Supria Basak | Business Intelligence | Analytics Excellence Award

Posted on by sciencefather

Ms. Supria Basak | Business Intelligence | Analytics Excellence Award

Data Analyst at Worcester Polytechnic Institute, United States

Supria Basak is currently pursuing a Master’s in Information Technology with a concentration in Data Analytics at Worcester Polytechnic Institute (WPI), Massachusetts, with an exceptional academic record. Holding a Bachelor’s in Computer Science and Engineering from NIT Trichy, India, she has showcased her expertise in data analytics, machine learning, and user behavior analysis. Her professional experiences span roles as a Data Analyst, Research Assistant, and Teaching Assistant at WPI, as well as an actuarial data intern at Quincy Mutual Group. Her research interests include Data Visualization, Business Analytics, Machine Learning, FinTech, and Healthcare Analytics. Supria is a certified specialist in Human Subjects Research, Adversarial Machine Learning, and Data Science.

Profile

Google Scholar

Education

Supria Basak’s educational journey began with a Bachelor’s degree in Computer Science & Engineering from NIT Trichy, where she also pursued a minor in Economics. Her academic coursework was focused on subjects such as Artificial Intelligence, Data Mining, and Cryptography, which laid the foundation for her analytical prowess. Currently, at WPI, she is on track to complete her MS in Information Technology by May 2025, concentrating on Data Analytics and Information Systems Design. Her coursework includes Business Intelligence, Machine Learning, and Database Design, and she has maintained a flawless GPA of 4.0, demonstrating her dedication and intellectual capability in the field.

Experience

Supria has amassed substantial experience across multiple sectors, especially in data analysis and research. At WPI, she serves as a Data Analyst, where she enhances data accuracy and drives strategic initiatives that inform business decisions. Her role includes analyzing institutional financial data and conducting research on alumni employment trends. She also played a key role in advising on the implementation of open educational resources, aiming to reduce financial burdens on students. Her previous experience as an Actuarial Data Analyst Intern at Quincy Mutual Group involved building predictive models for insurance premiums and developing automated reporting tools. As a Graduate Research Assistant and Teaching Assistant at WPI, she focused on health data analysis, contributing to the improvement of health outcomes via user behavior insights.

Research Interests

Supria’s research interests encompass a broad range of topics, including Data Visualization, Machine Learning, Healthcare Analytics, and User Behavior Analysis. She is particularly interested in studying how machine learning and data analytics can be utilized to improve decision-making processes in sectors like education, healthcare, and business. Supria has explored topics such as habit formation through app usage data, the influence of exercise routines on health outcomes, and the potential for machine learning to detect psychological disorders like Body Dysmorphic Disorder (BDD). Her work on sentiment analysis and social network studies exemplifies her ability to use data to gain deeper insights into human behavior and societal trends.

Awards

Supria has been recognized for her academic excellence and contributions to the field of data science. Notably, she was awarded the prestigious ICCR Scholarship for fully-funded undergraduate study, placing her in the top 0.5% of candidates from both India and Bangladesh. She also demonstrated leadership as the Marketing Head for Sports Club at NIT Trichy and as the Vice President of the Mental Health & Lifestyle Club. These roles illustrate her ability to balance academics with extracurricular commitments. Supria’s involvement in various hackathons and competitions, such as her placement in the TransfiNitte Hackathon and Smart India Hackathon, further emphasizes her exceptional problem-solving and innovative skills.

Publications

Alam, Mohammad Morshad, Basak, Nandita, Basak, Supria, et al. “Body Dysmorphic Disorder (BDD) Symptomatology Among Undergraduate University Students of Bangladesh.” Journal of Affective Disorders, Elsevier, Oct 2022. Impact Factor: 6.53.

Supria Basak’s forthcoming research paper will focus on detecting BDD using Machine Learning, specifically analyzing the role of cyberbullying through Natural Language Processing.

Conclusion

Supria Basak is an emerging leader in the field of Data Analytics, with a keen interest in leveraging machine learning and analytics to solve real-world problems. Her solid academic foundation, hands-on experience in various data-related roles, and her contributions to important research topics make her a promising candidate for future opportunities in data science, analytics, and beyond. Her combination of technical expertise, leadership skills, and an eagerness to continue advancing in her field ensures she will continue to make significant impacts in her chosen areas of research and industry.

jizhou Cao | Data-Driven Decision Making | Best Scholar Award

Posted on by sciencefather

Mr. jizhou Cao | Data-Driven Decision Making | Best Scholar Award

Student | Xinjiang University | China

Mr. Jizhou Cao is a dedicated academic and researcher currently serving at Xinjiang University. With a background in civil engineering and machine learning, he has significantly contributed to the understanding of reinforced concrete (RC) column shear behaviour, integrating advanced machine learning techniques into structural engineering. His work has explored the initial failure process in RC columns and prediction methods for shear capacity, demonstrating a unique synergy between civil engineering and machine learning. Mr. Cao’s research has been published in well-respected journals, furthering the application of machine learning to solve real-world engineering problems.

Profile

Scopus

Education

Mr. Cao earned his master’s degree from Hainan University, where he gained a solid foundation in civil engineering. He continued his academic journey by pursuing further studies at Xinjiang University, which has fostered his research interests in the intersection of civil engineering and machine learning. His educational path reflects a blend of practical expertise and theoretical understanding, particularly in the realm of structural analysis and innovative technologies such as machine learning.

Experience

With years of academic and research experience, Mr. Cao has engaged in multiple projects that apply cutting-edge technologies to civil engineering problems. His work has focused on developing predictive models for the shear capacity of RC columns and understanding the failure processes in concrete structures using machine learning techniques. He has also been involved in consultancy projects, contributing his expertise to real-world applications. His professional journey highlights his commitment to advancing both the scientific understanding and practical application of structural engineering.

Research Interest

Mr. Cao’s primary research interests lie in the integration of machine learning with civil engineering, particularly in structural analysis and the failure mechanisms of reinforced concrete structures. His research aims to bridge the gap between computational techniques and practical engineering solutions, with a special focus on the prediction of shear failure in RC columns. His work seeks to improve the accuracy of structural safety evaluations and enhance the resilience of concrete structures under various loading conditions.

Award

Mr. Cao has been recognized for his contributions to the field of civil engineering and machine learning. His research has garnered attention from leading academic institutions, with multiple nominations for prestigious awards such as the Young Scientist Award and the Excellence in Innovation Award. These accolades reflect his impactful contributions to advancing engineering practices, particularly in the realm of structural safety and the application of machine learning.

Publications

Mr. Cao has authored several influential articles, contributing to the academic discourse on machine learning applications in civil engineering. Some of his key publications include:

“Exploring the initial state of the shear failure process in RC columns based on machine learning,” Journal of Structural Engineering, 2024.

“Prediction of shear capacity of RC columns and discussion on shear contribution via the explainable machine learning,” Structural Safety Journal, 2023. These works have been cited by numerous researchers, highlighting the significance of his research in the field.

His publications have addressed critical aspects of structural engineering and have demonstrated the potential of machine learning to revolutionize the field.

Conclusion

Mr. Jizhou Cao’s work stands as a testament to the potential of machine learning in reshaping civil engineering practices. His academic background, coupled with a strong research focus on shear failure prediction in RC columns, underscores his commitment to advancing both theoretical and applied knowledge in structural engineering. As he continues to explore innovative solutions through machine learning, Mr. Cao is poised to make lasting contributions to the safety and efficiency of civil infrastructure, enhancing the way engineers approach complex structural challenges. His dedication to research and innovation makes him a valuable asset to both academia and the engineering community.