Rounak Raman | Information Technology | Research Excellence Award

Published-on by Indian Scientist

Mr. Rounak Raman | Information Technology | Research Excellence Award

Netaji Subhas University of Technology | India

Rounak Raman is a technology researcher and engineering innovator with a strong academic background in Information Technology and a multidisciplinary portfolio spanning artificial intelligence, machine learning, generative AI, computer vision, IoT systems, wireless sensor networks, and network security. He has gained significant research and development experience through contributions at DRDO-INMAS, where he worked on EEG-based cognitive analytics and neurofeedback systems, and at NSUT, where he designed advanced IoT protocols including energy-aware clustering, trust-based opportunistic communication, and secure hierarchical key-rotation mechanisms. His technical work extends into generative AI solutions, semantic search systems, real-time computer vision applications, and large-scale image and document intelligence models. He has led impactful projects such as PRAGATI smart parking, SyntheX document analysis framework, and QuickTag for AI-driven product taxonomy. His achievements include securing positions in national innovation challenges, hackathons, entrepreneurship competitions, and international fellowship programs. Alongside industry-recognized certifications in data science, system design, and cybersecurity, he has also held leadership roles in student organizations, mentoring teams, guiding open-source contributions, and facilitating research collaboration. His research interests include GenAI, NLP, IoT security, WSNs, cryptography, edge intelligence, and autonomous network optimization. He remains committed to creating scalable, socially impactful technological solutions.

Profiles: Google Scholar

Featured Publication

Raman, R., Yadav, A., Kukreja, D., & Sharma, D. K. (2025). CONTEXT-NET: A context-aware nexus-based aggregation protocol for opportunistic networks. Internet of Things, 101809.

Raman, R., Yadav, A., & Kukreja, D. (2025). ARMor-IoT: Aggregated reliable mechanism for optimized trust in IoT. In International Conference on Artificial Intelligence and Its Application (pp. 229–241).

Milind Cherukuri | Artificial Intelligence | Young Researcher Award

Published-on by Indian Scientist

Mr. Milind Cherukuri | Artificial Intelligence | Young Researcher Award

University of North Texas, India

Author Profile

ORCID

GOOGLE SCHOLAR

🎓 EARLY ACADEMIC PURSUITS

Milind Cherukuri’s academic journey began with a Bachelor’s in Computer Science from SRM University, Chennai (2015–2019), where he built a strong foundation in software engineering and algorithmic problem-solving. His pursuit of advanced knowledge led him to the University of North Texas, Dallas, where he completed his Master’s in Computer Science (2021–2022) with a focus on artificial intelligence, machine learning, and data systems.

🏢 PROFESSIONAL ENDEAVORS

Milind’s professional trajectory spans a blend of engineering rigor, AI research, and enterprise system design:

  • Caris Life Sciences (2025–Present)
    Role: Salesforce Business Analyst & Administrator
    Spearheading automation and optimization of clinical and research workflows, Milind integrates complex data systems and aligns AI tools with healthcare outcomes.

  • Amazon (2022–2024)
    Role: Software Engineer
    Engineered scalable microservices, improved customer personalization using AI, and contributed to global backend infrastructure, earning accolades for reliability and innovation.

  • Infor (2019–2021)
    Role: Software Engineer
    Led backend automation initiatives and research into NLP applications, with early contributions in recommendation systems and sentiment analysis pipelines.

📚 CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE

Milind’s AI research is grounded in both theoretical depth and applied innovation. His key research themes include:

  • Sentiment Analysis & Emotion Modeling

  • Safe and Responsible Development of Large Language Models (LLMs)

  • Image Segmentation and Validation Tools for Web Structures

  • Prompt Engineering for LLM Optimization

He has published five peer-reviewed research papers, presented at premier conferences such as IEEE AI Summit and EEET 2024, and contributed tools like WebChecker, which enhances web development quality control.

🏅 ACADEMIC CITES, ACCOLADES AND RECOGNITION

  • Elevated to Senior Member of IEEE (2025)

  • Peer reviewer for leading journals, including JOBARI

  • Citations across platforms including IEEE Xplore, ResearchGate, and arXiv

  • Recognized internally by Amazon and Caris Life Sciences for exemplary technical contributions

  • Invited speaker at international AI research forums

🌍 IMPACT AND INFLUENCE

Milind’s work bridges AI with healthcare, e-commerce, and cloud ecosystems, showing measurable improvements:

  • 30% efficiency gain in Salesforce workflows at Caris Life Sciences

  • Millions of fault-tolerant requests/day enabled by backend systems at Amazon

  • Influenced global discussions on AI safety through groundbreaking presentations

He continues to influence both industry and academia through tool development, peer-review contributions, and community engagement.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Milind aims to build a safer, smarter, and ethically grounded AI ecosystem. His future research plans focus on:

  • Explainable AI in healthcare diagnostics

  • Open-source tools for LLM safety benchmarking

  • Sustainable AI development aligning with ESG goals

He envisions fostering innovation at the crossroads of healthcare, AI, and policy, mentoring the next generation of AI practitioners and building intelligent systems that serve humanity.

 ✅CONCLUSION

Mr. Milind Cherukuri stands out as a technologist, researcher, and thought leader, bridging cutting-edge AI with practical impact. With a track record of academic brilliance, engineering excellence, and ethical AI advocacy, he continues to leave a mark on research, innovation, and global digital transformation.

 🔬NOTABLE PUBLICATION:

Title: Comparing Image Segmentation Algorithms

Author: M. Cherukuri
Journal/Conference: 2024 IEEE 4th International Conference on Data Science and Computer Applications (ICDSCA)
Year: 2024

Title: Cost, Complexity, and Efficacy of Prompt Engineering Techniques for Large Language Models

Author: M. Cherukuri
Journal/Conference: International Journal on Science and Technology
Year: 2025

Title: WebChecker: A Versatile EVL Plugin for Validating HTML Pages with Bootstrap Frameworks

Author: M. Cherukuri
Journal/Conference: arXiv preprint arXiv:2502.07479
Year: 2025

Title: Advancing AI Safely: Frameworks and Strategies for the Development of GPT-5 and Beyond

Author: M. Cherukuri
Journal/Conference: ResearchGate Preprint
Year: 2025

Title: Exploring Multi-Dimensional Sentiment Analysis: A Study on Emotion Representation Structures and Prediction Models

Author: M. Cherukuri
Journal/Conference: REST Journal on Data Analytics and Artificial Intelligence
Volume: 3, Pages 55–76
Year: 2024