Qinxu Ding | Machine Learning and AI Applications | Best Researcher Award

Dr. Qinxu Ding | Machine Learning and AI Applications | Best Researcher Award

Dr. Qinxu Ding at Singapore University of Social Sciences, Singapore

PROFILES👨‍🎓

EARLY ACADEMIC PURSUITS 📚

This accomplished individual began their academic journey with a B.S. in Information and Numerical Science from Nankai University, Tianjin, China, graduating in July 2015 with an impressive GPA of 89/100. Their undergraduate studies laid a strong foundation in Mathematical Statistics, Probability Theory, and Data Mining, which paved the way for further academic exploration. They pursued a Ph.D. in Computational Mathematics at Nanyang Technological University, completing their thesis on Numerical Treatment of Certain Fractional and Non-fractional Differential Equations in April 2020.

PROFESSIONAL ENDEAVORS 💼

Currently, this individual serves as a Lecturer and DBA Supervisor in the Finance Programme at the Business School of the Singapore University of Social Sciences (SUSS) since July 2021. Their teaching portfolio includes various fintech courses such as Machine Learning and AI for FinTech, Blockchain Technology, and Risk Management for Finance and Technology. Prior to this role, they were a Research Fellow at the Alibaba-NTU Singapore Joint Research Institute, focusing on Explainable Artificial Intelligence.

CONTRIBUTIONS AND RESEARCH FOCUS 🔍

Their research interests lie at the intersection of applied machine learning, computational mathematics, and blockchain technology in fintech. They have made significant contributions through publications in top-tier AI conferences, including ICLR, NeurIPS, AAAI, and CIKM, as well as prestigious journals in computational mathematics and fintech.

IMPACT AND INFLUENCE 🌟

The individual has played a pivotal role in enhancing the understanding of machine learning models and their applicability in real-world financial scenarios. Their work on adversarial attacks in deep neural networks and the development of explainable AI frameworks has positioned them as a thought leader in the field, influencing both academic and industrial practices.

ACADEMIC CITES 📖

Their groundbreaking research has been recognized in multiple high-impact venues, highlighting their innovative approaches to complex problems in fintech. Notable publications include works on adversarial defenses, counterfactual explanations, and recommendation systems, reflecting a robust commitment to advancing knowledge in AI and fintech.

LEGACY AND FUTURE CONTRIBUTIONS 🌱

As a Chartered Fintech Professional and a member of various academic committees, this individual continues to contribute to the fintech community. Their involvement in organizing the Global Web3 Eco Innovation Summit 2022 illustrates their dedication to fostering innovation and collaboration in the fintech space. Looking ahead, they aim to further bridge the gap between academia and industry, shaping the future of fintech through research and education.

TOP NOTED PUBLICATIONS 📖

Stable neural ode with lyapunov-stable equilibrium points for defending against adversarial attacks
    • Authors: Q. Kang, Y. Song, Q. Ding, W. P. Tay
    • Journal: Advances in Neural Information Processing Systems
    • Year: 2021
Non-polynomial Spline Method for Time-fractional Nonlinear Schrödinger Equation
    • Authors: Q. Ding, P. J. Y. Wong
    • Journal: 15th International Conference on Control, Automation, Robotics and …
    • Year: 2018
A hybrid bandit framework for diversified recommendation
    • Authors: Q. Ding, Y. Liu, C. Miao, F. Cheng, H. Tang
    • Journal: Proceedings of the AAAI Conference on Artificial Intelligence
    • Year: 2021
Quintic non-polynomial spline for time-fractional nonlinear Schrödinger equation
    • Authors: Q. Ding, P. J. Y. Wong
    • Journal: Advances in Difference Equations
    • Year: 2020
A survey on decentralized autonomous organizations (DAOs) and their governance
    • Authors: Q. Ding, D. Liebau, Z. Wang, W. Xu
    • Journal: World Scientific Annual Review of Fintech
    • Year: 2023
The skyline of counterfactual explanations for machine learning decision models
    • Authors: Y. Wang, Q. Ding, K. Wang, Y. Liu, X. Wu, J. Wang, Y. Liu, C. Miao
    • Journal: Proceedings of the 30th ACM International Conference on Information …
    • Year: 2021

Amir Reza Rahimi | artificial intelligence | Best Researcher Award

Mr. Amir Reza Rahimi, artificial intelligence, Best Researcher Award

Mr. Amir Reza Rahimi at Universidad de Valencia, Spain

Professional Profile

Google Scholar Profile
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Research Gate Profile

Summary

Amir Reza Rahimi is a Ph.D. candidate at the University of Valencia, specializing in Language, Literature, and Cultures and their applications. He has extensive teaching experience in English at universities, high schools, and language institutes in Iran. Rahimi has also conducted workshops on using technology in English language teaching. His research, focusing on psycholinguistics, computer-assisted language learning (CALL), and educational technology, has been published in leading journals and presented at international conferences.

Education

Amir Reza Rahimi holds a Master’s degree in English Language Teaching from Shahid Rajaee Teacher Training University in Tehran, Iran, where his thesis focused on the impact of Massive Open Online Courses (MOOCs) on the structural relationship between online regulation and online motivational self-systems among Iranian EFL learners. He earned his Bachelor’s degree in English Language Teaching from the University of Mohaghegh Ardabili in Ardabil, Iran. Currently, he is pursuing a Ph.D. in Language, Literature, and Cultures and its Applications at the University of Valencia, Spain, with research interests spanning computer-assisted language learning (CALL), educational technology, and psycholinguistics.

Professional Experience

Amir Reza Rahimi has amassed significant experience in English language education, having taught at various universities, high schools, and language institutes throughout Iran. His career includes conducting workshops aimed at integrating technology into English language teaching methodologies. Rahimi’s expertise extends to research in psycholinguistics, computer-assisted language learning (CALL), and educational psychology, contributing extensively to scholarly publications and presenting his work at prestigious international conferences. Currently a Ph.D. candidate at the University of Valencia, Spain, Rahimi continues to explore innovative approaches in language education and teacher development.

Research Interests

Amir Reza Rahimi’s research interests encompass several facets of language education and technology integration. His work primarily focuses on computer-assisted language learning (CALL), exploring the impact of Massive Open Online Courses (MOOCs) on language learners’ motivational self-systems and educational outcomes. Rahimi is also deeply engaged in psycholinguistics, investigating the cognitive processes involved in language acquisition and proficiency development. His research extends to educational technology, where he explores innovative methods and tools to enhance language teaching and learning experiences. Rahimi’s scholarly pursuits aim to contribute to theoretical advancements in the fields of language education and educational psychology, addressing contemporary challenges and opportunities in digital learning environments.

Conferences and Workshops

  • WorldCALL conference, Chiang Mai, Thailand
  • 21st Asia TEFL International Conference
  • TELLSI19 Conference, University of Birjand, Iran
  • AELTE 2022, Ankara, Turkey

Academic Membership

  • 2017-Present: Teaching English Language and Literature Society of Iran (TELLSI)

Technical Skills

  • SPSS, LISREL, AMOS, PLS-SEM, MAXQDA
  • Computer literacy (2018-2020)

Amir Reza Rahimi’s extensive background in teaching, research, and professional development showcases his expertise and contributions to the field of English Language Teaching and Educational Technology.

📖 Publication Top Noted