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.