Arti Singh | Machine learning | Best Researcher Award

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Mrs. Arti Singh | Machine learning | Best Researcher Award

Assistant Professor at DYPIEMR, India

Mrs. Arti Singh is an accomplished academician and researcher with a robust background in Computer Science, Artificial Intelligence, and Data Science. She is currently serving as an Assistant Professor at Dr. D Y Patil Institute of Engineering Management and Research. With a passion for teaching and research, her expertise lies in machine learning, sentiment analysis, data science, and computational intelligence. Mrs. Singh has presented and published several research papers at national and international conferences. She is committed to continuous learning, having completed various industry-relevant certifications and training programs.

Publication Profile

Google Scholar

Educational Details

  • M.Tech in Computer Technology and Applications from National Institute of Technical Teachers’ Training and Research (RGPV, Bhopal) – 2016 (CGPA: 8.69)
  • B.E. in Computer Science Engineering from Sagar Institute of Research Technology and Science (RGPV, Bhopal) – 2014 (CGPA: 8.35)

Professional Experience

  • Assistant Professor in the Department of Artificial Intelligence and Data Science at Dr. D Y Patil Institute of Engineering Management and Research since July 1, 2022.
  • Lecturer in the Computer Department at Marathwada Mitra Mandal Polytechnic College.
  • Assistant Professor at Sri Sai Shail Manglam College, Singrauli (June 1, 2019, to June 30, 2021).
  • Resource Person for the B.C.A Vocational course at Babasaheb Bhimrao Ambedkar Bihar University, Muzaffarpur (May 30, 2017, to May 27, 2019).

Research Interest

  • Data Science
  • Machine Learning
  • Software Engineering
  • Operating Systems
  • Quantum Artificial Intelligence
  • Pattern Recognition
  • Computational Intelligence

Top Noted Publication

An Opinion Mining for Indian Premier League Using Machine Learning Techniques

  • Authors: KP Dubey, S Agrawal
  • Conference: 2019 4th International Conference on Internet of Things: Smart Innovation, Usage, and Application
  • Pages: 25
  • Year: 2019
  • Summary: This paper presents a sentiment analysis model for social media data related to the Indian Premier League (IPL). The authors employed machine learning techniques to classify public opinions, enabling better understanding of audience engagement and predicting trends in sports sentiment.

Comparing Classification and Regression Tree and Support Vector Machine for Analyzing Sentiments for IPL

  • Author: Arti Singh
  • Journal: International Journal on Recent and Innovation Trends in Computing and Communication (IJRITCC)
  • Volume: 4
  • Issue: 6
  • Pages: 172-175
  • Year: 2016
  • ISSN: 2321-8169
  • Summary: This study compares the performance of two machine learning algorithms, Classification and Regression Tree (CART) and Support Vector Machine (SVM), for sentiment analysis on IPL data. The research evaluates the accuracy and effectiveness of both approaches for sports sentiment analysis.

AI Application in Production

  • Author: Arti Singh
  • Publisher: Taylor & Francis
  • Book Title: Industry 4.0: Enabling Technologies and Applications
  • Chapter: AI Application in Production
  • Year: 2024
  • URL: Link to book
  • Summary: This book chapter explores the integration of Artificial Intelligence (AI) in manufacturing and production processes. It highlights AI-driven innovations, predictive maintenance, process optimization, and intelligent automation in modern industrial setups.

Automated Invoice Data Extraction: Advancements and Challenges in OCR-Based Approaches

  • Authors: Arti Singh, Sneha Kanwade, Siddhant Shendge, Amoksh Layane, Kohsheen Tikoo
  • Journal: International Journal of Scientific Research in Engineering and Management (IJSREM)
  • Volume: 8
  • Pages: 1-6
  • ISSN: 2582-3930
  • Year: 2024
  • Summary: This paper addresses the growing need for automated invoice data extraction using Optical Character Recognition (OCR) technologies. It discusses the latest advancements, the challenges faced, and potential solutions to enhance accuracy in invoice processing systems.

An In-Depth Analysis of Sentiment Polarity Using Various Machine Learning Algorithms

  • Author: Arti Singh
  • Conference: 8th International Conference on ISDIA 2024
  • Volume: 1107
  • Pages: 157–167
  • Year: 2024
  • Summary: This research investigates the effectiveness of different machine learning algorithms for sentiment polarity detection. The study evaluates models such as SVM, Random Forest, and Extremely Randomized Trees to improve sentiment classification accuracy in social media data.

Comparative Study of Machine Learning Algorithms for Sentiment Polarity

  • Author: Arti Singh
  • Conference: IRF International Conference
  • Pages: 1-5
  • Year: 2017
  • Summary: The paper compares several machine learning techniques, including Naive Bayes, Decision Trees, and SVM, for sentiment polarity classification. It emphasizes the importance of selecting the appropriate algorithm for accurate sentiment detection in online text data.

Conclusion:

Mrs. Arti Singh is a strong candidate for the Best Researcher Award, given her consistent research output in machine learning and applied AI domains, industry-relevant research contributions, and dedication to academic excellence. Her work bridges the gap between theory and practice, making her a valuable contributor to the field of computational intelligence and Industry 4.0 applications.

With increased focus on high-impact journals, research funding, and industry collaborations, she has the potential to emerge as a leading figure in her field. Therefore, she is highly deserving of recognition through the Best Researcher Award.

 

 

Gokul Pandy | Robotics and AI | Best Researcher Award

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Mr. Gokul Pandy | Robotics and AI | Best Researcher Award

Application Development Manager at Accenture, United States

Summary:

Mr. Gokul Pandy is a dedicated and innovative IT professional with a comprehensive career at Accenture. His strategic mindset and hands-on expertise in application development, testing, and project management have positioned him as a leader in delivering high-quality solutions. Known for his ability to manage complex projects and lead cross-functional teams, Mr. Pandy’s work continues to impact the field through both practical application and contributions to industry standards.

Professional Profile:

👩‍🎓Education:

Mr. Gokul Pandy holds a robust academic foundation in software engineering and application development, which has been pivotal throughout his extensive career at Accenture.

🏢 Professional Experience:

Mr. Pandy has accumulated over 14 years of progressive experience in the IT sector, with a focus on application development, project management, and quality assurance. He currently serves as an Application Development Manager at Accenture, Richmond, where he has been leading a team of 35+ resources since December 2023. In this role, he has successfully steered complex projects, secured new contracts through successful project delivery, and contributed to the IEEE P3407 Working Group, shaping industry standards for testing.

Previously, as an Application Development Associate Manager (2019-2023), Mr. Pandy oversaw the full lifecycle of application development projects, managing onshore and offshore teams, ensuring on-time delivery, and maintaining client satisfaction. His tenure as a Test Engineering Specialist (2017-2019) and Senior Analyst (2014-2017) saw him implement innovative test automation frameworks, mentor junior engineers, and integrate testing processes within CI/CD pipelines to support continuous deployment.

Starting his career as an Associate Software Engineer (2010-2011) and progressing through roles as Test Engineering Analyst and beyond, Mr. Pandy demonstrated early expertise in developing and executing tests, managing defect tracking, and enhancing testing protocols to improve project outcomes.

Research & Industry Contributions:

Mr. Pandy’s technical acumen is exemplified by his active participation in industry standardization through the IEEE P3407 Working Group. His contributions have shaped the direction of application testing practices.

Skills & Core Competencies:

  • Technical Leadership & Project Management: Expertise in leading large-scale, cross-functional teams and ensuring projects are delivered within scope and budget.
  • Application Development: Full lifecycle management of application development with a strong track record in client management and contract negotiations.
  • Quality Assurance: Proven proficiency in test strategy development, automation frameworks, and defect resolution.
  • Risk Management: Conducting thorough risk assessments and developing mitigation strategies to maintain project timelines.
  • Mentorship & Team Development: Committed to developing talent, fostering a culture of continuous learning and collaboration.

Key Achievements:

  • Enhanced project efficiency by implementing goal-oriented team practices.
  • Spearheaded the integration of advanced quality assurance measures that improved software reliability.
  • Successfully delivered numerous high-stakes projects, securing ongoing client relationships and new contracts.

Top Noted Publication:

  • Reverse Engineering and Backdooring Router Firmwares
    Authors: A. Adithyan, K. Nagendran, R. Chethana, G. Pandy
    Conference: 2020 6th International Conference on Advanced Computing and Communication
    Summary: This paper examines the process of reverse engineering router firmware to identify security vulnerabilities and the subsequent backdoor insertion for penetration testing purposes. The authors outline the methodologies used for extracting firmware, the tools employed for reverse engineering, and the process of creating backdoors to test the robustness of network security. The research underscores the critical need for secure coding and firmware hardening in embedded systems.
    Citations: 12
  • Advancements in Robotics Process Automation: A Novel Model with Enhanced Empirical Validation and Theoretical Insights
    Authors: G. Pandy, V. Jayaram, M.S. Krishnappa, B.S. Ingole, K.K. Ganeeb, S. Joseph
    Preprint: arXiv (2024)
    Summary: This paper proposes an innovative model for enhancing Robotics Process Automation (RPA) through empirical validation and theoretical development. The study integrates machine learning to improve decision-making processes and workflow automation. Results from case studies and data analysis illustrate significant enhancements in operational efficiency and cost-effectiveness using the proposed framework.
    Citations: New publication, citations are pending.

Conclusion:

Mr. Gokul Pandy exemplifies a professional whose career embodies a blend of technical expertise, strategic leadership, and significant contributions to industry practices. His work with IEEE and successful project management at Accenture position him as a leader in Robotics and AI application development. To amplify his candidacy for prestigious research awards, expanding his body of peer-reviewed research and engaging more directly in AI and robotics-centric studies would be beneficial. Nevertheless, Mr. Pandy’s substantial industry contributions, leadership in advancing standards, and commitment to team development make him a commendable candidate for the Best Researcher Award.