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

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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).

 

Marcelo Ang – Machine Learning and AI Applications – Best Researcher Award 

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Prof Dr. Marcelo Ang - Machine Learning and AI Applications - Best Researcher Award 

National University of Singapore - Singapore

Author Profile

Early Academic Pursuits

Prof Dr. Marcelo H. Ang Jr.'s academic journey is marked by impressive scholarly achievements beginning with his education in the Philippines at De La Salle University, where he earned dual Cum Laude honors in Mechanical Engineering and Industrial Management Engineering in 1981. His pursuit of higher education led him to the University of Hawaii at Manoa, where he obtained an M.S. in Mechanical Engineering with a focus on the application of robotics in agriculture, specifically sugarcane propagation. He furthered his studies at the University of Rochester, earning both an M.S. and a Ph.D. in Electrical Engineering, with research focused on robotic manipulators—a foundational area that would define much of his future work.

Professional Endeavors and Contributions

Prof Dr. Marcelo H. Ang Jr. has had a distinguished career at the National University of Singapore (NUS), where he has held multiple leadership roles, including Director of the Advanced Robotics Center and Professor in the Department of Mechanical Engineering. His career began as an assistant professor at the University of Rochester before returning to Asia to shape Singapore's engineering and robotics landscape. Over the years, Ang has been instrumental in developing several academic programs at NUS, enhancing the university’s educational offerings significantly in the areas of robotics, mechatronics, and technology management.

Research Focus

Prof Dr. Ang's research interests are broad yet focused on critical areas of robotics and intelligent systems that include mobile robotic manipulation in unstructured environments, compliant motion and force control, self-driving vehicles, and distributed autonomous robotics systems. His work often employs advanced computational methods like deep learning, genetic algorithms, and fuzzy reasoning. These research endeavors aim not only to advance the theoretical aspects of robotics but also to find practical applications that enhance industrial productivity and everyday life.

Accolades and Recognition

Throughout his career, Ang has received numerous accolades that recognize his contributions to both academia and industry. These include the prestigious Capek Award for his contributions to the development and practical application of robotics and the Andrew P. Sage Best Transactions Paper Award from the IEEE Transactions on Systems, Man, and Cybernetics. His achievements are a testament to his leadership in the field and his commitment to advancing robotics technology and education globally.

Impact and Influence

Prof Dr. Ang's influence extends beyond academia into professional and societal contributions in the field of robotics. He has served as President of the International Steering Committee of the World Robot Olympiad, demonstrating his commitment to promoting robotics education worldwide. His work has not only shaped research and development strategies at NUS but has also influenced national and international robotics policies and initiatives.

Legacy and Future Contributions

Looking forward, Ang continues to shape the future of robotics with his involvement in developing new academic programs like the BEng in Intelligent Machines and an MSc in Robotics. His ongoing research and educational initiatives are likely to inspire the next generation of engineers and roboticists. Ang's legacy is that of a pioneer in robotics education and research, having laid down a robust framework for future exploration and innovation in the field. His continued efforts in advancing robotics technology promise further contributions that aim to solve real-world problems through innovative solutions.

Marcelo H. Ang Jr.’s career embodies a lifelong dedication to education, innovation, and the practical application of robotics technology in society. His contributions have not only been recognized through various awards but have also had a tangible impact on the engineering and robotics communities globally. As he continues to drive forward in his field, his work is set to inspire and shape future developments in robotics and automation.

Citations

A total of 131 citations for his publications, demonstrating the impact and recognition of her research within the academic community.

  • Citations    11471
  • h-index        51
  • i10-index     82

Notable Publication

 

Zheyi Chen | Machine Learning Applications | Best Researcher Award

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Zheyi Chen | Best Researcher Award - Biography

Prof Dr Zheyi Chen : Machine Learning Applications

Professional profile:

Early Academic Pursuits:

Prof Dr. Zheyi Chen embarked on his academic journey with a Bachelor's degree in Computer Science and Technology from Shanxi University, China, where he laid the foundation for his future endeavors. He continued his education with a Master's degree in Computer Science and Technology from Tsinghua University, China, under the guidance of Prof. Yongwei Wu.

For his doctoral studies, Prof. Chen pursued a Ph.D. in Computer Science at the University of Exeter, U.K., from September 2017 to October 2021. During this period, he worked under the supervision of Prof. Geyong Min and Dr. Jia Hu, contributing to the field of computer science and further honing his research skills.

Professional Endeavors:

Following his academic pursuits, Prof Dr. Zheyi Chen transitioned into the role of an Associate Professor and Ph.D. Supervisor at the College of Computer and Data Science, Fuzhou University, China, from December 2021 to January 2023. Subsequently, he assumed the position of a Professor and Ph.D. Supervisor in the same department from February 2023 onwards, signifying a progression in his academic career.

Contributions and Research Focus:

Prof Dr. Chen's research interests encompass Cloud/Edge Computing, Resource Optimization, Deep Learning, and Deep Reinforcement Learning. His notable contributions include leading research projects such as "Research on Efficient and Adaptive Resource Optimization in Cloud-Edge Environments" and "Research and Application of Key Technologies for Resource Optimization and Data Processing in Cloud-Edge Collaborative Environment."

He has significantly advanced the understanding of resource allocation in mobile edge computing and the development of key technologies for big data intelligence. His expertise extends to the exploration and practice of training postgraduate students aligned with the "Digital Fujian" strategy.

Accolades and Recognition:

Prof Dr. Zheyi Chen's contributions to the field have been acknowledged through prestigious awards, including the "World’s Top 2% Scientists" in 2023, the "First Prize of Fujian Science and Technology Progress" in 2021, and multiple "First Prizes for Outstanding Papers" at the Annual Academic Conference of Fujian Computer Society in 2021 and 2023.

Impact and Influence:

As an active member of IEEE, ACM, and CCF, Prof. Chen has played a pivotal role in the academic community. His involvement in conference organization, as seen in his roles as Web and System Management Chair for IEEE SustainCom-2020 and IEEE SmartCity-2018, highlights his commitment to fostering scholarly exchange.

He has also served as a reviewer for reputable journals and conferences, including IEEE Transactions on Parallel and Distributed Systems, IEEE Transactions on Cloud Computing, and IEEE/CAA Journal of Automatica Sinica, contributing to the rigorous evaluation and dissemination of research in his field.

Legacy and Future Contributions:

Prof Dr. Zheyi Chen's legacy is marked by his leadership in influential research projects, academic recognition, and service to the community. His commitment to advancing knowledge in Cloud/Edge Computing and related fields positions him as a key figure in shaping the future of computer science. As he continues to lead research projects, mentor students, and contribute to scholarly activities, Prof. Chen is poised to leave a lasting impact on the field and inspire future generations of researchers.

Notable Publications:

Citations:

A total of  921 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations      921
  • h-index         13
  • i10-index      15

Andrzej Ślebarski | Excellence in Research | Data Analysis Innovation

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Andrzej Ślebarski | Excellence in Research - Award Winner 2023

Prof Dr Andrzej Ślebarski : Data Analysis Innovation

Congratulations to Prof. Dr. Andrzej Ślebarski, a true trailblazer in the realm of Data Analysis Innovation! Your unwavering commitment to excellence in research has earned you the prestigious International Research Data Analysis Excellence Award. Your groundbreaking contributions and innovative approaches in data analysis have not only set a new standard but have also significantly advanced our understanding of complex datasets. Your dedication and achievements inspire us all. Here's to celebrating your well-deserved success and the impact you continue to make in the field. Cheers to a visionary leader and award winner!

Professional Profiles:

Early Academic Pursuits:

Andrzej Ślebarski began his academic journey at the University of Silesia in Katowice, where he obtained his Master's degree in Physics in 1973. Subsequently, he pursued his doctoral studies at the same university, earning his Ph.D. in 1978. His early research focused on structural and magnetic investigations of ternary Laves phases, particularly in the GdMn2-GdAl2 system.

Professional Endeavors:

Dr. Ślebarski's academic career has been extensive and impactful. He joined the Institute of Physics at the University of Silesia in 1973, starting as an Assistant and gradually progressing through various roles, including Adiunkt, Assistant Professor, Associate Professor, and finally reaching the position of Full Professor in 2003. His responsibilities included both teaching physics to students and conducting scientific research in experimental solid-state physics.

In 2021, he transitioned to become a Full Professor at the Institute of Low Temperatures and Structure Research, Polish Academy of Sciences, Wrocław, following his retirement from the University of Silesia in Katowice.

Contributions and Research Focus:

Dr. Ślebarski's research has primarily centered around solid-state physics, with a specific focus on the electronic structure of intermetallic compounds of rare earths. His experimental techniques involved X-ray spectroscopy, including XPS (X-ray photoelectron spectroscopy), XES (X-ray emission spectroscopy), BIS (Bremstrahlung isochromat spectroscopy), XANES, and others. His investigations delved into specific heat, electric and heat transport, and magnetic properties of metals and alloys containing rare earths, exploring phenomena such as fluctuant valency, Kondo effect, heavy fermion properties, and quantum phase transitions.

His interest extended to strongly correlated electron phenomena in d- and f-electron materials, encompassing superconductivity, magnetism, heavy fermion behavior, and non-Fermi liquid behavior. Notably, he focused on unconventional superconductivity arising from atomic disorder.

Accolades and Recognition:

Throughout his career, Dr. Andrzej Ślebarski has received prestigious awards, including the award of the Polish Academy of Sciences in 1990 and 1982, as well as the award of the Minister of Science and Education in 1983, 1979, and 2021. His contributions have been recognized both nationally and internationally.

Impact and Influence:

Dr. Ślebarski's international collaborations and numerous visits abroad have further enriched his research and contributed to the global scientific community. Noteworthy are his collaborations with institutions such as the University of Cologne, University of Osnabrueck, and University of California, San Diego, where he engaged in fruitful scientific exchanges and research programs.

Legacy and Future Contributions:

As a Vice President of the Committee of Physics of the Polish Academy of Sciences and a member of various scientific councils, Dr. Ślebarski continues to play a significant role in shaping the direction of physics research in Poland. His extensive experience, both in administration and academia, positions him as a valuable figure in the scientific community. The legacy of his research, mentorship, and leadership will likely continue to influence the field of solid-state physics for years to come.

Notable Publications:

Citations:

A total of  665  citations for his publications, demonstrating the impact and recognition of his research within the academic community.

Citations                665

h-index  19            16

i10-index                25

 

Zhi Liu | Best Researcher Award | Machine Learning Applications

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 Zhi Liu | Best Researcher Award  Winner 2023  🏆

Dr Zhi Liu : Machine Learning Applications

🏆 Congratulations to Dr. Zhi Liu!

 International Research Data Analysis Excellence Awards Best Researcher Award Winner Recognizing Dr. Liu's outstanding contributions in Machine Learning Applications. Your dedication to research excellence has set a benchmark for the global scientific community. Well-deserved honor!

Professional profile:

Early Academic Pursuits

Liu Z started his academic journey with a focus on computer software and theory at Northeast Normal University, where he pursued a master's degree in Computer Software and Theory from September 2014 to January 2017. During this period, his research interests included recommendation systems, artificial intelligence, machine learning, and natural language processing.

Professional Endeavors

Subsequently, he advanced his academic pursuits by obtaining a Ph.D. in Mechanical Manufacturing and Automation from the University of the Chinese Academy of Sciences (2017-2022). His doctoral research concentrated on artificial intelligence, machine teaching, knowledge graphs, natural language processing (NLP), natural language understanding (NLU), machine reading comprehension (MRC), and knowledge modeling.

Research Focus

The core of Liu Z's doctoral research was the development of machine teaching methods for human-machine collaboration. His dissertation focused on leveraging natural language processing (NLP) techniques in the medical domain to explore how AI models could be taught through interactive human-machine methods. The goal was to enhance learning efficiency by incorporating existing knowledge systems and incorporating correction mechanisms into the learning process.

Contributions and Research Output

Liu Z has made significant contributions to the field, as evidenced by his research outcomes and publications. Notably, he co-authored a paper titled "AttentiveHerb: A Novel Method for Traditional Medicine Prescription Generation" and secured a patent for a method analyzing symptom-drug relationships using new artificial intelligence technology.

His work extended to Chinese traditional medicine, with a paper on "TCMNER and PubMed: A Novel Chinese Character-Level-Based Model and a Dataset for TCM Named Entity Recognition." In addition, Liu Z contributed to the field of event extraction with a paper on structural dependency self-attention-based hierarchical event models.

Recognition and Impact

Liu Z's contributions have not gone unnoticed, as he received funding from the 71st batch of the China Postdoctoral Science Foundation. His work in the medical domain, specifically on the generation of traditional herbal medicine prescriptions, was acknowledged in a transfer learning model published in the journal "Artificial Intelligence in Medicine."

Future Contributions and Legacy

Transitioning to a postdoctoral role at Zhejiang Lab, Liu Z continued his research in natural language processing, understanding, and knowledge graphs. His accomplishments include the development of large models tailored to specific vertical domains, such as finance and traditional Chinese medicine. His work in numerical reasoning and a transfer learning-based dual-augmentation strategy for rare disease syndrome differentiation in traditional Chinese medicine showcases his commitment to advancing the field.

Liu Z's legacy extends beyond academic achievements, with patents, conference papers, and impactful research contributing to the broader landscape of artificial intelligence, natural language processing, and medical applications. His efforts are likely to leave a lasting mark on the integration of AI into medical practices and knowledge systems.

Notable publication :