudhary Charan Singh University, Meerut, U.P
Course: Information Technology
Percentage: 74% (First Division)

🎓 Diploma in Engineering
Government Girls Polytechnic, Lucknow (July 2010 – December 2013)
University: Board of Technical Education, Lucknow UP
Course: Information Technology
Percentage: 70% (First Division)

🎓 High School
Soni Pariya Inter College, Farrukhabad (Apr 2009 – Mar 2010)
Board: Board of High School and Intermediate Education, U.P.
Percentage: 58% (Second Division)

Experience

💼 Assistant Professor
Noida Institute of Technology, Greater Noida (11 April 2022 – 17 May 2023)
Responsibilities included evaluation of copies, research work, academic work, and preparation of question banks and presentations.

💼 Academic Associate
Indian Institute of Management, Rohtak (22 July 2021 – 7 April 2022)
Assisted faculties, conducted empirical research, managed conferences, and evaluated copies.

💼 Research Assistant
Ajay Kumar Garg Engineering College, Ghaziabad (12 Oct 2020 – 16 Jul 2021)
Worked on a project titled “Compressed parallel wavelet tree based on semantic search” funded by the Council of Science And Technology, Uttar Pradesh (UPCST).

Research Interest

🔬 Neha’s research interests include Cyber Security, Internet of Things (IoT), Machine Learning, and Artificial Intelligence. She has actively participated in various projects and research works, contributing to advancements in these fields.

Publications Top Notes

📚 Neha has authored several research papers and articles in reputed journals and conferences. Below are some of her notable publications:

Diabetes detection using IoT techniques and platform: A Survey – Published in the 1st International Conference on Recent Trends in Computer Science and Information Technology (ICRCSIT-20) at St. Martin’s Engineering College Secunderabad Telangana, on 17-18 June 2020.

A review: Target Based Sentiment Analysis using Machine Learning – Published in the 4th International Conference on Microelectronics and Telecommunications at SRM Institute of Science and Technology NCR Campus, on 26-27 Sept. 2020 (Springer Conference).

Index Optimization using Wavelet Tree and Compression – Published in the 2nd International Conference on Data Analytics and Management Conference (ICDAM 2021) at Panipat Institute of Engineering and Technology, on 26 June 2021.

A Survey on Wavelet Tree ensembles with Machine Learning and its classification – Published in 2021 at Sreyas Institute of Engineering and Technology, Hyderabad, on 9-10 July 2021.

A perspective towards 6G Networks – Published in the 5th ICMETE21 at SRM Institute of Science and Technology NCR Campus, on 24-25 Sept. 2021 (Springer Conference).

Trending IoT platform Middleware layer – Published in Taylor and Francis Group Journal on 3 May 2023.

Samir Younis | Machine Learning | Best Researcher Award

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Mr. Samir Younis | Machine Learning | Best Researcher Award

Machine Learning Engineer, Arab Academy for Science and Technology, Egypt

Samir Younis is a dynamic Data Scientist from Alexandria, Egypt, with a strong foundation in computer engineering and a passion for leveraging machine learning to solve real-world problems. With a track record of impactful projects and a commitment to innovation, he has quickly established himself in the field. 🌟💻

 Profile

Google Scholar

Education

Samir earned his Bachelor’s degree in Computer Engineering from the Arab Academy For Science and Technology in June 2023, graduating with a GPA of 3.2. His academic journey provided him with a solid grounding in engineering principles and advanced computational techniques. 🎓📚

Experience

 

  • Machine Learning Engineer, Upwork (May 2023 – Present)
    Samir builds and deploys custom machine learning models to address complex business challenges for clients on Upwork. His projects include an Atrial Fibrillation Detection System, an Autism Spectrum Disorder Early Detection Model, Transfer Learning Benchmarking Research, and an Automated Attendance System Using Facial Recognition.
  • Data Scientist Intern, Encryptix (May 2024 – June 2024)
    During his internship, Samir applied machine learning techniques to various prediction and classification tasks, enhancing his practical experience in the field. 🔍🤖

Research Interests

Samir’s research interests lie in machine learning applications in healthcare and image recognition. He focuses on developing robust algorithms for early disease detection and facial recognition, showcasing his versatility and commitment to advancing technology. 🧠🔬

Awards and Honors

Samir was honored by the Information Technology Industry Development Agency (ITIDA) as a Pre-Incubation Winner on a national scale for his innovative contributions to technology and research. This recognition underscores his potential and impact in the field. 🏆🎉

Publications Top Notes

  • Evaluating Convolutional Neural Networks and Vision Transformers for Baby Cry Sound Analysis
    Published in MDPI’s ‘Future Internet’ journal, this paper presents an advanced algorithm achieving a 98.3% accuracy rate in detecting the reasons behind baby crying, marking significant advancements in machine learning applications for infant care. Link, 2023.
  • IBM Capstone Project Utilizing AI for Early Lung Disease Detection
    This project involved data curation, quality assessment, and the implementation of the Compacted Convolutional Transformer (CCT) for robust medical image classification, contributing to improved healthcare outcomes. Link, 2024.
  • One Shot Face Recognition System
    Samir implemented a facial recognition system capable of recognizing individuals from just one image per person, utilizing pre-trained deep learning models and OpenCV for face detection and embedding generation. Link, 2023.