merve pฤฑnar | Machine Learning | Best Researcher Award

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Dr. merve pฤฑnar | Machine Learning | Best Researcher Award

Research Ass, Marmara University, Turkey

Merve Pinar is a Research Assistant in the Faculty of Technology, Computer Engineering Department at Marmara University, Turkey. She has been pursuing her doctorate since 2023 at Marmara University in the field of Computer Engineering. Her academic journey includes a postgraduate degree from the Institute for Graduate Studies in Pure and Applied Sciences (2019-2022) and an undergraduate degree from ร‡anakkale Onsekiz Mart University, where she studied Engineering (2009-2013). Merveโ€™s work primarily focuses on artificial intelligence, machine learning, and their applications in various fields, especially healthcare. She is dedicated to exploring innovative solutions using deep learning and pattern recognition techniques. Her contributions to the academic community include publications in respected journals and conferences. She also actively collaborates with other researchers to advance the field.

Profile 

Education

  • Doctorate (2023-Present): Marmara University, Faculty of Technology, Computer Engineering, Turkey.
  • Postgraduate (2019-2022): Marmara University, Institute for Graduate Studies in Pure and Applied Sciences, Turkey. Dissertation: โ€œDerinรถฤŸrenme yรถntemleri kullanฤฑlarak beyin tรผmรถrรผ tiplerinin ve sฤฑnฤฑrlarฤฑnฤฑn tahminlenmesiโ€ (Prediction of brain tumor types and boundaries using deep learning methods).
  • Undergraduate (2009-2013): ร‡anakkale Onsekiz Mart University, Faculty of Engineering, Turkey.

Merveโ€™s academic background provides a solid foundation in computer engineering, artificial intelligence, and data science. She continues to pursue advanced studies, focusing on leveraging machine learning and deep learning methods to address complex problems in health and technology.

Research Focus

Merve Pinarโ€™s research focuses on the intersection of artificial intelligence, machine learning, and medical applications. Her primary interests are database management, data structures, pattern recognition, and deep learning. She specializes in using AI techniques for medical imaging, particularly in the classification and segmentation of brain tumor types using MRI and surgical microscope images. Her work aims to enhance diagnostic tools, improving the accuracy and efficiency of healthcare systems. Additionally, she is involved in hyperparameter optimization for big data applications, which helps improve recommendation systems. Merveโ€™s interdisciplinary research is positioned at the cutting edge of AI, combining computer engineering with real-world applications, particularly in healthcare technology, where deep learning plays a crucial role in revolutionizing diagnostics and treatment strategies.

Publications

  • Deep Learning-Assisted Segmentation and Classification of Brain Tumor Types on Magnetic Resonance and Surgical Microscope Images ๐Ÿง ๐Ÿ’ป (2024)
  • Hyperparameter Optimization for Recommendation Systems with Big Data ๐Ÿ“Š๐Ÿ” (2017)

Karthikeyan P | Deeplearning | Best Paper Award

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Dr. Karthikeyan P | Deeplearning | Best Paper Award

Associate Professor, RV University, India

Dr. P. Karthikeyan is an Associate Professor at the School of Computer Science and Engineering, RV University, Bengaluru, with extensive expertise in Cloud Computing, Deep Learning, and Blockchain. With over 50 published research papers in international journals and conferences, Dr. Karthikeyan has significantly contributed to advancing knowledge in computer science. He has delivered over 30 talks and conducted workshops on emerging technologies, emphasizing practical applications of cloud infrastructure, deep learning, and programming. Throughout his career, he has worked with governmental projects in Taiwan and Saudi Arabia. His commitment to teaching is driven by his belief in using computer science to uplift society and improve lives. He is passionate about creating enriching learning experiences for students while fostering a collaborative academic environment.

Profile

Education 

Dr. P. Karthikeyan holds a Ph.D. from Anna University, Chennai (2018), with a focus on improving Virtual Machine instance allocation algorithms in cloud environments. He earned his M.E. in Computer Science & Engineering from Anna University Coimbatore (2009), with an impressive CGPA of 9.36/10.00. His undergraduate studies were completed at Muthayammal Engineering College, Namakkal, where he obtained a B.E. in Computer Science & Engineering (2005) with a percentage of 73%. Additionally, he holds a Diploma in Electrical and Electronics Engineering from Muthayammal Polytechnic College, Namakkal, with a percentage of 87%. Dr. Karthikeyanโ€™s educational foundation laid the groundwork for his future academic and research achievements in the field of computer science, particularly in cloud computing, deep learning, and blockchain technologies.

Experience

Dr. P. Karthikeyan has a rich teaching and research background, currently serving as an Associate Professor at RV University, Bengaluru, since September 2023. He previously held academic positions as Associate Professor at Jain Deemed-to-be University (2021โ€“2022) and Parul University (2020โ€“2021), where he also led the Department of Computer Science and Engineering. Dr. Karthikeyanโ€™s international experience includes serving as a Post-Doctoral Researcher at National Chung Cheng University, Taiwan (2022โ€“2023). His early career includes teaching roles at Presidency University, Bengaluru, and Karunya Institute of Technology and Sciences, Coimbatore, where he shaped the next generation of computer scientists. He has also contributed to the development of significant government projects in Taiwan and Saudi Arabia. Dr. Karthikeyan teaches subjects related to System Software, Cloud Computing, Deep Learning, and Cryptography, while guiding students in advanced research in these areas.

Awards and Honors 

Dr. P. Karthikeyan has been recognized for his exceptional contributions to research and academia. Notably, he received the Best Young Researcher Award (Male) at the 2nd International Academic and Research Excellence Awards (IARE) in 2020, acknowledging his significant research achievements in the field of computer science. His work in cloud computing, deep learning, and blockchain has led to over 50 publications in prestigious journals and conferences, further solidifying his reputation as a leading academic in these fields. Dr. Karthikeyan has also been a key speaker and workshop facilitator, sharing his knowledge in over 30 talks globally. His continued commitment to research and education, coupled with his active involvement in international collaborations and government projects, highlights his contribution to the development of technology and education.

Research Focus 

Dr. P. Karthikeyanโ€™s research interests lie at the intersection of Cloud Computing, Deep Learning, and Blockchain technologies. He focuses on optimizing cloud environments, particularly through virtual machine instance allocation algorithms, and has contributed significantly to enhancing cloud infrastructure. His work in deep learning spans multiple domains, from intrusion detection in IoT environments to applications in medical imaging and intelligent traffic management. Additionally, Dr. Karthikeyanโ€™s research in blockchain explores its use in IoT security, supply chain management, and energy transaction markets. He is also deeply involved in research on federated learning, explainable AI, and blockchain-enabled solutions for privacy and security. Through his research, Dr. Karthikeyan aims to develop socially relevant applications that not only advance academic knowledge but also contribute to solving real-world problems, such as improving supply chain security and advancing sustainable smart grid technologies.

Publications

  1. Hybrid electro search with genetic algorithm for task scheduling in cloud computing โ€“ Ain Shams Engineering Journal ๐ŸŒ๐Ÿ“…
  2. Detection of distributed denial of service attack in cloud computing using optimization-based deep networks โ€“ Journal of Experimental & Theoretical AI ๐Ÿ“‰โšก
  3. Blockchain Technology: Challenges and Security issues in Consensus algorithm โ€“ International Conference on Computer Communication and Informatics ๐Ÿ”—๐Ÿ”
  4. A survey on blockchain techniques for Internet of Vehicles security โ€“ Transactions on Emerging Telecommunication Technologies ๐Ÿš—๐Ÿ”’
  5. Review of Blockchain-based IoT application and its security issues โ€“ International Conference on Intelligent Computing ๐ŸŒ๐Ÿ”
  6. Efficient lightweight privacy-preserving mechanism for Industry 4.0 based on elliptic curve cryptography โ€“ IEEE Transactions on Industrial Informatics ๐Ÿญ๐Ÿ”
  7. Reinforcement learning integrated in heuristic search for self-driving vehicle using blockchain in supply chain management โ€“ International Journal of Intelligent Networks ๐Ÿš—๐Ÿ“Š
  8. Seafood supply chain management using blockchain โ€“ International Conference on Advanced Computing ๐Ÿฆ๐Ÿ”—
  9. Hybrid optimization scheme for intrusion detection using feature selection โ€“ Neural Computing and Applications ๐Ÿ›ก๏ธ๐Ÿง 
  10. Perishable food products in cold supply chain management using blockchain technology๐ŸŒ

รlvaro Figueira | Artificial Intelligence | Best Paper Award

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Assist. Prof. Dr. รlvaro Figueira | Artificial Intelligence | Best Paper Award

Professor Auxiliar, FCUP โ€“ Universidade do Porto, Portugal

Profile

Orcid

รlvaro Figueira is a distinguished academic and researcher in the field of Computer Science, currently serving as a Professor (Prof. Auxiliar) at Universidade do Porto, Faculdade de Ciรชncias in Portugal. With a robust academic background and extensive experience, his research focuses on data mining, machine learning, social network analysis, and eLearning. Figueiraโ€™s passion for technology and innovation is evident in his contribution to various scientific fields, including data visualization and text mining, where his work aims to bridge theory with practical applications. With years of experience in teaching and leading research initiatives, Figueira is a prominent figure in his discipline. ๐Ÿ“š๐Ÿ’ป

Education

รlvaro Figueiraโ€™s academic journey is distinguished by his advanced qualifications in Computer Science. He obtained his Bachelorโ€™s (BSc) degree from Universidade do Porto, followed by a Masterโ€™s (MSc) from Imperial College London. He continued his academic excellence by completing a Ph.D. at Universidade do Porto in 2004, where he focused on Computer Science. Additionally, Figueira pursued Post-Graduation in Business Intelligence and Analytics at Porto Business School in 2017, further enhancing his expertise. ๐ŸŽ“๐Ÿ“–

Experience

Throughout his career, รlvaro Figueira has amassed a wealth of academic and professional experience. He is currently a Professor at Universidade do Porto, where he teaches and supervises students in the field of Computer Science. He has also worked on a variety of research projects related to eLearning, data science, and machine learning, particularly focused on how these technologies can improve education and business practices. His previous experience includes a prestigious Masterโ€™s thesis position at Imperial College London. ๐ŸŒ๐Ÿ“Š

Research Interests

รlvaro Figueiraโ€™s research interests span a wide array of cutting-edge fields within Computer Science. His primary focus areas include Data Mining, Text Mining, Machine Learning, Social Network Analysis, Data Visualization, and eLearning. Figueiraโ€™s work aims to apply computational techniques to improve the analysis of large datasets, making significant strides in understanding and enhancing social networks and educational systems. His research has contributed to the advancement of automated assessment systems and the optimization of learning processes. ๐Ÿ“ˆ๐Ÿ”

Award

รlvaro Figueiraโ€™s contributions to computer science and education have been recognized with various awards and accolades. Notably, his research has been funded by several prestigious grants, including those from the Fundaรงรฃo para a Ciรชncia e Tecnologia I.P. and Instituto de Engenharia de Sistemas e Computadores. His excellence in research is further highlighted by his numerous publications in top-tier journals, where he continues to make an impact in the fields of data science and machine learning. ๐Ÿ†๐ŸŽ–๏ธ

Publications Top Notes

รlvaro Figueiraโ€™s publication record reflects his significant contributions to the fields of data science, machine learning, and eLearning. Some of his recent publications include:

โ€œTopic Extraction: BERTopicโ€™s Insight into the 117th Congressโ€™s Twitterverseโ€ โ€“ Informatics (2024).

โ€œClustering source code from automated assessment of programming assignmentsโ€ โ€“ International Journal of Data Science and Analytics (2024).

โ€œComparing Semantic Graph Representations of Source Code: The Case of Automatic Feedback on Programming Assignmentsโ€ โ€“ Computer Science and Information Systems (2024).

โ€œGANs in the Panorama of Synthetic Data Generation Methodsโ€ โ€“ ACM Transactions on Multimedia Computing, Communications, and Applications (2024).

โ€œOn the Quality of Synthetic Generated Tabular Dataโ€ โ€“ Mathematics (2023).

โ€œBibliometric Analysis of Automated Assessment in Programming Education: A Deeper Insight into Feedbackโ€ โ€“ Electronics (2023).

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

๐ŸŒŸ 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. ๐Ÿ’ป๐Ÿ”ฌ

Publication Profile

Google Scholar

Education

๐ŸŽ“ 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. ๐Ÿ“š๐ŸŒพ

Experience

๐Ÿ’ผ 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. Niknamโ€™s supervision. ๐Ÿค–๐ŸŒ

Research Focus

๐Ÿ” Arunabhโ€™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. ๐Ÿšœ๐Ÿฅ

Awards and Honors

๐Ÿ† Arunabhโ€™s excellence in academia is highlighted by his distinction in his masterโ€™s degree. He has also contributed to multiple impactful research projects and received recognition for his innovative work in AI, IoT, and machine learning. ๐Ÿฅ‡โœจ

Publications

๐Ÿ“ Arunabh has published research on various AI-driven applications. His notable works include:

โ€œSystematic Analysis of Retrieval-Augmented Generation-Based LLMs for Medical Chatbot Applicationsโ€ published in Machine Learning and Knowledge Extraction (2024), https://doi.org/10.3390/make6040116 cited by 10 articles.

โ€œMonitoring and Control of Water Requirements as Part of an Agricultural Management System using IoTโ€ 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

๐ŸŽ“ Doctorate
Bennett University, Greater Noida (July 2023 โ€“ Present)
Department: Computer Science & Engineering

๐ŸŽ“ Master of Technology
Madan Mohan Malviya University of Technology, Gorakhpur (Aug 2018 โ€“ July 2020)
Department: Information Technology and Computer Application
Percentage: 69% (First Division)

๐ŸŽ“ Bachelor of Technology
Sir Chootu Ram Institute of Engineering & Technology, Meerut (July 2015 โ€“ June 2018)
University: Chaudhary Charan Singh University, Meerut, U.P
Course: Information Technology
Percentage: 74% (First Division)

๐ŸŽ“ Diploma in Engineering
Government Girls Polytechnic, Lucknow (July 2010 โ€“ December 2013)
University: Board of Technical Education, Lucknow UP
Course: Information Technology
Percentage: 70% (First Division)

๐ŸŽ“ High School
Soni Pariya Inter College, Farrukhabad (Apr 2009 โ€“ Mar 2010)
Board: Board of High School and Intermediate Education, U.P.
Percentage: 58% (Second Division)

Experience

๐Ÿ’ผ Assistant Professor
Noida Institute of Technology, Greater Noida (11 April 2022 โ€“ 17 May 2023)
Responsibilities included evaluation of copies, research work, academic work, and preparation of question banks and presentations.

๐Ÿ’ผ Academic Associate
Indian Institute of Management, Rohtak (22 July 2021 โ€“ 7 April 2022)
Assisted faculties, conducted empirical research, managed conferences, and evaluated copies.

๐Ÿ’ผ Research Assistant
Ajay Kumar Garg Engineering College, Ghaziabad (12 Oct 2020 โ€“ 16 Jul 2021)
Worked on a project titled โ€œCompressed parallel wavelet tree based on semantic searchโ€ funded by the Council of Science And Technology, Uttar Pradesh (UPCST).

Research Interest

๐Ÿ”ฌ Nehaโ€™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

๐Ÿ“š 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 โ€“ Published in the 1st International Conference on Recent Trends in Computer Science and Information Technology (ICRCSIT-20) at St. Martinโ€™s Engineering College Secunderabad Telangana, on 17-18 June 2020.

A review: Target Based Sentiment Analysis using Machine Learning โ€“ 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 โ€“ 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 โ€“ Published in 2021 at Sreyas Institute of Engineering and Technology, Hyderabad, on 9-10 July 2021.

A perspective towards 6G Networks โ€“ 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 โ€“ Published in Taylor and Francis Group Journal on 3 May 2023.