Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

Ms. Swati Jitendrakmar Patel | Artificial Intelligence | Best Researcher Award

Software Engineer at Skyline Software Solutions, India

Ms. Swati Patel is an accomplished Data Analyst and Software Developer with extensive expertise in data science, machine learning, and software engineering. She has contributed significantly to academic research, publishing 8 journal papers, 2 IEEE conference papers, and 5 books on topics ranging from software security to predictive analytics. With strong analytical skills and a track record of developing efficient workflows and impactful applications, she has consistently delivered data-driven solutions for business optimization and research innovation.

Publication Profile

Google Scholar

Educational Details

Ms. Swati Patel holds a Master of Science in Advanced Computing Technologies from Birkbeck, University of London (2022-2023), where her projects included Principal Component Analysis on the Pima Indians Diabetes Dataset and predicting DDoS attacks using Darknet Time-Series data. She earned a Master’s degree in Computer Science from SES’s R. C. Patel Institute of Technology (NMU, India, 2012-2014), completing her thesis on software birthmark-based theft detection of JavaScript programs. Her Bachelor’s degree in Computer Engineering was completed at PSGVPM’s D. N. Patel College of Engineering, Shahada (NMU, India, 2008-2012), where she developed an Online Voting System using ASP.NET and SQL.

Professional Experience

Swati Patel is a Data Analyst and Entrepreneur with proven expertise in designing and optimizing workflows, data visualization, and software development. She served as a Data Analyst at SSP Group PLC, UK (2023-2024), where she created interactive Power BI dashboards to analyze sales data, optimized EPOS systems for data accuracy, and reduced data processing time by 30% through SQL optimization. As an entrepreneur, she successfully led Skyline Software Solutions (2014-2022), developing over 35 applications in Java, .NET, and other technologies. She managed end-to-end project execution, providing high-quality software solutions to diverse industries.

Research Interest

Swati’s research focuses on applied machine learning, natural language processing, and predictive modeling. She is particularly interested in statistical methods for data anomaly detection, speech-based health diagnostics, and secure systems in computing environments. Her work also extends to innovative clustering techniques for theft detection in software and dimensionality reduction in large datasets.

Author Metrics

  • Publications: 2 IEEE papers, 8 journal papers, 5 books.
  • Key Topics: Data science, machine learning, NLP, secure computing systems, predictive analytics.
  • Notable Works:
    • “A Review on Statistical Analysis-Based Approaches for Data Poison Detection Using Machine Learning.”
    • “Automated Depression Assessment from Speech Signals Using Pitch and Energy Features.”
    • “Long Short-Term Memory and Gated Recurrent Unit Networks for Accurate Stock Price Prediction.”
    • Books: COVID-19 Data Analysis for the United Kingdom and Data Exploration and Machine Learning using R.

Publication Top Notes

  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Frequent Subgraph Mining
    • Authors: S.J. Patel, T.M. Pattewar
    • Conference: 2014 International Conference on Embedded Systems (ICES)
    • Pages: 63–68
    • Citations: 9
    • Year: 2014
    • Summary: This paper presents a novel method for detecting software theft in JavaScript programs using software birthmarks. The approach employs agglomerative clustering and frequent subgraph mining to identify similarities between programs, aiding in theft detection.
  • K-Means Clustering Algorithm: Implementation and Critical Analysis
    • Author: S. Patel
    • Publisher: Scholars’ Press
    • Citations: 8
    • Year: 2019
    • Summary: This publication provides an in-depth exploration of the K-means clustering algorithm, including its implementation and a critical analysis of its efficiency and limitations in clustering diverse datasets.
  • Software Birthmark Based Theft Detection of JavaScript Programs Using Agglomerative Clustering and Improved Frequent Subgraph Mining
    • Authors: S. Patel, T. Pattewar
    • Conference: 2014 International Conference on Advances in Electronics, Computers, and Communications
    • Citations: 7
    • Year: 2014
    • Summary: This paper builds upon earlier research by introducing an improved method for frequent subgraph mining, enhancing the detection accuracy of JavaScript program theft through advanced birthmark-based techniques.
  • Software Birthmark for Theft Detection of JavaScript Programs: A Survey
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJAFRC (International Journal of Advanced Foundation and Research in Computers)
    • Volume: 1, Issue 2, Pages: 29–38
    • Citations: 2
    • Year: 2014
    • Summary: This survey reviews existing methods for detecting software theft in JavaScript programs, with a focus on software birthmark techniques. It outlines challenges, solutions, and future research directions.
  • Emerging Trends in Computer Technology (NCETCT)
    • Authors: S.J. Patel, T.M. Pattewar
    • Journal: IJCA (International Journal of Computer Applications)
    • Conference Issue: NCETCT, Number 1
    • Year: 2014
    • Summary: This conference paper discusses advancements in computer technology with a focus on software security. It explores the use of software birthmarks as a means of detecting and preventing intellectual property theft in programming.

Conclusion

Ms. Swati Patel is a highly qualified and deserving candidate for the Best Researcher Award. Her combination of academic excellence, impactful research, and real-world contributions to artificial intelligence and software engineering set her apart as an innovative thinker. To maximize her potential and visibility, she could focus on strengthening her citation impact, pursuing international collaborations, and contributing to higher-impact conferences. Overall, her track record reflects dedication, skill, and the ability to drive meaningful advancements in her field.

 

 

 

Gokul Pandy | Robotics and AI | Best Researcher Award

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.

 

Omar Soufi | Intelligence Artificial | Best Researcher Award

Dr. Omar Soufi | Intelligence Artificial | Best Researcher Award

Doctorate at Mohammed V University of Rabat Mohammadia School of Engineering, Morocco

Summary:

Dr. Omar Soufi is an expert in artificial intelligence and data science, with a specialized focus on remote sensing and geographic information systems (GIS). He completed his Ph.D. in Computer Engineering with a concentration in Artificial Intelligence at EMI Rabat in 2023, where his research centered on enhancing satellite image quality using deep learning techniques. With extensive experience in both academia and industry, Dr. Soufi has led numerous projects in AI, data science, and business intelligence. His contributions to the field include developing geospatial platforms for natural disaster risk management and implementing innovative solutions for satellite image processing. Dr. Soufi is currently advancing his research and professional endeavors as a postdoctoral researcher at CRTS Rabat, where he continues to explore the frontiers of AI and remote sensing.

Professional Profile:

👩‍🎓Education:

  • Ph.D. in Computer Engineering: Artificial Intelligence (2023)
    • Institution: EMI Rabat
    • Dissertation: Approche par Deep Learning au profit de la télédétection spatiale : Amélioration de la qualité d’images satellites et du procédé du capteur d’étoile.
  • Engineering Degree in Computer Science (2020)
    • Institution: EMI Rabat
    • Option: Ingénierie et Qualité Logicielle.
  • Engineering Degree in Information Systems Engineering (2020)
    • Institution: Polytechnique Grenoble, ENSIMAG
  • Fundamental License in Mechanical Engineering (2014)
    • Institution: ARM Merkèns
  • Diplôme des Études Universitaires (2015)
    • Institution: ARM Merkèns
  • Baccalauréat (2011)
    • Institution: 1ER LMR
    • Option: Sciences de Vie et de Terre

🏢 Professional Experience:

Dr. Omar Soufi is currently a Postdoctoral Researcher in Computer Engineering at CRTS Rabat, a position he has held since February 2024. In this role, he leads projects focused on artificial intelligence and data science, particularly for satellite image processing and spatial data analysis. Since 2022, Dr. Soufi has also been the Head of the Geomatics & Decision-Making Tools Department at CRTS Rabat, where he manages geomatics projects, develops decision-making tools, and oversees the implementation of geospatial platforms.

Previously, from 2020 to 2022, Dr. Soufi served as the Head of the Business Intelligence & Decision-Making Tools Department at CRTS Rabat. In this capacity, he directed business intelligence projects, developed data analytics solutions, and optimized decision-making processes. From 2017 to 2020, he was the Chief of Project at the Decision Support Center, managing decision support projects, implementing big data architectures, and developing e-learning platforms.

Dr. Soufi’s earlier professional experience includes serving as a Project Manager in the IT Department at CRTS Rabat from 2016 to 2017. He led IT projects, developed web applications, and implemented distributed data processing systems. His internships include a PFE internship on the super resolution of satellite images using deep learning (February 2020 – July 2020), an engineering internship on the development of a space station management platform at CRERS Rabat (July 2019 – August 2019), and an internship on the development of an agricultural campaign bulletin diffusion platform at CRTS Rabat (July 2019 – August 2019).

Research Interests

Dr. Omar Soufi’s research interests are centered on artificial intelligence, data science, remote sensing, and geographic information systems (GIS). His work focuses on applying deep learning techniques to improve the quality of satellite images and developing intelligent systems for spatial data analysis and geospatial applications. He is particularly interested in enhancing accessibility to high-resolution satellite imagery and advancing spacecraft attitude control using AI.

Top Noted Publication:

  • Study of Deep Learning-Based Models for Single Image Super-Resolution
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Revue d’Intelligence Artificielle, 2022
    • Link: DOI: 10.18280/ria.360616
  • FSRSI: New Deep Learning-Based Approach for Super-Resolution of Multispectral Satellite Images
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Ingénierie des Systèmes d’Information, 2023
    • Link: DOI: 10.18280/isi.280112
  • Deep Learning Technique for Image Satellite Processing
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Intell Methods Eng Sci, 2023
  • Enhancing Accessibility to High-Resolution Satellite Imagery: A Novel Deep Learning-Based Super-Resolution Approach
    • Authors: O. Soufi, F.Z. Belouadha
    • Published in: Journal of Environmental Treatment Techniques, 2023
  • An Intelligent Deep Learning Approach to Spacecraft Attitude Control: The Case of Satellites
    • Authors: O. Soufi, F.Z. Belouadha
    • Status: Under review, 2023