Vishnu Ramineni | Computer Science | Best Researcher Award

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Mr. Vishnu Ramineni | Computer Science | Best Researcher Award

Senior Staff Software Engineer at Albertsons Companies, USA

Summary:

Vishnu Ramineni is a seasoned software engineer with over seven years of experience in developing scalable and performance-driven software solutions. Specializing in frontend and mobile app development, he has contributed to the success of high-profile projects in industries such as retail, healthcare, and hospitality. Currently serving as a Senior Staff Software Engineer at Albertsons Companies, Vishnu has demonstrated leadership in architectural design, team management, and technical innovation.

Professional Profile:

👩‍🎓Education:

Master of Science in Computer Science, University of North Texas, Texas, USA (2021–2022)

🏢 Professional Experience:

Vishnu Ramineni is an accomplished software engineer with a wealth of experience across multiple industries, including retail, hospitality, and healthcare. Currently serving as a Senior Staff Software Engineer at Albertsons Companies in Plano, Texas, he leads a team of five developers in crafting scalable micro-frontend solutions using ReactJS and NextJS. He has developed innovative in-house tools to enhance application stability, saving significant operational costs, and implemented caching mechanisms and CI/CD processes that have drastically improved build efficiency and performance. Previously, at Treebo Hotels, Vishnu managed the highly-rated mobile app, developing SaaS features for Hotel Superhero and delivering scalable solutions with React, NodeJS, and GraphQL. During his tenure at Apollo 247, he optimized the UX of the patient and doctor apps, enhanced audio/video calling features, and established CI/CD pipelines. At Hiver, he designed and built a cross-platform mobile application from scratch, significantly boosting performance and ensuring consistency through a comprehensive component library. His early work at iB Hubs involved developing SaaS web and mobile applications, where he introduced service layers for testable and modular frontend architectures. Across all roles, Vishnu has demonstrated technical excellence, leadership, and a passion for building robust, high-performing software solutions.

Research Interests:

Vishnu is passionate about performance optimization, scalable micro-frontend architectures, and leveraging GraphQL for efficient API communication. He is also interested in CI/CD automation, error monitoring systems, and building high-performing, accessible applications adhering to ADA standards.

Author Metrics:

Although Vishnu’s contributions have primarily been in industry-driven software development, his innovative implementations, such as in-house error handling tools and scalable system designs, have earned recognition from leadership teams. His practical achievements reflect his ability to translate research-oriented problem-solving into real-world impact.

Top Noted Publication:

A Novel Image Encryption Algorithm Using AES and Visual Cryptography

  • Authors: VKP Kalubandi, H Vaddi, V Ramineni, A Loganathan
  • Published in: Proceedings of the 2nd International Conference on Next Generation Computing Technologies (2016)
  • Citation Count: 37
  • Abstract: Proposes a hybrid encryption technique combining AES and visual cryptography to enhance the security of image transmission. The approach demonstrates improved robustness against cryptographic attacks.

AI-Driven Innovation in Medicaid: Enhancing Access, Cost Efficiency, and Population Health Management

  • Authors: VJ Balaji Shesharao Ingole, Vishnu Ramineni, Manjunatha Sughaturu Krishnappa
  • Published in: International Journal of Healthcare Information Systems and Informatics (IJHISI), Vol. 1, Issue 1, 2024
  • Abstract: Explores the application of AI in Medicaid systems to improve healthcare delivery. Focuses on cost reduction, accessibility enhancement, and population health management using case studies and AI-based frameworks.

Mitigating Order Sensitivity in Large Language Models for Multiple-Choice Question Tasks

  • Authors: DVJ Vidyasagar Parlapalli, Balaji Shesharao Ingole, Manjunatha Sughaturu Krishnappa, Vishnu Ramineni
  • Published in: International Journal of Artificial Intelligence Research and Development (IJAIRD), Vol. 2, Issue 2, 2024
  • Abstract: Proposes solutions to address order sensitivity in LLMs, focusing on applications in educational assessments and MCQ tasks. Introduces novel mitigation strategies, improving model performance and reliability.

Advancements in Heart Disease Prediction: A Machine Learning Approach for Early Detection and Risk Assessment

  • Authors: BS Ingole, V Ramineni, N Bangad, KK Ganeeb, P Patel
  • Published in: arXiv preprint (2024)
  • Abstract: Develops machine learning models for early detection of heart disease, showcasing improved prediction accuracy and usability for clinical applications.

The Dual Impact of Artificial Intelligence in Healthcare: Balancing Advancements with Ethical and Operational Challenges

  • Authors: VJ Balaji Shesharao Ingole, Vishnu Ramineni, Nikhil Kumar Pulipeta, Manoj Kumar
  • Published in: European Journal of Computer Science and Information Technology (EJCSIT), Vol. 12, Issue 6, 2024
  • Abstract: Analyzes the ethical and operational challenges posed by AI in healthcare, alongside its potential to revolutionize the field. Provides strategies to balance advancements with responsible implementation.

Conclusion:

Mr. Vishnu Ramineni is a strong candidate for the Best Researcher Award in Computer Science. His contributions to scalable system architectures, healthcare innovations, and AI-driven solutions highlight his ability to address complex real-world challenges. His blend of academic research and industry expertise makes him a versatile and impactful researcher.

To further elevate his profile, Mr. Ramineni could focus on increasing his research outputs, engaging in interdisciplinary collaborations, and assuming leadership roles in academic and industry-driven research initiatives. With these advancements, he has the potential to emerge as a leading figure in the field of computer science.

 

Mithun Sarker | Artificial Intelligence-Machine Learning | Fast Cited Article Award

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Mr. Mithun Sarker | Artificial Intelligence-Machine Learning | Fast Cited Article Award

Lead Software Developer at Iron Horse Terminals LLC, United States

Summary:

Mr. Mithun Sarker is an accomplished software engineer specializing in full-stack development, scalable backend solutions, and AI-driven systems. With over a decade of professional experience, he has contributed to diverse industries, including transportation, social networking, and IoT, by building robust, user-focused applications. Mithun is skilled in Node.js, Python, Kotlin, MongoDB, and AWS, with a strong passion for research in AI and IoT technologies.

Professional Profile:

👩‍🎓Education:

  • Master of Science in Computer Science
    Lamar University, USA (2022)
  • Bachelor of Science in Computer Science and Engineering
    Khulna University of Engineering and Technology, Bangladesh (2013)

🏢 Professional Experience:

  • Lead Software Engineer, Iron Horse Terminals LLC (08/2022 – Present)
    Leads the development of a rail yard management system, designing backend APIs using Node.js and MongoDB, managing AWS infrastructure, and developing frontend applications for web and Android platforms.
  • Senior Software Engineer, W3Engineers Ltd. (11/2017 – 10/2020)
    Spearheaded projects like Yumi, an AI-powered dating app, and Telemesh, an off-grid messaging platform funded by UNICEF. Developed AI-based features, chatbots, and mesh networking solutions, while also creating graph-based ad networks using Amazon Neptune.
  • Software Engineer, SurroundApps Ltd. (06/2016 – 11/2017)
    Focused on live video and audio streaming applications, integrating GoPro connectivity with Android devices, and creating backend systems using Node.js and MongoDB.
  • Programmer, Arobil Limited (09/2015 – 06/2016)
    Developed music streaming and car parking management systems, emphasizing backend efficiency and user-centric design.
  • Software Engineer, Codemen Solution Inc. (07/2014 – 08/2015)
    Delivered comprehensive solutions, including real estate websites and employee management systems, leveraging WordPress and the LAMP stack.

Research Interests:

Mithun’s research focuses on AI-driven interactive systems, backend scalability, and IoT-based applications. His work includes advancements in image classification, chatbots, and mesh networking, with a commitment to enhancing real-world usability through technological innovation.

Author Metrics:

  • Published innovative projects involving AI-based chatbots, ad networks, and IoT applications.
  • Developed UNICEF-funded solutions like Telemesh, showcasing expertise in socially impactful technologies.
  • Certified in “Machine Learning with Python” by IBM through Coursera, reflecting his continuous learning and application of advanced AI methods.

Top Noted Publication:

1. Revolutionizing Cybersecurity: Unleashing the Power of Artificial Intelligence and Machine Learning for Next-Generation Threat Detection

  • Authors: A. Manoharan, M. Sarker
  • Journal/Proceedings: International Research Journal of Modernization in Engineering Technology
  • Year of Publication: 2022
  • Citations: 100
  • Abstract: The paper delves into how AI and machine learning can redefine cybersecurity by introducing advanced threat detection systems. It discusses autonomous threat response, predictive models, and their practical implications in enterprise security.

2. Revolutionizing Healthcare: The Role of Machine Learning in the Health Sector

  • Author: M. Sarker
  • Journal/Proceedings: Journal of Artificial Intelligence General Science (JAIGS)
  • Year of Publication: 2024
  • Citations: 34
  • Abstract: Focuses on the integration of machine learning in healthcare for enhanced diagnostics, personalized medicine, and healthcare management. The work outlines future trends and challenges in adopting ML technologies in the medical field.

3. Towards Precision Medicine for Cancer Patient Stratification by Classifying Cancer Using Machine Learning

  • Author: M. Sarker
  • Journal/Proceedings: Journal of Science & Technology
  • Volume/Issue: Vol. 3, Issue 3
  • Pages: 1-30
  • Year of Publication: 2022
  • Citations: 28
  • Abstract: Explores how machine learning techniques can help in classifying various types of cancer for precision medicine. It proposes new stratification algorithms based on genetic and phenotypic data.

4. Cloud-Based Reinforcement Learning for Autonomous Systems: Implementing Generative AI for Real-time Decision Making and Adaptation

  • Authors: K. Krishna, A. Mehra, M. Sarker, L. Mishra
  • Journal/Proceedings: Iconic Research and Engineering Journals
  • Year of Publication: 2023
  • Citations: 27
  • Abstract: The paper presents a novel integration of cloud-based reinforcement learning with generative AI to enable real-time decision-making and adaptability in autonomous systems. Applications span from robotics to IoT-enabled devices.

5. Assessing the Integration of AI Technologies in Enhancing Patient Care Delivery in US Hospitals

  • Author: M. Sarker
  • Journal/Proceedings: Journal of Knowledge Learning and Science Technology
  • ISSN: 2959-6386 (online)
  • Year of Publication: 2023
  • Citations: 11
  • Abstract: An analytical study evaluating the integration of AI technologies in US hospitals, emphasizing their impact on patient care efficiency, diagnostics, and overall healthcare outcomes.

Conclusion:

Mr. Mithun Sarker is a strong candidate for the Research for Fast Cited Article Award, given his remarkable achievement of a highly cited article in a short timeframe. His research reflects both depth and relevance in artificial intelligence and machine learning, with impactful contributions in cybersecurity, healthcare, and IoT-based applications.

Recommendation: With an emphasis on diversifying publication venues and fostering high-profile collaborations, Mithun can further solidify his standing as a researcher whose work drives both academic and practical innovation.

 

 

ShivaDutt Jangampeta | Machine Learning | Industry Innovation Research Award

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Mr. ShivaDutt Jangampeta, Machine Learning, Industry Innovation Research Award

ShivaDutt Jangampeta at JP Morgan Chase, United States

Mr. ShivaDutt Jangampeta appears to be a highly experienced professional with a strong background in cybersecurity, specifically in Security Information and Event Management (SIEM). However, determining his suitability for the “Research for Community Impact Award” requires an assessment of how his work impacts the community.

Relevant Criteria for the Research for Community Impact Award:

Community Impact: The award typically recognizes research that has a significant positive impact on the community, either through direct application or through contributions to knowledge that benefit the community.

Innovation and Advancement: Contributions to advancing the field and introducing innovative solutions or methodologies.

Collaboration and Dissemination: Engagement with stakeholders and dissemination of research findings to a broader audience.

Evaluation of Mr. Jangampeta’s Suitability:

Strengths:

Professional Experience:

  • Extensive experience in managing and optimizing SIEM systems.
  • Leadership roles in cybersecurity teams at major organizations like JPMorgan Chase and PEPSICO.
  • Development and implementation of advanced cybersecurity measures that could indirectly benefit community security by protecting sensitive data and reducing vulnerabilities.

Research Contributions:

  • Authored several publications related to data security, SIEM, and compliance, indicating a contribution to academic knowledge.
  • Research topics like anomaly detection in SIEM and the role of data security in compliance suggest a focus on enhancing cybersecurity frameworks, which can have broad implications for community safety and trust in digital systems.

Innovative Solutions:

  • Implementation of advanced technologies and automation in cybersecurity, contributing to more resilient and efficient security infrastructures.

Areas to Consider:

Direct Community Impact:

  • While Mr. Jangampeta’s work in cybersecurity is crucial, the direct impact on the community might be less apparent compared to other fields such as public health or environmental science.
  • It would be beneficial to highlight specific examples or case studies where his work directly protected community members or contributed to public safety.

Engagement and Dissemination:

  • The extent of his engagement with community stakeholders and efforts to disseminate his research findings to a broader, non-technical audience would strengthen his case for this award.

Conclusion:

Mr. Jangampeta’s extensive experience and contributions to the field of cybersecurity are impressive and certainly valuable. His work indirectly impacts the community by enhancing the security of digital infrastructures, which is increasingly important in today’s interconnected world. To bolster his application for the Research for Community Impact Award, it would be advantageous to emphasize any direct community benefits resulting from his cybersecurity initiatives and any outreach efforts he has made to educate or involve the community in his work.

If his research and professional activities can be framed to clearly demonstrate significant, tangible benefits to the community, Mr. Jangampeta could be a suitable candidate for the award.