Jingteng Liu | Business Analytics | Best Researcher Award

Mr. Jingteng Liu | Business Analytics | Best Researcher Award

ESADE Business School, Spain

Author Profile

Google Scholar

🎓 Early Academic Pursuits

Mr. Jingteng Liu’s academic journey began at Northwestern Polytechnical University, where he studied Software Engineering. After completing two years, he transferred to Arizona State University (ASU), where he pursued a Bachelor of Science in Computational Mathematical Sciences from 2017 to 2022. Alongside this, he obtained a Certification in Applied Business Data Analytics (2018-2022). During this period, Mr. Liu laid the foundation for his academic success by immersing himself in subjects that bridged computer science, mathematics, and business analytics.

💼 Professional Endeavors

Mr. Liu’s career has been marked by various leadership roles, with a strong focus on data analysis, machine learning, and business strategy. As Co-Founder of Hans & Associates LLC since May 2017, he formulated and executed comprehensive business strategies that helped transition the start-up into a stable organization. This experience helped him hone his strategic thinking, resource optimization, and market analysis skills. His involvement with Amazon Web Services (AWS) as a Professional Service Intern in 2020 allowed him to work on advanced machine learning models, particularly enhancing predictive analysis and using optimization algorithms. His professional journey has provided him with a wealth of experience, particularly in data-driven decision-making and strategic innovation.

📚 Contributions and Research Focus

Throughout his academic and professional career, Mr. Liu has contributed significantly to data-driven research. Notably, his research as a Barrett College Fellow at ASU in 2019-2022 focused on understanding consumer behavior and the preferences of hydrogen vehicle owners in California. He applied multinomial logistic regression and null hypothesis significance testing to evaluate the factors influencing gas station choices. Mr. Liu also contributed as a Research Assistant at ASU, co-authoring a published paper on mathematical modeling for cancer treatment responses. His research focus has consistently centered on the intersection of data analytics, machine learning, and their applications in real-world challenges.

🌍 Impact and Influence

Mr. Liu’s diverse experiences in data analytics, machine learning, and business strategy have had a significant impact on both academic and professional fields. His work with Amazon on developing predictive models and enhancing customer trend analysis reflects a deep understanding of how technology can transform business outcomes. Additionally, his entrepreneurial work in founding Hans & Associates and MiStraws demonstrates his ability to leverage data-driven insights for sustainable business growth. His contributions have influenced the development of strategic innovation, particularly in the use of AI to drive market forecasting and customer behavior analysis.

📑 Academic Citations

One of Mr. Liu’s key academic achievements was his co-authorship of a published paper titled “Clinical Data Validated Mathematical Model for Intermittent Abiraterone Response in Castration-Resistant Prostate Cancer Patients”. The research, published by SIAM Undergraduate Research Online, highlights his ability to apply complex mathematical models in the context of healthcare and medicine, contributing to the field of computational oncology. This paper demonstrates his expertise in applied mathematics and its real-world applications in clinical data analysis.

💻 Technical Skills

Mr. Liu possesses an extensive range of technical skills that span across programming languages, data analysis tools, and machine learning frameworks. Some of his core skills include proficiency in Python, SQL, and R, as well as expertise in machine learning algorithms and models such as BERT, Amazon Comprehend, and optimization techniques. He is also well-versed in Excel, Tableau, and Power BI, enabling him to deliver actionable insights from large datasets. These technical skills have been pivotal in his roles, particularly in optimizing business processes and enhancing predictive capabilities.

👨‍🏫 Teaching Experience

While Mr. Liu has not held formal teaching positions, his experiences as a research assistant and fellow at ASU have allowed him to contribute significantly to the academic community. His work on data analysis and research methodologies would have provided valuable mentorship to students and colleagues alike. His ability to communicate complex topics like statistical modeling and machine learning reflects his potential to make a meaningful impact in academia as a future educator.

🌟 Legacy and Future Contributions

Looking forward, Mr. Liu’s trajectory indicates his potential to become a key thought leader in the areas of AI-driven business analytics and strategic innovation. His multidisciplinary expertise in data science, machine learning, and business strategy positions him well to drive cutting-edge innovation in industries ranging from technology to healthcare. He envisions contributing to the advancement of AI and analytics solutions, developing models that offer enhanced business intelligence, operational efficiency, and predictive capabilities. His future contributions are poised to leave a lasting legacy, particularly in fostering sustainable business growth through data-driven decision-making and AI optimization.

Top Noted Publications 📖

  • Hydrogen Fuel Cell Vehicle Adopters Geographically Evaluate a Network of Refueling Stations in California
    • Authors: S Kelley, A Krafft, M Kuby, O Lopez, R Stotts, J Liu
    • Journal: Journal of Transport Geography
    • Year: 2020
  • Clinical Data Validated Mathematical Model for Intermittent Abiraterone Response in Castration-Resistant Prostate Cancer Patients
    • Authors: J Bennett, X Hu, K Gund, J Liu, A Porter
    • Journal: SIAM Undergraduate Research Online
    • Year: 2021
  • Extreme Heat Effects on Electric Vehicle Energy Utilization and Driving Range
    • Authors: NC Parker, M Kuby, J Liu, EB Stechel
    • Journal: Available at SSRN
    • Year: 2024

Fernando López | Healthcare Data Analysis | Excellence in Research

Assoc Prof Dr. Fernando López | Healthcare Data Analysis | Excellence in Research

Assoc Prof Dr. Fernando López at Hospital Clinico Universitario – Universidad de Valencia, Spain

👨‍🎓  Profile

Early Academic Pursuits 🎓

Dr. Fernando López began his academic journey at the Universidad de Cádiz, where he earned his Licenciatura in Medicine and Surgery from 1987 to 1993. His dedication led him to further his education through the Official Doctoral Program in Medicine and Surgery at the Universitat de València, culminating in a doctoral degree awarded with “Sobresaliente cum laude” in 2001.

Professional Endeavors 🏥

Dr. López completed his specialized training in General Surgery and Digestive System Surgery via the MIR program at the Hospital Clínico Universitario de Valencia from 1995 to 2000. He currently serves as an Associate Professor in the Department of Surgery at the Universitat de València, where he has been actively involved since 2011.

Contributions and Research Focus 🔍

Dr. López has made significant contributions to surgical research, particularly in the context of the COVID-19 pandemic. He is a co-author of several influential articles addressing surgical risks and outcomes during this crisis, with particular emphasis on the integration of machine learning for risk prediction. His work has been published in leading journals, reflecting his commitment to advancing surgical practices.

Impact and Influence 🌍

His research has garnered considerable attention, with publications in both national and international journals totaling 35, including articles in high-impact publications such as the British Journal of Surgery. His collaborative work with the COVIDSurg Collaborative has had a meaningful impact on surgical protocols during the pandemic.

Academic Cites 📚

Dr. López’s research has resulted in a notable cumulative impact factor of 76.697 across his indexed publications, illustrating the significant reach and influence of his work in the academic community.

Technical Skills ⚙️

As an experienced surgeon, Dr. López possesses a robust set of technical skills, particularly in advanced trauma and emergency care. He has been involved in teaching various advanced trauma life support courses and has contributed to international workshops, underscoring his proficiency and commitment to surgical education.

Teaching Experience 👨‍🏫

In addition to his clinical practice, Dr. López has extensive teaching experience, having tutored 35 residents in General Surgery and Digestive Surgery. He has organized and led numerous courses and seminars, including advanced trauma support training, reflecting his passion for educating the next generation of surgeons.

Legacy and Future Contributions 🌱

Looking ahead, Dr. López aims to continue his research in surgical safety and education, leveraging his experience and expertise to foster advancements in the field. His ongoing commitment to mentoring residents and collaborating on impactful research will undoubtedly leave a lasting legacy in the surgical community.

📖 Top Noted Publications

 

Characteristics of gastrointestinal stromal tumors associated to other tumors, 2024

Characteristics of gastrointestinal stromal tumors associated to other tumors, 2024

Glasbey, J. C., Nepogodiev, D., COVIDSurg Collaborative. (2021). Death following pulmonary complications of surgery before and during the SARS-CoV-2 pandemic. British Journal of Surgery, 6, pp. 1-19.

LUCENTUM Project Researchers. (2021). Simplified risk-prediction for benchmarking and quality improvement in emergency general surgery: Prospective, multicenter, observational cohort study. International Journal of Surgery, 97, pp. 1-35.

Glasbey, J. C., Nepogodiev, D., COVIDSurg Collaborative. (2021). Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score. British Journal of Surgery, 6, pp. 1-19.