Alexios Kaponis | Computer Science | Excellence in Research

Mr. Alexios Kaponis | Computer Science | Excellence in Research

PhD Candidate,Ionian University , Greece

Alexios Kaponis is a promising researcher with a robust portfolio of work in AI and digital marketing, focused on both technical innovation and ethical implications. His research output, coupled with hands-on project experience and a solid educational foundation, positions him as a dedicated and impactful researcher. He continues to develop expertise that addresses both theoretical and applied challenges in computer science.

Professional Profile

๐ŸŽ“ Educational Background

Alexios Kaponis was born in Patras on August 6, 1987. He earned his diploma in Cultural Management from the Department of Management of Cultural Environment and New Technologies at the University of Ioannina in 2009. Later, he obtained a masterโ€™s degree in Technologies and Management from the Department of Information and Communication Systems Engineering at the University of the Aegean in 2017. Currently, Alexios is pursuing a doctoral degree in Computer Science at the University of the Ionian Islands. His PhD research focuses on โ€œData analysis in digital marketing using machine learning and artificial intelligence techniques, business analysis, practices, and ethical dimensions in e-commerce.โ€

๐Ÿง‘โ€๐Ÿซ Professional Experience

Alexios currently works as an Intelligent Software Solutions expert at the National Research Centre for Physical Sciences (NCRS) “Demokritos.” Since April 2024, he has been involved in the WP2 Data Inspection and Generation and WP5 Trustworthy Efficiency & Performance Assessment Framework projects, focusing on advanced machine learning and AI tools to improve risk prediction and fraud detection. His responsibilities include proposing new intelligence tool developments, conducting data analysis, and leveraging big data and cloud-based technologies.

๐Ÿ”ฌ Research Focus

Alexiosโ€™s research primarily centers on the application of machine learning and AI techniques in digital marketing, with a strong emphasis on ethical and legal dimensions in e-commerce. He investigates the use of natural language processing and large-scale data mining for business intelligence and enhanced customer engagement. His ongoing doctoral work explores innovative data analysis methodologies to support decision-making in marketing strategies. Furthermore, he contributes to projects aiming to improve AI reliability and trustworthiness in practical applications, such as fraud detection and chatbot development.

๐Ÿ› ๏ธ Skills and Expertise

Alexios possesses strong expertise in big data, data analytics, artificial intelligence, data management, and cloud computing technologies. He has hands-on experience with machine learning, natural language processing, semantic web technologies, and digital marketing analytics. Additionally, Alexios is proficient in web development tools such as Joomla and WordPress and skilled in Google Analytics. He is fluent in Greek and highly proficient in English, complemented by a computer diploma certified by the University of Ioannina.

๐Ÿ… Awards & Honours

Alexios was distinguished by the General Secretariat for Lifelong Learning for his successful completion of a 25-hour seminar dedicated to training teachers in vocational adult education. His active participation as an examiner in national qualification certification examinations highlights his commitment to professional excellence in IT education. He has also presented and published multiple papers at prestigious international conferences, reflecting recognition of his research contributions in artificial intelligence, digital marketing, and assistive technologies.

Publication Top Notes

  1. Assist of AI in a Smart Learning Environment

    • Authors: K.C. Sofianos, Michalis Stefanidakis, Alexios Kaponis, Linas Bukauskas

    • Year: 2024

    • Citation count: 1

  2. Data Analysis in Digital Marketing using Machine Learning and Artificial Intelligence Techniques, Ethical and Legal Dimensions, State of the Art

    • Author: Alexios Kaponis, M. Maragoudakis

    • Year: 2022

    • Citation count: (Not provided, please add if known)

  3. Case Study Analysis of Medical and Pharmaceutical Chatbots in Digital Marketing and Proposal to Create a Reliable Chatbot with Summary Extraction Based on Usersโ€™ Keywords

    • Authors: Alexios S. Kaponis, Alexios A. Kaponis, Manolis Maragoudakis

    • Year: 2023

    • Citation count: (Not provided)

  4. Enhancing Disease Diagnosis: A CNN-Based Approach for Automated White Blood Cell Classification

    • Authors: Athanasios Kanavos, Orestis Papadimitriou, Alexios Kaponis, Manolis Maragoudakis

    • Year: 2023

    • Citation count: (Not provided)

Conclusion

Given his achievements and ongoing contributions, Alexios Kaponis is a fitting candidate for the Excellence in Research Award. Recognizing his work would not only honor his past accomplishments but also encourage further advancements in AI-driven research that balances innovation with ethical responsibility. With continued focus on increasing research impact and leadership, Alexios is well poised for future excellence in his field.

Prof. Dr. Wei Fang | Analytics Award | Best Researcher Award

Prof. Dr. Wei Fang | Analytics Award | Best Researcher Award

Prof. Dr. Wei Fang, Nanjing University of Information Science & Technology, China

Prof. Dr. Wei Fang is a Professor in the Department of Computer Science at Nanjing University of Information Science & Technology, China, and a member of the State Key Laboratory for Novel Software Technology, Nanjing University. He holds a Ph.D. and M.Sc. in Computer Science from Soochow University. Wei was a visiting scholar at the University of Florida in 2015-2016. His research interests include Artificial Intelligence, Big Data, Data Mining, and Meteorological Information Processing. He has led several research projects funded by the National Natural Science Foundation of China and is an active reviewer for international journals. Wei is a senior member of the CCF and ACM.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

Summary of Suitability for Best Researcher Award โ€“ Prof. Wei Fang

Prof. Wei Fang of Nanjing University of Information Science & Technology stands out as a highly meritorious candidate for the Best Researcher Award. With a solid academic foundation, national and international research exposure, and extensive contributions in Artificial Intelligence, Big Data, Computer Vision, and Applied Meteorology, his work bridges theoretical innovation with real-world application.

๐ŸŽ“ Education

  • Ph.D. in Computer Science โ€“ Soochow University, China

  • M.Sc. in Computer Science โ€“ Soochow University, China

๐Ÿ“š Visiting Scholar โ€“ University of Florida, USA (Faculty of Computer Science, Sept 2015 โ€“ Sept 2016)

๐Ÿ’ผ Work Experience

  • ๐Ÿ‘จโ€๐Ÿซ Professor, Department of Computer Science, NUIST

  • ๐Ÿงช Affiliated with the State Key Lab for Novel Software Technology, Nanjing University

  • ๐Ÿค Program Committee Member for multiple international conferences

  • ๐Ÿ“ Reviewer for various international journals

  • ๐ŸŒ International Research Scientist

๐Ÿ† Achievements & Honors

  • ๐Ÿง  Recognized for impactful research in:

    • Artificial Intelligence ๐Ÿค–

    • Big Data & Cloud Computing โ˜๏ธ๐Ÿ“Š

    • Computer Vision ๐Ÿ‘๏ธ

    • Applied Meteorology ๐ŸŒฆ๏ธ

  • ๐Ÿ”ฌ Project Leader of national and industrial research projects funded by:

    • National Natural Science Foundation of China

    • Guodian Nari Nanjing Control System Co., Ltd.

    • Baoshan Iron and Steel Co., Ltd.

  • ๐ŸŽ–๏ธ Senior Member of CCF (China Computer Federation) & ACM

  • ๐Ÿ“ˆ Cited in SCI-indexed journals

Publicationย Top Notes:

A rapid learning algorithm for vehicle classification

CITED: 562

A Method for Improving CNN-Based Image Recognition Using DCGAN.

CITED: 230

Efficient feature selection and classification for vehicle detection

CITED: 220

A survey of big data security and privacy preserving

CITED: 117

Survey on research of RNN-based spatio-temporal sequence prediction algorithms

CITED: 100