Tesfay Gidey | Statistical Modeling | Best Researcher Award

Dr. Tesfay Gidey | Statistical Modeling | Best Researcher Award

Dr. Tesfay Gidey at Addis Ababa Science and Technology University, Ethiopia

👨‍🎓 Professional Profile

 📚 Early Academic Pursuits

Dr. Tesfay Gidey Hailu’s academic journey began with a strong foundation in Statistics at Addis Ababa University, where he earned his BSc with a minor in Computer Science. This rigorous curriculum equipped him with vital skills in statistical methods and computer programming, laying the groundwork for his future studies. He furthered his education with an MSc in Health Informatics and Biostatistics at Mekelle University, delving into advanced topics such as epidemiology and public health, which ignited his passion for applying data-driven solutions in healthcare.

💼 Professional Endeavors

Dr. Gidey has demonstrated remarkable leadership in academia, serving as Associate Dean at Addis Ababa Science and Technology University (AASTU) for multiple departments. His responsibilities included driving research initiatives, enhancing curriculum quality, and overseeing student services. Additionally, his role as Head of Department at Jimma University showcased his commitment to improving departmental operations and student satisfaction. His extensive experience in project management underscores his ability to lead technology projects effectively.

🔬 Contributions and Research Focus

Dr. Gidey’s research is centered on critical areas such as signal processing, indoor localization, and machine learning. His Ph.D. work at the University of Electronic Science and Technology of China focused on applying advanced algorithms to real-world problems, particularly in indoor positioning systems. His contributions to quality control in manufacturing industries and the modeling of public health data further highlight his dedication to leveraging data for impactful solutions.

🌍 Impact and Influence

Through his academic and professional endeavors, Dr. Gidey has significantly influenced the fields of Information and Communication Engineering and data science. His ability to bridge theory and practical application positions him as a valuable asset in technology-driven environments. His commitment to mentoring students and faculty alike has fostered a culture of innovation and continuous improvement within the institutions he has served.

📊 Academic Citations

Dr. Gidey’s scholarly work has gained recognition within academic circles, with several publications focusing on his research areas. His contributions to journals as a reviewer and author have enriched the body of knowledge in his fields, emphasizing the importance of interdisciplinary approaches to problem-solving.

🛠️ Technical Skills

Dr. Gidey is proficient in a variety of programming languages, including Python, R, Java, and C++. He is skilled in using statistical tools such as SAS, SPSS, and advanced machine learning packages. His expertise in data visualization and business intelligence tools, like Tableau and Power BI, equips him to extract meaningful insights from complex datasets.

👩‍🏫 Teaching Experience

With years of teaching experience, Dr. Gidey has effectively communicated complex subjects to students, ensuring they grasp fundamental concepts in information technology and data science. His ability to adapt his teaching methods to diverse learning styles has contributed to high levels of student engagement and success.

🌟 Legacy and Future Contributions

Dr. Gidey is dedicated to advancing the fields of data science and information engineering through research, teaching, and community engagement. His vision includes fostering collaborations between academia and industry, particularly in developing innovative solutions for public health and manufacturing. As he continues his career, Dr. Gidey aims to leave a lasting legacy that inspires future generations of engineers and data scientists.

📈 Conclusion

With a strong foundation in academic excellence, professional leadership, and research innovation, Dr. Tesfay Gidey Hailu stands poised to make significant contributions to the field of Information and Communication Engineering. His passion for data and commitment to actionable results ensure he will continue to drive progress and inspire those around him.

 

📖 Top Noted Publications

Theories and Methods for Indoor Positioning Systems: A Comparative Analysis, Challenges, and Prospective Measures
  • Author: Tesfay Gidey Hailu; Xiansheng Guo; Haonan Si; Lin Li; Yukun Zhang
    Journal: Sensors
    Year: 2024
Ada-LT IP: Functional Discriminant Analysis of Feature Extraction for Adaptive Long-Term Wi-Fi Indoor Localization in Evolving Environments
  • Author: Tesfay Gidey Hailu; Xiansheng Guo; Haonan Si; Lin Li; Yukun Zhang
    Journal: Sensors
    Year: 2024
Measurement Science and Technology
  • Author: Bright Awuku; Ying Huang; Nita Yodo; Eric Asa
    Journal: Measurement Science and Technology
    Year: 2024
Measurement Science and Technology
  • Author: Xun Zhang; Guanghua Xu; Xiaobi Chen; Ruiquan Chen; Jieren Xie; Peiyuan Tian; Sicong Zhang; Qingqiang Wu
    Journal: Measurement Science and Technology
    Year: 2024
Machine Learning: Science and Technology
  • Author: Omer Subasi; Sayan Ghosh; Joseph Manzano; Bruce Palmer; Andrés Marquez
    Journal: Machine Learning: Science and Technology
    Year: 2024
 MultiDMet: Designing a Hybrid Multidimensional Metrics Framework to Predictive Modeling for Performance Evaluation and Feature Selection
  • Author: Tesfay Gidey Hailu; Taye Abdulkadir Edris
    Journal: Intelligent Information Management
    Year: 2023

Di Mao | Data Analysis | Best Researcher Award

Mr. Di Mao | Data Analysis | Best Researcher Award

Mr. Di Mao at Peking University Third Clinical School of Medicine, China

👨‍🎓 Profile

👩‍⚕️ Summary

Di Mao is a dedicated medical student at Peking University Health Science Center, specializing in clinical research. With a focus on reproductive health, she investigates the implications of various health conditions on fertility and pregnancy outcomes.

🎓 Education

Currently enrolled in the Eight-Year Undergraduate Program in Clinical Medicine at Peking University Health Science Center since 2021.

💼 Professional Experience

As a co-author of several research publications in high-impact journals, Di has contributed to studies examining the effects of artificial sweeteners, mental health disorders, and reproductive health in women.

🔍 Research Interests

Di’s research interests encompass reproductive health, infertility, and pregnancy outcomes, as well as the impact of mental health on fertility and thyroid function in assisted reproductive technologies. She also explores trends in postoperative complications and delirium.

📖  Top Noted Publications

Treatment outcomes of infertile women with endometrial hyperplasia undergoing their first IVF/ICSI cycle: A matched-pair study

  • Authors: Jing Yang, Mingmei Lin, Di Mao, Hongying Shan, Rong Li
    Journal: European Journal of Obstetrics & Gynecology and Reproductive Biology
    Year: 2024

Artificial Sweetener and the Risk of Adverse Pregnancy Outcomes: A Mendelian Randomization Study

  • Authors: Di Mao, Mingmei Lin, Zhonghong Zeng, Dan Mo, Kai-Lun Hu, Rong Li
    Journal: Nutrients
    Year: 2024

 Common mental disorders and risk of female infertility: a two-sample Mendelian randomization study

  • Authors: Di Mao, Mingmei Lin, Rong Li
    Journal: Frontiers in Endocrinology
    Year: 2024

 Impact of mildly evaluated thyroid-stimulating hormone levels on in vitro fertilization or intracytoplasmic sperm injection outcomes in women with the first fresh embryo transfer: a large study from China

  • Authors: Mingmei Lin, Di Mao, Kai-Lun Hu, Ping Zhou, Fen-Ting Liu, Jingwen Yin, Hua Zhang, Rong Li
    Journal: Journal of Assisted Reproduction and Genetics
    Year: 2024

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

Mr. Benjamin Borketey | Machine Learning for fraud detection | Global Data Innovation Recognition Award

Mr. Benjamin Borketey, Machine Learning for fraud detection, Global Data Innovation Recognition Award

Mr. Benjamin Borketey at First Citizens Bank, United States

Professional Profile

Orcid Profile

Summary of Skills

Over 5 years of experience in Data Analytics, Economic Forecasting, Time Series Modelling, Statistical Modelling, Machine Learning, and Data Management.

Professional Experience

Risk Analyst III, First Citizens Bank, NC
October 2023 to Date

  • Independently validate financial crime models (AML, fraud), probability of default (PD), loss given default (LGD), and exposure at default (EAD) for commercial and industrial portfolios.
  • Provide effective challenges, mitigate model risks, and produce comprehensive validation reports.

Quant Model Analyst, U.S Bank, NC
August 2021-September 2023

  • Perform complex mathematical analysis using statistical methods and machine learning techniques.
  • Build and validate fraud detection models and interpret statistical findings for senior management.

Quant Model Analyst, Flagstar Bank, MI
January 2018-August 2021

  • Validate bank-wide models and prepare reports for senior management and regulators.
  • Analyze large datasets to provide strategic insights.

Education

Purdue University
Post Graduate Program in AI and Machine Learning, August 2022

The University of Akron, Ohio
Master of Arts in Economics, December 2017

University of Cape Coast
Bachelor of Arts in Economics and Mathematics, May 2014

Professional Association

  • Association of Data Scientists
  • International Society for Data Science and Analytics (ISDSA)
  • Data Visualization Society
  • Institute of Electrical and Electronics Engineers (Computer Science Society)

Certification Awards

  • Economic Data Analytics Certificate, SAS Institute

Conference Presentation

  • Presented at Global Insight Conference on Artificial Intelligence, 2024
  • International Society for Data Science and Analytics, 2024

Certifications

  • Statistics Essential for Data Science (Simplilearn)
  • Introduction to Artificial Intelligence
  • Python for Data Science (Simplilearn)
  • Data Science with Python (Simplilearn)
  • Machine Learning (Simplilearn)
  • Deep Learning with TensorFlow and Keras (Simplilearn)
  • Advance Deep Learning and Computer Vision (Simplilearn)
  • SAS Certificate in Economics (SAS Institute)
  • Certified Peer Reviewer (Elsevier)

📖 Publication Top Noted

  • How hourly wage and the probability of committing a crime ( May 2024).

  • Real-Time Fraud Detection Using Machine Learning. ( May 2024).