Raghavendran Prabakaran | Machine Learning | Innovative Research Award

Innovative Research Award

Raghavendran Prabakaran
Easwari Engineering College, India

Raghavendran Prabakaran
Affiliation Easwari Engineering College
Country India
Scopus ID 58670546100
Documents 53
Citations 310
h-index 11
Subject Area Machine Learning
Event Research Data Analysis Awards
ORCID 0009-0001-7333-6555

Raghavendran Prabakaran recognizes scholarly excellence demonstrated through sustained research productivity, scientific impact, and contributions to the advancement of machine learning. Raghavendran Prabakaran has established an active research profile through peer-reviewed publications, interdisciplinary collaboration, and measurable citation performance. His academic achievements reflect continued engagement in applied artificial intelligence and data-driven research methodologies.[1]

Abstract

Raghavendran Prabakaran has contributed to machine learning research through scholarly publications, citation impact, and interdisciplinary collaboration. His work reflects a consistent focus on computational intelligence, predictive analytics, and intelligent systems while supporting practical applications across engineering disciplines.[2]

Keywords

Machine Learning, Artificial Intelligence, Predictive Analytics, Data Science, Intelligent Systems, Pattern Recognition, Research Analytics.

Introduction

Machine learning continues to influence modern engineering, healthcare, automation, and business analytics by enabling intelligent decision-making from complex datasets. Researchers with sustained publication records contribute to both theoretical understanding and practical innovation while strengthening scientific collaboration.[3]

Research Profile

The research profile demonstrates 53 indexed publications, 310 citations, and an h-index of 11 according to Scopus metrics. These indicators reflect sustained scholarly activity and growing academic visibility within the machine learning research community.[1]

Research Contributions

Research emphasizes predictive modelling and intelligent algorithm development for solving practical engineering problems while improving computational efficiency through data-driven learning approaches. Contributions explore AI-based decision support systems integrating analytical models with automation techniques to enhance reliability, scalability, and real-world implementation.

Publications

The publication portfolio consists of peer-reviewed journal articles and conference papers indexed in international scholarly databases. The body of work demonstrates continuing engagement with emerging topics in artificial intelligence and machine learning.[4]

Research Impact

Citation performance, publication consistency, and interdisciplinary collaborations indicate measurable academic influence. The research outputs contribute to knowledge dissemination while supporting future developments in intelligent computing technologies.

Award Suitability

Based on publication metrics, citation record, research quality, and ongoing scholarly engagement, the profile aligns with evaluation criteria commonly applied for academic innovation and research excellence awards. The combination of productivity and scientific impact supports recognition within international research communities.[6]

Conclusion

Raghavendran Prabakaran demonstrates sustained academic productivity through quality publications, measurable citation impact, and contributions to machine learning research. The overall scholarly profile reflects continued commitment to research excellence, innovation, and knowledge advancement within engineering and computational sciences.

References

  1. Elsevier. (n.d.). Scopus author details: Raghavendran Prabakaran, Author ID 58670546100.
    https://www.scopus.com/authid/detail.uri?authorId=58670546100
  2. ORCID. (n.d.). ORCID record for Raghavendran Prabakaran.
    https://orcid.org/0009-0001-7333-6555
  3. Parthiban, Y., Prabakaran, R., Thakur, D., & Madhumitha, S. (2026). Application of Upadhyaya transforms with machine learning for predictive and analytical solutions in complex systems. Transactions on Computational Modeling and Intelligent Systems.
    https://tcmis.org/index.php/files/article/view/23
  4. Tripathi, S., Gochhait, S., & Prabakaran, R. (2026). Neuromarketing applications and ethical implications in consumer behavior analysis. In Book chapter.
    https://www.igi-global.com/gateway/chapter/404055
  5. Prabakaran, R., Parthiban, Y., Thiravidarani, J., & Madhumitha, S. (2026). Application of fractional integro-differential equations in paracetamol drug release modeling. Oriental Journal of Chemistry.
    http://dx.doi.org/10.13005/ojc/420208

Charlene Mariscal | Ethics in Machine Learning | Best Researcher Award

Ms. Charlene Mariscal | Ethics in Machine Learning | Best Researcher Award

Ms. Charlene Mariscal at Bina Nusantara University, Indonesia

πŸ”—Β Profile

Scopus Profile

πŸ‘¨β€βš•οΈ Academic Background

A motivated and proactive fresh graduate with a keen enthusiasm for data and machine learning. I am a highly skilled Business Intelligence Functional Analyst specializing in data management, data integration, and dashboard development. With a proven track record of optimizing data flow from diverse sources and delivering actionable insights, I excel in driving informed decision-making within a multinational environment. I am adept at managing and training IT teams for operational excellence and passionate about leveraging data to create innovative solutions and drive business growth.

πŸ’ΌΒ Work Experience

Business Intelligence Functional Analyst & Data Scientist
PT. Japfa Comfeed Indonesia, Jakarta
πŸ—“ Jan 2023 – Apr 2024
As part of a leading multinational agribusiness company, I collaborated with 11 business user divisions to translate requirements into effective technical solutions within 3 months. I maintained over 5 dashboards to enhance data flow and performance, ensuring real-time access to data. My role involved documenting 9 data integration processes and models, troubleshooting data integration issues, and implementing data quality assurance processes across 100+ tables. I deployed 4 machine learning sales forecast models in AWS Forecast and achieved 97% accuracy in predicting birds’ body weight using XGBoost Models. Additionally, I conducted research on LLM performance, comparing ChatGPT, Amazon Bedrock, and Google Gemini.

AI Researcher Intern – BRI Brain Academy
PT. Bank Rakyat Indonesia, Jakarta
πŸ—“ Feb 2022 – Jul 2022
At one of Indonesia’s largest state-owned banks, I conducted research on bias and fairness in machine learning, improving fairness metrics by 70% while maintaining 90% performance in credit scoring models. I reduced data duplication by 30% using Excel’s conditional formatting and provided 7 fair credit scoring models with ML classifiers including Random Forest, XGBoost, and LightGBM. My role included presenting progress and results weekly to key stakeholders including the Head of AI Division and Senior Vice President of Digital Banking.

Skills & Tools

πŸ’» Programming Languages: SQL, Python, C++
🌐 LLMs: ChatGPT, Google Gemini, Amazon Bedrock
πŸ“Š Data & Business Intelligence: SAP ERP, Snowflake, QlikSense, QlikView, PowerBI
πŸ” Data Science: Google Cloud Platform (GCP), AWS Forecast, AWS SageMaker
πŸ“‘ Others: MS Office Suite (Word, Excel, PowerPoint) | Linguist, Attentive Learner, Initiative, Problem-solving, Teamwork

πŸŽ“ Education

Bina Nusantara University, Indonesia
πŸ“š Bachelor of Computer Science, 3.79/4.00
πŸ—“ Sept 2018 – Dec 2022

Lancaster University, United Kingdom
🌏 Study Abroad Program
πŸ—“ Oct 2021 – Dec 2021
Related Courses: Introduction to Business Intelligence & Analytics, Project Management Tools & Techniques

πŸ… Achievement

Indonesian International Student Mobility Awards (IISMA) Awardee 2021
Recognized for outstanding academic achievement and participation in the IISMA Program. Selected among 2,500+ applicants from 98 universities for a fully-funded study abroad program by the Government of the Republic of Indonesia.

πŸ“œ Certifications

πŸ“œ Google Advanced Data Analytics Professional Certificate, Jul 2024 – Present
πŸ“œ Google Data Analytics – Coursera, Dec 2022

🌍Volunteer Experience

International Community Development Program – BINUS University
Aug 2022
Collaborated with 38 students from international universities to solve real-world challenges in a tourism village in Malang, East Java, Indonesia. Conducted interviews with 20+ locals, analyzed community problems, and implemented the Design Thinking process to propose practical solutions. Promoted the problem-solving idea to over 200 visitors at the project exhibition to raise public awareness of the tourism village.

πŸ“– Publication

Implementing and analyzing fairness in banking credit scoring
  • Authors: Mariscal, C., Yustiawan, Y., Rochim, F.C., Tanuar, E.
  • Journal: Procedia Computer Science
  • Year: 2024